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Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis
Molecular and protein biomarker profiling are key to oncology drug development. Antibody-drug conjugates (ADCs) directly deliver chemotherapeutic agents into tumor cells based on unique cancer cell biomarkers. A pan-cancer tissue microarray (TMA) data set and gene panel were validated and gene signa...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498941/ https://www.ncbi.nlm.nih.gov/pubmed/36137139 http://dx.doi.org/10.1371/journal.pone.0274140 |
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author | Inaki, Koichiro Shibutani, Tomoko Maeda, Naoyuki Eppenberger-Castori, Serenella Nicolet, Stefan Kaneda, Yuki Koyama, Kumiko Qiu, Yang Wakita, Kenichi Murakami, Masato |
author_facet | Inaki, Koichiro Shibutani, Tomoko Maeda, Naoyuki Eppenberger-Castori, Serenella Nicolet, Stefan Kaneda, Yuki Koyama, Kumiko Qiu, Yang Wakita, Kenichi Murakami, Masato |
author_sort | Inaki, Koichiro |
collection | PubMed |
description | Molecular and protein biomarker profiling are key to oncology drug development. Antibody-drug conjugates (ADCs) directly deliver chemotherapeutic agents into tumor cells based on unique cancer cell biomarkers. A pan-cancer tissue microarray (TMA) data set and gene panel were validated and gene signature analyses were conducted on normal and cancer tissues to refine selection of ADC targets. Correlation of mRNA and protein levels, and human epidermal growth factor receptor (HER) expression patterns were assessed. An EdgeSeq biomarker panel (2862 genes) was used across 8531 samples (23 solid cancer types/subtypes; 16 normal tissues) with an established TMA data set, and immune cell and cell cycle gene signatures were analyzed. Discriminating gene expression signatures were defined based on pathological classification of cancer subtypes. Correlative analyses of HER2 and HER3 mRNA (EdgeSeq) and protein expression (immunohistochemistry [IHC]) were performed and compared with publicly available data (The Cancer Genome Atlas [TCGA]; Cancer Cell Line Encyclopedia [CCLE]). Gene expression patterns among cancer types in the TMA (EdgeSeq) and TCGA (RNA-seq) were similar. EdgeSeq gene signature analyses aligned with the majority of pathological cancer types/subtypes and identified cancer-specific gene expression patterns. TMA IHC H-scores for HER3 varied across cancer types/subtypes. In a few cancer types, HER3 mRNA and protein expression did not align, including lower liver hepatocellular carcinoma IHC H-score, compared with mRNA. Although all TNBC and ovarian cancer subtypes expressed mRNA, some had lower protein expression. This was seen in TMA and TCGA data sets, but not in CCLE. The EdgeSeq TMA data set can expand upon current biomarker data by including cancers not currently in TCGA. The primary analysis of EdgeSeq and IHC comparison suggested a unique protein-level regulation of HER3 in some tumor subtypes and highlights the importance of investigating protein levels of ADC targets in both tumor and normal tissues. |
format | Online Article Text |
id | pubmed-9498941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94989412022-09-23 Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis Inaki, Koichiro Shibutani, Tomoko Maeda, Naoyuki Eppenberger-Castori, Serenella Nicolet, Stefan Kaneda, Yuki Koyama, Kumiko Qiu, Yang Wakita, Kenichi Murakami, Masato PLoS One Research Article Molecular and protein biomarker profiling are key to oncology drug development. Antibody-drug conjugates (ADCs) directly deliver chemotherapeutic agents into tumor cells based on unique cancer cell biomarkers. A pan-cancer tissue microarray (TMA) data set and gene panel were validated and gene signature analyses were conducted on normal and cancer tissues to refine selection of ADC targets. Correlation of mRNA and protein levels, and human epidermal growth factor receptor (HER) expression patterns were assessed. An EdgeSeq biomarker panel (2862 genes) was used across 8531 samples (23 solid cancer types/subtypes; 16 normal tissues) with an established TMA data set, and immune cell and cell cycle gene signatures were analyzed. Discriminating gene expression signatures were defined based on pathological classification of cancer subtypes. Correlative analyses of HER2 and HER3 mRNA (EdgeSeq) and protein expression (immunohistochemistry [IHC]) were performed and compared with publicly available data (The Cancer Genome Atlas [TCGA]; Cancer Cell Line Encyclopedia [CCLE]). Gene expression patterns among cancer types in the TMA (EdgeSeq) and TCGA (RNA-seq) were similar. EdgeSeq gene signature analyses aligned with the majority of pathological cancer types/subtypes and identified cancer-specific gene expression patterns. TMA IHC H-scores for HER3 varied across cancer types/subtypes. In a few cancer types, HER3 mRNA and protein expression did not align, including lower liver hepatocellular carcinoma IHC H-score, compared with mRNA. Although all TNBC and ovarian cancer subtypes expressed mRNA, some had lower protein expression. This was seen in TMA and TCGA data sets, but not in CCLE. The EdgeSeq TMA data set can expand upon current biomarker data by including cancers not currently in TCGA. The primary analysis of EdgeSeq and IHC comparison suggested a unique protein-level regulation of HER3 in some tumor subtypes and highlights the importance of investigating protein levels of ADC targets in both tumor and normal tissues. Public Library of Science 2022-09-22 /pmc/articles/PMC9498941/ /pubmed/36137139 http://dx.doi.org/10.1371/journal.pone.0274140 Text en © 2022 Inaki et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Inaki, Koichiro Shibutani, Tomoko Maeda, Naoyuki Eppenberger-Castori, Serenella Nicolet, Stefan Kaneda, Yuki Koyama, Kumiko Qiu, Yang Wakita, Kenichi Murakami, Masato Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title | Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title_full | Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title_fullStr | Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title_full_unstemmed | Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title_short | Pan-cancer gene expression analysis of tissue microarray using EdgeSeq oncology biomarker panel and a cross-comparison with HER2 and HER3 immunohistochemical analysis |
title_sort | pan-cancer gene expression analysis of tissue microarray using edgeseq oncology biomarker panel and a cross-comparison with her2 and her3 immunohistochemical analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498941/ https://www.ncbi.nlm.nih.gov/pubmed/36137139 http://dx.doi.org/10.1371/journal.pone.0274140 |
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