Enhancing cancer subtype classification through convolutional neural networks: a deepinsight analysis of TCGA gene expression data

Xie T, Wang Z, Zhao Q, Bai Q, Zhou X, Gu Y, Peng W, Wang H. Machine learning-based analysis of mr multiparametric radiomics for the subtype classification of breast cancer. Front Oncol. 2019;9:505. https://doi.org/10.3389/fonc.2019.00505.

Article  Google Scholar 

Zhang L, Li C, Peng D, Yi X, He S, Li F, Zheng X, Huang WE, Zhao L, Huang X. Raman spectroscopy and machine learning for the classification of breast cancers. Spectrochim Acta Part A Mol Biomol Spectrosc (Print). 2022;1:1. https://doi.org/10.1016/j.saa.2021.120300.

Article  Google Scholar 

Bicakci M, Ayyildiz O, Aydin Z, Basturk A, Karacavus S, Yilmaz B. Metabolic imaging based sub-classification of lung cancer. IEEE Access. 2020;8:218470–6. https://doi.org/10.1109/ACCESS.2020.3040155.

Article  Google Scholar 

Park KH, Batbaatar E, Piao Y, Theera-Umpon N, Ryu KH. Deep learning feature extraction approach for hematopoietic cancer subtype classification. Int J Environ Res Public Health. 2021;18(4):2197. https://doi.org/10.3390/ijerph18042197.

Article  Google Scholar 

Kohli N, Tomal J, Yan Y. Identification of important snps using bayesian deep learning on whole-genome arabidopsis thaliana data. In: 2023 IEEE international conference on bioinformatics and biomedicine (BIBM). 2023. https://doi.org/10.1109/bibm58861.2023.10385457 .

Shen J, Shi J, Luo J. Deep learning approach for cancer subtype classification using high-dimensional gene expression data. BMC Bioinform. 2022;23:430. https://doi.org/10.1186/s12859-022-04980-9.

Article  Google Scholar 

Van Der Maaten L, Hinton G. Visualizing data using t-sne. J Mach Learn Res. 2008.

Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. Smote: synthetic minority over-sampling technique. J Artif Intell Res. 2002;16:321–57. https://doi.org/10.1613/jair.953.

Article  MATH  Google Scholar 

The Cancer Genome Atlas Program (TCGA). Accessed: 2024-10-01. https://www.cancer.gov/ccg/research/genome-sequencing/tcga

CBioPortal for Cancer Genomics. Accessed: 2024-10-01. https://www.cbioportal.org/

Li B, Dewey CN. Rsem: accurate transcript quantification from rna-seq data with or without a reference genome. BMC Bioinform. 2011;12:323. https://doi.org/10.1186/1471-2105-12-323.

Article  Google Scholar 

Yersal O, Barutca S. Biological subtypes of breast cancer: prognostic and therapeutic implications. World J Clin Oncol. 2014;5(3):412. https://doi.org/10.5306/wjco.v5.i3.412.

Article  Google Scholar 

Iqbal N, Iqbal N. Human epidermal growth factor receptor 2 (her2) in cancers: overexpression and therapeutic implications. BioMed Res Int. 2014. https://doi.org/10.1155/2014/852748.

Article  Google Scholar 

Yin L, Duan JJ, Bian XW, Yu SC. Triple-negative breast cancer molecular subtyping and treatment progress. Breast Cancer Res. 2020;22:2020. https://doi.org/10.1186/s13058-020-01296-5.

Article  Google Scholar 

Sharma A, Vans E, Shigemizu D, et al. Deepinsight: a methodology to transform a non-image data to an image for convolution neural network architecture. Sci Rep. 2019;9:11399. https://doi.org/10.1038/s41598-019-47765-6.

Article  Google Scholar 

Peng Y, Huang X, Wang H. lncrna acta2-as1 predicts malignancy and poor prognosis of triple-negative breast cancer and regulates tumor progression via modulating mir-532-5p. BMC Mol Cell Biol. 2022;23(1):34. https://doi.org/10.1186/s12860-022-00432-7.

Article  Google Scholar 

Takaku M, Grimm SA, Wade PA. Gata3 in breast cancer: tumor suppressor or oncogene? Gene Exp. 2015;16(4):163–8. https://doi.org/10.3727/105221615X14399878166113.

Article  Google Scholar 

Gui Z, Tian Y, Yu T, Liu S, Liu C, Zhang L. Clinical implications and immune features of CENPN in breast cancer. BMC Cancer. 2023. https://doi.org/10.1186/s12885-023-11376-2.

Article  Google Scholar 

Kondratyeva L, Chernov I, Kopantzev E, Didych D, Kuzmich A, Alekseenko I, Kostrov S, Sverdlov E. Pancreatic lineage specifier pdx1 increases adhesion and decreases motility of cancer cells. Cancers (Basel). 2021;13(17):4390. https://doi.org/10.3390/cancers13174390.

Article  Google Scholar 

World Intellectual Property Organization (WIPO): use of protein PDX1 as a marker for breast cancer. WO2005/123944, 2005. https://patentscope.wipo.int/

Ma J, Li J, Li H, Xiao X, Shen L, Fang L. Downregulation of pancreatic-duodenal homeobox 1 expression in breast cancer patients: a mechanism of proliferation and apoptosis in cancer. Mol Med Rep. 2012. https://doi.org/10.3892/mmr.2012.1067.

Article  Google Scholar 

Boland CR, Goel A. Microsatellite instability in colorectal cancer. Gastroenterology. 2010;138(6):2073–20873. https://doi.org/10.1053/j.gastro.2009.12.064.

Article  Google Scholar 

Epping MT, Hart AAM, Glas AM, Krijgsman O, Bernards R. Prame expression and clinical outcome of breast cancer. Br J Cancer. 2008;99(3):398–403. https://doi.org/10.1038/sj.bjc.6604494. (Epub 2008 Jul 22, PMID: 18648365, PMCID: PMC2527791.).

Article  Google Scholar 

Mourksi NE, Morin C, Fenouil T, Diaz JJ, Marcel V. snoRNAs offer novel insight and promising perspectives for lung cancer understanding and management. Cells. 2020;9(3):541. https://doi.org/10.3390/cells9030541. (PMCID: PMC7140444).

Article  Google Scholar 

...Hastings K, Yu HA, Wei W, Sanchez-Vega F, Deveaux M, Choi J, Rizvi H, Lisberg A, Lydon CA, Liu Z, Henick BS, Wurtz A, Cai G, Plodkowski AJ, Long NM, Halpenny DF, Schultz N, Riely GJ, Arcila ME, Ladanyi ML, Zelterman D, Herbst RS, Goldberg SB, Awad MM, Garon EB, Gettinger S, Hellmann MD, Politi K. EGFR mutation subtypes and response to immune checkpoint blockade treatment in non-small-cell lung cancer. Ann Oncol. 2019;30(8):1311–20. https://doi.org/10.1093/annonc/mdz141.

Article  Google Scholar 

Lau SCM, Fares AF, Le LW, Mackay KM, Soberano S, Chan SW, Smith E, Ryan M, Tsao MS, Bradbury PA, Pal P, Shepherd FA, Liu G, Leighl NB, Sacher AG. Subtypes of egfr- and her2-mutant metastatic nsclc influence response to immune checkpoint inhibitors. Clin Lung Cancer. 2021;22(4):253–9. https://doi.org/10.1016/j.cllc.2020.12.015.

Article  Google Scholar 

Lewis WE, Hong L, Mott FE, Simon G, Wu CC, Rinsurongkawong W, Lee JJ, Lam VK, Heymach JV, Zhang J, Le X. Efficacy of targeted inhibitors in metastatic lung squamous cell carcinoma with EGFR or ALK alterations. JTO Clin Res Rep. 2021;2(11):100237. https://doi.org/10.1016/j.jtocrr.2021.100237.

Article  Google Scholar 

g:Profiler—a web server for functional enrichment analysis and conversions of gene lists. https://biit.cs.ut.ee/gprofiler/gost (n.d.)

Kalluri R, Weinberg RA. The basics of epithelial-mesenchymal transition. J Clin Investig. 2009;119(6):1420–8. https://doi.org/10.1172/JCI39104.

Article  Google Scholar 

Sarrio D. Epithelial-mesenchymal transition in breast cancer relates to the basal-like phenotype. Cancer Res. 2008;68(4):989–97. https://doi.org/10.1158/0008-5472.CAN-07-2017.

Article  Google Scholar 

Giordano A, Gao H, Anfossi S, Cohen E, Mego M, Lee BN. Epithelial-mesenchymal transition and stem cell markers in patients with her2-positive metastatic breast cancer. Mol Cancer Ther. 2012;11(11):2526–34. https://doi.org/10.1158/1535-7163.MCT-12-0460.

Article  Google Scholar 

Weissberg I, Seneda AL, Pagnin AF, Lan W, Reis PP, Drigo SA. Pd.02.03 alterations in the immune profile of lusc and luad detected by a neural network may reveal new immunotherapy targets. J Thorac Oncol. 2023;18:7.

Article  Google Scholar 

Chen M, Liu X, Du J, Wang X-J, Xia L. Differentiated regulation of immune-response related genes between luad and lusc subtypes of lung cancers. Oncotarget. 2017;8:133–44. https://doi.org/10.18632/oncotarget.13346. (Published: November 15, 2016).

Article  Google Scholar 

Xiao D, He J. Epithelial mesenchymal transition and lung cancer. J Thorac Dis. 2010;2(3):154–9. https://doi.org/10.3978/j.issn.2072-1439.2010.02.03.7. (Accessed: 2025-01-01).

Article  MathSciNet  Google Scholar 

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