Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

Author:

Shukla Nidhi12,Kour Bhumandeep3ORCID,Sharma Devendra4,Vijayvargiya Maneesh5,Sadasukhi T. C.6,Medicherla Krishna Mohan17ORCID,Malik Babita2,Bissa Bhawana8,Vuree Sugunakar910ORCID,Lohiya Nirmal Kumar11,Suravajhala Prashanth912ORCID

Affiliation:

1. Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research (BISR), Statue Circle, Jaipur 302001, India

2. Department of Chemistry, School of Basic Sciences, Manipal University Jaipur, Jaipur 303007, India

3. Department of Biotechnology, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara 144001, India

4. Department of Urology, Rukmani Birla Hospital, Jaipur 302018, India

5. Department of Pathology, Mahatma Gandhi University of Medical Sciences and Technology, Jaipur 302022, India

6. Department of Urology, Mahatma Gandhi University of Medical Sciences and Technology, Jaipur 302022, India

7. Department of Bioengineering, Birla Institute of Technology, Mesra Jaipur Campus, 27-Malaviya Industrial Area, Jaipur 302017, India

8. Department of Biochemistry, Central University of Rajasthan, Ajmer 305817, India

9. Bioclues.org, Hyderabad 500072, India

10. MNR Foundation for Research & Innovation, MNR University, Sangareddy 502294, India

11. Department of Zoology, Center for Advanced Studies, University of Rajasthan, Jaipur 302004, India

12. Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India

Abstract

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

Funder

Department of Science and Technology (DST), Government of India for women scientist fellowshi

Publisher

MDPI AG

Subject

General Medicine

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