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Background: In the realm of tumor-targeted therapeutics, Polo-like kinases (PLKs) are a significant group of protein kinases that were found recently as being related to tumors. However, the significance of PLKs in pan-cancer remains systematically studied. Methods and materials: We integrated multi-omics data to comprehensively investigate the expression patterns of the PLK family across various cancer types. Subsequently, study examined the associations between tumor mutation burden (TMB), microsatellite instability (MSI), immune subtype classification, immune infiltration, tumor microenvironment scores, immune checkpoint gene expression, and the PLKs expression profiles within various tumor types. Furthermore, using our mRNA sequencing data (TRUCE01) and four bladder cancer (BLCA) cohorts (GSE111636, GSE176307, and IMvigor210), We examined the correlation between the expression level of PLK and immunotherapy effectiveness. Next, Gene set enrichment analysis (GSEA) was evaluated to find that potentially enriched PLK signaling pathways. Utilizing TIMER 2.0, we conducted an immune infiltration analysis underlying transcriptome expression, copy number variations (CNV), or somatic mutations of PLKs in BLCA. Finally, mRNA expression validation of PLK1/3/4 by real-time PCR within 10 paired BLCA tissues, protein expression verification through the Human Protein Atlas (HPA), and PLK4 in vitro cytological studies have been employed in BLCA. Results: The expression of most of the PLK family members exhibits variation between cancerous tissues and adjacent normal tissues across various cancer species. Furthermore, the expression of PLKs demonstrates a significant association with immunotyping, infiltration of immune cell, tumor mutational burden (TMB), microsatellite instability (MSI), immunological checkpoint gene activity and therapeutic effectiveness in pan-tumor tissues. Additional investigation into the correlation between the PLK family and BLCA has revealed that the expression of the PLK genes holds substantial significance in the biological processes of BLCA. Furthermore, a notable association has been observed between the copy number variation, variant status, and the degree of certain immunological cell infiltration. Of note, the expression validation and in vitro phenotypic experiments have demonstrated that PLK4 has a significant function in promoting the BLCA cell proliferation, migration, and invasion. Conclusion: Collectively, based on various databases, our results highlight the involvement of PLK gene family in the formation of different types of tumors and identify PLK-related genes that may be used for therapy.
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Background: During tumor growth, tumor cells interact with their tumor microenvironment (TME) resulting in the development of heterogeneous tumors that promote tumor occurrence and progression. Recently, there has been extensive attention on TME as a possible therapeutic target for cancers. However, an accurate TME-related prediction model is urgently needed to aid in the assessment of patients' prognoses and therapeutic value, and to assist in clinical decision-making. As such, this study aimed to develop and validate a new prognostic model based on TME-associated genes for BC patients. Methods: Transcriptome data and clinical information for BC patients were extracted from The Cancer Genome Atlas (TCGA) database. Gene Expression Omnibus (GEO) and IMvigor210 databases, along with the MSigDB, were utilized to identify genes associated with TMEs (TMRGs). A consensus clustering approach was used to identify molecular clusters associated with TMEs. LASSO Cox regression analysis was conducted to establish a prognostic TMRG-related signature, with verifications being successfully conducted internally and externally. Gene ontology (GO), KEGG, and single-sample gene set enrichment analyses (ssGSEA) were performed to investigate the underlying mechanisms. The potential response to ICB therapy was estimated using the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and Immunophenoscore (IPS). Additionally, it was found that the expression level of certain genes in the model was significantly correlated with objective responses to anti-PD-1 or anti-PD-L1 treatment in the IMvigor210, GSE111636, GSE176307, or Truce01 (registration number NCT04730219) cohorts. Finally, real-time PCR validation was performed on 10 paired tissue samples, and in vitro cytological experiments were also conducted on BC cell lines. Results: In BC patients, 133 genes differentially expressed that were associated with prognosis in TME. Consensus clustering analysis revealed three distinct clinicopathological characteristics and survival outcomes. A novel prognostic model based on nine TMRGs (including C3orf62, DPYSL2, GZMA, SERPINB3, RHCG, PTPRR, STMN3, TMPRSS4, COMP) was identified, and a TMEscore for OS prediction was constructed, with its reliable predictive performance in BC patients being validated. MultiCox analysis showed that the risk score was an independent prognostic factor. A nomogram was developed to facilitate the clinical viability of TMEscore. Based on GO and KEGG enrichment analyses, biological processes related to ECM and collagen binding were significantly enriched among high-risk individuals. In addition, the low-risk group, characterized by a higher number of infiltrating CD8+ T cells and a lower burden of tumor mutations, demonstrated a longer survival time. Our study also found that TMEscore correlated with drug susceptibility, immune cell infiltration, and the prediction of immunotherapy efficacy. Lastly, we identified SERPINB3 as significantly promoting BC cells migration and invasion through differential expression validation and in vitro phenotypic experiments. Conclusion: Our study developed a prognostic model based on nine TMRGs that accurately and stably predicted survival, guiding individual treatment for patients with BC, and providing new therapeutic strategies for the disease.
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Microambiente Tumoral , Neoplasias da Bexiga Urinária , Humanos , Microambiente Tumoral/genética , Neoplasias da Bexiga Urinária/genética , Prognóstico , Nomogramas , ImunoterapiaRESUMO
BACKGROUND: Bladder cancer (BCa) is a highly prevalent disease with a poor prognosis. There is no better forecasting method for it yet. Current studies demonstrate that pyroptosis is involved in the development and progression of various cancers. METHODS: This study employed bioinformatics techniques to analyze the data of BCa patients obtained from the TCGA and GEO databases in order to construct a prognostic risk model. The TCGA dataset was used for the training set, and the multiple external datasets (including GSE13507, GSE31684, GSE48075, IMvigor210, and GSE32894) were applied as the validation sets. Prognostic-associated pyroptosis genes screened by univariate Cox regression analysis were utilized to construct the lasso Cox regression model. GO and KEGG analysis results identified the selected genes that are primarily involved in the inflammation and cell death processes. The related patients were grouped into low- and high-risk groups. Kaplan-Meier survival analysis was performed to compare survival differences between the risk groups. The accuracy of this risk prediction model was assessed by ROC. We also applied the Human Protein Atlas (HPA) to detect the protein expression of these genes. Subsequently, qRT-PCR was performed to verify the expression of these model genes. RESULTS: There are 29 pyroptosis-related genes with significant expression differences between BCa and corresponding adjacent tissues, and 11 genes (SH2D2A, CHMP4C, MRFAP1L1, GBP2, EHBP1, RAD9A, ANXA1, TMEM109, HEYL, APOL2, ORMDL1) were picked by univariate and LASSO Cox regression analysis. Immunological cell infiltration and ssGSEA results further indicated that the low and high-risk groups were substantially correlated with the immune status of BCa patients. According to TCGA and multiple external datasets, Kaplan-Meier survival curves showed the overall survival rate of the high-risk group to be decreased. ROC curves showed the model established to be accurate and reliable. Moreover, the HPA database also demonstrated the verification of the modeled genes' expression in BCa and normal bladder tissue using the HPA database. qRT-PCR results also suggested the up-regulated EHBP1 and down-regulated RAD9A mRNA expression levels to be confirmed in 15 pairs of BCa and corresponding adjacent tissues. CONCLUSION: This study presents the development and validation of a novel gene signature associated with pyroptosis, which holds the potential for predicting patient outcomes in BCa and providing insights into the immune microenvironment of BCa.
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Tumor Metabolism is strongly correlated with prognosis. Nevertheless, the prognostic and therapeutic value of metabolic-associated genes in BCa patients has not been fully elucidated. First, in this study, metabolism-related differential expressed genes DEGs with prognostic value in BCa were determined. Through the consensus clustering algorithm, we identified two molecular clusters with significantly different clinicopathological features and survival prognosis. Next, a novel metabolism-related prognostic model was established. Its reliable predictive performance in BCa was verified by multiple external datasets. Multivariate Cox analysis exhibited that risk score were independent prognostic factors. Interestingly, GSEA enrichment analysis of GO, KEGG, and Hallmark gene sets showed that the biological processes and pathways associated with ECM and collagen binding in the high-risk group were significantly enriched. Notely, the model was also significantly correlated with drug sensitivity, immune cell infiltration, and immunotherapy efficacy prediction by the wilcox rank test and chi-square test. Based on the 7 immune infiltration algorithm, we found that Neutrophils, Myeloid dendritic cells, M2 macrophages, Cancer-associated fibroblasts, etc., were more concentrated in the high-risk group. Additionally, in the IMvigor210, GSE111636, GSE176307, or our Truce01 (registration number NCT04730219) cohorts, the expression levels of multiple model genes were significantly correlated with objective responses to anti-PD-1/anti-PD-L1 immunotherapy. Finally, the expression of interested model genes were verified in 10 pairs of BCa tissues and para-carcinoma tissues by the HPA and real-time fluorescent quantitative PCR. Altogether, the signature established and validated by us has high predictive power for the prognosis, immunotherapy responsiveness, and chemotherapy sensitivity of BCa.
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Neoplasias da Bexiga Urinária , Humanos , Neoplasias da Bexiga Urinária/genética , Prognóstico , Algoritmos , Análise por Conglomerados , Consenso , Microambiente TumoralRESUMO
[This corrects the article DOI: 10.1016/j.heliyon.2023.e16897.].
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Background: Transient receptor potential cation channel subfamily V (TRPV) play an essential in cancer initiation, progression, and treatment. TRPV expression alteration are shown relate to multiple cancers prognosis and treatment of cancers but are less-studied in pan-cancer. In this study, we characterize the clinical prediction value of TRPV at pan-cancer level. Methods: Several databases were used to examine the transcript expression difference in tumor vs. normal tissue, copy-number variant (CNV) and single nucleotide polymorphisms (SNP) mutation of each TRPV members in pan-cancer, including The Cancer Genome Atlas (TCGA) and cBioPortal. We performed K-M survival curve and univariate Cox regression analyses to identify survival and prognosis value of TRPV. CellMiner were selected to explore drug sensitivity. We also analyzed association between tumor mutation burden (TMB), microsatellite instability (MSI), tumor immune microenvironment and TRPV family genes expression. Moreover, we investigated the relationship between TRPVs expression and effectiveness of immunotherapy in multiple cohorts, including one melanoma (GSE78220), one renal cell carcinoma (GSE67501), and three bladder cancer cohorts (GSE111636, IMvigor210, GSE176307 and our own sequencing dataset (TRUCE-01)), and further analyzed the changes of TRPVs expression before and after treatment (tislelizumab combined with nab-paclitaxel) of bladder cancer. Next, we made a special effort to investigate and study biological functions of TRPV in bladder cancer using gene set enrichment analysis (GSEA), and conducted immune infiltration analysis with TRPVs family genes expression, copy number or somatic mutations of bladder cancer by TIMER 2.0. Finally, real-time PCR and protein expression validation of TRPVs within 10 paired cancer and para-carcinoma tissue samples, were also performed in bladder cancer. Results: Only TRPV2 expression was lower in most cancer types among TRPV family genes. All TRPVs were correlated with survival changes. Amplification was the significant gene alternation in all TRPVs. Next, analysis between TRPVs and clinical traits showed that TRPVs were related to pathologic stage, TNM stage and first course treatment outcome. Moreover, TRPV expression was highly correlated with MSI and TMB. Immunotherapy is a research hotspot at present, our result showed the significant association between TRPVs expression and immune infiltration indicated that TRPV expression alternation could be used to guide prognosis. In addition, we also discovered that the expression level of TRPV1/2/3/4/6 was positively or negatively correlated with objective responses to anti-PD-1/PD-L1 across multiple immunotherapy cohort. Further analysis of drug sensitivity showed the value to treatment. Based on the above analysis, we next focused on TRPV family in bladder cancer. The result demonstrated TRPV also played an important role in bladder cancer. Finally, qPCR assay verified our analysis in bladder cancer. Conclusion: Our study firstly revealed expression and genome alternation of TRPV in pan-cancer. TRPV could be used to predict prognosis or instructing treatment of human cancers, especially bladder cancer.
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The relationship between body mass index (BMI) and stroke type has remained controversial despite studies demonstrating that BMI is related to stroke risk, especially in specific groups. We assessed the age- and sex-associated impacts of BMI on stroke type in a low-income, poorly educated population in China. The association of BMI with stroke type was estimated using Cox regression analyses in this prospective cohort study, after adjusting for sex, age, education level, hypertension, diabetes, smoking, and alcohol drinking status. During the follow-up period, 638 stroke cases occurred among the 3,906 participants included in this prospective study. For men aged <65 years, being overweight was an independent predictor of all stroke subtypes, compared with normal-weight individuals; the hazard ratios (HRs) and 95% confidence intervals (CIs) were 1.98 (1.52-2.58) for total stroke, 1.69 (1.22-2.33) for ischemic stroke, and 3.62 (2.09-6.25) for hemorrhagic stroke, all P < 0.001. Being underweight was also an independent predictor of hemorrhagic stroke (HR, 5.10; 95%CI, 1.80-14.50, P = 0.002). For women <65-years-old, being overweight was a risk factor for total (HR, 1.38; 95% CI, 1.01-1.89; P = 0.044) and hemorrhagic strokes (HR, 2.06; 95% CI, 1.00-4.28; P = 0.050); obesity was a risk factor for total (HR, 2.47; 95% CI, 1.60-3.82) and ischemic strokes (HR, 2.53; 95% CI, 1.54-4.15), all P < 0.001. These findings suggest that weight management should be a high priority for substantially reducing the heavy burden of strokes in rural China among both men and women <65-years-old; men<65-years-old should maintain their weight within a reasonable range.
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Although strokes are the leading cause of death and disability in many countries, China still lacks long-term monitoring data on stroke incidence and risk factors. This study explored stroke risk factors in a low-income, rural population in China. The study population was derived from the Tianjin Brain Study, a population-based stroke monitoring study that began in 1985. This study documented the demographic characteristics, past medical histories, and personal lifestyles of the study participants. In addition, physical examinations, including measurements of blood pressure (BP), height, and weight, were performed. Hazard ratios (HRs) were estimated for the risk factors for all subtypes of stroke using multivariate Cox regression analyses. During the study with mean following-up time of 23.16 years, 3906 individuals were recruited at baseline, and during 27 years of follow-up, 638 strokes were documented. The multivariate Cox regression analyses revealed a positive correlation between age and stroke incidence. Limited education was associated with a 1.9-fold increase in stroke risk (lowest vs. highest education level). Stroke risk was higher among former smokers than among current smokers (HR, 1.8 vs. 1.6; both, P < 0.05). Moreover, stroke risk was significantly associated with sex (HR, 1.8), former alcohol drinking (HR, 2.7), baseline hypertension (HR, 3.1), and overweight (HR, 1.3). In conclusion, this study identified uncontrollable (sex and age) and controllable (education, smoking, alcohol drinking, hypertension, and overweight) risk factors for stroke in a low-income, rural population in China. Therefore, it is critical to control BP and weight effectively, advocate cessation of smoking/alcohol drinking, and enhance the education level in this population to prevent increase in the burden of stroke in China.