Survival prediction for prostate cancer using machine learning and bioinformatics models

Utpala Nanda Chowdhury, Shamim Ahmad, M. Babul Islam, Mohammad Ali Moni

Research output: Book chapter/Published conference paperConference paperpeer-review

2 Citations (Scopus)

Abstract

Prostate cancer (PC) is the most commonly diagnosed and the second most lethal malignancy in men. Proper understanding about the factors influencing the disease mechanism, response to the treatment and long term survival could facilitate effective disease management, treatment planning and decision making. Previous research initiatives reported a number of genes having impact on PC development but their genetic influence on the overall survival of the patients is still obscure. In this study, we fist identified PC related signature genes by analysing the RNA-seq transcriptomic data. Then we investigated the influence of those genes on the survival of PC patients using the clinical and transcriptomic data from the Cancer Genome Atlas (TCGA). Considering the univariate and multivariate analysis using the Cox proportional-hazards (CoxPH) model, we evidenced notable variation in the survival period between the altered and normal groups for two genes (APLN, and DUOXA1). We also identified ten hub genes such as RRAS, TUBB4A, CAV1, EFNB1, RHOU, ITGB4, TPM2, MYL9, UBC, and TGFB3 in protein-protein interaction analysis that could be the source of potential therapeutic intervention. Moreover, several significant molecular pathways through functional enrichment analysis was obtained. After verification through functional studies, the identified genetic determinants could serve as therapeutic target for prolonged PC survival.

Original languageEnglish
Title of host publicationThe 6th International conference on computer, communication, chemical, materials and electronic engineering
Subtitle of host publicationIC4ME2 2021
EditorsAbu Bakar Md. Ismail, Md. Ekramul Hamid, Md. Hasnat Kabir
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781665406376
ISBN (Print)9781665406383 (Print on demand)
DOIs
Publication statusPublished - 2021
Event6th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2021 - University of Rajshahi, Rajshahi, Bangladesh
Duration: 26 Dec 202127 Dec 2021
https://ieeexplore.ieee.org/xpl/conhome/9768399/proceeding (Proceedings)
https://web.archive.org/web/20220808043553/http://dept.ru.ac.bd/ic4me2/2021/ (Archived conference website)

Conference

Conference6th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2021
Country/TerritoryBangladesh
CityRajshahi
Period26/12/2127/12/21
OtherThe International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2-2021) will be held from December 26~27, 2021 at University of Rajshahi in Bangladesh. This conference is a sequel of our first conference ICMEIE-2015. This is the 6th episode of IC4ME2 conference which is going to take place. This year, this conference will be hosted in collaboration with Rajshahi University of Engineering and Technology (RUET) and Kyushu Institute of Technology (Kyutech), Japan. The conference will gather world-class researchers, engineers and educators engaged in the fields of Materials, Electronics, Chemical and Information Engineering to meet and present their latest activities. The main theme of this conference is Networking and Collaboration. Accepted papers will be submitted for inclusion into IEEE Xplore; subject to meeting IEEE Xplore’s scope and quality requirements. Papers outside the scope of IEEE will be published in the conference proceedings only. You are cordially invited to attend this interesting event.
Internet address

Fingerprint

Dive into the research topics of 'Survival prediction for prostate cancer using machine learning and bioinformatics models'. Together they form a unique fingerprint.

Cite this