Dataset Information

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology.

ABSTRACT: Information regarding the role of low-frequency hotspot cancer-driver mutations (CDMs) in breast carcinogenesis and therapeutic response is limited. Using the sensitive and quantitative Allele-specific Competitor Blocker PCR (ACB-PCR) approach, mutant fractions (MFs) of six CDMs (PIK3CA H1047R and E545K, KRAS G12D and G12V, HRAS G12D, and BRAF V600E) were quantified in invasive ductal carcinomas (IDCs; including ~20 samples per subtype). Measurable levels (i.e., ≥ 1 × 10-5, the lowest ACB-PCR standard employed) of the PIK3CA H1047R, PIK3CA E545K, KRAS G12D, KRAS G12V, HRAS G12D, and BRAF V600E mutations were observed in 34/81 (42%), 29/81 (36%), 51/81 (63%), 9/81 (11%), 70/81 (86%), and 48/81 (59%) of IDCs, respectively. Correlation analysis using available clinicopathological information revealed that PIK3CA H1047R and BRAF V600E MFs correlate positively with maximum tumor dimension. Analysis of IDC subtypes revealed minor mutant subpopulations of critical genes in the MAP kinase pathway (KRAS, HRAS, and BRAF) were prevalent across IDC subtypes. Few triple-negative breast cancers (TNBCs) had appreciable levels of PIK3CA mutation, suggesting that individuals with TNBC may be less responsive to inhibitors of the PI3K/AKT/mTOR pathway. These results suggest that low-frequency hotspot CDMs contribute significantly to the intertumoral and intratumoral genetic heterogeneity of IDCs, which has the potential to impact precision oncology approaches.

SUBMITTER: Myers MB

PROVIDER: S-EPMC6429455 | biostudies-other | 2019 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology.

Myers Meagan B MB McKim Karen L KL Banda Malathi M George Nysia I NI Parsons Barbara L BL

International journal of molecular sciences 20190226 5

Information regarding the role of low-frequency hotspot cancer-driver mutations (CDMs) in breast carcinogenesis and therapeutic response is limited. Using the sensitive and quantitative Allele-specific Competitor Blocker PCR (ACB-PCR) approach, mutant fractions (MFs) of six CDMs (PIK3CA H1047R and E545K, KRAS G12D and G12V, HRAS G12D, and BRAF V600E) were quantified in invasive ductal carcinomas (IDCs; including ~20 samples per subtype). Measurable levels (i.e., ≥ 1 × ...[more]

PMID: 30813596

Similar Datasets

Project description:BACKGROUND:The decreasing cost of obtaining high-quality calls of genomic variants and the increasing availability of clinically relevant data on such variants are important drivers for personalized oncology. To allow rational genome-based decisions in diagnosis and treatment, clinicians need intuitive access to up-to-date and comprehensive variant information, encompassing, for instance, prevalence in populations and diseases, functional impact at the molecular level, associations to druggable targets, or results from clinical trials. In practice, collecting such comprehensive information on genomic variants is difficult since the underlying data is dispersed over a multitude of distributed, heterogeneous, sometimes conflicting, and quickly evolving data sources. To work efficiently, clinicians require powerful Variant Information Systems (VIS) which automatically collect and aggregate available evidences from such data sources without suppressing existing uncertainty. METHODS:We address the most important cornerstones of modeling a VIS: We take from emerging community standards regarding the necessary breadth of variant information and procedures for their clinical assessment, long standing experience in implementing biomedical databases and information systems, our own clinical record of diagnosis and treatment of cancer patients based on molecular profiles, and extensive literature review to derive a set of design principles along which we develop a relational data model for variant level data. In addition, we characterize a number of public variant data sources, and describe a data integration pipeline to integrate their data into a VIS. RESULTS:We provide a number of contributions that are fundamental to the design and implementation of a comprehensive, operational VIS. In particular, we (a) present a relational data model to accurately reflect data extracted from public databases relevant for clinical variant interpretation, (b) introduce a fault tolerant and performant integration pipeline for public variant data sources, and (c) offer recommendations regarding a number of intricate challenges encountered when integrating variant data for clincal interpretation. CONCLUSION:The analysis of requirements for representation of variant level data in an operational data model, together with the implementation-ready relational data model presented here, and the instructional description of methods to acquire comprehensive information to fill it, are an important step towards variant information systems for genomic medicine.

Project description:Background: The genomic spectrum of biliary tract carcinoma (BTC) has been characterized and is associated with distinct anatomic and etiologic subtypes, yet limited studies have linked genomic alterations with personalized therapies in BTC patients. Methods: This study analyzed 803 patients with BTC:164 with gallbladder cancer, 475 with intrahepatic cholangiocarcinoma (ICC) and 164 with extrahepatic cholangiocarcinoma. We determined genomic alterations, mutational signatures related to etiology and histopathology and prognostic biomarkers. Personalized targeted therapies for patients harboring potentially actionable targets (PATs) were investigated. Results: The median tumor mutation burden (TMB) was 1.23 Mut/Mb, with 4.1% of patients having hypermutated BTCs. Unlike the results obtained from the Western population, the most frequently altered cancer-related genes in our cohort included TP53 (53%), KRAS (26%), ARID1A (18%), LRP1B (14%) and CDKN2A (14%). Germline mutations occurred mostly in DNA damage repair genes. Notably, 35.8% of the ICCs harbored aristolochic acid related signatures and an elevated TMB. TP53 and KRAS mutations and amplified 7q31.2 were demonstrated to negatively affect patient prognosis. Moreover, 19 genes were proposed to be PATs in BTCs, with 25.4% of patients harboring these PATs. Forty-six patients received PAT-matched targeted therapies, achieving a 26.1% objective response rate; the median progression-free survival (PFS) was 5.0 months, with 56.8% of patients obtaining PFS benefits. Conclusions: Extensive genomic diversity and heterogeneity were observed among BTC patients, with contributions according to potential etiology exposures, anatomical subtypes and clinicopathological characteristics. We also demonstrated that patients with refractory BTCs who have PATs can derive considerable benefit from receiving a matched therapy, initiating further prospective clinical trials guided by molecular profiling among this aggressive cancer.

Dataset Information

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology.

Publications

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets