15 Apr Icahn Mount Sinai Study Evaluates How Germline Mutations Shape Tumors
MedicalResearch.com Interview with:
Dr. Myvizhi Esai Selvan
Myvizhi Esai Selvan, PhD
Instructor of Genetics and Genomics
Dr. Zeynep Gümüş
Zeynep H. Gümüş, PhD
Associate Professor
Icahn School of Medicine at Mount Sinai
MedicalResearch.com: What is the background for this study?
Response: The germline genome of each individual person has a unique combination of millions of genetic variants that influence virtually all biological processes throughout life, including cancer evolution. In this study, we have investigated the impact of germline variants – genetic defects one is born with – on gene expression and protein abundance in tumors across cancer types.
MedicalResearch.com: Would you describe the technique of precision peptidomics?
Response: We have leveraged a cohort of 1,064 patients with multiple cancer types to explore the impact of germline variations on cancer-relevant genes through multiple-omics layers: from DNA to RNA, protein abundance and post-translational modifications. To assess the effects of coding variants and their association with cognate proteins, we used precision peptidomics, which is the quantification of peptides carrying genetic variants from individual patients. Through this approach, we mapped 337,469 protein coding germline variants onto patient peptides, revealing their potential impact on protein modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases.
MedicalResearch.com: What are the main findings?
Response: We identified how germline variants (both low- and high-frequency at population-level) shape the cancer proteome; the findings highlight the contribution of germline genetics in tumor heterogeneity and high-throughput precision protein/peptide abundance. Using precision peptidomics, we investigated the impact of germline variants on cancer patients’ proteomes, including effects on protein modifications, stability, and allele-specific expression. We identified the impact of germline variants on both gene expression and protein abundance (QTL analyses), reporting genes and proteins under germline genetic control across different tissues and tumors, which we report at our Sinai-hosted website: https://immuneregulation.mssm.edu/ . We further identified variants potentially impacting protein features other than abundance, including protein structure and phosphorylation. Precision peptidome analysis predicted destabilizing events in SIRPA and GFAP, relevant to immunomodulation and glioblastoma diagnostics, respectively. Polygenic risk scores correlated with distal effects from risk variants.
MedicalResearch.com: Can these findings help predict who is more likely to benefit from specific cancer screening tests?
Response: No, this work builds on growing evidence that genetic factors play a crucial role in cancer evolution. The study findings will help modify treatment recommendations of cancer patients based on the genetic makeup of their own cells, in addition to those of their tumors.
MedicalResearch.com: What recommendations do you have for future research as a results of this study?
Response: Study findings complement our research efforts on two different fronts. First, through a Cancer Moonshot Grant, as part of the NCI’s Cancer Immune Monitoring and Analysis Centers (CIMAC) and Cancer Immunologic Data Center (CIDC), we are deeply interested in understanding why some cancer patients respond so well to immunotherapies, while others do not. The study findings underscore that some of the clues to this mystery may reside in germline genetic variations. We will continue our efforts towards decoding the germline determinants of cancer immunotherapy response.
Second, we are currently developing advanced computational models to predict cancer risk —particularly lung cancer risk – based on a person’s inherited genetic profile, through analyses of the germline genetic makeup of up to a million participants in the Million Veteran Program, which we will pilot in an ongoing lung cancer screening study within the Veterans Affairs Health Care System. These risk models aim to guide healthcare providers make more personalized recommendations about when and how often individuals should be screened for lung cancers, moving beyond the current one-size-fits-all approach. The study findings on which germline genetic variants impact cancer evolution will help refine these risk models. By decoding germline genetic variants, we can target screening resources where they are most needed and potentially detect cancers earlier when treatment is the most effective.
MedicalResearch.com: Is there anything else you would like to add? Any disclosures?
Response: While our dataset is one of the largest multi-omic resources available, we were still limited by our sample size. Furthermore, our cohort included patients predominantly of European genetic ancestry, with smaller subsets of other ancestries. Future studies would need to include populations better reflective of the ancestral make-up of the US population.
Citation:
Precision proteogenomics reveals pan-cancer impact of germline variants
Martins Rodrigues, FernandaAn, Eunkyung et al.
Cell, Volume 0, Issue 0
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Last Updated on April 16, 2025 by Marie Benz MD FAAD