Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

ADME gene-driven prognostic model for bladder cancer: a breakthrough in predicting survival and personalized treatment

BACKGROUND

Genes that participate in the absorption, distribution, metabolism, excretion (ADME) processes occupy a central role in pharmacokinetics. Meanwhile, variability in clinical outcomes and responses to treatment is notable in bladder cancer (BLCA).

METHODS

Our study utilized expansive datasets from TCGA and the GEO to explore prognostic factors in bladder cancer. Utilizing both univariate Cox regression and the lasso regression techniques, we identified ADME genes critical for patient outcomes. Utilizing genes identified in our study, a model for assessing risk was constructed. The evaluation of this model's predictive precision was conducted using Kaplan-Meier survival curves and assessments based on ROC curves. Furthermore, we devised a predictive nomogram, offering a straightforward visualization of crucial prognostic indicators. To explore the potential factors mediating the differences in outcomes between high and low risk groups, we performed comprehensive analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)-based enrichment analyses, immune infiltration variations, somatic mutation landscapes, and pharmacological sensitivity response assessment etc. Immediately following this, we selected core genes based on the PPI network and explored the prognostic potential of the core genes as well as immune modulation, and pathway activation. And the differential expression was verified by immunohistochemistry and qRT-PCR. Finally we explored the potential of the core genes as pan-cancer biomarkers.

RESULTS

Our efforts culminated in the establishment of a validated 17-gene ADME-centered risk prediction model, displaying remarkable predictive accuracy for BLCA prognosis. Through separate cox regression analyses, the importance of the model's risk score in forecasting BLCA outcomes was substantiated. Furthermore, a novel nomogram incorporating clinical variables alongside the risk score was introduced. Comprehensive studies established a strong correlation between the risk score and several key indicators: patterns of immune cell infiltration, reactions to immunotherapy, landscape of somatic mutation and profiles of drug sensitivity. We screened the core prognostic gene CYP2C8, explored its role in tumor bioregulation and validated its upregulated expression in bladder cancer. Furthermore, we found that it can serve as a reliable biomarker for pan-cancer.

CONCLUSION

The risk assessment model formulated in our research stands as a formidable instrument for forecasting BLCA prognosis, while also providing insights into the disease's progression mechanisms and guiding clinical decision-making strategies.

Identifying ADME-related gene signature for immune landscape and prognosis in KIRC by single-cell and spatial transcriptome analysis

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of kidney cancer. Although multiple therapeutic agents have been proven effective in KIRC, their clinical application has been hindered by a lack of reliable biomarkers. This study focused on the prognostic value and function of drug absorption, distribution, metabolism, and excretion- (ADME-) related genes (ARGs) in KIRC to enhance personalized therapy. The critical role of ARGs in KIRC microenvironment was confirmed by single cell RNA-seq analysis and spatial transcriptome sequencing analysis for the first time. Then, an ADME-related prognostic signature (ARPS) was developed by the bulk RNA-seq analysis. The ARPS, created through Cox regression, LASSO, and stepAIC analyses, identified eight ARGs that stratified patients into high-risk and low-risk groups. High-risk patients had significantly poorer overall survival. Multivariate analysis confirmed the independent predictive ability of ARPS, and an ARPS-based nomogram was constructed for clinical application. Gene ontology and KEGG pathway analyses revealed immune-related functions and pathways enriched in these groups, with low-risk patients showing better responses to immunotherapy. Finally, the expression of ARGs was validated by qRT-PCR and Western blotting experiments. These findings underscore the prognostic significance of ARPS in KIRC and its potential application in guiding personalized treatment strategies.

Investigation of the relationships between eNOS T786C, G894T, intron 4 VNTR (4a/b) gene variations and prostate cancer development and progression

BACKGROUND

This study aimed to investigate the relationships between eNOS T786C, G894T, intron 4 VNTR (4a/b) gene variations and prostate cancer development and progression.

MATERIALS AND METHODS

This study included 88 patients diagnosed with prostate cancer and 91 healthy controls. Polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) methods were used to determine the genotype distributions of eNOS T786C, G894T, intron 4 VNTR (4a/b) gene variations.

RESULTS

In our study, the CC homozygous genotype of eNOS T786C gene variation was determined to be significantly higher in the prostate cancer patient group compared to the healthy control group (OR: 2.343, 95%Cl: 0.990-5.544, p = 0.026), while the CT heterozygous genotype was found to be significantly higher in the healthy control group compared to the prostate cancer patient group was found to be significantly higher (OR: 0.589, 95%Cl: 0.325-1.068, p = 0.041). In addition, while the TT homozygous genotype of the eNOS G894T gene variation was found to be significantly higher in the prostate cancer patient group compared to the healthy control group (OR: 9.068, 95%Cl: 4.396-18.777, p < 0.001), the GT heterozygous genotype was found to be significantly higher in the healthy control group compared to the prostate cancer patient group was determined significantly higher (OR: 0.227, 95%Cl: 0.121-0.427, p < 0.001). For eNOS (4VNTR (4a/b) - G894T) gene variations, aa-TT (p = 0.042) and bb-TT (p < 0.001) haplotype frequencies were significantly higher in the prostate cancer patient group, while aa-GT (p = 0.017), bb-GG (p = 0.049) and bb-GT (p < 0.001) haplotype frequencies were found to be significantly higher in the healthy control group. For eNOS (4VNTR (4a/b) - T786C) gene variations, the bb-CC haplotype frequency was determined to be significantly higher in the patient group (p = 0.049), while the bb-CT haplotype frequency was determined to be significantly higher in the control group (p = 0.008). For eNOS (T786C -G894T) gene variations, TT-TT (p < 0.001) and CC-TT (p = 0.025) haplotype frequencies were found to be significantly higher in the patient group. On the other hand, TT-GT (p = 0.002) and CT-GT (p < 0.001) haplotype frequencies were determined to be significantly higher in the control group. The aa genotype of the intron 4 VNTR (4a/b) gene variation was determined to be significantly higher at Gleason score ≥7 compared to Gleason score <7 (OR: 0.184, 95%Cl: 0.050-0.677, p = 0.005). PSA levels were determined significantly higher in patients with Gleason score 7 and above (p = 0.008). The risk of developing prostate cancer was found to be significantly higher in patients carrying the CC homozygous mutant genotype of the eNOS T786C gene variation (p = 0.024) and in patients carrying the TT homozygous genotype of the G894T gene variation (p = 0.021).

CONCLUSIONS

In our study, the CC homozygous genotype of the eNOS T786C gene variation was determined as a genetic risk factor for the development of prostate cancer, while the CT heterozygous genotype was determined as a protective factor against prostate cancer. For the eNOS G894T gene variation, the TT homozygous genotype was determined as a genetic risk factor for the development of prostate cancer, while the GT heterozygous genotype was determined as a protective factor against prostate cancer. Additionally, for eNOS (4VNTR (4a/b) - G894T) gene variations, aa-TT and bb-TT haplotypes have been identified as genetic risk factors for the development of prostate cancer, while aa-GT, bb-GG and bb-GT haplotypes have been identified as protective factors against the disease has been determined. For eNOS (4VNTR (4a/b) - T786C) gene variations, the bb-CC haplotype was determined as a genetic risk factor in the development of prostate cancer, while the bb-CT haplotype was determined as a protective factor against the disease. TT-TT and CC-TT haplotypes for eNOS (T786C -G894T) gene variations have been identified as genetic risk factors for the development of prostate cancer. In contrast, TT-GT and CT-GT haplotypes were found to be protective factors against the disease. The aa genotype of the intron 4 VNTR (4a/b) gene variation has also been identified as an important genetic risk factor in prostate cancer progression. Significantly increased PSA levels in patients with Gleason score 7 and above, and significantly increased PSA levels in patients carrying the CC and TT homozygous mutant genotype for T786C and G894T gene variations were determined as important risk factors. It is thought that the genetic biomarkers in our study may play a role as personalized therapeutic agents in slowing down the development of prostate cancer, increasing the effectiveness of treatment in prostate cancer, affecting the responses to drugs that regulate NO signaling, predetermining genetic predisposition to prostate cancer, and risk assessment in patients with prostate cancer.

Pan-cancer single-cell landscape of drug-metabolizing enzyme genes

OBJECTIVE

Varied expression of drug-metabolizing enzymes (DME) genes dictates the intensity and duration of drug response in cancer treatment. This study aimed to investigate the transcriptional profile of DMEs in tumor microenvironment (TME) at single-cell level and their impact on individual responses to anticancer therapy.

METHODS

Over 1.3 million cells from 481 normal/tumor samples across 9 solid cancer types were integrated to profile changes in the expression of DME genes. A ridge regression model based on the PRISM database was constructed to predict the influence of DME gene expression on drug sensitivity.

RESULTS

Distinct expression patterns of DME genes were revealed at single-cell resolution across different cancer types. Several DME genes were highly enriched in epithelial cells (e.g. GPX2, TST and CYP3A5 ) or different TME components (e.g. CYP4F3 in monocytes). Particularly, GPX2 and TST were differentially expressed in epithelial cells from tumor samples compared to those from normal samples. Utilizing the PRISM database, we found that elevated expression of GPX2, CYP3A5 and reduced expression of TST was linked to enhanced sensitivity of particular chemo-drugs (e.g. gemcitabine, daunorubicin, dasatinib, vincristine, paclitaxel and oxaliplatin).

CONCLUSION

Our findings underscore the varied expression pattern of DME genes in cancer cells and TME components, highlighting their potential as biomarkers for selecting appropriate chemotherapy agents.

MAOB expression correlates with a favourable prognosis in prostate cancer, and its genetic variants are associated with the metastasis of the disease

Monoamine oxidase B (MAOB), a neurotransmitter-degrading enzyme, was reported to reveal conflicting roles in various cancers. However, the functional role of MAOB and impacts of its genetic variants on prostate cancer (PCa) is unknown. Herein, we genotyped four loci of MAOB single-nucleotide polymorphisms (SNPs), including rs1799836 (A/G), rs3027452 (G/A), rs6651806 (A/C) and rs6324 (G/A) in 702 PCa Taiwanese patients. We discovered that PCa patients carrying the MAOB rs6324 A-allele exhibited an increased risk of having a high initial prostate-specific antigen (iPSA) level (>10 ng/mL). Additionally, patients with the rs3027452 A-allele had a higher risk of developing distal metastasis, particularly in the subpopulation with high iPSA levels. In a subpopulation without postoperative biochemical recurrence, patients carrying the rs1799836 G-allele had a higher risk of developing lymph node metastasis and recurrence compared to those carrying the A-allele. Furthermore, genotype screening in PCa cell lines revealed that cells carrying the rs1799836 G-allele expressed lower MAOB levels than those carrying the A-allele. Functionally, overexpression and knockdown of MAOB in PCa cells respectively suppressed and enhanced cell motility and proliferation. In clinical observations, correlations of lower MAOB expression levels with higher Gleason scores, advanced clinical T stages, tumour metastasis, and poorer prognosis in PCa patients were noted. Our findings suggest that MAOB may act as a suppressor of PCa progression, and the rs3027452 and rs1799836 genetic variants of MAOB are linked to PCa metastasis within the Taiwanese population.