| Title: | Pan-cancer analysis of whole-exome germline variants |
| Lead Institution: | Memorial Sloan Kettering Cancer Center |
| Principal investigator: | Dr Ronglai Shen |
Application 74025
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About
Inherited mutations can lead to an increased risk of various types of cancer. Studies have estimated that about one third of the variation in cancer risk is due to genetic factors. However, despite extensive research, most of this variation in risk is not explained by known mutations. The first aim of this project addresses the prominent hypothesis that the unexplained variation in risk is largely due to rare undiscovered mutations. Comprehensive studies of rare mutations were previously infeasible due to technological limitations, but in recent years, advances in genetic sequencing technology have made it possible to detect rare mutations on a large scale. We will use sequencing data to search for associations between rare inherited mutations in protein-coding regions and various types of cancer. The second aim focuses on developing models for cancer site classification. Existing models that use genetic mutations as predictors typically consider only a small set of mutations known to increase cancer risk. We will investigate whether accuracy gains can be achieved through the inclusion of additional predictors that summarize the distribution of mutations across protein-coding regions. Addressing these aims will lead to a better understanding of the genetic basis of cancer risk, improving our ability to identify high-risk individuals and allowing for more effective prevention and treatment.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7895 | Predicting cancer risk from germline whole-exome sequencing data using a novel context-based variant aggregation approach | Zoe Guan (+2) | 2023 | Cancer Research Communications |
Enabling scientific discoveries that improve human health