# Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

> **NIH NIH R01** · DANA-FARBER CANCER INST · 2020 · $407,175

## Abstract

PROJECT SUMMARY
The increased accessibility of comprehensive molecular characterization of tumors and germline samples from
cancer patients has accelerated translational discoveries and significantly impacted patient care. These
approaches ultimately form the basis for precision cancer medicine, whereby “clinically actionable” molecular
data about a patient's tumor and germline genomic profile, specifically defined as diagnostic, prognostic, and
predictive markers, are used at the point of care to guide treatment decision-making. While these strategies
have been successful in certain use cases, the approaches to understand somatic and germline components
of cancer patients are typically considered independently, and systematic characterization of the interaction
between the somatic and germline genomes in the context of diagnostic and predictive clinical relevance have
not yet been systematically performed across large cohorts of patients. This is in part the result of an absence
of computational algorithms that are able to consider these features simultaneously, along with a lack of patient
cohorts with both somatic and germline features and clinical annotations of relevant treatment responses to
guide these investigations. Our previous studies have demonstrated, through innovative computational
oncology approaches, how integrated germline and somatic analysis can determine diagnostic and predictive
features that have immediate clinical impact in select clinical contexts. The goal of this proposal is to directly
respond to Provocative Question PQ3: Do genetic interactions between germline variations and somatic
mutations contribute to differences in tumor evolution or response to therapy? Our overarching
hypothesis is that complex interactions between germline and somatic features within and across key DNA
repair and immune pathways mediate inherited clinical risk, and selective response to existing chemotherapies
and emerging immunotherapies. Specifically, in this proposal, we will leverage existing and emerging cohorts
of tumor and germline whole exome/transcriptome data from patients, along with relevant phenotypic data
regarding response to chemotherapies and immunotherapies, and develop innovative computational biology
algorithms to systematically dissect these cohorts and determine how interactions between germline and
somatic events shape clinical actionability. This proposal is unique in that it leverages the extensive and novel
resources at both the Dana-Farber Cancer Institute/Harvard Cancer Center and the Broad Institute of MIT and
Harvard, along with an international team of collaborators, to address the hypotheses outlined herein. The
proposed specific aims are: 1) To determine inherited cancer risk in solid tumors through integrative
computational biology, 2) To evaluate the impact of somatic and germline interactions on DNA repair defects
and response to platinum-based chemotherapies in solid tumors, and 3) To identify somatic and...

## Key facts

- **NIH application ID:** 9913487
- **Project number:** 5R01CA227388-03
- **Recipient organization:** DANA-FARBER CANCER INST
- **Principal Investigator:** Eliezer M Van Allen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $407,175
- **Award type:** 5
- **Project period:** 2018-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9913487

## Citation

> US National Institutes of Health, RePORTER application 9913487, Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors (5R01CA227388-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9913487. Licensed CC0.

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