Feifei Jia1,2, Jamie K Teer3, Todd C Knepper2, Jae K Lee3, Hong-Hao Zhou1, Yi-Jing He1,2, Howard L McLeod4,5. 1. Institute for Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China. 2. Division of Population Science, DeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, FL, USA. 3. Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA. 4. Institute for Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China. Howard.McLeod@moffitt.org. 5. Division of Population Science, DeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, FL, USA. Howard.McLeod@moffitt.org.
Abstract
BACKGROUND: Differences in response to cancer treatments have been observed among racially and ethnically diverse gastric cancer (GC) patient populations. In the era of targeted therapy, mutation profiling of cancer is a crucial aspect of making therapeutic decisions. Mapping driver gene mutations for the GC patient population as a whole has significant potential to advance precision therapy. METHODS: GC patients with sequencing data (N = 473) were obtained from The Cancer Genome Atlas (TCGA; n = 295), Moffitt Cancer Center Total Cancer Care™ (TCC; n = 33), and three published studies (n = 145). In addition, relevant somatic mutation frequency data were obtained from cBioPortal, the TCC database, and an in-house analysis tool, as well as relevant publications. RESULTS: We found that the somatic mutation rates of several driver genes vary significantly between GC patients of Asian and Caucasian descent, with substantial variation across different geographic regions. Non-parametric statistical tests were performed to examine the significant differences in protein-altering somatic mutations between Asian and Caucasian GC patient groups. The frequencies of somatic mutations of five genes were: APC (Asian: Caucasian 6.06 vs. 14.40%, p = 0.0076), ARIDIA (20.7 vs. 32.1%, p = 0.01), KMT2A (4.04 vs. 12.35%, p = 0.003), PIK3CA (9.6 vs. 18.52%, p = 0.01), and PTEN (2.52 vs. 9.05%, p = 0.008), showing significant differences between Asian and Caucasian GC patients. CONCLUSIONS: Our study found significant differences in protein-altering somatic mutation frequencies in diverse geographic populations. In particular, we found that the somatic patterns may offer better insight and important opportunities for both targeted drug development and precision therapeutic strategies between Asian and Caucasian GC patients.
BACKGROUND: Differences in response to cancer treatments have been observed among racially and ethnically diverse gastric cancer (GC) patient populations. In the era of targeted therapy, mutation profiling of cancer is a crucial aspect of making therapeutic decisions. Mapping driver gene mutations for the GC patient population as a whole has significant potential to advance precision therapy. METHODS: GC patients with sequencing data (N = 473) were obtained from The Cancer Genome Atlas (TCGA; n = 295), Moffitt Cancer Center Total Cancer Care™ (TCC; n = 33), and three published studies (n = 145). In addition, relevant somatic mutation frequency data were obtained from cBioPortal, the TCC database, and an in-house analysis tool, as well as relevant publications. RESULTS: We found that the somatic mutation rates of several driver genes vary significantly between GC patients of Asian and Caucasian descent, with substantial variation across different geographic regions. Non-parametric statistical tests were performed to examine the significant differences in protein-altering somatic mutations between Asian and Caucasian GC patient groups. The frequencies of somatic mutations of five genes were: APC (Asian: Caucasian 6.06 vs. 14.40%, p = 0.0076), ARIDIA (20.7 vs. 32.1%, p = 0.01), KMT2A (4.04 vs. 12.35%, p = 0.003), PIK3CA (9.6 vs. 18.52%, p = 0.01), and PTEN (2.52 vs. 9.05%, p = 0.008), showing significant differences between Asian and Caucasian GC patients. CONCLUSIONS: Our study found significant differences in protein-altering somatic mutation frequencies in diverse geographic populations. In particular, we found that the somatic patterns may offer better insight and important opportunities for both targeted drug development and precision therapeutic strategies between Asian and Caucasian GC patients.
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