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Large-scale analysis of tumor suppressors in lung cancer

Institution: Stanford University
Investigator(s): Hongchen Cai, Ph.D.
Award Cycle: 2019 (Cycle 28) Grant #: 28FT-0019 Award: $173,676
Subject Area: Cancer
Award Type: Postdoctoral Fellowship Awards

Initial Award Abstract

Lung cancer causes more deaths than the next top three cancers combined. In the United States alone, over 155,000 people die of lung cancer every year. Smoking causes about 90% of lung cancer cases and increases the chance that patients acquire oncogenic KRAS variants, a mutation that is very difficult to drug. Despite the progress in sequencing of patient genome, it is hard to distinguish the mutations that account for cancer progression (driver mutation) from those that have little effect (passengers). This causes difficulty in selecting drug targets, especially for treating KRAS-driven cancer. Because smoking increases mutation rate in lung cancer cells, there is a growing need to uncover the actual roles of mutated genes. Genetically engineered mouse models are fantastic systems to study gene function, but they are relatively expensive and inefficient. To overcome these limitations, my postdoctoral laboratory has developed a Tuba-seq platform to enable the assessment of large number of genes in vivo. Thus it is an economic way to study many genes in parallel.

As a TRDRP Postdoctoral Fellow, I will employ this platform to study the in vivo function of 42 genes that are likely to suppress lung cancer growth in tumors that carry an oncogenic KRAS mutation. I will test whether loss of these genes drives lung cancer growth and whether they inhibit cancer cell expansion or prevent cancer cells from gaining additional mutations. I will also study how these genes cooperate with well-characterized tumor suppressors in mouse models and human lung cancer datasets. In parallel, I will analyze the changes in molecular and cellular states that result from loss of tumor suppressors in oncogenic KRAS-initiated lung tumors. This will identify pathways that may mediate the function of these genes. I will collaborate with clinical oncology experts to further explore the effector pathways in human datasets and patient samples that harbor mutations in those tumor suppressors. My proposal will uncover novel aspects of tumor suppressor gene function and identify cancer cell state changes that are driven by different tumor suppressor alterations. These results may ultimately lead to the development of new therapies that may have an impact on clinical care for lung cancer patients that suffer from oncogenic KRAS-driven lung cancer.