Luminal- and basal-like prostate cancers demonstrate divergent clinical behavior, and patients with luminal B tumors respond better to postoperative ADT than do patients with non–luminal B tumors. These findings contribute novel insight into prostate cancer biology, providing a potential clinical tool to personalize ADT treatment for prostate cancer by predicting which men may benefit from ADT after surgery.
Molecular classification of cancers into subtypes has resulted in an advance in our understanding of tumour biology and treatment response across multiple tumour types. However, to date, cancer profiling has largely focused on protein-coding genes, which comprise <1% of the genome. Here we leverage a compendium of 58,648 long noncoding RNAs (lncRNAs) to subtype 947 breast cancer samples. We show that lncRNA-based profiling categorizes breast tumours by their known molecular subtypes in breast cancer. We identify a cohort of breast cancer-associated and oestrogen-regulated lncRNAs, and investigate the role of the top prioritized oestrogen receptor (ER)-regulated lncRNA, DSCAM-AS1. We demonstrate that DSCAM-AS1 mediates tumour progression and tamoxifen resistance and identify hnRNPL as an interacting protein involved in the mechanism of DSCAM-AS1 action. By highlighting the role of DSCAM-AS1 in breast cancer biology and treatment resistance, this study provides insight into the potential clinical implications of lncRNAs in breast cancer.
Importance Although poorly understood, there is heterogeneity in the molecular biology of cancer across race and ethnicities. The representation of racial minorities in large genomic sequencing efforts is unclear, and could have an impact on health care disparities. Objective To determine the racial distribution among samples sequenced within The Cancer Genome Atlas (TCGA) and the deficit of samples needed to detect moderately common mutational frequencies in racial minorities. Design, Setting, and Participants This was a retrospective review of individual patient data from TCGA data portal accessed in July 2015. TCGA comprises samples from a wide array of institutions primarily across the United States. Samples from 10 of the 31 currently available tumor types were analyzed, comprising 5729 samples from the approximately 11 000 available. Main Outcomes and Measures Using the estimated median somatic mutational frequency, the samples needed beyond TCGA to detect a 10% and 5% mutational frequency over the background somatic mutation frequency were calculated for each tumor type by racial ethnicity. Results Of the 5729 samples, 77% (n = 4389) were white, 12% (n = 660) were black, 3% (n = 173) were Asian, 3% (n = 149) were Hispanic, and less than 0.5% combined were from patients of Native Hawaiian, Pacific Islander, Alaskan Native, or American Indian decent. This overrepresents white patients compared with the US population and underrepresents primarily Asian and Hispanic patients. With a somatic mutational frequency of 0.7 (prostate cancer) to 9.9 (lung squamous cell cancer), all tumor types from white patients contained enough samples to detect a 10% mutational frequency. This is in contrast to all other racial ethnicities, for which group-specific mutations with 10% frequency would be detectable only for black patients with breast cancer. Group-specific mutations with 5% frequency would be undetectable in any racial minority, but detectable in white patients for all cancer types except lung (adenocarcinoma and squamous cell carcinoma) and colon cancer. Conclusions and Relevance It is probable, but poorly understood, that ethnic diversity is related to the pathogenesis of cancer, and may have an impact on the generalizability of findings from TCGA to racial minorities. Despite the important benefits that continue to be gained from genomic sequencing, dedicated efforts are needed to avoid widening the already pervasive gap in health care disparities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.