APPROVED DATA ACCESS REQUESTS

Lieke en Stef bio informatici

The DNA database of Hartwig Medical Foundation helps researchers with their research to improve the treatment of cancer patients.

Researchers may apply for data for scientific research. Below short summaries of the approved Data Access Requests can be found, per year, the name of the main applicant and the institute he or she works for (at the time the Data Access Request was approved).

Brain metastasis is a common and devastating complication of breast cancer, and is responsible for a large a growing fraction of breast cancer mortality.   In order to identify potential targets for therapeutic treatment, we performed genomic sequencing of brain metastases from breast cancer patients, with matched primary-tumor biopsy and normal tissues.   In order to identify potential drivers of metastasis, and brain metastasis specifically, we compared our data with previous studies of primary breast cancer, as well as extra-cranial metastatic breast cancer.   Statistical analysis of differences in genomic alterations and background frequencies in these datasets allowed us to prioritize candidate driver genes for functional followup studies.   

Scott Carter, Dana-Farber Cancer Institute, USA

Purpose: To develop an algorithm for robust estimation of the tumor mutational burden (TMB) using targeted sequencing. 

Data: Somatic analyses data DNA (SNVs, INDELs, SVs, Copy-numbers, MSI+/- etc) from the ~4000 metastatic cases available in the Hartwig Medical Database including the 2,520 cases recently published in Nature (P. Priestley et al. Nature, 2019). Clinical and outcomes data from the patients in the Hartwig Medical Database that have been treated with immunotherapy.

Relevance for patient: Immunotherapy, that is, reactivation of the patient’s own immune system to kill the cancer cells, has revolutionized treatment of advanced cancer of various origins. However, robust estimation of TMB by targeted sequencing is crucial to accurately identify patients with an elevated TMB that may benefit from immunotherapy. 

Johan Lindberg, Karolinska Instutet, Sweden

Glioblastoma multiforme (GBM) is the most lethal brain tumour. Mutations in certain genes have been implicated in GBM. However, the DNA sequence encoding for genes (coding regions) only represent 1% of the tumour DNA. We aim to use the whole genome sequencing (WGS) and clinical data from the Hartwig’s recurrent GBM cohort, together with other publicly available datasets, to characterise the mutations in the non-coding regions in GBM patients, and to determine if certain mutations in these regions can predict survival or response to therapy. We are particularly interested in structural variants (SVs) and require BAM/CRAM files to generate comparable new SV calls across all datasets (ie between Hartwig dataset and other datasets generated elsewhere), as we have recently for a combination of previously published and new ovarian tumour BAM files (see https://www.biorxiv.org/content/10.1101/2020.05.11.088278v1).

Colin Semple, The University Court of the University of Edinburgh, United Kingdom

We aim to apply computational tools to Hartwig Medical Foundation cancer genomes to establish the order in which harmful mutations were acquired, and approximately when they were acquired during a patient’s lifetime. Furthermore, we aim to infer what caused the mutations (for example, smoking, UV light, etc.), and estimate when the cell was exposed to these damaging processes. Across many cancer samples, this approach lets us build a picture of how different cancers evolve over time. By comparing these results to earlier analyses we performed on primary tumours (observed at initial cancer diagnosis), we seek to understand the development of cancer as it spreads from the initial site to another site (known as metastasis). This will show whether tumours that metastasise evolve in the same way as non-metastatic cancers, and may give insight that helps to predict the metastatic step in cancer evolution.

Peter van Loo, The Francis Crick Institute, United Kingdom

There are different types of breast cancer, one is referred to as Invasive Lobular Carcinoma (ILC). ILC accounts for around 10% of breast cancers, and while considered a distinct tumor subclass, these patients are treated identical as the predominant subclass Invasive Ductal Carcinoma (IDC). ILC cancers have a very specific feature: almost all of these tumors have a mutation in a gene called Ecadherin. Using this mutation to identify ILC, we aim to compare ILC and IDC breast cancer. With a better understanding of ILC, future therapeutic options could be better finetuned for this distinct breast cancer subclass.

Wilbert Zwart, Netherlands Cancer Institute, the Netherlands

Many tumors show mutations of kinase proteins. When these kinase proteins are mutated, they can provide a catastrophic effect because this favors cell division over cell death of tumor cells. Since every patient can have multiple kinase mutations, this provides options to inhibit these kinases simultaneously. Since kinase inhibitors commonly inhibit multiple kinases at once, their multiple targets could be optimally matched to individual patients. By using laboratory experiments, we have found that  simultaneous inhibition of multiple mutated kinases can lead to more effective therapies. Here we aim to provide a proof of concept that optimally matching drug-targets to patients with multiple kinase mutations can lead to more effective therapies.

Bart Westerman, VU Medical Center, Amsterdam UMC, The Netherlands

See also HMF-DR-031 as this study will be part of DR-031.

This project aims to assess the porportion of patients with mUC who have pathognomic germline mutations.

Joost Boormans, Erasmus MC, The Netherlands

In this project we aim at combining mathematical modelling of tumour evolution with cancer genomic data to measure fundamental evolutionary characteristics of metastatic tumours. These measurements will allow better understanding of how tumours spread to distant parts of the body. Importantly, we anticipate that the patient-specific ‘evolutionary rules’ we will measure from the data may be informative in terms of stratifying patients between good versus poor prognosis. Moreover, some of these measurements may also be predictive of the effectiveness of certain treatments. 

Andrea Sottoriva, The Institute of Cancer Research, United Kingdom

The applicants have devised a new measure of risk which we have named the etiologic index. This index is a way of estimating the risk associated with mutations (variants) in genes that are known to be altered in people with cancer. Usually, to estimate the risk for cancer, researchers need to collect many hundreds of persons with cancer, and many hundreds of persons without cancer who are well-matched to those with cancer. This can be difficult to achieve. The method proposed here just requires analysis of blood and tumor DNA from persons with cancer. This could greatly help with risk estimation for cancer-associated genes.

William Foulkes, Research Institute of the McGill University Health Centre, Canada

  1. For prostate cancer, identifying patients at risk for developing aggressive disease is clinically challenging [1]. This project aims to discover biomarkers prognostic for disease progression and predictive of treatment response.
  2. CPCT-2 DNA and RNA sequencing data.
  3. Clinical implementation of prognostic and predictive biomarkers will help personalize therapy, reducing the burden of uneffective treatments and improving patient survival.

Niven Mehra, Radboudumc, the Netherlands

Recent studies emphasize the importance of combined effects of germline and somatic alterations in cancer. The aim of the project is to study how germline and somatic alterations contribute together to gene expression and drive glioma development. We will use next-generation sequencing data derived from matched normal and tumor samples of glioma patients. The data will be integrated with tissue- and tumor-specific data of regulatory elements to identify cancer-driving gene regulatory elements. The study is expected to produce novel findings, which have potential to be used in diagnostics and therapeutic applications to improve patient care.

Matti Nykter, Tampere University, Finland

Previously, we found that copy number changes in several genes were significantly associated with abundance of repetitive elements in the two prostate cancer datasets. Since both datasets are originated from cell-free DNA in plasma, we proposed to validate the observed association in whole-genome sequencing data of prostate cancer tissues.

Liang Wang, Moffitt Cancer Center, USA

Cancers change over time. Understanding how cancers change is important for determining a patient’s prognosis and to improve the effectiveness of treatment. It is not possible to directly watch a cancer change, and so instead we have to infer the changes using the patterns of mutations across the cancer genome. These mutational patterns are analogous to the rings inside a tree trunk that are a ’secret diary’ of how the tree grew. We have developed mathematical tools to read the patterns and work out how cancers grow and change, and we apply these tools to study the rich data within the Hartwig dataset.

Trevor Graham, Queen Mary, University of London, United Kingdom

While mutations affecting protein-coding regions have been examined in prostate cancer, structural variants at the genome-wide level are still poorly defined. Here, we try to develop a new structural variants (SVs) detection tool in whole-genome sequence (WGS) data to identify complex structural variants in prostate cancer and characterize the role of SVs in metastatic tumor and gene expression aberrations. In addition, we will also investigate the impact of SVs in patient clinical phenotypes.

Wei Li, University of California, Irvine, USA

Cancer genomes harbor a substantial number of mutations, but only some contribute to tumor development. These so-called driver mutations serve as targets for new cancer therapies. Over the past years, the search for these driver mutations has been mostly focused on coding regions. The goal of this project is to develop a statistical framework to systematically identify driver mutations in non-coding regions. We will apply this approach to all whole-genome sequencing data in the HMF database, and characterize which mutations in non-coding regions are relevant to carcinogenesis. We will then follow up on these findings using clinical and expression data.

Eliezer Van Allen, Dana-Farber Cancer Institute, USA

The discovery of driver mutations and mutational processes in melanoma is complicated by high background mutation rates. With expanded melanoma cohorts, it is possible to expand discovery through examination of noncoding mutations and larger somatic events that result in oncogenesis specific to clinically and genomically defined melanoma subtypes. The overarching goal of this project is to examine cancer drivers and mutational processes (“signatures”) in melanoma using computational methodologies and compare these findings within melanoma subtypes. We will apply these frameworks to whole-genome sequencing data in the HMF database and examine signatures for associations with orthogonal somatic molecular and clinical data.

Eliezer Van Allen, Dana-Farber Cancer Institute, USA

In urothelial cancer, prognosis and responsiveness to treatments, such as chemotherapy and checkpoint inhibitors, differs substantially between patients. Although urothelial cancer is known to be an immunogenic tumour, little is know about the prognostic and predictive value of the immune infiltrate in metastatic urothelial cancer. Here, we will use RNA sequencing data to infer immune cell composition and study its relation with clinical outcome, micronenvironmental factors and long non-coding RNAs. Identification of prognostic or predictive biomarkers is needed to tailor treatment to the individual patient. Moreover, a better understanding of factors that influence the immune infiltrate might provide a rationale for new treatment strategies.

Niven Mehra, Radboudumc, the Netherlands

In the past two decades, the exploration of molecular mechanisms and genetic information in cancer led to the new approaches for treatment. Despite its undesirable consequences, conventional chemotherapy is still the first-line treatment in metastastic cancer. Nowadays, targeted therapies (monoclonal antibodies and small molecules) are approved for some tumour types. Resistance to these agents is a challenging problem in the clinic and could be a result of activation of alternative molecular pathways involved in tumourigenesis. This finding highlights the need for further research to optimize treatment with targeted therapies by combining them in patients with more than one actionability.

Neeltje Steeghs, NKI-AvL, the Netherlands

The main reason that cancer is lethal lies in its ability to spread in the body, a process called metastasis. The immune system is important in determining tumour development and treatment response. We will conduct in-depth analyses of metastatic cancer by using the transcriptomic data to understand how immune and stromal cell gene expression may be correlated with changes in tumour size and patient outcomes. We will also determine the key genes that the alteration of which may improve disease outcome, which may provide potential therapeutic targets.

Binzhi Qian, The University of Edinburgh, QMRI, United Kingdom

The prognosis of patients with metastatic colorectal cancer is poor. Some of these patients are eligible for receiving potentially life-saving immunotherapy, but only if their tumor is classified as having microsatellite instability (MSI). Thus identifying these patients is important. The ability of the tests, that are used in routine medical practice, to correctly classify metastatic tumors as MSI is unclear. Comparing routine test results on MSI status, derived from the Dutch PALGA database, with MSI status based on whole genome sequencing, i.e. gold standard, using data from the Hartwig Medical Foundation, offers a unique opportunity to clarify this important issue.

Petur Snaebjornsson, Netherlands Cancer Institute, the Netherlands

Cancer is caused by mutations that occur over time via genetic and environmental exposures. Some mutations called drivers unlock oncogenic cellular properties, while most mutations are neutral passengers. A complete driver catalogue is important for developing therapies, while passengers reflect tumor evolution and exposures. Most known drivers affect protein-coding genes while the non-coding genome is less characterized. Here we use our machine-learning tools to study the non-coding genomes of metastatic tumors. We will compare drivers and passengers to understand the emergence of metastasis and investigate regional mutation processes to decipher tumor evolution and its exposures at functional genomic elements.

Jüri Reimand, Ontario Institute for Cancer Research, Canada

In this project we will investigate to what extent the cooperation of inherited polymorphisms within regulatory regions and somatic aberration patterns affects evolution of cancer by altering oncogenic signalling pathways and promoting disease progression. Whole Genome Sequencing (WGS) data of metastatic cancer patients (tissue and matched control) will be analysed and compared/integrated to data from other sources (PCAWG, GTeX and ENCODE). This project will lead to the identification of germline biomarkers capable to announce the emergence of specific cancer subtypes and driver cancer aberration patterns, hence help stratifying patients with potential aggressive progression.

Alessandro Romanel, University of Trento, Italy

The Personalized OncoGenomics (POG) Program sequences cancers from patients with advanced and metastatic tumours to determine which therapies are most likely to help combat their disease. Analysis of the complete tumour DNA sequence and gene activity has revealed how these tumours are affected by the therapies that patient have received and can potentially inform future clinical decision making. In this proposal, we aim to use the sequence data from the Hartwig Medical Foundation to aid in interpretation of patient findings, and also to validate novel observations in advanced cancers.

Steven Jones, BC Cancer, Part of the Provincial Health Services Authority, Canada

Using mouse models, we found certain variants of the fibroblast growth factor receptor 2 gene (Fgfr2) to be strong tumor drivers. These oncogenic Fgfr2 variants all lack the last exon resulting in shortened FGFR2 proteins. Importantly, cells expressing shortened FGFR2 are very sensitive to inhibitors blocking FGFR2 signaling. Moreover, preliminary data suggest that human cancers might also recurrently harbor genetic alterations of the FGFR2 locus presumably producing shortened FGFR2. To strengthen and validate these findings, the Hartwig Medical Foundation whole-genome sequencing and RNA sequencing datasets represent valuable resources. Ultimately, these findings might refine the inclusion criteria for FGFR2-targeting precision therapies.

Daniel Zingg, NKI-AvL, the Netherlands

HecoPerMed seeks to improve health economic models for personalized medicine, both payment models and evaluation (HTA) models. We seek to develop a model to assess the cost-effectiveness of new tumor agnostic treatments, and the data of the Hartwig medical foundation could help establish the current survival of patients, so we can investigate how good the new treatment is relative to current care.

Irene Santi, Erasmus University Rotterdam, The Netherlands

We plan to investigate the evolution of lung tumours at different stages of cancer development. The molecular data used to track cancer evolution gives us information about the key genes and processes involved in the tumour’s ability to overcome the patient’s immune system and external treatments. With the data from the HMF we additionally plan to investigate such processes at later stages of cancer development. Specifically, we will explore the role of genes and processes relevant at early stages of cancer evolution and at later stages, after treatment.

Ultimately, these data will inform the identification of new targets for a more personalised therapy and prognosis.

Nicholas McGranahan, University College London, United Kingdom 

Circulating tumor DNA is an emerging biomarker for cancer response assessment. Our group has previously assessed its utility in multiple malignancies including lung cancer and lymphomas. We perform ultra-deep sequencing of plasma-derived DNA targeting recurrently mutated genomic regions identified from prior sequencing studies. We are requesting access to WGS data to identify the most relevant coding and non-coding regions across multiple malignancies. This process is improved by including as many high-quality cases as possible. Determining optimal recurrent aberrations is critical to maximize assay performance, and therefore the future utility of such assays in patient care.

Ash Alizadeh, Alizadeh Lab, Stanford University, USA

Targeted cancer therapies can be remarkably effective but a considerable number of patients develop resistance as treatment proceeds. Resistance can be caused by specific mutations in cancer cells. Using computational analysis we have shown that a significant fraction of these resistance mutations are predicted to have immunogenic potential across a large proportion of the healthy human population. We intend to use the Hartwig Medical Database to verify if this holds true also in a patients’ population. If immunogenic in patients, recurrent resistance mutations could be extremely interesting in the context of off-the-shelf precision immunotherapies such as therapeutic cancer vaccines.

Stefano Lise, The Institute of Cancer Research, United Kingdom

Cancer is a complex disease, characterized by a wide spectrum of genome abnormalities. We aim to describe the order and magnitude of carcinogenic events (mutations and copy number changes). This will allow us to construct evolutionary trajectories for individual cancer types. Using the Hartwig Medical Foundation’s data on metastatic cancer samples, we wish to explore the last step in the transformation of the normal cell to lethal disseminated metastatic cancer. By deciphering cancer evolutionary trajectories we may be able to develop tools that can predict how cancer evolves in the presence of therapy, and determine cancer phenotypes associated with response. This may allow for improved patient treatment through stratification.

Nicolai Juul Birkbak, Aarhus University, Denmark

After treatment with a combination of chemotherapy and radiotherapy for esophageal cancer, the current standard treatment is to continue with resection. However, in circa 20% of patients, no vital tumor cells are found in the resection specimen. On the other side, circa 10% of patients develop metastases shortly after esophageal resection. These patients could have possibly been spared esophagus resection. A nation-wide study, initiated by the department of surgery of the Erasmus MC, is currently recruiting patients (the SANO study, PI prof. dr. van Lanschot) and aims to clarify the role of esophagus resection in patients with no radiological or pathological (on biopsy) evidence of disease after pre-operative chemoradiation. A rapidly developing minimally invasive method to improve detection of minimal amounts of tumor cells or fragments could help to identity those patients in whom true cure has been accomplished. Therefor, we are currently biobanking blood of the patients in the SANO trial to serially measure tumor DNA in the blood

To come to a comprehensive panel of genetic variants to be measured in the blood, we wish to incorporate the genetic variants found in the metastases of esophageal cancer patients, as these variants are expected to be the drivers of resistance to treatment and disease recurrence. Also, we want to explore the genetic characteristics of metastases of esophageal cancer.

Discovering new genetic variants in metasatses that have not been identified in primary tumors could lead to new therapeutic approaches. Optimizing the blood assay could lead to a new and minimally inavsive means to monitor tumor response.

Bianca Mostert, Erasmus MC, the Netherlands

Since almost 10 years, the outcome of patients with metastatic melanoma has improved significantly and long term durable responses have been realized. However, it remains difficult to predict which patient will benefit from therapy and besides that, severe adverse events occur in about 30-50% of the patients.
The aim of this project is to describe the genomic landscape of melanoma patients and to incorporate this into immunological and clinical analyses which we are currently performing. More insight into immunologic and genomic alterations in these patients could contribute to improved and more individualized therapeutic decision making.

Astrid van der Veldt, Erasmus MC, the Netherlands

The Personalised Breast Cancer Program (PBCP) is an initiative based at the Cancer Research UK Cambridge Institute and the Addenbrooke’s Hospital Breast Cancer Unit to sequence the DNA and RNA of breast cancer patients’ tumours. For every patient, their DNA was checked for mutations which could have an effect on which treatment would work best for them. Crucially, the results of the analysis are returned to the patient and their clinician within 12 weeks. However, most of the data in PBCP comes from primary breast tumours. We aim to understand how our findings from PBCP can be translated to metastatic tumours.

Carlos Caldas, University of Cambridge, United Kingdom

Despite the continued increase in the rate of survival in childhood cancer, the chemo- and radio-therapy at young age causes chronic long-term complications in childhood cancer survivors. A child treated for cancer is given up to 20 therapeutics, including DNA damaging agents, leading to survivors being 8 times more likely to develop a severe condition, including a second tumor, compared to their siblings. To study the contribution of therapy to tumor recurrence in childhood cancer, samples from ~250 patients are being sequenced at the whole-genome level. This study is focused on the mutagenic processes driving childhood cancer at recurrence following therapy.

Adam Shlien, Hospital for Sick Children, United States

Androgen receptor inhibitors (ARi) are frequently used to treat metastatic prostate carcinomas. In this project, we focus on identifying genetic causes for resistance to these new ARi to facilitate the development of new treatment options.

Michiel van der Heijden, NKI-AvL, the Netherlands

Breast Cancer is estimated to affect every one out of eight women over the course of their lifetimes. Although several molecular markers such as BRCA1/2, explain genetic risk, they do not explain the genetic origin of all breast cancers. We plan to study the non-coding part of the genome which primarily consist of transposable elements (TEs). Our analysis of patients from public databases such as TCGA and ICGC have revealed that TEs could be responsible for early onset of breast cancer. Availability of whole genome sequences from the Hartwig Medical Foundation will help verify those findings.

Milan Radovich, The Trustees of Indiana University’s, United States

We aim to understand the molecular mechanisms leading to the high degree of mutability observed in certain types of tumors and to clarify how these same mechanisms can influence tumor evolution and therapeutic response, with the ultimate goal to effectively tailor treatment to each individual tumor patient. We will use the Hartwig Medical Foundation (HMF) WGS cancer dataset to compare the type, number and genomic distribution of somatic mutations across different tumor subtypes, ultimately gaining insights into the precise factors that lead to tumor initiation, growth and evolution.

Edison Liu, The Jackson Laboratory, United States

We recently finalized an extensive genomic analysis of breast and prostate cancer, which provided important novel insights into the biology of these diseases and identified clinically relevant subgroups of patients who might benefit from specific therapies. With this project we aim to identify how transcriptome changes deepen our understanding of disease progression and improve predictive subgrouping. This will be achieved through pan-cancer analysis of different RNA types (mRNAs, lncRNAs, circRNAs, fusions, etc.) and integration with the genomic changes and clinical data. The RNA-Seq analyses will identify novel cancer-associated transcripts and new predictive and prognostic genes, strengthening classification on genome-level. Our ultimate goal is to improve personalized cancer treatment for patients with metastatic cancer.

John Martens, Erasmus MC, the Netherlands

The purpose of this project is to study the evolution of clonal heterogeneity in progressive solid tumors, including breast, ovarian, lung and brain, using single-cell sequencing in response to treatment. We intend to use the requested data as a validation cohort for the various somatic alterations identified in the tumor subclones revealed by our analyses. We require annotated somatic and germline variants along with clinical information to validate the alterations in our data and to assess clinical relevance. This project will help identify subclonal drivers of drug resistance which may ultimately help improve therapeutic strategies for advanced cancers.

Andrea Bild, Beckman Research Institute of the City of Hope, United States

Priestley et al. (2019), the study introducing the Hartwig Medical Foundation data collection, used several state-of-the-art analysis tools for calling different types of somatic variation. As a result, they provided a number of new candidates of germline and somatic variation with a potential functional role in metastatic cancers. We have recently developed a new variant caller that provides a unified probabilistic framework for calling different types of variation from short substitutions and indels up to large-scale copy-number events. With it, we would like to further refine variation identification to aid in prioritization for functional testing.

Johannes Koster, University Hospital Essen, Germany

We would like to revel mechanisms underlying cancer genome instability by analyzing the genomics data. For that purpose we would like to obtain mutation, structural variation, copy number changes calls; mRNA seq data. Mutagenesis and other types of genome instability have been previously established as important landmarks and/or causes of cancer. Understanding causes of metastatic cancer genome instability may result in improved metatsasis prevention. Extended knowledge about mechanisms undelying genome instability in metastatic cancers may help in planning individualized treatment strategies reducing the chance of metastases.

Dmitry Gordenin, National Institute of Environmental Health Sciences, United States

HER2-positive breast cancer is an aggressive subtype driven by amplification of the Her2/Erbb2 gene. This oncogene is thought to be amplified via chromothripsis, a catastrophic event that causes massive genomic rearrangements. Characterizing chromothripsis in HER2-positive breast cancer is an important step towards improved therapeutic targeting. We will use whole-genome sequencing data to identify structural rearrangements at single nucleotide resolution and infer mechanisms of chromosome shattering and repair. We hope to understand whether chromothripsis associated with poor outcome in HER2-positive breast cancer, the prevalence in metastatic vs. non-metastatic tumors, and how treatment influences chromothripsis.

Christina Curtis, Stanford University School of Medicine, United States

Oesophageal adenocarcinoma (EAC) is an aggressive cancer with a poor overall prognosis. Our data from shallow sequencing of 95 patients with EAC show a worse prognosis in patients who present a homozygous germline deletion of ADAM3A gene, treated with chemoradiotherapy according to CROSS schema. Approximately 20% of the European population shows deletion in this region, however the frequency and consequences of this deletion are not yet well characterised in patients with cancer, in general. The aim of this data request is to investigate the association of ADAM3A germline and somatic deletions in patients with metastatic cancer and to elucidate the role of this deletion in prediction of clinical outcome in patients treated with different chemo(radiation) regimens.

Liudmila Kodach, NKI-AvL, the Netherlands

This project will validate the role of a gene thought to be involved in causing mitotic catastrophe when cancer cells try to divide, spilling DNA out of the nucleus. We will achieve this by assessing structural variations in the genome that are caused in cancer cells that manage to survive this process, and correlate the level of these changes with the presence of copy number changes and mutations in this gene. Presence of this defect would suggest vulnerability to treatment with established and emerging cell cycle checkpoint inhibitors and other DNA repair targeted therapies. Identification of the frequency of this event and the cancer types it is prevalent in will guide future preclinical investigation and clinical trials.

Matthew Wakefield, The Walter and Eliza Hall Institute of Medical Research, Australia

Immunotherapy can achieve great results for NSCLC patients, yet this costly therapy is only efficient in a small number of patients. Our goal is to see whether RNA data, being a level closer to the proteins produced than DNA, can be used to identify which patients will respond. To do so, we plan to combine RNA expression data with clinical data. RNA data to identify which genes are relevant, and clinical data to minimize confounding by other factors and ofcourse to identify responders and non responders.

Harry Groen, UMCG, the Netherlands

Colorectal cancer (CRC) is the second most common cause of cancer death worldwide. Cancer is caused by DNA alterations. Detailed information about DNA alterations in tumors from clinically well-characterized CRC patients offers excellent opportunities for translational research. The main purpose of this project is to facilitate querying and viewing of the HMF CRC data by members of the HMF focus group, allowing individual researchers to easily judge whether the HMF CRC dataset is (not) suited to address their specific research question(s).

Data:
• DNA whole genome sequencing data from CRC samples, indicative for the landscape of genomic aberrations in CRC patients.
• RNA sequencing data, indicative for biological consequences of DNA alterations.
• Clinical and pathological data, to relate DNA mutations and RNA expression data to clinical characteristics.

Relevance for patient:
Easy querying and viewing of HMF CRC data in cBioPortal will stimulate the use of HMF CRC data for translational research purposes. Facilitating initiation of discovery and validation studies will ultimately lead to better disease management of CRC patients.

Remond Fijneman, NKI-AvL, the Netherlands

Purpose: Colorectal cancer (CRC) is the second most common cause of cancer death worldwide. Cancer is caused by DNA alterations. Little is known about the prevalence and biological and clinical relevance of genomic regions that are affected by chromosomal breakpoints. The aim of this project is to learn more about the prevalence of chromosomal breakpoints in colorectal cancer, and their biological and clinical consequences.

Data: DNA whole genome sequencing data from CRC samples, to determine the landscape of genomic regions affected by chromosomal breakpoints. RNA sequencing data, to determine biological consequences of DNA breakpoints; and clinical data to relate DNA mutations to clinical characteristics. We will use lung cancer and breast cancer data in addition to CRC data, to determine organ-specificity of the chromosomal breakpoints.

Relevance for patient: Better knowledge about DNA mutations will lead to biomarkers for better diagnosis, prognosis, prediction of therapy response, and treatment monitoring of CRC patients.

Remond Fijneman, NKI-AvL, the Netherlands

By performing exome sequencing in matched primary and metastasis lesions from treatment-naïve genetically engineered models of metastatic breast cancer our laboratory has identified a number of recurrently mutated genes that are highly enriched in metastatic lesions. Preliminary functional analysis has validated at least some of these genes as metastasis drivers in the animal models. We therefore would like to examine the human metastasis sequencing data to determine whether these genes might also be mutated in human breast cancer metastases to assay the potential role in mediating human breast cancer progression.

Kent Hunter, National Cancer Institute, United States

Estrogen Receptor is a hormone-responsive protein, responsible for breast tumor growth. We found that DNA-binding specificity can predict treatment response, and profiled estrogen receptor/DNA interactions in over 100 breast tumors. Now, we aim to determine whether these bound-regions are mutated in breast cancer, and how this impacts tumor biology. For this, we request access to data from the metastatic breast cancers sequenced at the HMF. In metastatatic breast cancer, estrogen receptor remains critically important. We know that this DNA occupancy differs between patients, whether mutations at these sites alter biology is unknown. This information may explain why some tumors are resistant to therapy, and how we can resolve this.

Wilbert Zwart, NKI-AvL, the Netherlands

Mutations are generated by endogenous (replication errors) and exogenous processes (UV light). Studying the mutational patterns observed across both genes and the entire genome of metastatic patients, we plan to elucidate the interplay of endogenous and external factors that ultimately shape the mutational processes. Based on the knowledge acquired on mutational processes we will improve the methods to detect signals of positive selection in both coding and non-coding elements, in order to accurately identify those involved in tumorigenesis.

Nuria Lopez Bigas, IRB Barcelona, Spain

Our group produces WGS data for 100 Non-Melanoma Skin Cancers (NMSC) in order to characterise mutational landscape and driver mutations in relevant tumor types. Produced data will be compaired with the mutational landscapes of publically available skin cancers genomes. Understanding of the mutational process in skin cancers which are characterised by high mutation rates as well as characterisation of the mutated cancer pathways may be useful for chosing optimal treatment strategy.

Sergey Nikolaev, Gustave Roussy Cancer Campus, France

We have mapped in metastatic prostate cancer how genes are being regulated. Now, we aim to combine these results with mutations and gene activation status in these and other tumor samples, aimed to better understand how prostate cancer gene regulation and mutations are connected. Metastatic prostate cancer samples.

Wilbert Zwart, NKI-AvL, the Netherlands

Mutational signatures are patterns of mutations that inform us on the mutational process underlying tumorigenesis. We will investigate the mutational signatures caused by chemotherapeutics, to better understand how chemotherapy affects cancer cells. We will use all the sequencing data from tumors that were treated with chemotherapeutics prior to surgery to discover the mutational signatures. Mutations induced by chemotherapy can play a role in how cancers develop resistance to the chemotherapy, therefore understanding where those mutations are likely to form will help us understand how resistance could develop. This knowledge can guide us in avoiding/overcoming resistance to chemotherapy.

Steve Rozen, Duke-NUS Medical School, Singapore

Systematic analysis of cancer genomes has revealed a number of characteristic mutational signatures. Some of these have been linked to endogenous processes induced by inherited or somatic pathogenic variants, or by exogenous challenges, like exposure to UV-light, chemotherapeutic drugs or other types of mutagenic agents. In this research, we will explore, characterize and validate mutational patterns, signatures and processes in primary and metastatic cancer patients. The results of this study will provide a better understanding of the processes that are operational at different stages of carcinogenesis. Such information may be used for design of preventive strategies (for tumorgenesis or metastatic seeding) but can also be used for stratifying patients towards targeted treatments based on such characterics (e.g. homologous recombination deficiency as we have already demonstrated by development of the CHORD algorithm, DR-018).

Edwin Cuppen, University Medical Center Utrecht, the Netherlands

 

An aggressive subtype of colorectal cancer (CRC) harbours activating mutations in the BRAF oncogene and inactivating mutations in the RNF43 tumor suppressor gene. The purpose of this study is to assess BRAF and RNF43 copy number variation (CNV) and mutant allele frequency (MAF) in these tumors. Using whole genome sequencing data from BRAF/RNF43 mutant tumors we aim to assess whether selective amplification of the mutant BRAF allele is a frequent event in mCRC, and how this relates to loss of RNF43. Such genetic events may have an impact on the tumor response to drugs targeting the MEK/ERK and WNT pathways.

Onno Kranenburg, University Medical Center Utrecht, the Netherlands

The treatment of bladder cancer patients with immunotherapy is a very promising and effective treatment. However, only a minority of patients responds to the treatment with only immune therapy (up to 30%). These patients benefit from this treatment and do not need other treatments, whereas other patients do need some other form of treatment. We have performed a study: the RESPONDER study to collect multiple different tissues from patients including a CPCT-02 biopsy. In this proposal we aim to combine the data on immune monitoring/ circulating tumor derived DNA (ctDNA) analysis and clinical outcome with the genomic data obtained by the HMF to improve the identification of those patients that are at risk of failing treatment and those patients that could be spared from potentially toxic combination treatments.

Martijn Lolkema, Erasmus MC, the Netherlands

The purpose of our project is to derive genomic signatures based on presence of structural rearrangements and copy number from high resolution WGS data of advanced prostate cancer biopsies. The data we plan to use are the 212 high resolution WGS from the Lisanne F. van Dessel, et. al. study (The genomic landscape of metastatic castration-resistant prostate cancers using whole genome sequencing reveals multiple distinct genotypes with potential clinical). We aim to characterize the presence of specific signatures associated with the presence of mutations in DNA repair genes; with the final goal of using them as biomarker for predicting which patients could benefit from specific treatments.

Joaquin Mateo, Vall d’Hebron Institute of Oncology, Spain

The main purpose of the research project is to develop new diagnostic biomarkers that will be used for personalised therapy selection in glioma patients. We will download the genomes of Central Nervous System (CNS) tumors from the Hartwig Medical Foundation and perform Whole-Genome Sequencing (WGS) data analyses with particular emphasis on the assessment of development of new diagnostic tool predicting the response to temozolomide. This data mining will also demonstrate the trajectories of cancer development, for example genome-wide response to inflammation and molecular mechanisms responsible for the origin of the mutational signatures.

Paweł Zawadzki, Paweł Zawadzki, Adam Mickiewicz University, Poland

Pancreatic cancer and esophagogastric cancer are among the most deadly forms of cancer: despite intensive treatment with chemotherapy and / or surgery, the majority of patients die from the disease. In PEGASUS we investigate whether molecular techniques are of value in predicting which patients will benefit from such intensive treatment, both with regard to the chance of survival as well as quality of life. We are also investigating whether there are molecular targets that could improve treatment even further with patient tailored drugs. We will weigh the costs of using molecular techniques against the benefits and risks for the patient.

Hanneke van Laarhoven, Amsterdam UMC, the Netherlands

The main purpose of the research project is to understand the mechanism of interplay between DNA repair pathways associated with acquired chemotherapy resistance. We will download the genomes of ovary cancer patients from the Hartwig Medical Foundation and perform whole-genome sequencing data analyses with particular emphasis on the assessment of DNA repair pathways and its correlation with clinical outcomes. This data mining will reveal the genetic differences between sensitive and resistant tumors and a dominant mechanism that provides the resistance in clinics.

Paweł Zawadzki, Adam Mickiewicz University, Poland

The nature and impact of genomic changes induced by cisplatin treatment of germ cell tumors is unknown. This is relevant to identify mechanisms of treatment sensitivity and resistance. Genomic data on metastatic germ cell tumors will be compared with primary (non-metastasized) cases, supported by cell line-based observations. Recent data demonstrate that heterogeneity exist in the genomic constitution of primary human germ cell tumors before chemotherapy treatment. Selection of a defined subclone is likely related to treatment resistance, which might help to identify the mechanism involved, being the basis for development of alternatve treatment strategies.

Laurens van der Vlier, Princes Maxima Centrum, the Netherlands

If we are able to better predict who will respond to treatment, this could have major implications for clinical practice. By better identification of patients who will benefit from treatment, we would prevent patients from undergoing aggressive treatment in the end stage of their lifes from which they will not benefit, with as an added benefit reduced health care costs.

Marcin Imielinski, Weill Cornell Medicine, United Stated

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in adults. Since 2005, standard treatment consists of surgery followed by radiation therapy with concurrent and adjuvant temozolomide chemotherapy, taking ± 8.5 months in total. Despite optimal treatment, GBM outcome is almost inevitably fatal, usually within 16 months after diagnosis. There is an urgent need to improve treatment of patients with GBM, both by selection of patients most likely to respond to standard therapy, as well as through the identification of novel targets for [combination] treatment.

Filip de Vos, University Medical Center Utrecht, the Netherlands

DR-093 is an extension of DR-060 en DR-076

While localized prostate cancer can be cured, metastastatic disease is associated with high morbidity and mortality. Prostate cancer typically metastasizes to lymph nodes and the bone, while metastases to organs like liver, lung or the peritoneum are less common. This project is aimed to describe what the differences are in the genomic (DNA) make up of prostate cancer metastases in the different sites. Knowledge hereof might spark further research into ‘site-preference’ and ‘site-specific alterations’ of the prostate cancer metastases genome, which ultimately might result in means to better treat or even prevent metastases.

Andre Bergman, NKI/AvL, the Netherlands

This project concerns a feasibility study, in which tumor biopsies collected in different hospitals in the CPCT-02 trial will be used to perform extensive protein analysis. The results of the DNA analysis and protein analysis will be compared to see how changes in the tumor DNA translate to the protein profile in the tumor, for better understanding of tumor biology. In the future, we hope to develop an integrated analysis of tumor DNA and protein profile, in order to better predict which patients will benefit from targeted therapy.

Mariette Labots, Amsterdam UMC, the Netherlands

Venous thromboembolism (VTE), a venous blood clot,  frequently occurs in cancer patients, and substantially affects morbidity, quality of life, and mortality. Yet, it is incompletely understood why cancer patients are at increased risk of this disease. The risk of VTE varies greatly across cancer types, strongly suggesting a role for cancer-specific oncogenic mutations which indirectly cause thrombosis. 
We aim to investigate this possible association by using clinical data and genomic data from tumor biopsies acquired within the CPCT-02 study. Results could help understand the pathogenesis of cancer-associated venous thromboembolism, lead to new therapeutic targets, and identify high-risk patients for thromboprophylaxis.

Harry Büller, Amsterdam UMC, the Netherlands

The introduction of new therapeutic options, i.e. antiangiogenic drugs and immunotherapy, has significantly changed the treatment and perspectives of patients with advanced and metastatic renal cell cancer (RCC). Currently, the choice for first-line treatment is based on a risk calculation model, using only clinical parameters such as performance status. The aim of the current project is to describe the genomic landscape of RCC patients focusing on the immunogenic and angiogenic mutations/genes. More insight into immunogenic and angiogenic driver mutations together with the genomic landscape of RCC may contribute to improved and more individualized therapeutic decision making.

Astrid van der Veldt, Erasmus MC, the Netherlands

We aim to stratify cancer types by the degree of intratumour heterogeneity demonstrated both between metastases (when the cancer spreads) and primary disease (observed at the initial cancer diagnosis) as well as within the metastases or primary tumors themselves. To do this we will use the same techniques to analyse the metastatic data from the Hartwig Medical Foundation as we have previously used in the TRACERx (Tracking cancer evolution through therapy) prospective clinical trial (ID: NCT01888601) to contrast and compare the mutation and chromosomal alteration heterogeneity present in the data held by Hartwig Medical Foundation with data from primary tumors in our studies. By comparing and contrasting these patterns of heterogeneity across cancer types we will determine whether cancers that metastasise have similar or different patterns of intratumor heterogeneity to those that do not. These patterns may give us insight that helps identify which patients are likely to suffer from metastasis.

Charles Swanton, The Francis Crick Institute, London, United Kingdom

The treatment of metastatic colorectal cancer (mCRC) is still based on traditional chemotherapies. mCRC is a very heterogeneous disease, and a tumor from a single patient might respond to one therapy, but not to the other. Unfortunately, personalized cancer treatment for chemotherapy is currently lacking, since we are not able to correctly predict chemotherapy response upfront. Consequently, patients do not always get the optimal (order of) treatment. By looking at the cellular composition of a tumor (i.e. all different cell types), we aim to optimize the chemotherapy choice and select the most effective therapy for every individual patient.

Emile Voest, NKI/AvL, the Netherlands

Breast cancer is the most common cancer among women Worldwide. Inherited variants in breast cancer susceptibility genes or other regions in the genome that increase breast cancer risk play an important role in the development of breast cancer. These germline genetic variants facilitate the establishment of risk prediction models for women. Furthermore, understanding of the mechanisms by which these genetic variants cause the development of breast cancer is important to devise novel prevention and treatment strategies for women who carry these variants. Here we aim to discover novel germline genetic variants and the features associated with currently known variants.

John Martens, NKI/AvL, the Netherlands
Marjanka Schmidt, Erasmus MC, the Netherlands

Numerous environmental triggers have been found to leave a footprint on the DNA of human cancers. By treating human cells with bacteria which frequently occur in colorectal cancer, we have identified the first mutational signature caused by a bacterium. Now we aim to determine how many mutations of cancer patients can be attributed to this signature. Furthermore, we want to search for bacterial genetic information in patient sequencing data and evaluate if more bacterial DNA correlates with this mutational signature. Our results may help identify subgroups of individuals at risk, paving the way for better screening and prevention measures.

Hans Clevers, Hubrecht Institute Utrecht, the Netherlands 

Personalized medicine driven treatments in major diseases like non-small cell lung cancer (NSCLC) and melanoma offer important health benefits to specific genetically determined subgroups, but can be expensive and may induce severe side effects. Whole Genome Sequencing (WGS) simultaneously tests for all relevant genetic aberrations in tumor tissue from individual cancer patients thereby allowing immediate selection of optimal therapy. This approach is likely to improve patient survival, avoid adverse effects, and to assist in controlling health care costs by offering treatment to only those identified to benefit. The TANGO project aims to detect the most effective way of using WGS in clinical practice by comparing with standard of care diagnostics, in order to let all NSCLC and melanoma patients benefit from personalized medicine driven treatments.

Edwin Cuppen, University Medical Center Utrecht, the Netherlands

Insights into the genomic landscape of metastatic tumors have learned us that metastasis acquire genomic alterations over time and during treatment. Those alterations could be informative on the sensitivity of the tumor to specific therapies. Taxanes are chemotherapy agents widely used for the treatment of different tumor types. The aim of this project is to identify genomic alterations associated with outcome to taxane-based chemotherapy.

Stefan Sleijfer, Erasmus MC, the Netherlands

Gallbladder cancer (GBC) is a rare cancer type in most countries, and carries a dismal prognosis because of its aggressive behaviour and absence of effective treatment options. Only a minority of patients is eligible for surgical resection at time of diagnosis, which offers the only chance of cure. Moreover, the scarce literature on GBC shows extensive molecular heterogeneity between tumors. By exploring the genetic spectrum of GBC, we aim gain to a better understanding of the complex biology of GBC and aim to identify tumor-specific alterations that provide novel therapeutic targets for tailored treatment.

Marjolijn Ligtenberg, Radboud University Medical Center, the Netherlands

Immunotherapy is being tested as a treatment option for patients with metastasized gastrointestinal (GI) malignancies (colon/stomach/esophagus). Only a subset of these patients benefit from this therapy and adverse reactions with regards to autoimmunity are common. However, there are currently no diagnostic tools to discern responders from non-responders. Recent evidence shows an important role for the cells adjancent to the tumor cells, collectively called tumor stroma, in suppressing the immune system. Therefore, we will investigate the ratio between the tumor and stromal cells (tumor-stroma ratio/TSR) in tumors of patients with gastrointestinal malignancies and see whether this can predict response towards immunotherapy.

Lukas Hawinkels, Leiden University Medical Center, the Netherlands

This project aims to identify biomarkers (obtained by whole genome sequencing) that are predictive for response to immunotherapy (check-point inhibitors) in melanoma patients. As more than half of the patients do not respond to immunotherapy, which is a very expensive treatment and may induce severe side effects, ability to identify these patients before start of treatment would have an enormous impact on quality of life and care budgets, which will also be studied as part of this project.

Fons van den Eertwegh, Amsterdam UMC, the Netherlands

In this project we aim at combining somatic mutations at the whole-genome level with information about the epigenetic structure of cancer cell genomes from orthogonal data. The goal is to study the influence of the epigenome on the accumulation of somatic mutations and the identification of epigenetic determinants of cancer evolution.

Andrea Sottoriva, The Institute of Cancer Research, London, UK

The human genome contains tens of thousands of recently-discovered genes called long noncoding RNAs (lncRNAs). It is unknown whether mutations in lncRNAs can drive metastasis. Such “metastasis-driver-lncRNAs”, if they existed, would be attractive targets for therapy. In our previous work with the International Cancer Genome Consortium (ICGC), we have developed bioinformatic methods to identify driver lncRNAs in primary tumors using whole-genome mutation maps. In this project, we aim to use similar approaches to identify metastasis-driver-lncRNAs

Rory Johnson, University of Bern, Switserland

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in adults. Since 2005, standard treatment consists of surgery followed by radiation therapy with concurrent and adjuvant temozolomide chemotherapy, taking ± 8.5 months in total. Despite optimal treatment, GBM outcome is almost inevitably fatal, usually within 16 months after diagnosis. There is an urgent need to improve treatment of patients with GBM, both by selection of patients most likely to respond to standard therapy, as well as through the identification of novel targets for (combination) treatment.
Whole genome sequencing is a personalised medicine approach that can be applied to characterize the complete DNA sequence of individual patient’s tumors. Thus far, tumor specimen of 80 patients with GBM have been collected in the Dutch Center for Personalized Cancer Treatment (CPCT) biopsy study, together with information on the response to temozolomide-based chemoradiation.
In this research proposal, a multidisciplinary team of Dutch neurologists, oncologists and neuro-surgeons propose to investigate the relation between the genetic properties of these tumors and response to temozolomide-based treatment.

Pim French, Erasmus MC, the Netherlands

DR-076 is an extension of DR-060

In this project we aim at combining mathematical modelling of tumor evolution with cancer genomic data to measure fundamental evolutionary characteristics of metastatic tumors. These measurements will allow better understanding of how tumors spread to distant parts of the body. Importantly, we anticipate that the patient-specific ‘evolutionary rules’ we will measure from the data may be informative in terms of stratifying patients between good versus poor prognosis. Moreover, some of these measurements may also be predictive of the effectiveness of certain treatments.

Andrea Sottoriva, The Institute of Cancer Research, London, United Kingdom

DR-075 is an extension of DR-052

The overall goal of this project is to characterize the molecular and therapy response landscape of metastatic cancers through computational data integration. We will focus on the samples from the data base where both RNAseq and WGS data are available. We aim to identify activated pathways/modules and (intergenic) regulators of these modules and to employ these to map the pan-cancer landscape of metastatic cancer. We also aim to construct predictors of drug response derived from the patient response data as well as transferrable predictors built on cell lines to stratify patients for drugs they have not been exposed to and hence enable drug repurposing.

Lodewyk Wessels, NKI/AvL, the Netherlands

In this project we aim to use whole genome sequencing data to improve the way we treat patients with prostate cancer. Providing a better understanding of the subgroups with different clinical and genomic characteristics may improve the treatment outcomes. To this end we need to know which alterations are present in the tumor genome of prostate cancer samples.

Martijn Lolkema, Erasmus MC, the Netherlands

DR-071 is an extension of DR-011

Small intestinal neuroendocrine tumors (SI-NETs) represent a heterogenous group of rare tumors. At time of diagnosis approximately 50% of patients present with metastasized disease (Frilling 2014)1. Patients with metastasized disease are (usually) ineligible for curative surgery and have few treatment options with limited survival benefit. Unraveling the molecular events underlying SI-NET tumorigenesis could facilitate the identification of therapeutic targets and improve prognosis. In order to expand the limited existing knowledge on molecular factors in SI-NETs and move towards personalized treatment, we would like to study somatic and germline mutations of SI-NETs by using DNA next generation sequencing.

Margot Tesselaar, NKI/AvL, the Netherlands

1 Frilling A, Modlin I, Kidd M, Russel C, Breitenstein S, Salem R et al (2014). Recommendations for management of patients with neuroendocrine liver metastases. The Lancet Oncology15(1), pp. e8-e21

Cancer is a disease of the genome. Random factors, environmental exposures and also certain biological mechanisms have the potential to cause mutations in DNA, while the sophisticated DNA repair mechanisms available to human cells prevent such changes in genes. We will use the whole-genome sequences from metastatic tumors to examine how the balance between DNA damage and DNA repair shapes the mutation patterns observed in cancer. This is relevant to patients because we will further investigate how such mutational patterns are associated with risk of cancer progression and with response to various drugs, with implications to prevention and treatment.

Fran Supek, IRB Barcelona, Spain

Breast cancer is the most common malignancy among women wordwide. To reveal the genomic landscape of metastatic breast cancer, we recently performed an extensive genomic analysis which provided important novel insights into the biology of metastatic breast cancer  and identified clinically relevant subgroups of patients who might benefit in the future from specific therapies. With this project we aim to correlate the findings on the DNA level with data generated from RNA. This will lead to increased knowledge of metastatic breast cancer and probably provides new predictive and prognostic information by integrating these two data sources. Finally, our goal is to improve personalized cancer treatment for patients with metastatic breast cancer.

John Martens, Erasmus MC, the Netherlands

Many viruses that commonly infect humans have been found to fuse cells. Evidence suggests that the products of cell fusion can retain some characteristics of the original cells, but that they can also develop malignant characteristics, accelerate cancer progression, and facilitate spread to secondary sites (metastasis). 
Using whole genome sequencing data we aim to identify tumours in which virus-induced cell-cell fusion may have played a role, and potentially contributed to metastasis.  This will lead to novel insights into the origins of metastasis, and may be used to identify patients who are at risk of virus-induced cell-cell fusion mediated metastasis.

Maria Jakobsdottir (before David Wedge), University of Oxford, United Kingdom

Cancer affects millions of people worldwide. Current DNA sequencing technologies allow routine screening of patients for cancer-associated mutations that can be targeted in personalized cancer treatments. Accurate computational methods for the identification of mutations, in particular structural variants (SVs), are lacking, together with methods that can prioritize mutations for further intervention. To solve this problem, we are developing a new set of machine learning approaches that can learn to detect SVs directly from ‘raw’ sequencing data and prioritize them for clinical intervention based on multiple sources of genomic information. Our work will open up a new avenue of machine-learned SV detection and prioritization, and accelerate the introduction of SV-based screenings for new treatments in clinical settings.

Jeroen de Ridder, UMC Utrecht, the Netherlands

We will analyse the Hartwig Medical Foundation metastatic cohort with advanced network analysis techniques to identify genes and key pathways that drive the onset of metastatic cancer and in particular metastatic prostate cancer. This fundamental insight in the genetic origin of metastatic prostate cancer will help identifying biomarkers that can optimally stratify patients for metastasis directed therapies.

Kathleen Marchal, Ghent University (UGhent), Belgium

Despite the fact that completion of human genome project that was announced over 15 years ago, our knowledge of human genomes is still incomplete. The most challenging pieces missing from our genome “blueprint” are large insertions that are not present in genome of every individual or located in genomic regions that are difficult to assemble. The aim of this project is to identify such segments, finemap them to chromosomes and characterize their molecular function. The completeness of genome reference will greatly simplify, speedup and improve analysis of genomic information from wide range of samples: from healthy subjects to cancer patients.

Victor Guryev, UMC Groningen, the Netherlands

Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy that arises from the mesothelial surfaces of the pleural cavity. Currently no curative treatment options are available. Recently, promising new treatment options have emerged, including immune checkpoint inhibitors and cell based vaccines. In order to give the best therapy to each patient, a better understanding of the tumor cells and their interaction with their microenvionment is necessary. We would like to investigate how abberations in the genetic material of the tumor can lead to the development, maintenance and progression of  the tumor and how different therapies can influence these processes.

Joachim Aerts, Erasmus MC, the Netherlands

We aim to apply computational tools to Hartwig Medical Foundation cancer genomes to establish the order in which harmful mutations were acquired, and approximately when they were acquired during a patient’s lifetime. Furthermore, we can infer what caused the mutations (for example, smoking, UV light, etc.), and estimate when the cell was exposed to these damaging processes. Across many cancer samples, this approach lets us build a picture of how different cancers evolve over time. By comparing these results to earlier analyses we performed on primary tumours (observed at initial cancer diagnosis), we seek to understand the development of cancer as it spreads from the initial site to another site (known as metastasis). This will show whether tumours that metastasise evolve in the same way as non-metastatic cancers, and may give insight that helps to predict the metastatic step in cancer evolution.

Peter van Loo, The Francis Crick Institute, United Kingdom

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in adults. Since 2005, standard treatment consists of surgery followed by radiation therapy with concurrent and adjuvant temozolomide chemotherapy, taking ± 8.5 months in total. Despite optimal treatment, GBM outcome is almost inevitably fatal, usually within 16 months after diagnosis. There is an urgent need to improve treatment of patients with GBM, both by selection of patients most likely to respond to standard therapy, as well as through the identification of novel targets for [combination] treatment.
Whole-genome sequencing is a personalized medicine approach that can be applied to characterize the complete DNA sequence of individual patient’s tumors. Thus far, tumor specimen of 80 patients with GBM have been collected in the Dutch Center for Personalized Cancer Treatment [CPCT] biopsy study, together with information on the response to temozolomide-based chemoradiation. In this research proposal, a multidisciplinary team of Dutch neurologists, oncologists and neuro-surgeons propose to investigate the relation between the genetic properties of these tumors and response to temozolomide-based treatment.

Filip De Vos, UMC Utrecht, the Netherlands

In order to enable the next phase of genomic discovery and build a mutational atlas for future Precision Oncology purposes in pancreatic cancer, we wish to create a harmonised genomic dataset spanning all stages, from pre-cancerous lesions, primary resectable tumours to metastatic disease. This will provide an accurate map of cancer driving mutations and the relative timing of their accrual during disease progression, hence allowing early detection of disease, therapy optimisation and to design new drugs.

Sean Grimmond, University of Melbourne, Australia

The treatment of inoperable metastatic colorectal cancer consists of systemic treatment through chemotherapy with or without additional targeted treatment. Until now, no good model exists to provide personalized treatment and to predict which treatment could benefit individual patients the most. With this project we aim to reveal the genetic landscape of metastatic colorectal cancer. This will not only lead to an increased knowledge of the metastatic disease, but it will provide new information on the possible predictive potential of this information. With this combined knowledge we want to improve personalized medicine options for patients with metastasized colorectal cancer.

Saskia M. Wilting, Erasmus MC, the Netherlands

We aim to identify and characterize the molecular and cellular factors that distinguish cancer cells that metastasize from cancer cells that do not migrate. Discovering and better understanding these factors will enable the development of treatment options that specifically target the metastatic process.

Roel Verhaak, The Jackson Laboratory, United States

The use of molecular pathology (for example DNA-testing) has increasingly allowed the selection of the right treatment for the right patient (personalized medicine). Nonetheless, the majority of anticancer treatments remains not patient-specific. As a result, patients still receive ineffective treatments. A possible explanation for this might be found in the tumoral heterogeneity (ie. the presence of different types of cells). Recently, an computional algorithm (Tumor Cell Deconvolution (TCD)) has been developed in breast cancer patients to assess the cellular heterogeneity of a tumor, for every patient specific. With the TCD, we can identify specific cell types, and can explore whether these specific cell types determine the response to therapy.

Emile Voest, NKI/AvL, the Netherlands

Biliary tract cancer (BTC) is malignancy of bile ducts (also called cholangiocarcinoma) and gallbladder. BTC is a rare malignancy in Western countries with a poor prognosis. Surgical resection in the only available treatment that potentially can cure patients with BTC, but most patients present with advanced BTC (including metastatic disease) that can not be completely removed by an operation. Chemotherapy is the standard treatment for those patients with advanced BTC. Treatments with agents directed to DNA changes (targeted therapy) did not show better survival in different studies because of the heterogeneous nature of BTC. To improve the treatment of advanced BTC, a more comprehensive overview of the genomic changes in advanced BTC is required. If we can identify subgroups of patients with different prognosis based on genomic changes, new clinical studies could be initiated to study a specific treatment in one or more of these subgroup of patients.

Heinz-Josef Klümpen, Amsterdam UMC, the Netherlands

The changes to the DNA (mutations) found in a tumor are expected to be largely unique to each tumor as there are 3 billion places in the DNA that can be changed. However, in a cancer study with 2,583 participants we observed over a million non-unique mutations. We used characteristics of these mutations and all mutations detected, to classify the tumors into 16 groups that have clinical relevance. We want to refine these classes to gain further insights into the biological processes inducing mutations (‘mutagenesis’), inform on treatment, help in diagnosis, and predict the origin of a metastatic tumor.

Ivo Gut, Centro Nacional de Análisis Genómico, Spain

Pancreatic cancer is the fourth leading cause of cancer-realated deaths in the world. Current therapeutic options including chemo-, radio- and combinational therapy are not giving satisfactory results. Therefore, there is an emerging need to develop a novel, effective targeted therapy. Immunotherapy engaging the patient’s own immune system is among the newest approaches to target and destroy tumor cells. The immune system can be trained to recognize cancer specific antigens that are encoded by tumor-specific mutated genes (neoantigens). By analysing the seqeuncing data provided by Hartwig Medical Foundation, a list of the most common neoantigens in pancreatic cancer patients will be generated and utilized to synthesize specific peptides in the form of an off-the-shelf vaccine ready to be used for a broad audience. This project is part of the Oncolytic Virus Immune Therapy (OVIT) consortium aiming to employ viro-immunotherapy to treat patients with aggressive cancer types.

Casper van Eijck, Erasmus MC, the Netherlands

We use whole cancer genome sequences to understand the order of mutations in cancer development so that we can infer which mutations arise early versus late during the process. The ability to determine the order and importance of mutations is critical for early detection and treatment of disease. We can also understand the environmental exposires that cause cancer based on the pattern of mutations.

Paul Spellman, Oregon Health & Science University, United States

 

In this project we aim at combining mathematical modelling of tumor evolution with cancer genomic data to measure fundamental evolutionary characteristics of metastatic tumors. These measurements will allow better understanding of how tumors spread to distant parts of the body. Importantly, we anticipate that the patient-specific ‘evolutionary rules’ we will measure from the data may be informative in terms of stratifying patients between good versus poor prognosis. Moreover, some of these measurements may also be predictive of the effectiveness of certain treatments.

Andrea Sottoriva, The Institute of Cancer Research, United Kingdom

The two strongest factors predicting a human cancer’s clinical behaviour are the primary tumour’s anatomic organ of origin and its histopathology. However, roughly 3% of the time a cancer presents with metastatic disease and no primary can be determined even after a thorough radiological survey. A related dilemma arises when a radiologically defined mass is sampled by cytology yielding cancerous cells, but the cytologist cannot distinguish between a primary tumour and a metastasis from elsewhere. Here we use whole genome sequencing (WGS) data from the ICGC/TCGA PanCancer Analysis of Whole Genomes (PCAWG) and Hartwig Medical Foundation to develop a machine learning classifier able to accurately distinguish among 24 major cancer types using information derived from somatic mutations alone. This demonstrates the feasibility of automated cancer type discrimination based on next-generation sequencing of clinical samples. In addition, this work opens the possibility of determining the origin of tumours detected by the emerging technology of deep sequencing of circulating cell-free DNA in blood plasma.

Lincoln Stein, Ontario Institute for Cancer Research, Canada

Cancer genomes typically harbor a substantial number of somatic mutations. However, only few of these mutations actually contribute to tumor development. To identify these so-called driver mutations, large-scale aggregated sequencing datasets are needed. Over the past decade, the search for driver mutations has been mostly focussed on coding regions. Substantially less is known whether and to which degree mutations in non-coding regions are functionally involved in tumor formation. With the drop in sequencing costs over the past years, it became possible to sequence the entire genomes of large cohorts of cancer patients (e.g. the dataset provided by Hartwig Medical Foundation). However, the avaialalbity of these datasets has not been met with the of algorithms that are particularly designed to the underlying biology of these data yet. The goal of this project is to develop a statistical framework which systematically identifies driver mutations in non-coding regions in aggregated whole-genome sequencing data. For this purpose, we will particularly consider the biological differences between coding an non-coding regions, in order to specifically taylor our algorithm to non-coding regions. Applying this refined approach to ~2500 Whole Genome Sequencing data, we will systematically characterize which mutations in non-coding regions are relevant to oncogenesis.

Eliezer van Allen, Dana-Farber Cancer Institute, United States

Anticancer drugs can (in)directly interfere with DNA and thereby potentially generate a characteristic pattern of somatic mutations (mutational signature). Identifying treatment-specific mutational signatures in a cancer genome will not only improve the mechanistic understanding of the mutational processes of the drug itself, but will also delineate the proportion of the mutational side effects. This research seeks to characterize the mutational patterns that are generated by anticancer drugs and tries to advance our understanding of the mutational signatures with unknown etiology.

Edwin Cuppen, UMC Utrecht, the Netherlands

Resistance to therapy is one of the main challenges in treatment of metastatic breast cancer. We know that treatment resistance is often driven by changes in the genetic material of the tumor. Tumor DNA is, to some extend, detectable in the blood of cancer patients as circulating tumor DNA (ctDNA). Analysis of ctDNA might enable monitoring of response to anti cancer therapy over time and at low impact. The aim of this study is therefore to identify aberrations in ctDNA related to treatment outcome and to see whether those aberrations change during treatment. Furthermore, we aim to explore to what extend ctDNA represents the genomic landscape of metastastic breast cancer. Therefore, our findings in ctDNA and in metastatic tumor tissue will be compared in a subset of patients.

John Martens, Erasmus MC, the Netherlands

Immunotherapies stimulate the patients own immune system to kill tumor cells. These relatively new therapies have shown impressive treatment results in many different tumor types. However, these impressive responses are restricted to only a subset of patients; many patients do not have benefit from these treatments, as the tumors keep growing and the patients suffer from treatment side-effects. We set up an ongoing project in which we try to understand why particular patients are not responding based on their DNA. If we understand this, we could (1) prevent treatment of patients with tumors resistant to immunotherapy and (2) develop strategies to overcome such resistance.

Emile Voest, NKI/AvL, the Netherlands

DR-045 is an extension of DR-009 en DR-023

Cancer develops by accumulation of mutations in the DNA of individual cells. In many patients, DNA repair mechanisms are often perturbed early in cancer development, leading to an increased mutation rate and faster development of the cancer. However, repair deficiencies can also make the cancer cells more susceptible to certain types of treatments. Better understanding and detection of DNA repair deficiencies may thus help improve treatment of cancer patients.

Using the cancer genomics data from Hartwig Medical Foundation, we aim to characterize the pattern of DNA deficiencies across different cancer types. We further aim to improve the detection of DNA repair deficiencies through their effect on mutation rates and patterns across the genomes of cancer cells. Finally, we aim further clarify the relationship between DNA repair deficiencies and cancer treatment efficacy.

Jakob Skou Pedersen, Aarhus University, Denmark

Some cancers are the result of viral infections. A novel type of cancer therapy, called immunotherapy, has been shown to work exceptionally well against such virus-driven cancers. These therapies stimulate the patients own immune system to kill the virus-infected tumor cells. Many viruses have, like humans, a genome of DNA. In this project we are searching for viral DNA within the tumors of patients, to identify the patients with virus-driven tumors. These patients are potential candidates for immutherapy treatment.

Emile Voest, NKI/AvL, the Netherlands

Cancer is driven by accumulation of single DNA mutations, but also by catastrophic events involving multiple simultaneous changes. One such catastrophic event is called kataegis (thunder), which concerns multiple DNA mutations occurring in a small region of the DNA. Using Hartwig Medical Foundation whole-genome repository, we can improve our sophisticated computational methods to better detect such somatic events in cancer patients. By identifying and characterizing these events in cancer we gain insight in the molecular mechanisms that give rise to kataegis. These molecular insights will improve our understanding of the biology of (metastatic) cancer.

Harmen van de Werken, Erasmus MC, the Netherlands

Pancreatic cancer is the fourth leading cause of cancer-realated deaths in the world. Current therapeutic options including chemo-, radio- and combinational therapy are not giving satisfactory results. Therefore, there is an emerging need to develop a novel, effective targeted therapy. Immunotherapy engaging the patient’s own immune system is among the newest approaches to target and destroy tumor cells. The immune system can be trained to recognize cancer specific antigens that are encoded by tumor-specific mutated genes (neoantigens). By analysing the seqeuncing data provided by Hartwig Medical Foundation, a list of the most common neoantigens in pancreatic cancer patients will be generated and utilized to synthesize specific peptides in the form of an off-the-shelf vaccine ready to be used for a broad audience. This project is part of the Oncolytic Virus Immune Therapy (OVIT) consortium aiming to employ viro-immunotherapy to treat patients with aggressive cancer types.

Casper van Eijck, Erasmus MC, the Netherlands

Recent whole genome sequencing efforts have identified a broad spectrum of gains and losses of DNA in cancer genomes. This has led to the identification of novel mechanisms for genome rearrangement like chromothripsis, where chromosomes are shattered and stitched back together in a different order. However, little is known about the prevalence of these types of events throughout different tumor types and their relevance for patient outcome. Furthermore, the data provided by Hartwig Medical Foundation provides unprecedented detail and resolution, enabling us to detect small gains/losses of DNA that would have previously remained unnoticed.

Bauke Ylstra, Amsterdam UMC, the Netherlands

Endometrium cancer is one of the most common gynecological cancer and accounts for approx. 6% of all cancers in women. The vast majority of enometrium cancers are dependent on a hormone receptor, Estrogen Receptor a (ERa). We aim to identify how changes in the DNA sequence of the tumor would affect the function of ERa, and how this would ultimately impact gene activity and tumor cell growth.

Wilbert Zwart, NKI/AvL, the Netherlands

Tumor-specific defect in the DNA repair offer great potential for DNA damage based chemo/radio therapy. Present data implicate that this therapeutic intervention strategy has not been explored sufficiently. To provide optimal therapy with less side effects, there is an unmet need tot take further advantage of cancer-specific defect within the molecular network that controls DNA repair. This project will reveal the novel therapeutic opportunities for patients with tumor-specific DNA repair defects. The mission, optimize tumor intervention strategies to achieve higher cue rates with less side effects by developing optimised pesonalised medicine.

Heinz Jacobs, NKI/AvL, the Netherlands

Neuroendocrine tumors are rare cancers most often arising in the lungs, pancreas or gastro-intestinal tract. Its behavior can vary greatly among patients, from very slowly growing tumors that can be kept under control with a relatively low-impact treatment, to very aggressive tumors that quickly progress despite intensive (chemotherapeutic) treatment. Currently, we cannot optimally select the right treatment for the right patient, possibly because the characteristics we are using to select this treatment are not based on the genetic make-up of the tumor.
A minimally-invasive method to determine which patient will benefit from a certain treatment, is by taking so-called liquid biopsies. In liquid biopsies we look at tumor-specific genetic variations in the blood of our patients. Thus far, the implementation of liquid biopsies in neuroendocrine tumors have been hampered by the lack of a known genetic variation which occurs in the majority of our patients and is thus a suitable liquid biopsy marker.
In this project, we want to explore the genetic charactertistics of metastases of neuroendocrine tumors and use these data to develop a liquid biopsy test by which we can better determine who will benefit from a certain treatment, and who should be spared unnecessary toxicity.

Bianca Mostert, Erasmus MC, the Netherlands

Histological, immunohistochemical and gene expression markers are routinely used to stratify tumours into clinically distinct subtypes, some of which have targeted therapies that improve prognosis. Recent work has shown that unsupervised clustering using genomic profiling can reveal novel subtypes with distinct clinical outcomes. We will explore if stratifying patients directly from whole genome mutation profiles can identify novel subtypes and driver pathways that could lead to improved personalised therapy opportunities.

David Wedge, University of Oxford, United Kingdom

To date, translational cancer genomics has focused on somatic genetics, driven by the desire to identify mutated targets that indicate specific therapies. Therapeutic information is also present within the germline genome. However, this germline information is currently ‘subtracted’ in clinical analytic pipelines, discarding valuable information relevant to therapy. Within this project we will identify and study the value of this inherited germline information.

David Thomas, Garvan Institute Medical Research, Australia

Patients with head and neck cancer too advanced for surgical resection have a very poor prognosis, despite the currently standard, very intensive treatment which consists of a combination of chemotherapy and radiotherapy. Until now we have not been successful in identifying patients with a very poor prognosis. To spare these patients unnecessary treatment and its side-effects, better upfront patient selection is urgently warranted.
A minimally-invasive method to determine which patient will benefit from a certain treatment, is by taking so-called liquid biopsies. In liquid biopsies, we look at tumor-specific genetic variations in the blood of our patients. We are planning to do a study in which we correlate the level of a specific mutation which is often found in head and neck cancer, TP53, with the chance of disease recurrence. We also want to look at other genetic variants in liquid biopsies that are associated with poor prognosis. So far, the known genetic variants have been identified in the original primary tumors. However, genes that are mutated specifically in metastases, which we know can differ from the original primary tumor, are likely largely responsible for its aggressive behavior. Therefore, we will identify recurrent genetic variations in the metastases of patients with head and neck cancer. These variations will then be included in an elaborate liquid biopsy test, which we will correlate with prognosis in our observational study.

Bianca Mostert, Erasmus MC, the Netherlands

This project aims to unravel molecular mechanisms that drive the high metastatic potential of urothelial cancer. In addition predictive markers that correspond with response to chemo- or targeted therapy are urgently needed both in the neoadjuvant and metastatic setting to improve patient stratification.

Joost Boormans, Erasmus MC, the Netherlands

DR-031 is an extension of DR-008

Irinotecan is a widely used cytostatic treatment for a broad range of tumor types. However, response is highly variable making the identifiation of biomarkers that can predict treatment outcome highly desirable. In this project Whole Genome Sequencing characteristics will be explored for all patients that received irinotec treatment and compared with clinical response to the drug.

Martijn Lolkema, Erasmus MC, the Netherlands

This project aims to characterize the genetic landscape of sarcoma tumors and relate this to treatment outcome data. Improving patient care for this relatively rare cancer indication requires the identification of biomarkers that enable stratification of patients towards the most effective therapies. Understanding underlying mechansisms of carcinogenesis, notably driver genes and pathways, is imperative to reach these goals.

Eric Wiemer, Erasmus MC, the Netherlands

The effect of anti-cancer drugs depends on the amount of drug that is present in the tumor cells. If these tumor cells have decreased uptake or increased excretion of a drug, the tumor has less exposure to the drug and therefore the drug might be less effective. Uptake and excretion of drugs is regulated by drug transporters, which we will investigate at DNA level. If (subtypes of) tumors have reduced exposure via this mechanism, it might be beneficial to give higher doses of that drug or to switch to an alternative drug.

Stefan Sleijfer, Erasmus MC, the Netherlands

This project aims to create a systematic overview of the mutation landscape of metastatic breast cancer patients and identify similarities and differences with comparable primary breast cancer data set obtained from elsewhere. This resource may identify patient subcategories that may benefit from different treatment strategies.

John Martens, Erasmus MC, the Netherlands

The aim of our bioinformatics project is to investigate the presence and length distribution in tumors of encoded peptides that result from frameshift mutations. We refer to them as Novel Open Reading Frame Peptides, or NOPs. Such peptides may be important triggers of the immune response.

Jan Koster, Academisch Medisch Centrum, the Netherlands

Most studies have focused on mutations in the few percent of the genome that encode proteins. In this study, large amounts of tumor genomes will be used to identify loci in the non-coding regulatory part of the genome that contribute to tumor development when mutated.

Nuria López-Bigas, IRB Barcelona, Spain

DR-024 is an extension of DR-017

The response to checkpoint inhibitors (immunotherapy) is highly variable between tumor types. The researchers will search for novel biomarkers based on Whole Genome Sequencing and RNA sequencing data accross and within all tumor types to better stratify patients for this treatment type and to understand the underlying biology driving treatment sensitivity or response.

Emile Voest, NKI/AvL, the Netherlands

DR-023 is an extension of DR-009

The DNA in normal – and tumor cells are continuously exposed to internal and external challenges. The objective of this project is to computationally derive specific footprints (signatures) that are left in the tumor genomes. Previous work has shown that environmental challenges like UV radiation and smoking leave very characteristic patterns, as well as intrinsic process like DNA repair deficiencies. Such knowledge is of importance for cancer prevention and treatment strategies.

Serena Nik-Zainal, University of Cambridge, United Kingdom

The goal is to investigate the presence of actionable biomarkers in whole genome sequencing (WGS) data of glioblastoma cases and compare these with results obtained with standard diagnostic targeted gene panels. This research should provide insight in what the best diagnostic strategy would be for this category of patients.

Paul van Diest, UMC Utrecht, the Netherlands

The objective of this project is to assess the value of ‘big data’ approaches for interpreting cancer genomes for diagnostic purposes and treatment decision making. Results of IBM Watson interpretation will be compared with automated curated database approach as commonly used at Hartwig Medical Foundation and other diagnostic centers.

Hans van Snellenberg, Hartwig Medical Foundation, the Netherlands

The goal of this study is to systematically compare the mutation landscape and underlying mutagenic mechanisms that are active in primary and advanced metastatic tumors. This study is expected to provide insight in the molecular mechanisms that drive different stages of tumor development and in the mutagenic effects of specific treatments.

Edwin Cuppen, UMC Utrecht, the Netherlands

Deficiency in DNA repair pathways is a key characteristic in many tumors. The goal of this project is to develop tools based on genome-wide mutation characterists that better detect defects in the homologous recombination DNA repair pathway. This is relevant as such patients may better respond to platinum drug-based therapies or PARPinhibitor targeted treatment.

Edwin Cuppen, UMC Utrecht, the Netherlands

Most studies have focused on mutations in the few percent of the genome that encode proteins. In this study, large amounts of tumor genomes will be used to identify loci in the non-coding regulatory part of the genome that contribute to tumor development when mutated.

Nuria López-Bigas, IRB Barcelona, Spain

The researchers will study the involvement of structural variation in the tumor genomes of colorectal cancer patients and investigate their role in tumor development and treatment response.

Remond Fijneman, NKI/AvL, the Netherlands

In this study genetic factors will be explored that may explain response to standard chemotherapy (FOLFOX/CAPOX/Irinotecan/capecitabine) in coloroctal cancer patients.
These results will be compared and integrated with results obtained with in vitro treated tumor organoids.

Louisa Hoes, NKI/AvL, the Netherlands

DR-015 is an extension of DR-003

This project is focused on biomarker discovery for specific targeted treatments in breast cancer patients. Specific focus will be on patients treated with aromatase inhibitors.

John Martens, Erasmus MC, the Netherlands

The research question is focused on the improvement and development of novel treatment approaches in prostate cancer patients that have become resistant to androgen deprivation therapy. The goal is to identify mechansisms that explain resistance and which could be developed in a circulating tumor DNA test for easy monitoring of treatment response.

Michiel van der Heijden, NKI/AvL, the Netherlands

The goal of this project is to correlate systematic DNA and protein measurement data from the same patients. This pilot may provide indications if multi-level measurements are feasible and provide additive information and form jointly stronger biomarkers. Furthermore, this work may provide insight in the molecular mechanisms that are perturbed by cancer mutations.

Henk Verheul, Amsterdam UMC locatie VUmc, the Netherlands

This project aims to create a systematic overview of the mutation landscape of metastatic prostate cancer patients with a special focus on structural variation. This resource may identify patient subcategories that may benefit from different treatment strategies.

Martijn Lolkema, Erasmus MC, the Netherlands

The goal of this project is to identify inherited mutations in genes that result in higher chances to develop cancer (cancer pre-disposition genes).

Edwin Cuppen, UMC Utrecht, the Netherlands

The response to check-point inhibitors (immunotherapy) is highly variable between tumor types. The researchers will search for novel biomarkers based on Whole Genome Sequencing and RNA sequencing data accross and within all tumor types to better stratify patients for this treatment type and to understand the underlying biology driving treatment sensitivity or response.

Emile Voest, NKI/AvL, the Netherlands

This project aims to identify biomarkers that are predictive for response to immunotherapy (check-point inhibitors) in lung cancer patients. As only ~20 to 30% of patients respond to this very expensive treatment, ability to identify these patients before start of treatment would have an enormous impact on quality of life and care budgets, which will also be studied as part of this project.

Joachim Aerts, Erasmus MC, the Netherlands

In this project, pairs of tumor biopsies are requested to study evolution of tumors over time. This project may provide insights in potential mutagenic effects of specific tumor treatments and resulting from selection pressure and shed light on treatment resistance mechanisms.

Emile Voest, NKI/AvL, the Netherlands

The researchers will explore the prevalance of mutations in the KRAS gene in GIST patients and study the response to specific treatments. This work may result in better stratifiation of patients towards targeted treatments.

Neeltje Steeghs, NKI/AvL, the Netherlands

The goal of this request is to enable Hartwig Medical Foundation Australia team to optimize bio informatic tools and pipelines for the identification of all types of somatic variants to obtain the most complete genetic picture of every individual tumor genome. Data of Hartwig Medical Foundation allows the researchers to test and validate their tools on real-world data.

Hans van Snellenberg, Hartwig Medical Foundation, the Netherlands

The goal of this project is to identify genetic factors that are involved in chemotherapy resistence in ovarium cancer and to identify novel targets for treatment. To this end, the spectrum of genetic aberrations in chemoresistant ovarium tumors will be compared with chemo sensitive tumors.

Edwin Cuppen (previous Wigard Kloosterman), UMC Utrecht, the Netherlands

The objective of this request is to connect genetic information obtained in the CPCT-02 study and in vitro tumor organoid data from the TUMEROID and SENSOR studies form the same patient. This connection allows for the identification and exploration of the potential genetic basis for (in vitro) treatment sensitvity for a broad range of drugs.

Louisa Hoes (previous Fleur Weeber), NKI/AvL, the Netherlands

In this project, data from CRC patients treated with anti-EGFR therapy will be used to identify biomarkers that predict treatement response. A specific hypothesis on the involvement of mutations in the MAPK will be tested which provides novel treatment strategies involving existing MEK inhibitors.

René Bernards, NKI/AvL, the Netherlands

The objective of this project is to determine if the microenvironment of metastases influences mutation patterns. The investigators will test if colorectal cancer tumor lesions that develop as metastases in different tissues show differences in the type of mutations that are accumulated.

Edwin Cuppen (previous Ruben van Boxtel), UMC Utrecht, the Netherlands