Abstract PO-167: Predictive genetic risk factors and prognostic nomogram for colorectal cancer in Native Hawaiian population

Abstract

Abstract Background While Native Hawaiians (NH) comprise a small portion of the US population, their numbers are expected to increase. Concerningly, NH exhibit disproportionate health issues, and specifically those with colorectal cancer (CRC) present elevated incidence and mortality above the US population. This study aims to identify race-specific genetic factors for CRC early detection and prognosis in this unique population. Methods Paired tumor and adjacent normal biospecimens from NH patients with primary CRC were collected from the Hawaii Tumor Registry (HTR), and RNA sequencing on 41 paired samples were performed to establish the first genome-wide transcriptome profiling dataset specifically for NH with CRC. RNAseq data of 18 paired samples and additional 212 cancer samples were taken from The Cancer Genome Atlas (TCGA) white patients. Differential expressed genes (DEGs) were identified for both NH and TCGA cohorts via DESeq2 with FDR q-value < 0.05 and a cutoff of 2-fold change. A diagnostic model was built by Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 10-fold cross validation, and Ingenuity Pathway Analysis (IPA) was processed for canonical pathways and network discovery. Univariate Cox proportional regression was performed to identify DEGs related to NH patient survival; multivariable Cox regression model with stepwise fitting generated a prognostic index (PI): PI=Σbi × expGenei (where expGene defines the gene expression and b equals the regression coefficient), and the prediction value was examined by the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC). A nomogram was developed by integrating PI and clinicopathologic factors; calibration curves were provided to internally validate the performance, and discriminative ability was appraised by concordance index. Results In total, 2096 DEGs were identified between tumor and normal groups, and 1740 transcripts were unique to NH compared to the TCGA Whites cohort. A set of 23 genes including 10 NH specific DEGs was identified as genetic risk factors for detecting NH with CRC, and the AUC was 99.8%. A 9 gene-signature prognostic model including 5 NH specific DEGs was built with high survival prediction capability (AUC=0.99), and Kaplan-Meier curve showed that the low PI group had a better survival than the high PI group in NH with CRC (Logrank P=3.6E-05). After adjustment by age, gender, and tumor grade, the prognostic 9 gene-signature was still significant (P=0.0059). By integrating the above signatures with prognostic clinicopathologic features, a nomogram was constructed to stratified patients with overall survival rates for 3, 10, and 20 years. Conclusion Divergent DEGs and consequential pathways between NH and TCGA cohort reinforced the necessity of NH race specific biomedical research. The prognostic gene signature offered evidence that genomic data provided independent and complementary prognostic information, and the nomogram incorporating genetic and clinicopathological factors refined the prognosis of CRC for this unique population. Citation Format: Yuanyuan Fu, Devin Takahashi, Vedbar Khadka, Masaki Nasu, Mayumi Jijiwa, Yu Chen, Heather Borgard, Youping Deng. Predictive genetic risk factors and prognostic nomogram for colorectal cancer in Native Hawaiian population [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-167.