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ArticleMolecular biology reports2025

Xenobiotic metabolizing gene polymorphisms and their influence on ovarian cancer susceptibility: A Case-Control and an in silico approach.

Harshavardhani Canchi Sistla, Arun Seshachalam, Krishna Kumar Rathnam, Taruna Rajagopal, Srikanth Talluri, Nageswara Rao Dunna

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Article in Molecular biology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Harshavardhani Canchi SistlaCancer Genomics Laboratory, Department of Biotechnology, School of Chemical and Biotechnology, SASTRA - Deemed University, Thanjavur, 613 401, India.
Arun SeshachalamDepartment of Medical and Paediatric Oncology, Dr. G.V.N Cancer Institute, Riverside, Trichy, 620 005, India.
Krishna Kumar RathnamDepartment of Hemato Oncology - Medical Oncology and Bone Marrow Transplantation, Meenakshi Mission Hospital & Research Centre, Madurai, 625 107, India.
Taruna RajagopalDepartment of Biotechnology, Sona College of Arts and Science, Salem, 636 005, India.
Srikanth TalluriDana Farber Cancer Institute, Boston, MA, 02215, USA.
Nageswara Rao DunnaCancer Genomics Laboratory, Department of Biotechnology, School of Chemical and Biotechnology, SASTRA - Deemed University, Thanjavur, 613 401, India. dnrao@biotech.sastra.edu.

Funding

SASTRA University SASTRA-TRR-SCBT-1-11092024
6 · The paper itself

Abstract

backgroundIdentifying the impact of low-penetrance genes in ovarian cancer (OC) presents a significant challenge. Polymorphisms in xenobiotic metabolism genes (XMGs) have influenced carcinogen detoxification, cancer susceptibility, and treatment response in many cancers, yet their role in OC remains fragmentary. The present study examined the genetic variants in crucial XMGs such as CYP2D6, NQO1, GSTT1, GSTM1, and GSTP1 in 460 subjects (209 OC patients and 251 controls).

methodsPCR-RFLP (CYP2D6, NQO1, and GST-P1) and multiplex-PCR (GSTT1 and GSTM1) were used for genotyping. Logistic regression was employed to evaluate the association of genotypes with OC risk. MDR analysis was used to detect SNP-SNP interactions. Various computational tools were used to assess the impact of variants on protein function, structure, and stability.

resultsThe results revealed that the intermediate metabolizers (GA) of CYP2D6*4 variant conferred a 2-fold elevated OC risk (OR 2.01; 95% CI 1.35-3.01; p = 0.0023). Similarly, for NQO1*2 (P187S) variant, the mutant TT genotype showed a significant association with increased OC risk (OR 2.35; 95% CI 1.25-4.42; p = 0.023). No association of GSTT1, GSTM1, and GSTP1 variants was observed in the present study. However, combinatorial gene analysis using MDR indicated that the AG (GSTP1), TT (NQO1), and GA (CYP2D6) genotypes conferred 18.4-fold increased OC risk (OR 18.42; 95% CI 2.18-155.21; p = 0.007). In silico analyses predicted the functional impact of two missense variants (rs1800566 and rs1695) and the effect on splicing for the CYP2D6*4 splice variant.

conclusionThe present study highlights the association of CYP2D6, GSTP1, and NQO1 variants with elevated risk of OC in South Indian women.

Indexed as

Ovarian NeoplasmsXenobioticsAdultAgedCase-Control StudiesComputer SimulationCytochrome P-450 CYP2D6FemaleGenetic Predisposition to DiseaseGenotypeGlutathione S-Transferase piGlutathione TransferaseHumansMiddle AgedNAD(P)H Dehydrogenase (Quinone)Polymorphism, Single NucleotideCytochrome P-450 CYP2D6Glutathione S-Transferase piglutathione S-transferase T1Glutathione TransferaseGSTP1 protein, humanNAD(P)H Dehydrogenase (Quinone)NQO1 protein, humanXenobioticsCYP2D6GSTM1GSTP1GSTT1NQO1Ovarian cancerPolymorphisms

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