Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data

Overview

Journal Cancer Discov

Specialty Oncology

Date 2024 Feb 28

PMID 38416134

Authors

Madison Darmofal

Shalabh Suman

Gurnit Atwal

Michael Toomey

Jie-Fu Chen

Jason C Chang

Efsevia Vakiani

Anna M Varghese

Anoop Balakrishnan Rema

Aijazuddin Syed

Nikolaus Schultz

Michael F Berger

Quaid Morris

Affiliations

Soon will be listed here.

Abstract

Significance: We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

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