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A pan-cancer analysis of HER2 index revealed transcriptional pattern for precise selection of HER2-targeted therapy.
- Source :
-
EBioMedicine [EBioMedicine] 2020 Dec; Vol. 62, pp. 103074. Date of Electronic Publication: 2020 Nov 09. - Publication Year :
- 2020
-
Abstract
- Background: The prevalence of HER2 alterations in pan-cancer indicates a broader range of application of HER2-targeted therapies; however, biomarkers for such therapies are still insufficient and limited to breast cancer and gastric cancer.<br />Methods: Using multi-omics data from The Cancer Genome Atlas (TCGA), the landscape of HER2 alterations was exhibited across 33 tumor types. A HER2 index was constructed using one-class logistic regression (OCLR). With the predictive value validated in GEO cohorts and pan-cancer cell lines, the index was then applied to evaluate the HER2-enriched expression pattern across TCGA pan-cancer types.<br />Findings: Increased HER2 somatic copy number alterations (SCNAs) could be divided into two patterns, focal- or arm-level. The expression-based HER2 index successfully distinguished the HER2-enriched subtype from the others and provided a stable and superior performance in predicting the response to HER2-targeted therapies both in breast tumor tissue and pan-cancer cell lines. With frequencies varying from 12.0% to 0.9%, tumors including head and neck squamous tumors, gastrointestinal tumors, bladder cancer, lung cancer and uterine tumors exhibited high HER2 indices together with HER2 amplification or overexpression, which may be more suitable for HER2-targeted therapies. The BLCA.3 and HNSC.Basal were the most distinguishable subtypes within bladder cancer and head and neck cancer respectively by HER2 index, implying their potential benefits from HER2-targeted therapies.<br />Interpretation: As a pan-cancer predictive biomarker of HER2-targeted therapies, the HER2 index could help identify potential candidates for such treatment in multiple tumor types by combining with HER2 multi-omics features. The discoveries of our study highlight the importance of incorporating transcriptional pattern into the assessment of HER2 status for better patient selection.<br />Funding: The National Key Research and Development Program of China; Clinical Research and Cultivation Project of Shanghai ShenKang Hospital Development Center.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests.<br /> (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)
- Subjects :
- Clinical Decision-Making
Computational Biology methods
DNA Copy Number Variations
Databases, Genetic
Disease Management
Disease Susceptibility
Gene Amplification
Gene Expression Profiling
Humans
Machine Learning
Molecular Targeted Therapy methods
Neoplasms drug therapy
Neoplasms metabolism
Polymorphism, Single Nucleotide
Proteomics methods
Receptor, ErbB-2 metabolism
Biomarkers, Tumor genetics
Gene Expression Regulation
Neoplasms genetics
Receptor, ErbB-2 genetics
Transcription, Genetic
Subjects
Details
- Language :
- English
- ISSN :
- 2352-3964
- Volume :
- 62
- Database :
- MEDLINE
- Journal :
- EBioMedicine
- Publication Type :
- Academic Journal
- Accession number :
- 33161227
- Full Text :
- https://doi.org/10.1016/j.ebiom.2020.103074