DR-188 Leveraging tumor evolutionary dynamics for selection inference in human cancers
Cancer is a genetic disease, caused by changes in the cellular hereditary material. When a cancer tumor is detected, a common clinical practice foresees treatment with chemotherapeutic drugs. If the cancer relapses after this treatment, the resulting metastatic tumors will carry information about which of their genetic features made them resistant to the treatment. We aim to analyze the data from metastatic tumors contained in the Hartwig Medical Foundation cohort in order to investigate connections between the tumor genetic makeup and its response to therapy.
Donate Weghorn Centre for Genomic Regulation (CRG) Spain
DR-187 Discovering non-coding driver alterations and the clinical utility of mutational signatures
Cancers develop by the accumulation of "driver" genetic alterations providing tumor cells a growth advantage. Whole genome sequencing allows to identify these driver events, but also the mechanisms at the origin of genome insults. Our project has two major aims. Firstly, we will use deep learning approaches to discover driver alterations in the non-coding part of the genome that remains poorly understood. Secondly, we will analyze mutational signatures to discover genomic instability phenotypes related to treatment response. Leveraging the tremendous resource of HMF genomic and clinical data, we hope to identify new oncogenic mechanisms and therapeutic vulnerabilities.
Eric Letouze Cordeliers Research Center France
DR-184 Combatting therapy resistance in advanced breast cancer
We are investigating drug resistance mechanisms in two different types of breast cancer, 1) invasive lobular carcinoma (ILC) to PI3K/mTOR inhibitors and 2) BRCA-deficient breast cancer to PARP inhibitor. To this end, we used in-vivo mouse models mimicking human ILC and BRCA-deficient breast cancer and obtained drug-resistant tumors through prolonged treatment of mTOR inhibitor and PARP inhibitor. Genomic and proteomic analyses of the treatment-naive/resistant tumors revealed several resistance factors, which were further experimentally validated by in-vitro experiment. To strengthen and validate our findings in clinical relevance, we believe that the HMF WGS, RNA-seq and treatment response data provide valuable resources.
Daniel Zingg Netherlands Cancer Institute the Netherlands
DR-178 Image-driven prognostic chemotherapy response insights using Artificial Intelligence
Modern machine learning techniques will be applied to the data in an exploratory study in order to identify possible new insights into chemotherapy response. In particular genomic information will be combined with CT and MRI images to identify common morphological characteristics of different pathways.
Sean Benson Netherlands Cancer Institute the Netherlands
DR-176 Responder study, Biomarker discovery study to identify patients with advanced urothelial cancer benefitting from pembrolizumab treatment.
Immune checkpoint inhibitors have been approved for first- and second-line treatment of metastatic urothelial cancer (mUC) patients, and lead to durable clinical responses in a small subset of patients. As a consequence many patients are being exposed to ineffective treatment with the risk of developing (severe) side effects. The aim of this study is to identify potential predictive markers for clinical benefit of immunotherapy. We will use the genomics data to identify predictors based on the sequencing but we will also combine it with other modalities such as staining of tumor biopsies and liquid biopsies. Furthermore, mechanisms underlying primary and acquired resistance to immunotherapy will be studied, potentially facilitating the development of improved (combinatorial) treatment strategies for mUC patients.
Martijn Lolkema Erasmus MC the Netherlands
DR-174 Effects of FHIT gene in cancers
We aim to understand the effects of the FHIT gene in cancers. FHIT is involved in purine metabolism, and contains a fragile site (FRA3B), leading to translocations which have been associated to many types of cancers. Given its function, FHIT is a good candidate gene for cancer. However, previous genetic studies on this gene were small and not conclusive. Here, we will perform a large and comprehensive genetic study shedding light on FHIT role in cancer.
Claudio Toma Centro de Biología Molecular Severo Ochoa (CBMSO) Spain
DR-173 Detection of microsatellite instability in metastatic colorectal cancer: the diagnostic accuracy of routine mismatch repair or microsatellite testing compared to whole genome sequencing.
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 with MSI status based on whole genome sequencing, i.e. gold standard, offers a unique opportunity to clarify this important issue. Therefere, coupling to external parties (PALGA and NKR) is part of this project.
Petur Snaebjornsson Netherlands Cancer Institute the Netherlands
DR-172 Detecting RET gene fusions in lung cancer: multicenter experience and comparison of molecular testing modalities
RET fusion gene testing will soon become very important for selection of lung cancer patients for treatment with the novel tyrosine kinase inhibitor, selpercatinib. In our diagnostic setting we observed that RET in situ hybridization (ISH) testing, a molecular test that is used worldwide for screening lung cancer for genomic breaks at the RET locus often yields false-positive results. As a result patients might be(come) treated wrongly. To explain the many false-positive RET ISH results, we would like to investigate WGS data for the presence of structural variations at the RET locus (versus ALK and ROS1 loci) in lung cancers.
Erik Jan Dubbink Erasmus MC the Netherlands
DR-170 Combining somatic alterations in intergenic, intronic and exonic regions to improve tumor mutational burden estimation by targeted sequencing.
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
DR-169 Assessing drug response in breast cancer tissue samples
Breast cancer (BC) is the most common malignancy among women, constituting the prominent cause of cancer-associated mortality. Despite considerable knowledge of the BC molecular subtypes, there is no strategy for accurate stratification of BC patients. The main purpose of this project is to identify genomic alterations that differentiate patients, who respond and who don’t respond to a particular treatment type. For this purpose, we will perform whole-genome sequencing data analyses on BC patients genomes downloaded from Hartwig Medical Foundation and build clinical predictor. This tool will help in treatment decision-making, indicating benefits and risks connected with a particular treatment type.
Pawel Zawadzki Adam Mickiewicz University in Poznań Poland
DR-164 Functional annotation of the mutated regulatory landscape in glioblastoma
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
DR-163 Molecular archaeology of cancer metastases
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
DR-162 Genomic and transcriptomic analysis of e-cadherin mutated breast cancer
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
DR-160 Predicting the target-landscape of kinase-inhibitors with explainable 3D convolutional neural networks enables selection of highly personalized therapies
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
DR-159 "Genomic characterization of metastatic urothelial carcinoma. DR-159 is an extension of DR-031"
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
DR-158 Measuring the evolutionary dynamics of positive and negative selection in metastatic cancers
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
DR-155 Towards personalized cancer therapy: identifying genomic and transcriptomic features predictive of treatment response in patients with castration resistant prostate cancer.
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.CPCT-2 DNA and RNA sequencing data.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
DR-154 Understanding co-effect of inherited and somatic alterations in cancer
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
DR-152 Cancer evolutionary dynamics
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
DR-151 Characterizing the role of structural variations in prostate cancer
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
DR-150 Discovery and Characterization of Cancer Driver Mutations in Noncoding regions
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
DR-149 Discovery and Characterization of Mutational Processes and Cancer Driver Mutations in Melanoma
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
DR-147 An exploratory study on the prognostic and predictive value of the immune infiltrate in metastastic bladder cancer and its relation with other microenvironmental factors and long non-coding RNAs.
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
DR-146 Treatment with targeted therapy based on genetic profiling by whole genome sequencing in patients with solid tumours
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 Netherlands Cancer Institute the Netherlands
DR-145 Immune and stromal gene expression signature in metastatic prostate and breast cancer
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
DR-142 Genomic landscape of non-small cell lung cancer (NSCLC) tumors and metastases.
Despite the advancements in lung cancer treatment in the last decades, most patients diagnosed with non-small cell lung cancer (NSCLC), still suffer from a severe disease characterized by rapid progression and low survival rates. All cancers are caused by genetic alterations in healthy cells. Lung cancer is characterized by a high number of these genetic alterations. We would like to explore the genetic abnormalities that can be found in lung tumors. These abnormalities can help us predict which patients are likely to respond to different therapies. Furthermore, the analysis can probably lead to the discovery of new targets for patient specific therapy.
Joachim Aerts Erasmus MC The Netherlands
DR-141 Driver mechanisms and regional mutation rates in the non-coding cancer genome
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
DR-140 Landscape of cooperative interactions between germline and somatic events in cancer
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
DR-139 Personalized OncoGenomics: A comprehensive pan-cancer analysis
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
DR-138 Genomic identification and expression of oncogenic FGFR2 structural variants.
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 Netherlands Cancer Institute the Netherlands
DR-137 HEcoPerMed (Healthcare- and pharma-economics in support of the International Consortium for Personalised Medicine)
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
DR-136 Tracking cancer evolution from emergence to metastasis
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
DR-134 The immunogenic potential of recurrent cancer drug resistance mutations: an in silico study
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
DR-133 Pan-cancer investigation of cancer evolution and tumour evolutionary trajectories
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
DR-132 ctDNA analysis to monitor response to neoadjuvant chemoradiation in esohageal cancer patients
"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
DR-131 The link between the immunologic and genomic characteristics of patients with metastatic melanoma and the possible effect on response to (immuno)therapy.
"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
DR-129 Comparing metastatic and primary breast tumours through the lens of integrated subtypes
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
DR-127 "Genetic causes of resistance to new androgen receptor signaling inhibitors in metastasized castration-resistant prostate cancer patients. DR-127 is an extension of DR-013"
"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.
DR-127 is an extension of DR-013"
Michiel van der Heijden NKI-AvL the Netherlands
DR-125 Characterizing genome instability profiles in human cancers
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 USA
DR-123 Pan-cancer RNA landscape analysis to explain functional changes, identify novel biomarkers and therapeutic targets
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
DR-121 Refining the candidate identification of germline and somatic variation with a functional role in metastatic cancers
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
DR-118 The role of chromosomal catastrophe in breast cancer pathogenesis
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 USA
DR-115 The association between the homozygous germline deletion of chromosome 8 (ADAM3A region) and survival of patients with the tumours of digestive system treated with different regimens.
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
DR-104 A comprehensive analysis of mutational processes and signatures in primary and metastatic cancer tumors
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
DR-099 PEGASUS – Pancreatic and EsophagoGastric cAncer, improving Survival and qUality of life through personalized medicine
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
DR-095 Towards the clinical implementation of whole-genome sequencing (WGS) to guide precision oncology
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.
Harry Groen UMCG the Netherlands
DR-094 RNA (immune) markers in non-small cell lung cancer patients treated with immune checkpoint inhibitors (RIMINI)
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
DR-093 Whole genome Sequencing to estimate TEmozolomide Associated Response IN Gliomas (STEARING)
"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.
DR-093 is an extension of DR-060 and DR-076"
Filip de Vos University Medical Center Utrecht the Netherlands
DR-090 Phosphoproteomics for therapy response prediction
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
DR-073 Making HMF colorectal cancer data accessible for the HMF CRC focus group through cBioPortal
"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
DR-072 Chromosomal breakpoints in colorectal cancer
"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
DR-055 The whole-genome landscape of advanced biliary tract cancer
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