Elevated ADH5 expression suggested better prognosis in kidney renal clear cell carcinoma (KIRC) and related to immunity through single-cell and bulk RNA-sequencing.

BACKGROUND: Despite the rapid advances in modern medical technology, kidney renal clear cell carcinoma (KIRC) remains a challenging clinical problem in urology. Researchers urgently search for useful markers to break through the therapeutic conundrum due to its high lethality. Therefore, the study explores the value of ADH5 on overall survival (OS) and the immunology of KIRC. METHODS: The gene expression matrix and clinical information on ADH5 in the TCGA database were validated using external databases and qRT-PCR. To confirm the correlation between ADH5 and KIRC prognosis, univariate/multivariate Cox regression analysis was used. We also explored the signaling pathways associated with ADH5 in KIRC and investigated its association with immunity. RESULTS: The mRNA and protein levels showed an apparent downregulation of ADH5 in KIRC. Correlation analysis revealed that ADH5 was directly related to histological grade, clinical stage, and TMN stage (p < 0.05). Univariate and multivariate Cox regression analysis identified ADH5 as an independent factor affecting the prognosis of KIRC. Enrichment analysis looked into five ADH5-related signaling pathways. The results showed no correlation between ADH5 and TMB, TNB, and MSI. From an immunological perspective, ADH5 was found to be associated with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Lower ADH5 expression was associated with greater responsiveness to immunotherapy. Single-cell sequencing revealed that ADH5 is highly expressed in immune cells. CONCLUSION: ADH5 could be a promising prognostic biomarker and a potential therapeutic target for KIRC. Besides, it was found that KIRC patients with low ADH5 expression were more sensitive to immunotherapy.

Exploration of YBX1 role in the prognostic value and immune characteristics by single-cell and bulk sequencing analysis for liver hepatocellular carcinoma.

BACKGROUND: Y-box binding protein 1 (YBX1) plays a variety of roles in progression of multiple tumors. However, the role of YBX1 in prognostic value and immune regulation for liver hepatocellular carcinoma (LIHC) remains unclear. The present study aimed to examine the effect of YBX1 on the regulation of tumor immunity and survival prediction in LIHC patients. METHODS: YBX1-related expression profiles and single-cell and bulk sequencing analysis were performed using online databases. YBX1 expression was validated by a quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry. Univariate/multivariate Cox regression analysis was performed to determine independent predictors of overall survival (OS). The ESTIMATE (i.e., Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) algorithm and Tumor Immune Dysfunction and Exclusion (TIDE) analysis were used to assess the relationships between YBX1 and LIHC immunity. RESULTS: YBX1 was over-expressed in LIHC tissues and cell lines. High YBX1 expression was significantly associated with poor OS. Univariate/multivariate Cox regression analysis revealed that YBX1 was an independent prognostic factor for LIHC. Gene set enrichment analysis revealed that YBX1 was associated with multiple signaling pathways correlated to LIHC. Additionally, YBX1 was expressed in multiple immune cells and was significantly correlated with immune cells, immune checkpoint markers and tumor immune microenvironment. The TIDE analysis demonstrated that LIHC patients with high YBX1 expression showed a higher T-cell dysfunction score and a higher exclusion score, as well as poorer immunotherapy response. CONCLUSIONS: YBX1 plays crucial oncogenic roles in LIHC and is closely associated with the immune defense system. YBX1 inhibition may serve as a potential treatment for LIHC.

Elevated CDC45 Expression Predicts Poorer Overall Survival Prognoses and Worse Immune Responses for Kidney Renal Clear Cell Carcinoma via Single-Cell and Bulk RNA-Sequencing.

The main objective of this paper is to analyze the prognostic and immunological value of CDC45 in kidney renal clear cell carcinoma (KIRC) using single-cell and bulk RNA-sequencing approaches. The expression of CDC45 in KIRC was evaluated by the HPA database, the TCGA-KIRC dataset and verified by PCR analysis and single-cell RNA-sequencing. The ability of CDC45 to independently predict prognosis in KIRC was confirmed by univariate/multivariate regression analysis. Gene set enrichment analysis (GSEA) was employed to explore CDC45-related pathways in KIRC. In addition, Relationships between CDC45 and immunity were also examined. Elevated CDC45 expression in KIRC was demonstrated at mRNA and protein levels. The results of the correlation analysis showed that as CDC45 expression increased, so did the histological grade, clinical stage, and TNM stage of the patients (p < 0.05). Univariate/multivariate regression analysis suggested CDC45 as an independent prognostic factor for KIRC. Seven pathways related to CDC45 were screened through GSEA. Meanwhile, we found that CDC45 was correlated with tumor mutational burden (TMB) and microsatellite instability (MSI) but not tumor neoantigen burden (TNB). Regarding immunity, CDC45 exhibited correlations with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Besides, low CDC45 expression was shown to be associated with a better response to immunotherapy. Single-cell RNA-sequencing revealed that CDC45 was differently expressed in T cells (p < 0.05). CDC45 showed potential as a prognostic biomarker and therapeutic target for KIRC. Meanwhile, the CDC45 low expression group was more sensitive to immunotherapy.

Integrated analyses reveal the prognostic, immunological features and mechanisms of cuproptosis critical mediator gene FDX1 in KIRC.

The ferredoxin 1 (FDX1) gene had been recently reported as a critical mediator of cuproptosis, and without doubt, its roles in KIRC would be of importance. Hence, this paper was to explore the roles of FDX1 in kidney renal clear cell carcinoma (KIRC) and its potential molecular mechanisms via scRNA-sequencing and bulk RNA-sequencing analyses. FDX1 was lowly expressed in KIRC and validated both at the protein and mRNA levels (all p < 0.05). Moreover, its elevated expression was linked with a better overall survival (OS) prognosis in KIRC (p < 0.01). The independent impact of FDX1 on KIRC prognosis was demonstrated by univariate/multivariate regression analysis (p < 0.01). Gene set enrichment analysis (GSEA) identified seven pathways strongly associated with FDX1 in KIRC. Furthermore, FDX1 was also revealed to be significantly related with immunity (p < 0.05). In addition, patients with low expression of FDX1 might be more sensitive to immunotherapies. ScRNA-seq analysis found that FDX1 could be expressed in immune cells and was mainly differently expressed in Mono/Macro cells. Ultimately, we also identified several LncRNA/RBP/FDX1 mRNA networks to reveal its underlying mechanisms in KIRC. Taken together, FDX1 was closely related to prognosis and immunity in KIRC, and its RBP-involved mechanisms of LncRNA/RBP/FDX1 networks were also revealed by us.

Elevated PTTG1 predicts poor prognosis in kidney renal clear cell carcinoma and correlates with immunity.

Background: PTTG1 has been reported to be linked with the prognosis and progression of various cancers, including kidney renal clear cell carcinoma (KIRC). In this article, we mainly investigated the associations between prognosis, immunity, and PTTG1 in KIRC patients. Method: We downloaded transcriptome data from the TCGA-KIRC database. PCR and immunohistochemistry were used, respectively, to validate the expression of PTTG1 in KIRC at the cell line and the protein levels. Survival analyses as well as univariate or multivariate Cox hazard regression analyses were used to prove whether PTTG1 alone could affect the prognosis of KIRC. The most important point was to study the relationship between PTTG1 and immunity. Results: The results of the paper revealed that the expression levels of PTTG1 were elevated in KIRC compared with para-cancerous normal tissues, validated by PCR and immunohistochemistry at the cell line and the protein levels (P < 0.05). High PTTG1 expression was related to shorter overall survival (OS) in patients with KIRC (P < 0.05). Through univariate or multivariate regression analysis, PTTG1 was confirmed to be an independent prognostic factor for OS of KIRC (P < 0.05), and its related seven pathways were obtained through gene set enrichment analysis (GSEA; P < 0.05). Moreover, tumor mutational burden (TMB) and immunity were found to be significantly connected with PTTG1 in KIRC (P < 0.05). Correlations between PTTG1 and immunotherapy responses implied that the low-PTTG1 group was more sensitive to immunotherapy (P < 0.05). Conclusions: PTTG1 was closely associated with TMB or immunity, and it had a superior ability to forecast the prognosis of KIRC patients.

Molecular subtypes based on metabolic genes are potential biomarkers for predicting prognosis and immune responses of clear cell renal cell carcinoma.

Due to the existence of tumor molecular heterogeneity, even patients having similar clinicopathological features could have vastly different survival rates. Hence, we aimed to explore novel metabolism-associated genes (MAGs) related molecular subtypes for clear cell renal cell carcinoma (ccRCC) and their immune landscapes for predicting prognosis and immune responses. Gene matrices and clinical information were downloaded from TCGA and ICGC datasets. Consensus clustering was conducted by the R "ConsensusClusterPlus" package. ccRCC patients were successfully divided into three clusters (MC1, MC2, and MC3) based on MAGs in both TCGA and ICGC datasets. Our established three MAGs were significantly associated with chemokine/chemokine receptor, IFN, CYT, angiogenesis, immune checkpoint molecules, tumor-infiltrating immune cells, oncogenic pathways, pan-cancer immune subtypes, and tumor microenvironment (TME) scores or expressions. Moreover, these three metabolic ccRCC subtypes could predict immunotherapeutic responses. We further constructed a characteristic index (LDAscore) in three metabolic ccRCC subtypes and identified LDAscore-related modules by WGCNA. After deep data mining, 10 hub genes were obtained and seven genes (ATRX, BPTF, DHX9, EP300, POLR2B, SIN3A, UBE3A) were finally validated by qRT-PCR. Our results successfully established a novel ccRCC subtype based on MAGs, providing novel insights into metabolism-related ccRCC tumor heterogeneity and facilitating individualized therapy for future work.

Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction.

BACKGROUND: Currently, patients with diabetic erectile dysfunction (DMED) were not satisfied with the effects of first-line phosphodiesterase type 5 inhibitors (PDE5Is). Hence, this paper was designed to mine hub biomarkers in DMED and explore its potential mechanisms. METHODS: Gene expression matrix of DMED was downloaded from the gene expression omnibus (GEO; GSE2457) dataset. The top 20 genes were selected based on the connectivity degrees in protein-protein interaction (PPI) network. Functional enrichment analysis was utilized to reveal DMED-related signaling pathways. We also explored the roles of immunity, m6A, ferroptosis, or cuproptosis in DMED and constructed Sprague Dawley (SD) rats DMED model to verify gene expressions by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: Based on the threshold, a total of 122 differently expressed genes (DEGs) were identified in DMED, including 39 up-regulated and 83 down-regulated genes. Functional enrichment analysis implied that these DEGs were significantly enriched in peroxisome proliferator-activated receptors, ferroptosis, hypoxia-inducible factor 1 signaling pathways, and so on. SD rats DMED model was also successfully established by us and validated by intracavernous pressure/mean arterial pressure, Masson's trichrome staining, and immunohistochemical analysis. We further verified the expression of these top 20 genes from the PPI network by qRT-PCR in the SD rats DMED model and finally identified Sparc, Lox, Srebf1, and Mmp3 as hub biomarkers (all p < 0.05). As for immunity and cuproptosis, our analysis indicated that DMED had nothing to do with them (all p > 0.05). Actually, DMED was markedly associated with m6A regulators and ferroptosis. CONCLUSIONS: We identified Sparc, Lox, Srebf1, and Mmp3 as potential hub biomarkers in the SD rats DMED model for future drug development and found its significant associations with m6A regulators and ferroptosis, but not with immunity or cuproptosis.

High expression of PI4K2A predicted poor prognosis of colon adenocarcinoma (COAD) and correlated with immunity.

BACKGROUND: PI4K2A has been found to have a tumor-promoting role in various solid tumors and be involved in various biological procedures. In this article, we aim to investigate the prognostic values of PI4K2A and provide new insights in colon adenocarcinoma (COAD). METHODS: The Cancer Genome Atlas (TCGA) database, Human Protein Atlas online database, and UALCAN database were used to analyze the expression of PI4K2A in COAD and the survival of patients. Univariate and multifactorial Cox regression analyses were used to assess the prognosis of PI4K2A on COAD. GSEA was used to explore PI4K2A-related signaling pathways. In addition, the effect of PI4K2A on immune checkpoint inhibitors (ICIs) treatment was investigated by constructing a TIDE model and predicting the association between PI4K2A and anticancer drug sensitivity through the CellMiner database. RESULTS: In the TCGA database, PI4K2A was highly expressed in COAD and the similar results were verified by qRT-PCR. Survival analysis, utilizing Kaplan-Meier curves, revealed that COAD patients with high PI4K2A expression had a worse prognosis. In addition, PI4K2A expression was discovered to have been associated with T-stage, N-stage, and pathological stage by logistic analysis. Next, we utilized univariate and multifactorial Cox regression analyses to identify PI4K2A as an independent predictor. Additionally, GSEA analysis indicates that PI4K2A is enriched in MAPK signaling pathway, Toll-like receptor signaling pathway, etc. In COAD, PI4K2A was remarkably associated with the tumor immune microenvironment. In addition, by constructing a TIDE model, we discovered that COAD patients in the PI4K2A low-expression cohort were better treated with ICI. Finally, analysis of the CellMiner database predicted that PI4K2A was adversely correlated with the sensitivity of various anticancer drugs. CONCLUSIONS: Our study suggests that PI4K2A may be a potential predictor of poor prognosis in COAD and a potential biomarker for early diagnosis, prognosis, and treatment.

Elevated THBS3 predicts poor overall survival for clear cell renal cell carcinoma and identifies LncRNA/RBP/THBS3 mRNA networks.

This study was used to assess THBS3's overall survival (OS) prognostic values in clear cell renal cell carcinoma (ccRCC) as well as to determine the LncRNA/RNA binding protein (RBP)/THBS3 interactions. Clinical data and RNA sequencing data were gathered from the TCGA dataset. Significant pathways associated with THBS3 were identified by gene set enrichment analysis (GSEA). Cox regression analyses, both univariate and multivariate, were applied to assess factors with independent prognostic abilities. We also discussed THBS3's relationship to immunity. We discovered that THBS3 expression was increased in ccRCC samples, as well as shorter OS in the TCGA dataset (P<0.05). External verification results in GSE6344, ICGC, ArrayExpress, UALCAN datasets, and qRT-PCR remained consistent (all P<0.05). Cox regression analyses, both univariate and multivariate, identified THBS3 as a factor with independent prognostic ability (both P<0.001). THBS3 expression as well as several clinicopathological variables were included in the nomogram OS prognosis prediction method as well. GSEA identified four THBS3-related signal pathways and THBS3 was revealed to be significantly associated with MSI, TMB, neoantigen, and immunity (all P<0.05). We also identified several LncRNA/RBP/THBS3 mRNA networks as potentially THBS3-related mechanisms. For THBS3-related drug sensitivities, THBS3 was negatively associated with Actinomycin D, Cobimetinib, Eribulin mesilate, Geldanamycin analog, and Vinblastine, while it was positively related to Erlotinib drug sensitivity. In addition to being an independent prognostic factor for ccRCC, THBS3 had a close connection to immunity, with identifying LncRNA/RBPs/THBS3 mRNA networks. Verifications of our findings in vivo and in vitro should be done in the future.

A novel 17 apoptosis-related genes signature could predict overall survival for bladder cancer and its associations with immune infiltration.

Background: Apoptosis-related genes (ARGs) were used to develop a novel signature for forecasting overall survival (OS) and examining their relationships with immune infiltrates in bladder cancer (BC). Methods: Gene expression matrices as well as related clinical data were acquired for BC samples from online datasets. According to differentially expressed ARGs acquired from normal bladder tissues and cancer samples, functional enrichment analyses were conducted. With the assistance of LASSO and Cox regression analysis, a novel model was successfully established and evaluated by external and internal validations. Results: Eventually, 17 ARGs (SLC5A6, GULP1, TAP1, MMP9, P4HB, FOXL2, CIDEC, EN2, NES, EPHA7, SUSD2, TMPRSS3, HOXB7, SATB1, MEST, PCDHGC3, ASPM) were utilized to construct the signature. Our constructed signature significantly distinguished high-risk from low-risk BC patients of OS by internal and external validations and was also proven to be able to serve as an independent prognostic biomarker (all P < 0.05). Furthermore, a prognostic nomogram was also constructed based on TCGA dataset to predict OS prognosis in BC suffers. Besides, this ARG based model was markedly associated with clinical characteristics like tumor stage (P = 3.98e-06), race (P = 8.255e-06), N stage (P = 0.002), T stage (P = 3.679e-05) and M stage (P = 0.002). As for immune infiltration, our established model was significantly associated with seven tumor-infiltrating immune cells. Conclusions: A prognostic signature was successfully developed by us according to 17 ARGs in BC using external and internal verifications, enabling clinicians to predict BC suffers' OS and promote specific individualization of patient care.

COLGALT1 is a potential biomarker for predicting prognosis and immune responses for kidney renal clear cell carcinoma and its mechanisms of ceRNA networks.

BACKGROUND: As precision medicine gradually played an inaccessible role in cancer treatment, there was an urgent need to explore biomarkers or signatures for predicting cancer prognosis. Currently, little was known about the associations between COLGALT1 and kidney renal clear cell carcinoma (KIRC). Hence, this study was performed to reveal its roles in KIRC and to identify potential mechanisms of competing endogenous RNA (ceRNA) networks. METHODS: R 4.1.1 software was utilized to conduct bioinformatics analyses with the data derived from online databases. Difference analysis, survival analysis, univariate/multivariate cox regression analysis and correlation analysis were carried out successively in this article. Besides, we also investigated potential effects and mechanisms of COLGALT1 in KIRC. RESULTS: COLGALT1 expression was overexpressed in KIRC samples compared with the normal samples and it was associated with poor OS (P < 0.001). COLGALT1 was also found to be significantly related to clinicopathological characteristics such as grade, T, N, M, stage and Cox regression analysis with univariate and multivariate data suggested it might be an independent prognostic parameter in KIRC (P < 0.001). Furthermore, Seven significantly enriched pathways were identified. Interestingly, correlation analyses revealed an association between COLGALT1 and microsatellite instability (MSI), tumor mutational burden (TMB) and immunity (P < 0.001). In addition, we used TIDE and TCIA databases to predict the immune response of COLGALT1 in KIRC and it suggested low expression of COLGALT1 is more likely to benefit from immunotherapy. Besides, we identified a ceRNA network of SLC16A1-AS1/hsa-mir-502-3p/COLGALT1 for its potential mechanism. Finally, experiments in vitro indicated that COLGALT1 was significantly related to cell proliferation. CONCLUSIONS: COLGALT1 could act as a valid immune-related prognostic indicator for KIRC and participated in a ceRNA network of SLC16A1-AS1/hsa-mir-502-3p/COLGALT1, offering one potential biomarker to investigate the mechanism and clinical therapeutic value of KIRC.

Survival Prognosis, Tumor Immune Landscape, and Immune Responses of ADAMTS14 in Clear Cell Renal Cell Carcinoma and Its Potential Mechanisms.

Background: ADAMTS14 played a crucial role in the formation and development of various cancers. Currently, no associations had been revealed between ADAMTS14 and clear cell renal cell carcinoma (ccRCC). Hence, this study was designed to assess the prognostic values and immunological roles of ADAMTS14 in ccRCC and to reveal its potential mechanisms. Methods: ADAMTS14-related expression profiles and related clinical data were downloaded from The Cancer Genome Atlas (TCGA) dataset, validated by the ICGC dataset, qRT-PCR, and immunohistochemistry. We utilized gene set enrichment analysis (GSEA) to find potentially ADAMTS14-related pathways and applied univariate/multivariate Cox regression analyses to identify independent factors significantly related to overall survival (OS) for ccRCC. A nomogram consisted of independent prognostic factors was also conducted. We further explored the associations between ADAMTS14 with immunity and revealed its potential mechanisms. Results: ADAMTS14 displayed a higher expression in ccRCC tumor than in adjacent normal tissues, and further validated results of the ICGC dataset; qRT-PCR and immunohistochemistry remained consistent (all p < 0.05). Moreover, elevated ADAMTS14 expression was significantly associated with poor OS (p < 0.001). Through univariate/multivariate Cox regression analyses, ADAMTS14 was found to be an independent prognostic factor for ccRCC (both p < 0.05) and GSEA identified several signaling pathways including INSULIN, MTOR, and PPAR pathways. The nomogram based on independent prognostic factors was successfully established and well evaluated. Moreover, the expression of ADAMTS14 was remarkably associated with immune checkpoint molecules, tumor mutational burden (TMB), immune cells, and tumor immune microenvironment (all p < 0.05). Results from TIDE and TCIA showed that highly expressed ADAMTS14 could predict worse efficacy of immunotherapy (all p < 0.05). As for its potential mechanisms, we also revealed several LncRNA/RNA binding protein (RBP)/ADAMTS14 mRNA networks. Conclusions: ADAMTS14 was found to play oncogenic roles in ccRCC and to be significantly associated with immunity. Several LncRNA/RBP/ADAMTS14 mRNA networks were also identified for its potential mechanisms.

Survival Prognosis, Tumor Immune Landscape, and Immune Responses of PPP1R18 in Kidney Renal Clear Cell Carcinoma and Its Potentially Double Mechanisms.

Background: The aim of this study was to investigate the immunological and prognostic roles of protein phosphatase 1 regulatory subunit 18 (PPP1R18) for overall survival (OS) in kidney renal clear cell carcinoma (KIRC) patients, as well as the prediction of its potential mechanisms. Methods: Based on PPP1R18 single gene expression matrices and clinical information from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and GSE6344 datasets, the relationships between PPP1R18 and prognosis/immunity were fully explored. Univariate and multivariate Cox regression analyses were applied to assess its independent prognostic ability and gene set enrichment analysis (GSEA) was implemented to find its related pathways. Besides, we also explored possible mechanisms of PPP1R18 involved in KIRC. Results: PPP1R18 was highly expressed in KIRC samples than in non-tumor tissues in TCGA, ICGC and GSE6344 datasets, with validations from quantitative real-time polymerase chain reaction (qRT-PCR) in both cell lines and KIRC tissues (all P < 0.05). Univariate and multivariate Cox regression analyses indicated that PPP1R18 was also considered to be with independent prognostic ability in KIRC (both P < 0.01). GSEA results showed that PPP1R18 gene expression was significantly related to Chemokine, JAK STAT, MAPK, and NOTCH pathways. Furthermore, PPP1R18 was also firmly associated with microsatellite instability (MSI), tumor mutational burden (TMB), immune microenvironment, immune cells, immune checkpoints and immune infiltration (all P < 0.05). Analysis of tumor immune dysfunction and exclusion (TIDE) and Imvigor210 datasets suggested that patients with low PPP1R18 expression are more likely to benefit from immunotherapy. Finally, we identified two potential mechanisms of a classical competing endogenous RNA (ceRNA) mechanism and an RNA-binding protein (RBP) involved mechanism of PPP1R18 in KIRC. Conclusions: PPP1R18 played oncogenic and immunological roles of OS in KIRC, offering potential antigens for developing KIRC mRNA vaccines.

A Novel Nine Apoptosis-Related Genes Signature Predicting Overall Survival for Kidney Renal Clear Cell Carcinoma and its Associations with Immune Infiltration.

Background: This study was designed to establish a sensitive prognostic model based on apoptosis-related genes to predict overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). Methods: Obtaining the expression of apoptosis-related genes and associated clinical parameters from online datasets (The Cancer Genome Atlas, TCGA), their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by internal and external databases (both TCGA and ArrayExpress). Results: A total of nine apoptosis-related genes (SLC27A2, TNFAIP2, IFI44, CSF2, IL4, MDK, DOCK8, WNT5A, APP) were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in both the internal and external datasets of OS (all p < 0.05) and verified their expressions by qRT-PCR. Moreover, we conducted the Receiver Operating Characteristic (ROC), finding the area under the ROC curves (AUCs) were all above 0.70 which indicated that riskScore was a stable independent prognostic factor (p < 0.05). Furthermore, prognostic nomograms were established to figure out the relationship between 1-, 3- and 5-year OS and individual parameters for ccRCC patients. Additionally, survival analyses indicated that our riskScore worked well in predicting OS in subgroups of age, gender, grade, stage, T, M, N0, White (all p < 0.05), except for African, Asian and N1 (p > 0.05). We also explored its association with immune infiltration and applied cMap database to seek out highly correlated small molecule drugs. Conclusion: Our study successfully constructed a prognostic model containing nine hub apoptosis-related genes for ccRCC, helping clinicians predict patients' OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

Decreased expression of METTL14 predicts poor prognosis and construction of a prognostic signature for clear cell renal cell carcinoma.

BACKGROUND: METTL14, as one of N6-methyladenosine (m6A) related genes, has been found to be associated with promoting tumorigenesis in different types of cancers. This study was aimed to investigate the prognostic value of METTL14 in clear cell renal cell carcinoma (ccRCC). METHODS: We collected ccRCC patients' clinicopathological parameters information and 13 m6A related genes expression from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to investigate whether METTL14 could serve as an independent factor correlated with overall survival (OS). Gene Set Enrichment Analysis (GSEA) was carried out to identify METTL14-related signaling pathways. Moreover, a risk score (RS) was calculated to predict the prognosis of ccRCC. Quantitative real-time PCR (qRT-PCR) was also utilized to verify the expression of METTL14 in clinical specimens. RESULTS: Differently expressed m6A related genes were identified between ccRCC tissues and normal tissues. Therein, METTL14 was lowly expressed in ccRCC tissues and verified by qRT-PCR (all p < 0.01). Survival analysis indicated that high expression of METTL14 was associated with better OS (p = 1e-05). GSEA results revealed that high METTL14 expression was enriched in ERBB pathway, MAPK pathway, mTOR pathway, TGF-ß pathway and Wnt pathway. Moreover, METTL14 was proved to be an independent prognostic factor by means of univariate and multivariate Cox regression analyses. Nomogram integrating both the METTL14 expression and clinicopathologic variables was also established to provide clinicians with a quantitative approach for predicting survival probabilities of ccRCC. Furthermore, a METTL14-based riskscore (RS) was developed with significant OS (p = 6.661e-16) and increased AUC of 0.856. Besides, significant correlated genes with METTL14 were also provided. CONCLUSIONS: Our results indicated that METTL14 could serve as a favorable prognostic factor for ccRCC. Moreover, this study also provided a prognostic signature to predict prognosis of ccRCC and identified METTL14-related signaling pathways.

Cytotoxic jatrophane diterpenoids from the aerial parts of Euphorbia helioscopia.

A phytochemical study of 80% ethanol extract from the aerial parts of Euphorbia helioscopia led to the isolation of three new jatrophane diterpenoids, euphoheliphanes A-C (1-3). Their structures were established on the basis of spectroscopic data (NMR, IR, UV, and MS). The isolated diterpenoids were tested in vitro for cytotoxic potentials against 6 renal cancer cell lines. As a result, compounds 1-3 exhibited some cytotoxic activities against all the tested tumor cell lines with IC50 values less than 50 µM.[Formula: see text].

Identification of small molecule drugs and development of a novel autophagy-related prognostic signature for kidney renal clear cell carcinoma.

Abnormal autophagic levels have been implicated in the pathogenesis of multiple cancers, however, its role in tumors is complex and has not yet been explored clearly. Hence, we aimed to explore the prognostic values of autophagy-related genes (ARGs) for kidney renal clear cell carcinoma (KIRC). Differentially expressed ARGs and transcription factors (TFs) were identified in KIRC patients obtaining from the The Cancer Genome Atlas (TCGA) database. Then, networks between TFs and ARGs, gene ontology functional annotations and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted. Next, we performed consensus clustering, COX regression analysis and Lasso regression analysis to identify the prognostic ARGs. Finally, an individual prognostic index (PI, riskScore) was established. Based on TCGA cohort and ArrayExpress cohort, Survival analysis, ROC curve, independent prognostic analysis, and clinical correlation analysis were also performed to evaluate this PI. Based on differentially expressed ARGs, KIRC patients were successfully divided into two clusters (P = 5.916e-04). AS for PI, it was constructed based on 11 ARGs and significantly classified KIRC patients into high-risk group and low-risk group in terms of OS (P = 4.885e-15 for TCGA cohort, P = 6.366e-03 for ArrayExpress cohort). AUC of its ROC curve reached 0.747 for TCGA cohort and 0.779 for ArrayExpress cohort. What's more, this PI was proven to be a valuable independent prognostic factor in both univariate and multivariate COX regression analysis (P < .001). Prognostic nomograms were also performed to visualize the relationship between individual predictors and survival rates in patients with KIRC. By means of connectivity map database, emetine, cephaeline and co-dergocrine mesilate related to ARGs were found to be negatively correlated with KIRC. This study provided an effective PI for KIRC and also displayed networks between TFs and ARGs. KIRC patients were successfully divided into two clusters based on differentially expressed ARGs. Besides, small molecule drugs related to ARGs were also identified for KIRC.

MiR-455-5p Suppresses the Progression of Prostate Cancer by Targeting CCR5.

Accumulated evidence indicates that miR-455-5p functions as tumor suppressor in the progression of various cancers. However, the mechanism through which miR-455-5p influences the tumorigenesis of human prostate cancer (PCa) remains undetermined. In this study, reanalysis of data obtained from the Memorial Sloan Kettering Cancer Center showed that miR-455-5p can be used as biomarker for PCa diagnosis and predictor of poor prognosis. Functional assays indicated that miR-455-5p overexpression could suppress cellular proliferation, inhibit tumor growth, and trigger apoptosis by activating and cleaving caspase 3. We experimentally verified that miR-455-5p negatively regulated the C-C motif chemokine receptor 5 (CCR5). Overall, our data demonstrate that miR-455-5p suppressed PCa cellular proliferation and induced cell apoptosis by downregulating CCR5. Thus, miR-455-5p may be considered a new therapeutic strategy for PCa.