Personalized Oncogenomics in the Management of Gastrointestinal Carcinomas-early Experiences from a Pilot Study

Overview

Journal Curr Oncol

Publisher MDPI

Specialty Oncology

Date 2017 Jan 5

PMID 28050146

Citations 7

Authors

B S Sheffield

B Tessier-Cloutier

H Li-Chang

Y Shen

E Pleasance

K Kasaian

Y Li

S J M Jones

H J Lim

D J Renouf

D G Huntsman

S Yip

J Laskin

M Marra

D F Schaeffer

Affiliations

Soon will be listed here.

Abstract

Background: Gastrointestinal carcinomas are genomically complex cancers that are lethal in the metastatic setting. Whole-genome and transcriptome sequencing allow for the simultaneous characterization of multiple oncogenic pathways.

Methods: We report 3 cases of metastatic gastrointestinal carcinoma in patients enrolled in the Personalized Onco-Genomics program at the BC Cancer Agency. Real-time genomic profiling was combined with clinical expertise to diagnose a carcinoma of unknown primary, to explore treatment response to bevacizumab in a colorectal cancer, and to characterize an appendiceal adenocarcinoma.

Results: In the first case, genomic profiling revealed an somatic mutation, supporting the diagnosis of cholangiocarcinoma in a malignancy of unknown origin, and further guided therapy by identifying epidermal growth factor receptor amplification. In the second case, a V600E mutation and wild-type profile justified the use of targeted therapies to treat a colonic adenocarcinoma. The third case was an appendiceal adenocarcinoma defined by a p53 inactivation; Ras/raf/mek, Akt/mtor, Wnt, and notch pathway activation; and overexpression of ret, erbb2 (her2), erbb3, met, and cell cycle regulators.

Summary: We show that whole-genome and transcriptome sequencing can be achieved within clinically effective timelines, yielding clinically useful and actionable information.

Citing Articles

Recent Major Transcriptomics and Epitranscriptomics Contributions toward Personalized and Precision Medicine.

Mubarak G, Zahir F J Pers Med. 2022; 12(2).

PMID: 35207687 PMC: 8877836. DOI: 10.3390/jpm12020199.

Evaluating DNA Methylation, Gene Expression, Somatic Mutation, and Their Combinations in Inferring Tumor Tissue-of-Origin.

Liu H, Qiu C, Wang B, Bing P, Tian G, Zhang X Front Cell Dev Biol. 2021; 9:619330.

PMID: 34012960 PMC: 8126648. DOI: 10.3389/fcell.2021.619330.

Predicting Cancer Tissue-of-Origin by a Machine Learning Method Using DNA Somatic Mutation Data.

Liu X, Li L, Peng L, Wang B, Lang J, Lu Q Front Genet. 2020; 11:674.

PMID: 32760423 PMC: 7372518. DOI: 10.3389/fgene.2020.00674.

TOOme: A Novel Computational Framework to Infer Cancer Tissue-of-Origin by Integrating Both Gene Mutation and Expression.

He B, Lang J, Wang B, Liu X, Lu Q, He J Front Bioeng Biotechnol. 2020; 8:394.

PMID: 32509741 PMC: 7248358. DOI: 10.3389/fbioe.2020.00394.

A Case of Metastatic Biliary Tract Cancer Diagnosed Through Identification of an Mutation.

Kamath S, Lin X, Kalyan A Oncologist. 2018; 24(2):151-156.

PMID: 30352944 PMC: 6369936. DOI: 10.1634/theoncologist.2018-0210.

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