Evidence map›Paper›PMID 35737091›Full record

ArticleJournal of cancer research and clinical oncology2023

Whole-exome sequencing of Indian prostate cancer reveals a novel therapeutic target: POLQ.

Febina Ravindran, Anika Jain, Sagar Desai, Navjoth Menon, Kriti Srivastava, Pushpinder Singh Bawa, K Sateesh, N Srivatsa, S K Raghunath, Subhashini Srinivasan and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Febina Ravindran *Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Anika Jain *Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Sagar DesaiInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Navjoth MenonInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Kriti SrivastavaInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Pushpinder Singh BawaInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
K SateeshHealthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India.
N SrivatsaHealthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India.
S K RaghunathHealthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India.
Subhashini SrinivasanInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Bibha ChoudharyInstitute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India. vibha@ibab.ac.in.
Institute of Bioinformatics and Applied Biotechnology · INHealthcare Global Enterprises · IN

Funding

Department of Biotechnology, Ministry of Science and Technology, India BT/PR13458/COE/34/33/2015 and BT/PR13616/GET/119/9/2015Department of Science and Technology, Ministry of Science and Technology, India SR/FST/LSI-5361/2012
6 · The paper itself

Abstract

purposeProstate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms.

methodsWhole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock.

resultsTP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug.

conclusionIn this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.

Indexed as

DNA-Directed DNA PolymeraseProstatic NeoplasmsSemenDNA Polymerase thetaDNA Repair EnzymesExome SequencingHumansMaleMutationPilot ProjectsDNA-Directed DNA PolymeraseDNA Polymerase thetaDNA Repair EnzymesDriver mutationsIndian prostate cancerPOLQ mutationTargeted therapyWhole-exome sequencing

Identifiers

PMID35737091
PMCPMC11797685
OpenAlexW4283369122

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.