Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer

Minhyeong Lee

doi:10.20944/preprints201912.0183.v2

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preprints.org > medicine and pharmacology > oncology and oncogenics > doi: 10.20944/preprints201912.0183.v2

Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer

Minhyeong Lee

Version 1 : Received: 9 December 2019 / Approved: 13 December 2019 / Online: 13 December 2019 (10:57:29 CET)
Version 2 : Received: 21 August 2020 / Approved: 21 August 2020 / Online: 21 August 2020 (11:26:33 CEST)

How to cite: Lee, M. Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer. Preprints 2019, 2019120183. https://doi.org/10.20944/preprints201912.0183.v2 Lee, M. Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer. Preprints 2019, 2019120183. https://doi.org/10.20944/preprints201912.0183.v2

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MDPI and ACS Style

Lee, M. Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer. Preprints 2019, 2019120183. https://doi.org/10.20944/preprints201912.0183.v2

APA Style

Lee, M. (2020). Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer. Preprints. https://doi.org/10.20944/preprints201912.0183.v2

Chicago/Turabian Style

Lee, M. 2020 "Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer" Preprints. https://doi.org/10.20944/preprints201912.0183.v2

Abstract

This study aimed to rank cancers based on the strength of the relationship between the comprehensive mRNA expression levels of the most harmful or protective genes and patient survival. Using The Cancer Genome Atlas dataset that includes the RNA sequencing and c linical data, we investigated not only gene specific prognostic availability, but also comprehensive prognostic availability of prognostic genes filtered by the Cox coefficient values, and ranked cancers using a specially designed prognostic indicator. Usi ng Kaplan Meier plots, we found that cancers vary in the strength of the influence of their prognostic genes, and can be ranked based on this finding. There is a high probability that the treatment developed by using methods that reduce or increase the exp ression levels of biomarkers, for cancers that ranked at the bottom will not be efficient. The results of this study could be used as scientific evidence for the same.

Supplementary and Associated Material

https:// github.com/Minhyeong 1022/TCGA_mRNA expression_survival_ correlation_research: All files and R codes generated for this study, including figures and tables, can be downloaded from the author’s github page

Keywords

Bioinformatics, Genomics, TCGA, Cox Model.

Subject

Medicine and Pharmacology, Oncology and Oncogenics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Comments (1)

Comment 1

Received: 21 August 2020
Commenter: Minhyeong Lee
Commenter's Conflict of Interests: Author

Comment: English proofreading and editing, figure and formula modification

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