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The tumor microenvironment (TME) comprises immune-infiltrating cells that are closely linked to tumor development. By screening and analyzing genes associated with tumor-infiltrating M0 cells, we developed a risk model to provide therapeutic and prognostic guidance in clear cell renal cell carcinoma (ccRCC). First, the infiltration abundance of each immune cell type and its correlation with patient prognosis were analyzed. After assessing the potential link between the depth of immune cell infiltration and prognosis, we screened the infiltrating M0 cells to establish a risk model centered on three key genes (TMEN174, LRRC19, and SAA1). The correlation analysis indicated a positive correlation between the risk score and various stages of the tumor immune cycle, including B-cell recruitment. Furthermore, the risk score was positively correlated with CD8 expression and several popular immune checkpoints (ICs) (TIGIT, CTLA4, CD274, LAG3, and PDCD1). Additionally, the high-risk group (HRG) had higher scores for tumor immune dysfunction and exclusion (TIDE) and exclusion than the low-risk group (LRG). Importantly, the risk score was negatively correlated with the immunotherapy-related pathway enrichment scores, and the LRG showed a greater therapeutic benefit than the HRG. Differences in sensitivity to targeted drugs between the HRG and LRG were analyzed. For commonly used targeted drugs in RCC, including axitinib, pazopanib, temsirolimus, and sunitinib, LRG had lower IC50 values, indicating increased sensitivity. Finally, immunohistochemistry results of 66 paraffin-embedded specimens indicated that SAA1 was strongly expressed in the tumor samples and was associated with tumor metastasis, stage, and grade. SAA1 was found to have a significant pro-tumorigenic effect by experimental validation. In summary, these data confirmed that tumor-infiltrating M0 cells play a key role in the prognosis and treatment of patients with ccRCC. This discovery offers new insights and directions for the prognostic prediction and treatment of ccRCC. [ABSTRACT FROM AUTHOR]

Purpose: Disulfidptosis is a novel type of cell death induced by disulphide stress that depends on the accumulation of cystine disulphide, causing cytotoxicity and triggering cell death. However, the direct prognostic effect and regulatory mechanism of disulfidptosis-related genes in bladder urothelial carcinoma (BLCA) remain unclear. Methods: To explore the role of 10 disulfidptosis-related genes, the multiomic data of 10 genes were comprehensively analysed. Next, based on seven disulfidptosis-related differentially expressed genes, a novel disulfidptosis-related gene score was developed to help predict the prognosis of BLCA. Immunohistochemistry, EDU, Real-time PCR and western blot were used to verify the model. Results: Significant functional differences were found between the high- and low-risk score groups, and samples with a higher risk score were more malignant. Furthermore, the tumour exclusion and Tumour Immune Dysfunction and Exclusion scores of the high-risk score group were higher than those of the low-risk score group. The risk score was positively correlated with the expression of immune checkpoints. Drug sensitivity analyses revealed that the low-risk score group had a higher sensitivity to cisplatin, doxorubicin, docetaxel and gemcitabine than the high-risk score group. Moreover, the expression of the TM4SF1 was positively correlated with the malignancy degree of BLCA, and the proliferation ability of BLCA cells was reduced after knockdown TM4SF1. Conclusion: The present study results suggest that disulfidptosis-related genes influence the prognosis of BLCA through their involvement in immune cell infiltration. Thus, these findings indicate the role of disulfidptosis in BLCA and its potential regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Background: Metastasis is a crucial aspect of disease progression leading to death in patients with prostate cancer (PCa). However, its mechanism remains unclear. We aimed to explore the mechanism of lymph node metastasis (LNM) by analyzing the heterogeneity of tumor microenvironment (TME) in PCa using scRNA-seq. Methods: A total of 32,766 cells were obtained from four PCa tissue samples for scRNA-seq, annotated, and grouped. InferCNV, GSVA, DEG functional enrichment analysis, trajectory analysis, intercellular network evaluation, and transcription factor analysis were carried out for each cell subgroup. Furthermore, validation experiments targeting luminal cell subgroups and CXCR4 + fibroblast subgroup were performed. Results: The results showed that only EEF2 + and FOLH1 + luminal subgroups were present in LNM, and they appeared at the initial stage of luminal cell differentiation, which were comfirmed by verification experiments. The MYC pathway was enriched in the EEF2 + and FOLH1 + luminal subgroups, and MYC was associated with PCa LNM. Moreover, MYC did not only promote the progression of PCa, but also led to immunosuppression in TME by regulating PDL1 and CD47. The proportion of CD8 + T cells in TME and among NK cells and monocytes was lower in LNM than in the primary lesion, while the opposite was true for Th and Treg cells. Furthermore, these immune cells in TME underwent transcriptional reprogramming, including CD8 + T subgroups of CCR7 + and IL7R+, as well as M2-like monocyte subgroups expressing tumor-associated signature genes, like CCR7, SGKI, and RPL31. Furthermore, STEAP4+, ADGRF5 + and CXCR4+, and SRGNC + fibroblast subgroups were closely related to tumor progression, tumor metabolism, and immunosuppression, indicating their contributions in PCa metastasis. Meanwhile, The presence of CXCR4 + Fibroblasts in PCa was confirmed by polychromatic immunofluorescence. Conclusions: The significant heterogeneity of luminal, immune, and interstitial cells in PCa LNM may not only directly contribute to tumor progression, but also indirectly result in TME immunosuppression, which may be the cause of metastasis in PCa and in which MYC played an role. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "ScRNA-seq revealed an immunosuppression state and tumor microenvironment heterogeneity related to lymph node metastasis in prostate cancer" published in Experimental Hematology & Oncology. The correction addresses an error in Fig. 3E, F of the article, where the authors mistakenly used the wrong picture. The correct figure is provided in the correction notice. The original article has been corrected. The publisher, Springer Nature, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

The platelet-derived growth factor (PDGF) pathway is important in angiogenesis, which can accelerate the formation of vessels in tumor tissues and promote the progression of malignant tumors. To clarify the role of PDGF in the occurrence of renal cell carcinoma and targeted drug resistance, we explored the pathway in kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis with the aim of supporting comprehensive and individualized therapy. First, we found 40 genes related to the PDGF pathway through gene set enrichment analysis and then obtained their expressions and clinical data in 32 different cancers from The Cancer Genome Atlas (TCGA). Mutations in these genes (including copy number and single-nucleotide variation) and mRNA expression were also detected. Next, we conducted a hazard ratio analysis to determine whether the PDGF pathway genes were risk or protective factors in tumors. Although PDGF-related genes acted as traditional oncogenes and were closely related to tumor angiogenesis in many cancers, our results indicated that most genes had a protective role in KIRC. We further analyzed the methylation modification of PDGF pathway genes and found that they were prevalent in 32 different cancers. Furthermore, 539 KIRC samples obtained from TCGA were divided into three clusters based on the mRNA expression of PDGF genes, including normal, inactive, and active PDGF gene expressions. The results from survival curve analysis indicated that the active PDGF cluster of patients had the best survival rate. Using the three clusters, we studied the correlation between the PDGF pathway and 12 common targeted drugs, as well as classical oncogenes and infiltrating immune cells. A prognostic risk model was constructed based on the PDGF score using LASSO-Cox regression analysis to analyze the value of the model in predicting the prognosis of patients with KIRC. Finally, 11 genes were selected for LASSO regression analysis, and the results demonstrated the high predictive value of this risk model and its close relationship with the pathological characteristics of KIRC (metastasis, size, grade, stage, etc.). In addition, we found that the risk score was an independent risk factor correlated with overall survival through univariate and multivariate analyses and a nomogram was built to assess patient prognosis. In conclusion, the occurrence and development of KIRC may be associated with an abnormally activated PDGF pathway, which may be a potential drug target in the treatment of KIRC. [ABSTRACT FROM AUTHOR]

Objectives: MiR-21 induces neoplastic transformation, cell proliferation, and metastasis and downregulates programmed cell death4 (PDCD4) in some cancers. The aim of this study was to investigate the roles and interactions of PDCD4 and miR-21 in human renal cell carcinoma (RCC). Materials and Methods: A total of 32 paired tumor and normal tissue specimens from RCC patients as well as three renal cancer cell lines (786-O, A498, caki-1) and one normal epithelial kidney cell line (HK-2) were studied. The expression levels of PDCD4 (protein and mRNA) and miR-21 were examined by Western blot analysis and by qRT-PCR and luciferase reporter assays. Furthermore, we transfected 786-O cells with pre-miR-21 (mimics) and anti-miR-21 (inhibitor) and then again analyzed the expression of PDCD4 protein and mRNA, and determined cell proliferation and transformation capabilities by EDU and soft agar colony formation assay. Results: MiR-21 expression was significantly upregulated in RCC, metastatic RCC specimens and renal cancer cell lines (A498, 786-O, caki-1) compared to normal non-metastatic RCC specimens and HK-2 cells (P<0.05). In contrast, PDCD4 protein expression significantly decreased (P<0.05), whereas PDCD4 mRNA expression remained unaltered (P>0.05). Moreover, we observed a significant reduction in PDCD4 protein levels in miR-21mimic-transfected cells, but a significant increase in miR-21inhibitor-transfected cells (P<0.05), whereas PDCD4 mRNA was practically unaltered (P>0.05). Furthermore, miR-21mimic-transfected cells exhibited increased cell proliferation and transformation capacity according to EDU analysis and soft agar formation assay, whereas miR-21inhibitor-transfected cells exhibited the opposite phenomenon(P<0.05). Conclusions: MiR-21 not only promoted cancer cell hyperplasia and contributed to tumor cell transformation and metastasis, but also post-transcriptionally downregulated PDCD4 protein expression. PDCD4 and miR-21 expression levels potentially play an important role in renal cell cancer. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objectives: The tumor suppressor gene entitled programmed cell death 4 (PDCD4) encodes a protein that inhibits neoplastic transformation and invasion. The aim of this study was to investigate the expression of PDCD4 and its prognostic roles in human renal cell carcinoma (RCC). Materials and methods: A total of 32 paired fresh tumor specimens and adjacent non-cancerous renal tissue from RCC patients by western blot to detect the difference of PDCD4 expression in tumor tissues and non-cancerous tissues. 66 RCC paraffin-embedded specimens and 18 normal renal tissues were analyzed by immunohistochemistry to investigate the association of PDCD4 expression with RCC clinicopathological features. Results: PDCD4 expression was significantly decreased in RCC compared with normal renal tissues ( P = 0.03), and it was found to be significantly associated with RCC metastasis ( P = 0.007), tumor T-stage ( P = 0.022) and tumor grade ( P = 0.015). The mean overall survival was significantly decreased in the low PDCD4 group compared to the high PDCD4 group (low PDCD4: mean overall survival 41.9 months, high PDCD4: mean overall survival 52.9 months, P = 0.008). Conclusion: PDCD4 expression strongly correlated to RCC stage, tumor grade, tumor metastasis and tumor-related death. PDCD4 expression was also appears to be a marker in RCC prognosis. [ABSTRACT FROM AUTHOR]

Background. Reprogramming of lipid metabolism is closely associated with tumor development, serving as a common and critical metabolic feature that emerges during tumor evolution. Meanwhile, immune cells in the tumor microenvironment also undergo aberrant lipid metabolism, and altered lipid metabolism also has an impact on the function and status of immune cells, further promoting malignant biological behavior. Consequently, we focused on lipid metabolism-related genes for constructing a novel prognostic marker and evaluating immune status in prostate cancer. Methods. Information about prostate cancer patients was obtained from TCGA and GEO databases. The NMF algorithm was conducted to identify the molecular subtypes. The least absolute shrinkage and selection operator (Lasso) regression analysis was applied to establish a prognostic risk signature. CIBERSORT algorithm was used to calculate immune cell infiltration levels in prostate cancer. External clinical validation data were used to validate the results. Results. Prostate cancer samples were divided into two subtypes according to the NMF algorithm. A six-gene risk signature (PTGS2, SGPP2, ALB, PLA2G2A, SRD5A2, and SLC2A4) was independent of prognosis and showed good stability. There were significant differences between risk groups of patients with respect to the infiltration of immune cells and clinical variables. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR. Conclusion. We constructed a six-gene signature with lipid metabolism in prostate cancer to effectively predict prognosis and reflect immune microenvironment status. [ABSTRACT FROM AUTHOR]

Background. Despite the constant iteration of small-molecule inhibitors and immune checkpoint inhibitors, PRAD (prostate adenocarcinoma) patients with distant metastases and biochemical recurrence maintain a poor survival outcome along with an increasing morbidity in recent years. N7-Methylguanine, a new-found type of RNA modification, has demonstrated an essential role in tumor progression but has hardly been studied for its effect on prostate carcinoma. The current study aimed to seek m7G (N7-methylguanosine) related prognostic biomarkers and potential targets for PRAD treatment. Methods. 42 genes related to m7G were collected from former literatures and GSEA (Gene Set Enrichment Analysis) website. Then, RNA-seq (RNA sequencing) and clinical data from TCGA-PRAD (The Cancer Genome Atlas-Prostate) cohort were retrieved to screen the differentially expressed m7G genes to further construct a multivariate Cox prognostic model for PRAD. Next, GSE116918, a prostate cancer cohort acquired from GEO (Gene Expression Omnibus) database, was analyzed for the external validation group to assess the ability to predict BFFS (biochemical failure-free survival) of our m7G prognostic signature. Kaplan-Meier, ROC (receiver operator characteristic), AUC (areas under ROC curve), and calibration curves were adopted to display the performance of this prognostic signature. In addition, immune infiltration analysis was implemented to evaluate the effect of these m7G genes on immunoinfiltrating cells. Correlation with drug susceptibility of the m7G signature was also analyzed by matching drug information in CellMiner database. Results. The m7G-related prognostic signature, including three genes (EIF3D, EIF4A1, LARP1) illustrated superior prognostic ability for PRAD in both training and validation cohorts. The 5-year AUC were 0.768 for TCGA-PRAD and 0.608 for GSE116918. It can well distinguish patients into different risk groups of biochemical recurrence (p =1e-04 for TCGA-PRAD and p =0.0186 for GSE116918). Immune infiltration analysis suggested potential regulation of m7G genes on neutrophils and dendritic cells in PRAD. Conclusions. A m7G-related prognostic signature was constructed and validated in the current study, giving new sights of m7G methylation in predicting the prognostic and improving the treatment of PRAD. [ABSTRACT FROM AUTHOR]

Primary Sjögren's syndrome (pSS) is a chronic inflammatory autoimmune disease, which mainly damages patients' exocrine glands. Sensitive early diagnostic indicators and effective treatments for pSS are lacking. Using machine learning methods to find diagnostic markers and effective therapeutic ways for pSS is of great significance. In our study, first, 1643 differentially expressed genes (DEGs; 737 were upregulated and 906 were downregulated) were ultimately screened out and analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes based on the datasets from the Gene Expression Omnibus. Then, support vector machine, least absolute shrinkage and selection operator regression, random forest, and weighted correlation network analysis were used to screen out feature genes from DEGs. Subsequently, the intersection of the feature genes was taken to screen 10 genes as hub genes. Meanwhile, the analysis of the diagnostic efficiency of 10 hub genes showed their good diagnostic value for pSS, which was validated through immunohistochemistry on the paraffin sections of the labial gland. Subsequently, a multi-factor regulatory network and correlation analysis of hub genes were performed, and the results showed that ELAVL1 and IGF1R were positively correlated with each other but both negatively correlated with the other seven hub genes. Moreover, several meaningful results were detected through the immune infiltration landscape. Finally, we used molecular docking to screen potential therapeutic compounds of pSS based on the hub genes. We found that the small molecules DB08006, DB08036, and DB15308 had good docking scores with ELAVL1 and IGF1R simultaneously. Our study might provide effective diagnostic biomarkers and new therapeutic ideas for pSS. Primary Sjögren's syndrome(pSS) is a chronic inflammatory autoimmune disease, sensitive early diagnostic indicators and effective treatments for pSS are lacking. The goal of our study was to screen out the effective markers and related potential therapeutic agents for pSS by analyzing the experimental dataset from multiple data platforms and validating through the validation dataset combined with experiments. This might provide effective diagnostic biomarkers and new therapeutic ideas for treating pSS. [ABSTRACT FROM AUTHOR]