Gene variants that may cause adverse drug reactions in non-Hodgkin’s lymphoma therapy: a genomic and bioinformatics approach

Introduction. Chemotherapy remains a cornerstone treatment for most non-Hodgkin lymphoma (NHL) patients, yet it is frequently associated with significant adverse effects that compromise their quality of life. Emerging evidence highlights that genetic factors, particularly single nucleotide polymorphisms (SNPs), play a critical role in determining individual variability in treatment responses and susceptibility to drug-related complications.

Aim of this study: to identify SNPs associated with chemotherapy-induced adverse events in NHL through advanced bioinformatics approaches, enabling personalized therapeutic strategies to mitigate risks.

Material abd Methods. This study leveraged the PharmGKB database to identify SNPs associated with Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone. SNPs meeting inclusion criteria (Level of Evidence 1A-3, p<0.01) were prioritized for functional impact analysis using PolyPhen-2 scores. Data extraction and computational analysis utilized SNPnexus, HaploReg v4.2, Ensembl Genome Browser (GRCh37), and PharmGKB. The methodology employed a descriptive approach, relying exclusively on secondary data sources.

Results. This study identified 11 SNPs that may be important for hematological toxicity, liver damage, and nausea risk. These genes are SLC22A16, GSTP1, NAT2, ATM, ABCB1, CYP2B6, XRCC1, ERCC1, MUTYH PIK3R2, and PNPLA3. In terms of priority and risk, the most significant variants were rs738409 (PNPLA3), rs12210538 (SLC22A16), rs2229109 (ABCB1), and rs56022120 (PIK3R2). The distribution of SNP alleles is more common in European populations than in Asians or Africans.

Conclusion. For the first time, we found SNPs that indicate an increase in drug side effects. These SNPs rs738409, rs12210538, rs2229109 and rs56022120 increase the severity of NHL patients during chemotherapy. In order to ensure that these biomarkers can be used in clinical practice and to support the creation of precision medicine strategies, additional clinical validation is needed.

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