UNASSIGNED: Bladder cancer (BC) is the sixth most common cancer and the ninth leading cause of cancer death among men in the world. Previous studies have shown that tumor hypoxia plays an important role in the occurrence and development of BC, but the role of tumor hypoxia in the prognosis and immune infiltration of BC remains unclear. Our aim was to perform a bioinformatics analysis combined with a clinical analysis to explore the roles of hypoxia in BC.
UNASSIGNED: We acquired datasets (GSE13507, GSE5287, and GSE1827) containing mRNA expression information from BC cohorts from the Gene Expression Omnibus (GEO) and measured the Hypoxia score using the Gene Set Variation Analysis (GSVA). Then we used X-tile method and log-rank test and Pearson\'s correlation test to analyze the relation among the Hypoxia score and the clinicopathological and immunological characteristics of BC and used stepwise Cox regression analysis to establish a Prognostic model.
UNASSIGNED: Hypoxia was found to be closely associated with tumor grade, pathological type, invasion, and prognosis of BC in our study. Moreover, we determined that hypoxia was closely related to the infiltration abundance of multiple immune cells through a correlation analysis, and the tumor immune cell infiltration was further found to be significantly associated with the tumor grade and tumor type of BC. Furthermore, we constructed several models based on the Hypoxia score and tumor immune infiltration with C-indexes ranging from 0.703 and 0.888, which showed good performance in predicting the prognosis of BC.
UNASSIGNED: Our study showed that hypoxia plays an important role in the progression, prognosis, and tumor immune infiltration of BC. Our models based on hypoxia and tumor immune infiltration play a guiding role in the prognosis and treatment of BC patients.

UNASSIGNED: This study aims to screen inflammation-related genes closely associated with the prognosis of hepatocellular carcinoma (HCC) to accurately forecast the prognosis of HCC patients.
UNASSIGNED: Gene expression matrices and clinical information for liver cancer samples were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). An intersection of differentially expressed genes of HCC and normal and GeneCards yielded inflammation-related genes associated with HCC. Cox regression and the minor absolute shrinkage and selection operator (LASSO) regression analysis to filter genes associated with HCC prognosis. The prognostic value of the model was confirmed by drawing Kaplan-Meier and ROC curves. Select differentially expressed genes between the high-risk and low-risk groups and perform GO and KEGG pathways analyses. CIBERSORT analysis was conducted to assess associations of risk models with immune cells and verified using real-time qPCR.
UNASSIGNED: A total of six hub genes (C3, CTNNB1, CYBC1, DNASE1L3, IRAK1, and SERPINE1) were selected using multivariate Cox regression to construct a prognostic model. The validation evaluation of the prognostic model showed that it has an excellent ability to predict prognosis. A line plot was drawn to indicate the HCC patients\' survival, and the calibration curve revealed satisfactory predictability. Among the six hub genes, C3 and DNASE1L3 are relatively low expressed in HCCLM3 and 97H liver cancer cell lines, while CTNNB1, CYBC1, IRAK1, and SERPINE1 are relatively overexpressed in liver cancer cell lines.
UNASSIGNED: One new inflammatory factor-associated prognostic model was constructed in this study. The risk score can be an independent predictor for judging the prognosis of HCC patients\' survival.

OBJECTIVE: To investigate cyclin D2 (CCND2) expression in papillary thyroid carcinoma (PTC) and its association with the clinicopathological features.
METHODS: The public databases TCGA, TIMER 2.0 and UALCAN were used to explore CCND2 expression level in PTC and adjacent tissues, and its diagnostic value for PTC was analyzed using ROC curves. GO enrichment analysis of CCND2-related differentially expressed genes (DEGs) in PTC was performed, and tumor immune infiltration of CCND2 in thyroid cancer was analyzed using TIMER database and CIBERSORT data source. RT-qPCR and Western blot were used to detect CCND2 expression in normal human thyroid cell line Nthy-ori-3-1 and human PTC cell lines TPC-1 and BCPAP. CCND2 expression was also detected in clinical specimens of PTC and adjacent tissues by immunohistochemistry, and its correlation with clinicopathological features of the patients were analyzed.
RESULTS: Informatic analysis revealed significantly higher CCND2 mRNA expression in thyroid cancer than in the adjacent tissues (P < 0.001) in close correlation with tumor stage, gender, age, pathological subtype, and lymph node involvement (P < 0.05). ROC curve analysis showed that at the cutoff value of 4.983, the diagnostic sensitivity, specificity, and accuracy of CCND2 expression for PTC was 83.6%, 94.9%, and 78.5%, respectively. CCND2 expression was positively correlated with B cells, CD4+ T cells, and macrophages (P < 0.001) and negatively with CD8+ T cells (P < 0.01), and also correlated with memory B-cell infiltration, CD4+ T-cell memory activation, M2 macrophages, resting mast cells, and mast cell activation (P < 0.05). RT-qPCR, Western blot and immunohistochemistry showed significantly higher CCND2 expression in the PTC cells than in Nthy-ori-3-1 cells (P < 0.01) and also in clinical PTC tissues than in the adjacent tissues (P < 0.05) in correlation with tumor size, lymph node metastasis and TNM stage (P < 0.05).
CONCLUSIONS: CCND2 overexpression is closely correlated with tumor progression and immune cell infiltration in PTC patients..

BACKGROUND: Immunogenic cell death (ICD) is a process in which dying cells stimulate an immune response. It is a regulated form of cell death that can remodel the tumor microenvironment (TME) and activate the immune system, making immunotherapy more effective. This work was designed to identify prognostic gene features associated with ICD in cervical cancer (CC).
METHODS: Based on CC datasets and a set of ICD-related genes obtained from public databases, we first filtered out ICD-related genes unrelated to CC survival using univariate analysis. Subsequently, LASSO regression and multivariate Cox regression analysis were employed to develop prognostic feature genes based on ICD. For the construction and validation of the model, eight genes (CXCL1, IL1B, TNF, YKT6, PDIA3, ROCK1, CXCR3, and CLEC9A) were chosen. A nomogram was created to forecast the prognosis of CC individuals, and Kaplan-Meier curves were utilized to explore the survival disparities among different risk groups of CC individuals.
RESULTS: ssGSEA analysis was employed to investigate immune differences between two risk groups, revealing that the low-risk group exhibited elevated levels of immune cell infiltration, enhanced activation of immune function, and a higher immunophenoscore compared with the other group, which highlighted the relevance of ICD to TME.
CONCLUSIONS: We constructed a prognostic model based on genetic biomarkers of ICD for prognostic prediction of CC patients. Our model demonstrated excellent discriminative and calibration capabilities, providing a valuable tool for prognostic prediction and assessing the potential efficacy of immunotherapy in CC.

Theragnostic biomarkers are still needed to select patients with digestive neuroendocrine neoplasms (NENs) for an optimal management. The PD-1/PD-L1 pathway plays a pivotal role in T cells activation and host immune response to cancer and PD-L1 expression in tumor and/or immune cells is used to identify patients who would benefit of treatment with immune checkpoint inhibitors. However, its role as a biomarker is still unclear in digestive NENs. We investigated PD-L1 expression in 68 well-characterized digestive NENs (32 NETs, 32 NECs and 4 MiNENs) and TPS and CPS scores were calculated. In addition, tumor infiltrating T-lymphocytes and mismatch repair protein expression (MMR) were evaluated. All results were correlated with clinicopathological features. PD-L1 expression was higher in NECs than in NETs: TPS > 1% and/or CPS > 1 were observed in 16% of NETs, 68.8% of NECs and 50% of MiNENs (p: 0.05). The mean TPS score in positive cases was 6.3% in NETs, 16.2% in NECs and 5% in MiNENs. The CPS score was 4.8 in NETs, 8.1 in NECs and 6 in MiNENs. MMR-deficient neoplasms were more frequently observed in NECs than in NETs (p: < 0.05) as well as intra-tumor immune infiltration (p: 0.00001). No correlation between PD-L1 expression and survival or other clinicopathological parameters was observed. Our results suggest that treatment with immune checkpoint inhibitors may have a potential role only in selected cases, mainly in NECs and MiNENs.

Background: Telomere maintenance takes part in the regulation of gastric cancer (GC) pathogenesis and is essential for patients\' clinical features. Though the correlation between a single telomere maintenance-related gene and GC has previously been published, comprehensive exploration and systematic analysis remain to be studied. Our study is aimed at determining telomere maintenance-related molecular subtypes and examining their role in GC. Methods: By analyzing the transcriptome data, we identified three telomere maintenance-associated clusters (TMCs) with heterogeneity in clinical features and tumor microenvironment (TME). Then, we screened five prognostic telomere maintenance-related genes and established corresponding TM scores. Additionally, the expression level and biological function of tubulin beta 6 class V (TUBB6) were validated in GC tissues and cells. Results: TMC1 was correlated with EMT and TGF-beta pathway and predicted low tumor mutation burden (TMB) as well as bad prognostic outcomes. TMC3 was associated with cell cycle and DNA repair. In terms of TMB and overall survival, TMC3 exhibited opposite results against TMC1. Significant heterogeneity was observed between TMCs. TUBB6 was upregulated and could promote GC proliferation, migration, and invasion. Conclusion: Altogether, combining bioinformatics and functional experiments, we identified three molecular subtypes based on telomere maintenance-associated genes in GC, which could bring new ideas and novel biomarkers to the clinic.

Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.

OBJECTIVE: Programmed death receptor ligand-1 (PD-L1) expression and tumor mutational burden (TMB) are approved screening biomarkers for immune checkpoint inhibition (ICI) in advanced triple negative breast cancer. We examined these biomarkers along with characterization of the tumor microenvironment (TME) between breast tumors (BrTs), axillary metastases (AxMs), liver metastases (LvMs), non-axillary lymph node metastases, and non-liver metastases to determine differences related to site of metastatic disease.
METHODS: 3076 unpaired biopsies from breast cancer patients were analyzed using whole transcriptome sequencing and NextGen DNA depicting TMB within tumor sites. The PD-L1 positivity was determined with VENTANA PD-L1 (SP142) assay. The immune cell fraction within the TME was calculated by QuantiSeq and MCP-counter.
RESULTS: Compared to BrT, more LvM samples had a high TMB (≥ 10 mutations/Mb) and fewer LvM samples had PD-L1+ expression. Evaluation of the TME revealed that LvM sites harbored lower infiltration of adaptive immune cells, such as CD4+, CD8+, and regulatory T-cells compared with the BrT foci. We saw differences in innate immune cell infiltration in LvM compared to BrT, including neutrophils and NK cells.
CONCLUSIONS: LvMs are less likely to express PD-L1+ tumor cells but more likely to harbor high TMB as compared to BrTs. Unlike AxMs, LvMs represent a more immunosuppressed TME and demonstrate lower gene expression associated with adaptive immunity compared to BrTs. These findings suggest biopsy site be considered when interpreting results that influence ICI use for treatment and further investigation of immune composition and biomarkers expression by metastatic site.

Background: IQGAP3 plays a crucial role in regulating cell proliferation, division, and cytoskeletal organization. Abnormal expression of IQGAP3 has been linked to various tumors, but its function in glioma is not well understood. Methods: Various methods, including genetic differential analysis, single-cell analysis, ROC curve analysis, Cox regression, Kaplan-Meier analysis, and enrichment analysis, were employed to analyze the expression patterns, diagnostic potential, prognostic implications, and biological processes involving IQGAP3 in normal and tumor tissues. The impact of IQGAP3 on immune infiltration and the immune microenvironment in gliomas was evaluated using immunofluorescence. Additionally, the cBioPortal database was used to analyze copy number variations and mutation sites of IQGAP3. Experimental validation was also performed to assess the effects of IQGAP3 on glioma cells and explore underlying mechanisms. Results: High IQGAP3 expression in gliomas is associated with an unfavorable prognosis, particularly in wild-type IDH and 1p/19q non-codeleted gliomas. Enrichment analysis revealed that IQGAP3 is involved in regulating the cell cycle, PI3K/AKT signaling, p53 signaling, and PLK1-related pathways. Furthermore, IQGAP3 expression may be closely related to the immunosuppressive microenvironment of glioblastoma. BRD-K88742110 and LY-303511 are potential drugs for targeting IQGAP3 in anti-glioma therapy. In vitro experiments showed that downregulation of IQGAP3 inhibits the proliferation and migration of glioma cells, with the PLK1/PI3K/AKT pathway potentially playing a crucial role in IQGAP3-mediated glioma progression. Conclusion: IQGAP3 shows promise as a valuable biomarker for diagnosis, prognosis, and immunotherapeutic strategies in gliomas.

Cancer testis antigen (CTA) Melanoma Antigen Gene A3 (MAGEA3) were overexpressed in multiple tumor types, but the expression pattern of MAGEA3 in the serum of lung adenocarcinoma (LUAD) remains unclear. Clinically derived serum and serum exosome samples were used to assess the mRNA expression of MAGEA3 and MAGEA4 by qRT-PCR, and serum MAGEA3 and MAGEA4 protein expression were evaluated by ELISA in total 133 healthy volunteers\' and 289 LUAD patients\' serum samples. An analysis of the relationship of the mRNA and protein expression of MAGEA3 and MAGEA4 with clinicopathologic parameters was performed and the diagnostic value of MAGEA3 and MAGEA4 was plotted on an ROC curve. In addition, the correlation of MAGEA3 mRNA with infiltrating immune cells was investigated through TIMER, the CIBERSORT algorithm and the TISIDB database. Expression of serum and serum exosome MAGEA3 and MAGEA4 mRNA were significantly higher in LUAD patients than in healthy donors. MAGEA3 mRNA associated with tumor diameter, TMN stage, and NSE in LUAD serum samples, and MAGEA3 mRNA correlated with N stage in serum-derived exosomes, possessing areas under the curve (AUC) of 0.721 and 0.832, respectively. Besides, serum MAGEA3 protein levels were elevated in LUAD patients, and were closely related to stage and NSE levels, possessing AUC of 0.781. Further analysis signified that the expression of MAGEA3 mRNA was positive correlation with neutrophil, macrophages M2, dendritic cells resting, and eosinophilic, but negatively correlated with B cells, plasma cells, CD8 + T cells, CD4 + T cells, Th17 cells, macrophages and dendritic cells. Collectively, our results suggested that the MAGEA3 expression in mRNA and protein were upregulated in LUAD, and MAGEA3 could be used as a diagnostic biomarker and immunotherapy target for LUAD patients.