The value of erlotinib related target molecules in kidney renal cell carcinoma via bioinformatics analysis

The Emerging Roles and Mechanisms of PAQR3 in Human Cancer: Pathophysiology and Therapeutic Implications

Cancer was one of the common causes of death in the world, and it was increasing year by year. At present, Progestin and AdipoQ receptor family member 3 (PAQR3) was widely studied in cancer. It has been found that PAQR3 was down regulated in various cancers, such as the gastric cancer, osteosarcoma, glioma, hepatocellular carcinoma, acute lymphoblastic leukemia, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, non-small cell lung cancer, and colorectal cancer. The decreased expression of PAQR3 was associated with short overall survival and disease-free survival in patients with gastric cancer, hepatocellular carcinoma, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, and non-small cell lung cancer. PAQR3 could inhibit cancer progression by using the Ras/Raf/MEK/ERK, PI3/AKT, EMT and other mechanisms, and was negatively regulated by the miR-543, miR-15b-5p and miR-15b. The roles and signaling mechanisms of PAQR3, and the relationship between the expression of PAQR3 and prognosis in cancer progression are reviewed in this article, and provides new tumor marker and idea to guide cancer treatment.

A novel risk model of three gefitinib-related genes FBP1, SBK1 and AURKA is related to the immune microenvironment and is predicting prognosis of lung adenocarcinoma patients

PURPOSE

Gefitinib, an anticancer drug, has been reported to potentially improve the prognosis of patients with lung adenocarcinoma (LUAD). This study aims to investigate the roles and mechanisms of Gefitinib.

METHODS

The effects of Gefitinib on the growth and migration of LUAD cells were assessed using various methods, including CCK-8, flow cytometry, wound healing, and Transwell assays. To analyze the function and mechanisms of the differentially expressed Gefitinib target genes (GTGs), data from the TCGA database were utilized. Kaplan-Meier survival and ROC analysis identified prognostic-related GTGs and constructed a prognostic nomogram in LUAD. Consensus clustering, COX analysis and survival analysis evaluated the relationship between GTGs and the prognosis of LUAD patients. The mechanisms of the risk model involved LUAD progression, and the relationship between the risk model and immune microenvironment were investigated.

RESULTS

Gefitinib could inhibit proliferation, migration and invasion and promote cell apoptosis. 84 DEGTGs were involved in RAS, MAPK, ERBB pathways. The DEGTGs (FBP1, SBK1, and AURKA) were the independent risk factors for dismal prognosis of LUAD patients and were used to establish risk model and nomogram. Gefitinib could promote the expression of FBP1 and inhibit the expression of SBK1 and AURKA. High-risk LUAD patients had the dismal prognosis, and the high-risk score group was significantly associated with the immune microenvironment.

CONCLUSION

FBP1, SBK1, and AURKA are prognostic risk factors, and the risk model and nomogram of FBP1, SBK1 and AURKA are associated with dismal prognosis and immune cell infiltration, and have huge prospects for application in evaluating the prognosis in LUAD.

Electrochemical and theoretical study on interaction between erlotinib and DNA

A comprehensive investigation of tyrosine kinase inhibitor erlotinib (ERL) electrochemical behavior and interaction with DNA was performed with the aim to clarify its redox mechanism and to determine the mode of binding. Irreversible oxidation and reduction processes of ERL on glassy carbon electrode were investigated using three voltammetric techniques CV, DPV, SWV in pH range between 2.0 and 9.0. Oxidation was established as an adsorption-controlled process, while the reduction manifested diffusion-adsorption mixed controlled process in acidic medium and adsorption became predominant in the neutral solutions. According to the determined number of transferred electrons and protons, oxidation and reduction mechanism of ERL are proposed. To follow the interaction between ERL and DNA, the multilayer ct-DNA electrochemical biosensor was incubated in ERL solutions concentrations ranged from 2 × 10-7 M to 5 × 10-5 M (pH 4.6) for 30 min. SWV measurements have shown the decrease in deoxyadenosine peak current as a consequence of ERL increased concentration and binding to ct-DNA. The calculated value of binding constant was K = 8.25 × 104 M-1. Molecular docking showed that ERL forms hydrophobic interactions when docked into minor groove, as well as when intercalated, and molecular dynamics analysis predicted the stability of obtained complexes. These results together with voltammetric studies imply that the intercalation could be more dominant way ERL binding to DNA compared to minor groove binding.

CLC-Pred 2.0: A Freely Available Web Application for In Silico Prediction of Human Cell Line Cytotoxicity and Molecular Mechanisms of Action for Druglike Compounds

In vitro cell-line cytotoxicity is widely used in the experimental studies of potential antineoplastic agents and evaluation of safety in drug discovery. In silico estimation of cytotoxicity against hundreds of tumor cell lines and dozens of normal cell lines considerably reduces the time and costs of drug development and the assessment of new pharmaceutical agent perspectives. In 2018, we developed the first freely available web application (CLC-Pred) for the qualitative prediction of cytotoxicity against 278 tumor and 27 normal cell lines based on structural formulas of 59,882 compounds. Here, we present a new version of this web application: CLC-Pred 2.0. It also employs the PASS (Prediction of Activity Spectra for Substance) approach based on substructural atom centric MNA descriptors and a Bayesian algorithm. CLC-Pred 2.0 provides three types of qualitative prediction: (1) cytotoxicity against 391 tumor and 47 normal human cell lines based on ChEMBL and PubChem data (128,545 structures) with a mean accuracy of prediction (AUC), calculated by the leave-one-out (LOO CV) and the 20-fold cross-validation (20F CV) procedures, of 0.925 and 0.923, respectively; (2) cytotoxicity against an NCI60 tumor cell-line panel based on the Developmental Therapeutics Program's NCI60 data (22,726 structures) with different thresholds of IG₅₀ data (100, 10 and 1 nM) and a mean accuracy of prediction from 0.870 to 0.945 (LOO CV) and from 0.869 to 0.942 (20F CV), respectively; (3) 2170 molecular mechanisms of actions based on ChEMBL and PubChem data (656,011 structures) with a mean accuracy of prediction 0.979 (LOO CV) and 0.978 (20F CV). Therefore, CLC-Pred 2.0 is a significant extension of the capabilities of the initial web application.

The Roles and Mechanisms of TRAT1 in the Progression of Non-Small Cell Lung Cancer

OBJECTIVE

T cell receptor-associated transmembrane adaptor 1 (TRAT1) is one of the hub genes regulating T cell receptors (TCRs). Herein, the roles of TRAT1 in the prognosis and immune microenvironment of non-small cell lung cancer (NSCLC) were investigated.

METHODS

The expression and prognosis values of TRAT1 in NSCLC, and the relationship between TRAT1 expression levels and cancer immune cell infiltration was identified via the TIMER, UALCAN, TISIDB, and other databases. The mechanism of TRAT1 in NSCLC was analyzed using gene set enrichment analysis (GSEA).

RESULTS

The expression level of TRAT1 was decreased in NSCLC tissues. Low TRAT1 expression was associated with shorter overall survival of patients with NSCLC and was related to gender, smoking, and tumor grade. TRAT1 was involved in regulating immune response, TCR signaling pathway, PI3K/AKT, and other processes. TRAT1 expression levels were positively correlated with immune cell infiltration in NSCLC.

CONCLUSION

Down-regulation of TRAT1 expression was associated with an unfavorable prognosis and immune infiltration of NSCLC.

SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer

It has been established that long-chain coding RNA (lncRNA) SLC25A25-AS1 is associated with cancer progression. However, the roles and mechanisms of SLC25A25-AS1 in prostate cancer (PC) have not been reported in the literature. The present study explored the relationship between SLC25A25-AS1 expression and PC progression via comprehensive analysis. The pan-cancer expression of SLC25A25-AS1 was identified using data from The Cancer Genome Atlas (TCGA) database and tissue specimens from our hospital. The expression levels of SLC25A25-AS1 in various subgroups based on the clinical features were identified. The prognostic value of SLC25A25-AS1 and SLC25A25-AS1 co-expressed lncRNAs in PC patients was assessed by survival analysis and ROC analysis, and prognosis-related risk models of SLC25A25-AS1 were constructed. The relationship between SLC25A25-AS1 and the PC immune microenvironment was investigated using correlation analysis. SLC25A25-AS1 expression in PC was significantly increased and correlated with the T stage, clinical stage, Gleason score (GS), and dismal prognosis. SLC25A25-AS1 overexpression exhibited good performance in evaluating the prognosis of PC patients. The area under the curves (AUCs) of the 1-, 3-, and 5-year overall survival (OS) for SLC25A25-AS1 was 1, 0.876, and 0.749. Moreover, the AUCs for the 1-, 3-, and 5-year progress free interval (PFI) for SLC25A25-AS1 were 0.731, 0.701, and 0.718. SLC25A25-AS1 overexpression correlated with the infiltration of CD8 T cells, interstitial dendritic cells (IDC), macrophages and other cells. AC020558.2, ZNF32-AS2, AP4B1-AS1, AL355488.1, AC109460.3, SNHG1, C3orf35, LMNTD2-AS1, and AL365330.1 were significantly associated with SLC25A25-AS1 expression, and short OS and PFI in PC patients. The risk models of the SLC25A25-AS1-related lncRNAs were associated with a dismal prognosis in PC. Overall, SLC25A25-AS1 expression was increased in PC and related to the prognosis and PC immune microenvironment. The risk model of SLC25A25-AS1 have huge prospect for application as prognostic tools in PC.

The m6A/m5C/m1A Regulated Gene Signature Predicts the Prognosis and Correlates With the Immune Status of Hepatocellular Carcinoma

RNA modification of m6A/m5C/m1A contributes to the occurrence and development of cancer. Consequently, this study aimed to investigate the functions of m6A/m5C/m1A regulated genes in the prognosis and immune microenvironment of hepatocellular carcinoma (HCC). The expression levels of 45 m6A/m5C/m1A regulated genes in HCC tissues were determined. The functional mechanisms and protein–protein interaction network of m6A/m5C/m1A regulated genes were investigated. The Cancer Genome Atlas (TCGA) HCC gene set was categorized based on 45 m6A/m5C/m1A regulated genes, and survival analysis was used to determine the relationship between the overall survival of HCC patients in subgroups. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the risk model and nomogram for m6A/m5C/m1A regulated genes. The relationships between m6A/m5C/m1A regulated gene subsets and risk model and immune cell infiltration were analyzed using CIBERSORT. m6A/m5C/m1A regulated genes were involved in mRNA and RNA modifications, mRNA and RNA methylation, mRNA and RNA stability, and other processes. There was a statistically significant difference between cluster1 and cluster2 groups of genes regulated by m6A/m5C/m1A. The prognosis of cluster1 patients was significantly better than that of cluster2 patients. There were statistically significant differences between the two cluster groups in terms of fustat status, grade, clinical stage, and T stage of HCC patients. The risk model comprised the overexpression of YBX1, ZC3H13, YTHDF1, TRMT10C, YTHDF2, RRP8, TRMT6, LRPPRC, and IGF2BP3, which contributed to the poor prognosis of HCC patients. The high-risk score was associated with prognosis, fustat status, grade, clinical stage, T stage, and M stage and was an independent risk factor for poor prognosis in HCC patients. High-risk score mechanisms included spliceosome, RNA degradation, and DNA replication, among others, and high-risk was closely related to stromal score, CD4 memory resting T cells, M0 macrophages, M1 macrophages, resting mast cells, CD4 memory activated T cells, and follicular helper T cells. In conclusion, the cluster subgroup and risk model of m6A/m5C/m1A regulated genes were associated with the poor prognosis and immune microenvironment in HCC and are expected to be the new tools for assessing the prognosis of HCC patients.

FMR1 is identified as an immune-related novel prognostic biomarker for renal clear cell carcinoma: A bioinformatics analysis of TAZ/YAP

WW domain-containing transcription regulator 1 (TAZ, or WWTR1) and Yes-associated protein 1 (YAP) are both important effectors of the Hippo pathway and exhibit different functions. However, few studies have explored their co-regulatory mechanisms in kidney renal clear cell carcinoma (KIRC). Here, we used bioinformatics approaches to evaluate the co-regulatory roles of TAZ/YAP and screen novel biomarkers in KIRC. GSE121689 and GSE146354 were downloaded from the GEO. The limma was applied to identify the differential expression genes (DEGs) and the Venn diagram was utilized to screen co-expressed DEGs. Co-expressed DEGs obtained the corresponding pathways through GO and KEGG analysis. The protein-protein interaction (PPI) network was constructed using STRING. The hub genes were selected applying MCODE and CytoHubba. GSEA was further applied to identify the hub gene-related signaling pathways. The expression, survival, receiver operating character (ROC), and immune infiltration of the hub genes were analyzed by HPA, UALCAN, GEPIA, pROC, and TIMER. A total of 51 DEGs were co-expressed in the two datasets. The KEGG results showed that the enriched pathways were concentrated in the TGF-β signaling pathway and endocytosis. In the PPI network, the hub genes (STAU2, AGO2, FMR1) were identified by the MCODE and CytoHubba. The GSEA results revealed that the hub genes were correlated with the signaling pathways of metabolism and immunomodulation. We found that STAU2 and FMR1 were weakly expressed in tumors and were negatively associated with the tumor stages. The overall survival (OS) and disease-free survival (DFS) rate of the high-expressed group of FMR1 was greater than that of the low-expressed group. The ROC result exhibited that FMR1 had certainly a predictive ability. The TIMER results indicated that FMR1 was positively correlated to immune cell infiltration. The abovementioned results indicated that TAZ/YAP was involved in the TGF-β signaling pathway and endocytosis. FMR1 possibly served as an immune-related novel prognostic gene in KIRC.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Background

Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients.

Methods

OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration.

Results

We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells.

Conclusion

In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.