While whole‐genome and exome sequencing have transformed our collective understanding of genetics' role in disease pathogenesis, there are certain conditions and populations for whom DNA‐level data fails to identify the underlying genetic etiology. Specifically, patients of non‐White race and non‐European ancestry are disproportionately affected by “variants of unknown/uncertain significance” (VUS), limiting the scope of precision medicine for minority patients and perpetuating health disparities. VUS often include deep intronic and splicing variants which are difficult to interpret from DNA data alone. RNA analysis can illuminate the consequences of VUS, thereby allowing for their reclassification as pathogenic versus benign. Here we review the critical role transcriptome analysis plays in clarifying VUS in both neoplastic and non‐neoplastic diseases.

Background: Small bowel carcinoids are insidious tumors that are often metastatic when diagnosed. Limited mutation landscape studies of carcinoids indicate that these tumors have a relatively low mutational burden. The development of targeted therapies will depend upon the identification of mutations that drive the pathogenesis and metastasis of carcinoid tumors. Methods: Whole exome and RNA sequencing of 5 matched sets of normal tissue, primary small intestine carcinoid tumors, and liver metastases were investigated. Germline and somatic variants included: single nucleotide variants (SNVs), insertions/deletions (indels), structural variants, and copy number alterations (CNAs). The functional impact of mutations was predicted using Ensembl Variant Effect Predictor. Results: Large-scale CNAs were observed including the loss of chromosome 18 in all 5 metastases and 3/5 primary tumors. Certain somatic SNVs were metastasis-specific; including mutations in ATRX, CDKN1B, MXRA5 (leading to the activation of a cryptic splice site and loss of mRNA), SMARCA2, and the loss of UBE4B. Additional mutations in ATRX, and splice site loss of PYGL, leading to intron retention observed in primary and metastatic tumors. Conclusions: We observed novel mutations in primary/metastatic carcinoid tumor pairs, and some have been observed in other types of neuroendocrine tumors. We confirmed a previously observed loss of chromosome 18 and CDKN1B. Transcriptome sequencing added relevant information that would not have been appreciated with DNA sequencing alone. The detection of several splicing mutations on the DNA level and their consequences at the RNA level suggests that RNA splicing aberrations may be an important mechanism underlying carcinoid tumors.

The vast volume of data that has been generated as a result of the next-generation sequencing revolution is overwhelming to sift through and interpret. Parsing functional vs. non-functional and benign vs. pathogenic variants continues to be a challenge. Out of three billion bases, the genomes of two given individuals will only differ by about 3 million variants (0.1%). Furthermore, only a small fraction of these are biologically-relevant and, of those that are functional, only a handful actually drive disease pathology. While whole genome and exome sequencing have transformed our collective understanding of the role that genetics plays in disease pathogenesis, there are certain conditions and populations for whom DNA-level data has failed to produce a molecular diagnosis. Patients of non-White race/non-European ancestry are disproportionately affected by “variants of unknown/uncertain significance” (VUS). This limits the scope of precision medicine for minority patients and perpetuates health disparities. VUS often include deep intronic and splicing variants which are difficult to interpret in DNA alone. RNA analysis is capable of illuminating the consequences of VUS thereby allowing for their reclassification as pathogenic vs. benign. Here we review the critical role, going forward, of transcriptome analysis for clarifying VUS in both neoplastic and non-neoplastic diseases.

The objective of this study is to determine whether genetic ancestry analysis can provide additional insight into the genetic determinants of cancer disparities distinct from socially constructed variables like self-reported race and ethnicity. The Oncology Research Information Exchange Network (ORIEN) “Avatar” project is a diverse dataset of extensive, longitudinal clinical and molecular data from 18 cancer centers across the U.S.; the ORIEN Intermember Ancestry Project cohort described in this study is a subset of the larger dataset. Using paired tumor/germline whole exome sequencing data from ORIEN, the Genome Aggregation Database (gnomAD) dataset of ancestry reference individuals, and the software tools ADMIXTURE and RFMix, we have estimated genetic ancestry for cancer cases from both ORIEN and The Cancer Genome Atlas (TCGA). The ORIEN dataset has 2.6X greater representation of self-reported Hispanic/Latinos than does TCGA, with Hispanic/Latinos making up 9% of the ORIEN dataset vs. 4% in TCGA. As expected, individuals of Hispanic/Latino ethnicity are heterogeneous in their admixture proportions of Indigenous American, African, and European ancestries. We performed statistical analyses in R to identify molecular and clinical correlations with ancestry. This study highlights the clinical utility of genetic ancestry analysis as an approach to understand the genetic contributions to cancer disparities in diverse, admixed populations. Citation Format: Mackenzie D. Postel, Jamie K. Teer, Steven A. Eschrich, Julie Dutil, Erin M. Siegel, William D. Cress, John D. Carpten, David W. Craig. Molecular and clinical correlates of genetic ancestry in a diverse, admixed cancer dataset [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3117.