Dataset Information

Genome-Derived Classification Signature for Ampullary Adenocarcinoma to Improve Clinical Cancer Care.

ABSTRACT:

Purpose

The clinical behavior of ampullary adenocarcinoma varies widely. Targeted tumor sequencing may better define biologically distinct subtypes to improve diagnosis and management.

Experimental design

The hidden-genome algorithm, a multilevel meta-feature regression model, was trained on a prospectively sequenced cohort of 3,411 patients (1,001 pancreatic adenocarcinoma, 165 distal bile-duct adenocarcinoma, 2,245 colorectal adenocarcinoma) and subsequently applied to targeted panel DNA-sequencing data from ampullary adenocarcinomas. Genomic classification (i.e., colorectal vs. pancreatic) was correlated with standard histologic classification [i.e., intestinal (INT) vs. pancreatobiliary (PB)] and clinical outcome.

Results

Colorectal genomic subtype prediction was primarily influenced by mutations in APC and PIK3CA, tumor mutational burden, and DNA mismatch repair (MMR)-deficiency signature. Pancreatic genomic-subtype prediction was dictated by KRAS gene alterations, particularly KRAS G12D, KRAS G12R, and KRAS G12V. Distal bile-duct adenocarcinoma genomic subtype was most influenced by copy-number gains in the MDM2 gene. Despite high (73%) concordance between immunomorphologic subtype and genomic category, there was significant genomic heterogeneity within both histologic subtypes. Genomic scores with higher colorectal probability were associated with greater survival compared with those with a higher pancreatic probability.

Conclusions

The genomic classifier provides insight into the heterogeneity of ampullary adenocarcinoma and improves stratification, which is dictated by the proportion of colorectal and pancreatic genomic alterations. This approach is reproducible with available molecular testing and obviates subjective histologic interpretation.

SUBMITTER: Chakraborty S

PROVIDER: S-EPMC8563403 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Publications

Genome-Derived Classification Signature for Ampullary Adenocarcinoma to Improve Clinical Cancer Care.

Chakraborty Saptarshi S Ecker Brett L BL Seier Ken K Aveson Victoria G VG Balachandran Vinod P VP Drebin Jeffrey A JA D'Angelica Michael I MI Kingham T Peter TP Sigel Carlie S CS Soares Kevin C KC Vakiani Efsevia E Wei Alice C AC Chandwani Rohit R Gonen Mithat M Shen Ronglai R Jarnagin William R WR

Clinical cancer research : an official journal of the American Association for Cancer Research 20210825 21

<h4>Purpose</h4>The clinical behavior of ampullary adenocarcinoma varies widely. Targeted tumor sequencing may better define biologically distinct subtypes to improve diagnosis and management.<h4>Experimental design</h4>The hidden-genome algorithm, a multilevel meta-feature regression model, was trained on a prospectively sequenced cohort of 3,411 patients (1,001 pancreatic adenocarcinoma, 165 distal bile-duct adenocarcinoma, 2,245 colorectal adenocarcinoma) and subsequently applied to targeted ...[more]

PMID: 34433650

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Dataset Information

Genome-Derived Classification Signature for Ampullary Adenocarcinoma to Improve Clinical Cancer Care.

Purpose

Experimental design

Results

Conclusions

Publications

Genome-Derived Classification Signature for Ampullary Adenocarcinoma to Improve Clinical Cancer Care.

Similar Datasets

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