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Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors
BACKGROUND: Cancer cell lines are important research models for studying tumor biology in vivo. The accuracy of such studies is highly dependent on the phenotypic and genetic similarity of cell lines to patient tumors, but this is not always the case, particularly for pancreatic cancer. METHODS: We...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174970/ https://www.ncbi.nlm.nih.gov/pubmed/37180676 http://dx.doi.org/10.21037/tcr-23-173 |
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author | Hu, Yan Gao, Peng Xu, Gaoqi Sun, Jiao Xin, Wenxiu Kong, Sisi Ding, Haiying Zhu, Junfeng Fang, Luo |
author_facet | Hu, Yan Gao, Peng Xu, Gaoqi Sun, Jiao Xin, Wenxiu Kong, Sisi Ding, Haiying Zhu, Junfeng Fang, Luo |
author_sort | Hu, Yan |
collection | PubMed |
description | BACKGROUND: Cancer cell lines are important research models for studying tumor biology in vivo. The accuracy of such studies is highly dependent on the phenotypic and genetic similarity of cell lines to patient tumors, but this is not always the case, particularly for pancreatic cancer. METHODS: We compared the gene expression profiles of various pancreatic cancer cell lines and primary human pancreatic tumor tissues to determine which pancreatic cancer cell line best models human primary tumor. Profiles of messenger RNA (mRNA) expression of 33 pancreatic cancer cell lines and 892 patient samples of pancreatic adenocarcinoma (PAAD) were obtained from the Gene Expression Omnibus (GEO) database. Microarray data were normalized using the robust multichip average (RMA) algorithm and batch effect removal was performed using ComBat. The pooled data of each PAAD cell line were compared to patient tumors based on the top 2,000 genes with largest interquartile range (IQR), 134 gene-collections of cancer-related pathways, and 504 gene-collections of cancer-related functions using pairwise Pearson’s correlation analysis. RESULTS: PAAD cell lines were poorly correlated with patient tumor tissues based on the top 2,000 genes. Up to 50% of cancer-related pathways were not strongly recommended in PAAD cell lines, and a small proportion of cancer-related functions (12–17%) were poorly correlated with PAAD cell lines. In pan-pathway analysis, the cell lines showing the highest genetic correlation to patient tumors were Panc 03.27 for PAAD cell lines from a primary lesion site and CFPAC-1 for PAAD cell lines from a metastatic lesion site. In pan-function analysis, the cell lines showing the highest genetic correlation to patient tumors were Panc 03.27 for PAAD cell lines from a primary lesion site and Capan-1 for PAAD cell lines from a metastatic lesion site. CONCLUSIONS: The gene expression profiles of PAAD cell lines correlate weakly with those of primary pancreatic tumors. Through comparison of the genetic similarity between PAAD cell lines and human tumor tissue, we have provided a strategy for choosing the appropriate PAAD cell line. |
format | Online Article Text |
id | pubmed-10174970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-101749702023-05-12 Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors Hu, Yan Gao, Peng Xu, Gaoqi Sun, Jiao Xin, Wenxiu Kong, Sisi Ding, Haiying Zhu, Junfeng Fang, Luo Transl Cancer Res Original Article BACKGROUND: Cancer cell lines are important research models for studying tumor biology in vivo. The accuracy of such studies is highly dependent on the phenotypic and genetic similarity of cell lines to patient tumors, but this is not always the case, particularly for pancreatic cancer. METHODS: We compared the gene expression profiles of various pancreatic cancer cell lines and primary human pancreatic tumor tissues to determine which pancreatic cancer cell line best models human primary tumor. Profiles of messenger RNA (mRNA) expression of 33 pancreatic cancer cell lines and 892 patient samples of pancreatic adenocarcinoma (PAAD) were obtained from the Gene Expression Omnibus (GEO) database. Microarray data were normalized using the robust multichip average (RMA) algorithm and batch effect removal was performed using ComBat. The pooled data of each PAAD cell line were compared to patient tumors based on the top 2,000 genes with largest interquartile range (IQR), 134 gene-collections of cancer-related pathways, and 504 gene-collections of cancer-related functions using pairwise Pearson’s correlation analysis. RESULTS: PAAD cell lines were poorly correlated with patient tumor tissues based on the top 2,000 genes. Up to 50% of cancer-related pathways were not strongly recommended in PAAD cell lines, and a small proportion of cancer-related functions (12–17%) were poorly correlated with PAAD cell lines. In pan-pathway analysis, the cell lines showing the highest genetic correlation to patient tumors were Panc 03.27 for PAAD cell lines from a primary lesion site and CFPAC-1 for PAAD cell lines from a metastatic lesion site. In pan-function analysis, the cell lines showing the highest genetic correlation to patient tumors were Panc 03.27 for PAAD cell lines from a primary lesion site and Capan-1 for PAAD cell lines from a metastatic lesion site. CONCLUSIONS: The gene expression profiles of PAAD cell lines correlate weakly with those of primary pancreatic tumors. Through comparison of the genetic similarity between PAAD cell lines and human tumor tissue, we have provided a strategy for choosing the appropriate PAAD cell line. AME Publishing Company 2023-04-25 2023-04-28 /pmc/articles/PMC10174970/ /pubmed/37180676 http://dx.doi.org/10.21037/tcr-23-173 Text en 2023 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Hu, Yan Gao, Peng Xu, Gaoqi Sun, Jiao Xin, Wenxiu Kong, Sisi Ding, Haiying Zhu, Junfeng Fang, Luo Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title | Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title_full | Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title_fullStr | Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title_full_unstemmed | Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title_short | Correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
title_sort | correlation of gene expression profiles to identify pancreatic cancer cell lines that best model primary human tumors |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174970/ https://www.ncbi.nlm.nih.gov/pubmed/37180676 http://dx.doi.org/10.21037/tcr-23-173 |
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