Pan-cancer analysis for studying cancer stage using protein and gene expression data

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Sameer MishraMay D Wang

Abstract

Pan-cancer analyses attempt to discover similar features among multiple cancers to identify fundamental patterns common to cancer development and progression. A pan-cancer analysis integrating both protein expression and transcriptomic data is important because it can identify genes that are linked to proteins potentially responsible for a patient's status. This study aims to identify differentially expressed (DE) genes between early and advanced cases of multiple cancer types through the usage of RNA sequencing data. The relevance of these genes is further investigated by developing predictive models using K-nearest neighbor and linear discriminant analysis classifiers. The use of cancer-specific and non-cancer specific features resulted in several moderately performing models. Highlighted genes were further investigated to determine if they encoded for proteins identified in a previously conducted pan-cancer analysis. The results of this study suggest that a pan-cancer analysis may be highly complementary to standard analyses of individual cancers for identifying biologically relevant DE genes and can assist in developing effective predictive models for cancer progression.

References

Sep 17, 2020·BMC Medical Informatics and Decision Making·Li TongMay D Wang

Related Concepts

Study
Gene Expression Regulation, Neoplastic
Antineoplastic Agents
TNM Staging System
Genes
Sequence Determinations, RNA
Neoplasms
Cancer Progression
JM 2820
Gene Expression

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