A pharmacogenetics study of platinum-based chemotherapy in lung cancer: ABCG2 polymorphism and its genetic interaction with SLC31A1 are associated with response and survival

Genetic polymorphisms as potential pharmacogenetic biomarkers for platinum-based chemotherapy in non-small cell lung cancer

Platinum-based chemotherapy (PBC) is a widely used treatment for various solid tumors, including non-small cell lung cancer (NSCLC). However, its efficacy is often compromised by the emergence of drug resistance in patients. There is growing evidence that genetic variations may influence the susceptibility of NSCLC patients to develop resistance to PBC. Here, we provide a comprehensive overview of the mechanisms underlying platinum drug resistance and highlight the important role that genetic polymorphisms play in this process. This paper discussed the genetic variants that regulate DNA repair, cellular movement, drug transport, metabolic processing, and immune response, with a focus on their effects on response to PBC. The potential applications of these genetic polymorphisms as predictive indicators in clinical practice are explored, as are the challenges associated with their implementation.

Identification of cuproptosis-related asthma diagnostic genes by WGCNA analysis and machine learning

OBJECTIVE

Cuproptosis is the latest novel form of cell death. However, the relationship between asthma and cuproptosis is not fully understood.

METHODS

In this study, we screened differentially expressed cuproptosis-related genes from the Gene Expression Omnibus (GEO) database and performed immune infiltration analysis. Subsequently, patients with asthma were typed and analyzed by Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) was performed to calculate the module-trait correlations, and the hub genes of the intersection were taken to construct machine learning (XGB, SVM, RF, GLM). Finally, we used TGF-β to establish a BEAS-2B asthma model to observe the expression levels of hub genes.

RESULTS

Six cuproptosis-related genes were obtained. Immune-infiltration analysis shows that cuproptosis-related genes are associated with a variety of biological functions. We classified asthma patients into two subtypes based on the expression of cuproptosis-related genes and found significant Gene Ontology (GO) and immune function differences between the different subtypes. WGCNA selected 2 significant modules associated with disease features and typing. Finally, we identified TRIM25, DYSF, NCF4, ABTB1, CXCR1 as asthma biomarkers by taking the intersection of the hub genes of the 2 modules and constructing a 5-genes signature, which nomograph, decision curve analysis (DCA) and calibration curves, receiver operating characteristic curve (ROC) showed high efficiency in diagnosing the probability of survival of asthma patients. Finally, in vitro experiments have shown that DYSF and CXCR1 expression is up expressed in asthma.

CONCLUSIONS

Our study provides further directions for studying the molecular mechanism of asthma.

Systematic pan-cancer analysis identifies SLC31A1 as a biomarker in multiple tumor types

BACKGROUND

Solute Carrier Family 31 Member 1 (SLC31A1) has recently been identified as a cuproptosis-regulatory gene. Recent studies have indicated that SLC31A1 may play a role in colorectal and lung cancer tumorigenesis. However, the role of SLC31A1 and its cuproptosis-regulatory functions in multiple tumor types remains to be further elucidated.

METHODS

Online websites and datasets such as HPA, TIMER2, GEPIA, OncoVar, and cProSite were used to extract data on SLC31A1 in multiple cancers. DAVID and BioGRID were used to conduct functional analysis and construct the protein-protein interaction (PPI) network, respectively. The protein expression data of SLC31A1 was obtained from the cProSite database.

RESULTS

The Cancer Genome Atlas (TCGA) datasets showed increased SLC31A1 expression in tumor tissues compared with non-tumor tissues in most tumor types. In patients with tumor types including adrenocortical carcinoma, low-grade glioma, or mesothelioma, higher SLC31A1 expression was associated with shorter overall survival and disease-free survival. S105Y was the most prevalent point mutation in SLC31A1 in TCGA pan-cancer datasets. Moreover, SLC31A1 expression was positively correlated with the infiltration of immune cells such as macrophages and neutrophils in tumor tissues in several tumor types. Functional enrichment analysis showed that SLC31A1 co-expressed genes were involved in protein binding, integral components of the membrane, metabolic pathways, protein processing, and endoplasmic reticulum. Copper Chaperone For Superoxide Dismutase, Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha and Solute Carrier Family 31 Member 2 were copper homeostasis-regulated genes shown in the PPI network, and their expression was positively correlated with SLC31A1. Analysis showed there was a correlation between SLC31A1 protein and mRNA in various tumors.

CONCLUSIONS

These findings demonstrated that SLC31A1 is associated with multiple tumor types and disease prognosis. SLC31A1 may be a potential key biomarker and therapeutic target in cancers.

Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis

Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis.

Pan-cancer genetic analysis of cuproptosis and copper metabolism-related gene set

Background

A recent paper has revealed a novel cell death pathway, cuproptosis, a programmed cell death based on copper. This study aimed to evaluate the pan-cancer genomics and clinical association of cuproptosis and copper metabolism-related cell death genes, including SLC25A3, SLC25A37, SLC31A1, FDX1, DLAT, LIAS, ATP7A, ATP7B, COX17, SCO1, SCO2, COX11, and COX19.

Methods

By mining multi-omics profiling data, we performed a comprehensive and systematic characterization of cuproptosis genes across more than 9,000 samples of over 30 types of cancer.

Results

ATP7B and ATP7A were the two most frequently mutated copper cell death genes in cancer. UCEC and SKCM were the two cancer types that have the highest mutation rates while the mutation of LIAS was associated with worse survival of BRCA. Brain cancer was potentially affected by copper cell death because of the difference in copper cell death gene expression among subtypes and stages. On the contrary, KIRC might have a lower cuproptosis activity because of the decrease in copper cell death gene expression. In lung cancer and kidney cancer, most of the cancer–noncancer expression patterns of copper cell death genes were consistent between mRNA and protein levels. Some of the cuproptosis gene expression was associated with the survival of LGG, KIRC, and ACC. The top five expression-copy numbers correlating cancer types were BRCA, OV, LUSC, HNSC, BLCA, and LUAD. Generally, the copy number variations of these genes in KIRC, UCEC, and LGG were associated with survival. The expression of DLAT, LIAS, and ATP7B was negatively correlated with the methylation in most of the cancer types. The copper cell death genes regulating miRNA and pathway regulation networks were constructed. The copper cell death genes were correlated with immune cell infiltration levels of multiple immune cells. These genes were correlated with the sensitivity of cancer cells to multiple drugs.

Conclusion

Copper cell death genes are potentially involved in many cancer types and can be developed as candidates for cancer diagnosis, prognosis, and therapeutic biomarkers.

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

Construction of a Cuprotosis-Related Gene-Based Model to Improve the Prognostic Evaluation of Patients with Gastric Cancer

Background

Gastric cancer (GC) is one of the most serious gastrointestinal malignancies with bad prognosis. The association between GC and cuprotosis-related genes has not been reported.

Methods

The clinical and RNA expression of patients with GC were downloaded from TCGA database. The CIBERSORT package was used to quantify the abundance of specific cell types. Using the Cox regression analysis, we conducted a prognostic nomogram model based on cuprotosis-related differential genes in GC. We evaluated the prognostic power of this model using the Kaplan-Meier (K-M) survival curve analysis, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve analysis.

Results

The plasma cells, monocytes, and mast cells in GC tissue were significantly less than those in adjacent tissue (p < 0.05), while T cell CD4 memory activated macrophage M0, macrophage M1, and macrophages in GC tissue. The number of M2 was significantly more than that in the adjacent tissue (p < 0.05). Additionally, GC patients in the test group, the training group, and all the sample groups had shorter survival time with the increase of the risk factor (p < 0.05). The nomogram of GC based on cuprotosis prognosis-related genes was conducted. The AUC of the nomogram to predict 1-, 3-, and 5-year survival rate was 0.618, 0.618, and 0.625, respectively.

Conclusion

A novel cuprotosis-related gene signature impacts on the prognosis of GC. Our research provides new insights and potential targets for studying the link between GC and cuprotosis point, thereby providing new insights into understanding the molecular mechanism of GC.

Cuproptosis-Related Gene - SLC31A1, FDX1 and ATP7B - Polymorphisms are Associated with Risk of Lung Cancer

Background

Cuproptosis is a novel copper-dependent cell death, and the copper level was increased in lung cancer patients. However, few studies evaluated the association between single-nucleotide polymorphisms (SNPs) in cuproptosis-related genes and lung cancer risk.

Methods

Six SNPs of the SLC31A1, FDX1 and ATP7B genes were genotyped in a case-control cohort including 650 lung cancer cases and 650 controls using the MassARRAY platform.

Results

The minor alleles of SLC31A1-rs10981694 and FDX1-rs10488764 were associated with an increased risk of lung cancer (rs10981694: OR=1.455, 95% CI: 1.201-1.763, p<0.001; rs10488764: OR=1.483, 95% CI: 1.244-1.768, p<0.001). In contrast, the minor alleles of rs9535826 and rs9535828 in ATP7B were related to a decreased risk of the disease (rs9535826: OR=0.714, 95% CI: 0.608-0.838 p<0.001; rs9535828: OR=0.679, 95% CI: 0.579-0.796, p<0.001). The frequencies of rs10981694-TG/GG and rs10488764-GA/AA genotypes were significantly higher in lung cancer cases than that in controls, making them risk genotypes for the disease (p < 0.001); while the rs9535826-TG/GG and rs9535828-GA/AA genotypes were protective genotypes and associated with a reduced risk of the disease (p<0.001). Genetic model evaluation revealed that SLC31A1-rs10981694 and FDX1-rs10488764 were associated with a growing risk of lung cancer in dominant, recessive and log-additive models (p<0.001). Moreover, rs9535826 and rs9535828 in ATP7B were related to a declining risk of the disease in three genetic models (p<0.001). In addition, stratification analysis showed that FDX1-rs10488764 was risk variant for lung cancer in both smokers and nonsmokers, and was associated with risk of each pathological type of lung cancer (p<0.008).

Conclusion

The results shed new light on the correlation between cuproptosis-related genes and risk of lung cancer.

Association between polymorphisms of ABCB1 and prognosis in esophageal squamous cell carcinoma patients treated with taxane

In China, most esophageal cancer patients are squamous cell carcinomas and treated with taxane-containing regimens; however, few studies have examined taxane pharmacokinetics genes and esophageal squamous cell carcinoma (ESCC) prognosis. A total of 227 pathologically confirmed ESCC patients receiving chemotherapy with taxane were included in the analysis. We genotyped seven SNPs-rs1045642, rs2032582, and rs3213619 of ABCB1; rs2231137 and rs2231142 of ABCG2; and ABCC1 rs246221 and ABCC2 rs3740066-and analyzed their relationship with overall survival. With a retrospective cohort study design, by Cox regression and semi-Bayesian shrinkage, in the genetic recessive model, the variant homozygote of ABCB1 rs1045642 was inversely associated with survival (semi-Bayesian shrinkage cHR=1.82, 95% CI=1.00, 3.31; p=0.0482). Due to inherent defects of the research itself, the finding that the ABCB1 rs1045642 variant was related to poor prognosis in ESCC patients treated with taxane-containing regimens needs to be tested in a larger population and by more genetic and molecular mechanism experiments.

Overexpression of ABCG2 Confers Resistance to MLN7243, a Ubiquitin-Activating Enzyme (UAE) Inhibitor

Overexpression of ATP-binding cassette transporter superfamily G member 2 (ABCG2), is known as a major mechanism mediating multidrug resistance (MDR) in cancer cells. MLN7243 is a small-molecule ubiquitin activating enzyme inhibitor currently under clinical investigation. The aim of the current study is to determine if MLN7243 is a substrate of MDR-related ABCG2 transporter. Our results showed that cancer cells overexpressing ABCG2 transporter were resistant to MLN7243 compared to the parental cells, while knockout of ABCG2 gene or pharmacological inhibition of ABCG2 efflux function completely reversed the drug resistance. Unexpectedly, the endogenous low expression of ABCG2 is sufficient to confer cancer cells resistance to MLN7243. The ABCG2 ATPase assay and HPLC assay suggested that MLN7243 can significantly stimulate ABCG2 ATPase activity and be pumped out from ABCG2-overexpressing cells by ABCG2. The docking analysis also implied that MLN7243 binds to ABCG2 drug-binding pocket with optimal binding affinity. However, MLN7243 did not competitively inhibit the efflux of other ABCG2 substrate drugs, indicating it may not serve as an MDR reversal agent. In conclusion, our study provides direct in vitro evidence to show that MLN7243 is a potent ABCG2 substrate. If our results can be translated to humans, it suggests that combining MLN7243 with ABCG2 inhibitors may enhance the anticancer efficacy for patients with high tumor ABCG2 level.