Relating pancreatic ductal adenocarcinoma tumor samples and cell lines using gene expression data in translational research

Liu Shuaichen; Wang Guangyi

doi:10.14715/cmb/2018.64.5.26

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Vol. 64 No. 5: Issue 5

Issue Published : May 1, 2018

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Relating pancreatic ductal adenocarcinoma tumor samples and cell lines using gene expression data in translational research

https://doi.org/10.14715/cmb/2018.64.5.26

Liu Shuaichen

Department of Hepatobiliary & Pancreas Surgery, The First Hospital, Jilin University, Changchun, Jilin 130021, China

Wang Guangyi

Department of Hepatobiliary & Pancreas Surgery, The First Hospital, Jilin University, Changchun, Jilin 130021, China

Corresponding Author(s) : Wang Guangyi

rz1332@163.com

Cellular and Molecular Biology, Vol. 64 No. 5: Issue 5
Article Published : April 30, 2018

Abstract

Cancer cell lines are useful tools to study cancer biology. Choosing proper cell lines based on experimental design for different experiments is vital. Relating tumors and cell lines, and recognizing their similarities and differences are thus very important for translational research. Abundant online databases with genomic and expression profile are suitable resources for conducting the assessment. Pancreatic ductal adenocarcinoma (PDAC) is a severe cancer with grim prognosis. Current effective treatments of PDAC remain limited. In this study, we compared the gene expression profile of 178 PDAC tumor samples from The Cancer Genome Atlas and 44 pancreatic cancer cell lines from Cancer Cell Line Encyclopedia. We showed that all pancreatic cancer cell lines resemble PDAC tumors but the correlation is different. Our study will be used to guide the selection of PDAC cell lines.

Keywords

Pancreatic ductal adenocarcinoma Cancer cell line Gene expression correlation TCGA CCLE.

Shuaichen, L., & Guangyi, W. (2018). Relating pancreatic ductal adenocarcinoma tumor samples and cell lines using gene expression data in translational research. Cellular and Molecular Biology, 64(5), 157–162. https://doi.org/10.14715/cmb/2018.64.5.26

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References

(1)Saensa-Ard, S., et al., Establishment of cholangiocarcinoma cell lines from patients in the endemic area of liver fluke infection in Thailand. Tumour Biol, 2017. 39(11): p. 1010428317725925.
(2)Kambara, H., et al., Establishment of a novel permissive cell line for the propagation of hepatitis C virus by expression of microRNA miR122. J Virol, 2012. 86(3): p. 1382-93.
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(4)Weinstein, J.N., et al., The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet, 2013. 45(10): p. 1113-20.
(5)Li, B., et al., miR-3174 Contributes to Apoptosis and Autophagic Cell Death Defects in Gastric Cancer Cells by Targeting ARHGAP10. Mol Ther Nucleic Acids, 2017. 9: p. 294-311.
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(7)Huang da, W., B.T. Sherman, and R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009. 4(1): p. 44-57.
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(9)Moore, P.S., et al., Genetic profile of 22 pancreatic carcinoma cell lines. Analysis of K-ras, p53, p16 and DPC4/Smad4. Virchows Arch, 2001. 439(6): p. 798-802.
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(11)Guo, Y., et al., Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data. PLoS One, 2013. 8(8): p. e71462.
(12)Agarwal, R., et al., Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets. Cancer Genet, 2017. 216-217: p. 37-51.
(13)Domcke, S., et al., Evaluating cell lines as tumour models by comparison of genomic profiles. Nat Commun. 4.
(14)Deer, E.L., et al., Phenotype and Genotype of Pancreatic Cancer Cell Lines. Pancreas, 2010. 39(4): p. 425-35.
(15)Lee, J.S., Exploring cancer genomic data from the cancer genome atlas project. BMB Rep, 2016. 49(11): p. 607-611.
(16)Barretina, J., et al., The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity. Nature, 2012. 483(7391): p. 603-7.
(17)Liu, M., et al., MCM6 promotes metastasis of hepatocellular carcinoma via MEK/ERK pathway and serves as a novel serum biomarker for early recurrence. J Exp Clin Cancer Res, 2018. 37(1): p. 10.
(18)Chang, W., et al., MiR-377 inhibits the proliferation of pancreatic cancer by targeting Pim-3. Tumour Biol, 2016. 37(11): p. 14813-14824.
(19)Sun, C., et al., F-box protein 11 promotes the growth and metastasis of gastric cancer via PI3K/AKT pathway-mediated EMT. Biomed Pharmacother, 2018. 98: p. 416-423.
(20)Chen, B., et al., Relating hepatocellular carcinoma tumor samples and cell lines using gene expression data in translational research. BMC Med Genomics, 2015. 8 Suppl 2: p. S5.
(21)Zeitouni, D., et al., KRAS Mutant Pancreatic Cancer: No Lone Path to an Effective Treatment. Cancers (Basel), 2016. 8(4).
(22)Wei, F., et al., K-Ras mutation-mediated IGF-1-induced feedback ERK activation contributes to the rapalog resistance in pancreatic ductal adenocarcinomas. Cancer Lett, 2012. 322(1): p. 58-69.
(23)Jaenisch, R. and A. Bird, Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet, 2003. 33 Suppl: p. 245-54.
(24)Robinson, E.K., et al., Cell cycle regulation of human pancreatic cancer by tamoxifen. Ann Surg Oncol, 1998. 5(4): p. 342-9.
(25)Couch, F.J., et al., Association of Mitotic Regulation Pathway Polymorphisms with Pancreatic Cancer Risk and Outcome. Cancer Epidemiol Biomarkers Prev, 2010. 19(1): p. 251-7.
(26)Martinez-Bosch, N., J. Vinaixa, and P. Navarro, Immune Evasion in Pancreatic Cancer: From Mechanisms to Therapy. Cancers (Basel), 2018. 10(1).

References

(1)Saensa-Ard, S., et al., Establishment of cholangiocarcinoma cell lines from patients in the endemic area of liver fluke infection in Thailand. Tumour Biol, 2017. 39(11): p. 1010428317725925.

(2)Kambara, H., et al., Establishment of a novel permissive cell line for the propagation of hepatitis C virus by expression of microRNA miR122. J Virol, 2012. 86(3): p. 1382-93.

(3)Barretina, J., et al., The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature, 2012. 483(7391): p. 603-7.

(4)Weinstein, J.N., et al., The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet, 2013. 45(10): p. 1113-20.

(5)Li, B., et al., miR-3174 Contributes to Apoptosis and Autophagic Cell Death Defects in Gastric Cancer Cells by Targeting ARHGAP10. Mol Ther Nucleic Acids, 2017. 9: p. 294-311.

(6)Domcke, S., et al., Evaluating cell lines as tumour models by comparison of genomic profiles. Nat Commun, 2013. 4: p. 2126.

(7)Huang da, W., B.T. Sherman, and R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009. 4(1): p. 44-57.

(8)Hamidi, H., et al., KRAS mutational subtype and copy number predict in vitro response of human pancreatic cancer cell lines to MEK inhibition. Br J Cancer, 2014. 111(9): p. 1788-801.

(9)Moore, P.S., et al., Genetic profile of 22 pancreatic carcinoma cell lines. Analysis of K-ras, p53, p16 and DPC4/Smad4. Virchows Arch, 2001. 439(6): p. 798-802.

(10)Sun, C., et al., Characterization of the mutations of the K-ras, p53, p16, and SMAD4 genes in 15 human pancreatic cancer cell lines. Oncol Rep, 2001. 8(1): p. 89-92.

(11)Guo, Y., et al., Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data. PLoS One, 2013. 8(8): p. e71462.

(12)Agarwal, R., et al., Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets. Cancer Genet, 2017. 216-217: p. 37-51.

(13)Domcke, S., et al., Evaluating cell lines as tumour models by comparison of genomic profiles. Nat Commun. 4.

(14)Deer, E.L., et al., Phenotype and Genotype of Pancreatic Cancer Cell Lines. Pancreas, 2010. 39(4): p. 425-35.

(15)Lee, J.S., Exploring cancer genomic data from the cancer genome atlas project. BMB Rep, 2016. 49(11): p. 607-611.

(16)Barretina, J., et al., The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity. Nature, 2012. 483(7391): p. 603-7.

(17)Liu, M., et al., MCM6 promotes metastasis of hepatocellular carcinoma via MEK/ERK pathway and serves as a novel serum biomarker for early recurrence. J Exp Clin Cancer Res, 2018. 37(1): p. 10.

(18)Chang, W., et al., MiR-377 inhibits the proliferation of pancreatic cancer by targeting Pim-3. Tumour Biol, 2016. 37(11): p. 14813-14824.

(19)Sun, C., et al., F-box protein 11 promotes the growth and metastasis of gastric cancer via PI3K/AKT pathway-mediated EMT. Biomed Pharmacother, 2018. 98: p. 416-423.

(20)Chen, B., et al., Relating hepatocellular carcinoma tumor samples and cell lines using gene expression data in translational research. BMC Med Genomics, 2015. 8 Suppl 2: p. S5.

(21)Zeitouni, D., et al., KRAS Mutant Pancreatic Cancer: No Lone Path to an Effective Treatment. Cancers (Basel), 2016. 8(4).

(22)Wei, F., et al., K-Ras mutation-mediated IGF-1-induced feedback ERK activation contributes to the rapalog resistance in pancreatic ductal adenocarcinomas. Cancer Lett, 2012. 322(1): p. 58-69.

(23)Jaenisch, R. and A. Bird, Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet, 2003. 33 Suppl: p. 245-54.

(24)Robinson, E.K., et al., Cell cycle regulation of human pancreatic cancer by tamoxifen. Ann Surg Oncol, 1998. 5(4): p. 342-9.

(25)Couch, F.J., et al., Association of Mitotic Regulation Pathway Polymorphisms with Pancreatic Cancer Risk and Outcome. Cancer Epidemiol Biomarkers Prev, 2010. 19(1): p. 251-7.

(26)Martinez-Bosch, N., J. Vinaixa, and P. Navarro, Immune Evasion in Pancreatic Cancer: From Mechanisms to Therapy. Cancers (Basel), 2018. 10(1).

Author biographies is not available.