Abstract 1761: Comprehensive profiling of the FAT3-associated gene signature in deciphering immunophenotypes of gastrointestinal cancers: Analysis of institutional cohort and TCGA dataset
Authors: Ahluwalia Pankaj Kumar , Leeman Tiffanie , Mondal Ashis , Vashisht Ashutosh , Singh Harmanpreet , Kolhe Ravindra 
Published: March 2024

Gastrointestinal (GI) cancers are among the most prevalent cancers affecting the US population. Anatomically, GI cancer includes cancers of the organs in the digestive tract, from the esophagus to the rectum. Advances in molecular oncology have started to transform the therapeutic landscape and offer tremendous promise for patients across diverse lineages. However, the equitable benefit of this approach has been hampered due to tumor heterogeneity and the lack of accurate, tumor-agnostic biomarkers with prognosis and predictive utility. Thus, there is a need to identify novel biomarkers that affect gastrointestinal malignancies to improve the management of cancer patients. This study analyzed a single institution's whole genome sequencing dataset to explore the genomic variation in GI cancers. Between 2020 and 2022, 302 AU patients underwent molecular profiling, including whole-exome sequencing (WES) profiling at Caris Life Sciences. WES is an NGS assay that analyzes the DNA sequences of all protein-coding exons in the genome, representing approximately 1-2% of the human genome with coverage of over 22,000 genes. We analyzed the TCGA dataset for comparative analysis, which included cancer data from &gt;1800 GI cancer patients. In addition, survival and network analyses were performed to identify a 6-gene FAT3-related signature for GI cancers. In our cohort, we identified FAT3 (Fat atypical cadherin 3) as the most frequently mutated gene after TP53, APC, and KRAS. FAT3 encodes a cadherin protein involved in cell-cell interactions and adhesion. In the institutional cohort, FAT3 was found to be mutated in 16% of all GI cases. Further analysis of TCGA datasets comprising 1808 GI cancer patients revealed FAT3 mutations in 12% of the cases. To identify additional prognostic biomarkers associated with FAT3, we performed network analysis and identified a 6-gene FAT3-related signature (FAT3, RYK, FAT2, EGFLAM, NTRK3, IGSF9, and HMGA2) that significantly stratified GI cancer patients based on overall survival, progression-free survival, and disease-specific survival. The perturbation profile of the 6-gene signature was associated with 509 patients or 28% of total GI patients. Further, immune deconvolution analysis of stratified patients revealed increased infiltration of immune cells with immunosuppressive phenotypic properties in GI cancer patients with higher expression of the FAT3-related gene signature. In summary, this analysis reveals the distribution of FAT3 mutational profiles in GI patients and identifies a gene signature that stratifies patients based on survival outcomes. This analysis can provide new tools for patient stratification and therapy implementation, leading to better outcomes for cancer patients.

Citation Format: Pankaj Kumar Ahluwalia, Tiffanie Leeman, Ashis Mondal, Ashutosh Vashisht, Harmanpreet Singh, Ravindra Kolhe. Comprehensive profiling of the FAT3-associated gene signature in deciphering immunophenotypes of gastrointestinal cancers: Analysis of institutional cohort and TCGA dataset [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1761.