Tumor hypoxia in immune infiltration and prognosis of bladder cancer.

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

Constructing a prognostic model for hepatocellular carcinoma based on bioinformatics analysis of inflammation-related genes.

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Exploring the prognostic significance of immunogenic cell death-related genes as risk biomarkers in cervical cancer.

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. CONCLUSION: 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.

[Bioinformatic analysis of CCND2 expression in papillary thyroid carcinoma and its impact on immune infiltration].

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). CONCLUSION: CCND2 overexpression is closely correlated with tumor progression and immune cell infiltration in PTC patients..

SpatialCells: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data.

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.

PD-L1 expression, tumor-infiltrating lymphocytes, and mismatch repair proteins status in digestive neuroendocrine neoplasms: exploring their potential role as theragnostic and prognostic biomarkers.

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.

Cross-talk of Three Molecular Subtypes of Telomere Maintenance Defines Clinical Characteristics and Tumor Microenvironment in Gastric Cancer.

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.

IQGAP3 promotes the progression of glioma as an immune and prognostic marker.

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.

Evaluation of markers of immunity in different metastatic immune microenvironments suggests more suppression within breast to liver metastases in breast cancer.

PURPOSE: 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.

The potential of DEirlncRNAs: A novel approach to predict glioblastoma prognosis.

Background: Despite tremendous evolution in therapies, the prognosis of glioblastoma (GBM) remains grim, which calls for innovative approaches to optimize chemotherapy efficacy and predict risk. Methods: The transcriptome and clinical data of GBM were acquired from the Cancer Genome Atlas (TCGA), followed by the identification of differentially expressed immune-related long noncoding RNAs (DEirlncRNAs) with Pearson correlation and limma packet analyses. Survival-related DEirlncRNA pairs were screened with univariate Cox proportional hazard regression. Prognostic markers were obtained, and risk scores were calculated with Lasso regression and multivariate Cox risk regression analyses. The association of the prognostic risk model with immune cell infiltration was evaluated by comprehensively analyzing tumor-infiltrating immune cells with TIMER, XCELL, CIBERSORT, QUANTISEQ, and EPIC. Differences in half-maximal inhibitory concentration (IC50) values between the high- and low-risk groups were assessed with the Wilcoxon signed-rank test. Results: A total of 276 DEirlncRNAs were identified, followed by the visualization of their expression patterns. Two prognosis-related DEirlncRNA pairs were screened, with high accuracy and reliability. The constructed prognostic risk model effectively distinguished between high- and low-risk patients, and significant differences were observed in survival outcomes between the high- and low-risk groups. Furthermore, risk scores were associated with tumor-infiltrating immune cells and DEirlncRNA expression. Additionally, the risk model had a correlation with the effectiveness of commonly used chemotherapeutic agents, providing clues into potential treatment responses. Conclusions: In our study, a novel signature was constructed with paired DEirlncRNAs (regardless of their expression), which holds significant clinical predictive value and is a potential breakthrough for personalized management of GBM.

Cancer testis antigen MAGEA3 in serum and serum-derived exosomes serves as a promising biomarker in lung adenocarcinoma.

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.

Tumor-infiltrating immune cells and survival in head and neck squamous cell carcinoma: a retrospective computational study.

The immune infiltration profiles of the tumor microenvironment have effects on the prognosis of head and neck squamous cell carcinoma (HNSCC). Whereas, HNSCC is a heterogeneous group of tumors, but past work has not taken this into consideration. Herein, we investigate the associations between survival and the function of immune cells in different tumorigenic sites of HNSCC. 1149 samples of HNSCC were collected from publicly accessible databases. Based on gene expression data, CIBERSORTx was applied to determine the proportion of 22 immune cell subpopulations. In the Cox regression model, the associations between overall survival, disease-free survival, and immune cells were examined, modeling gene expression and immune cell proportion as quartiles. Consensus cluster analysis was utilized to uncover immune infiltration profiles. Regardless of tumor sites, CD8+ T cells and activated CD4 memory T cells were associated with favorable survival, while eosinophils were the opposite. The survival of the hypopharynx, oral cavity, and larynx subsites was somewhat affected by immune cells, while the survival of the oropharynx subsite potentially was the most impacted. High expression of TIGIT, CIITA, and CXCR6 was linked to better survival, mainly in the oropharynx subsite. Immune cell clusters with four distinct survival profiles were discovered, of which the cluster with a high CD8+ T cell content had a better prognosis. The immune-infiltration pattern is related to the survival of HNSCC to varying degrees depending on the tumor sites; forthcoming studies into immune-mediated infiltration profiles will lay the groundwork for treating HNSCC with precision therapy.

Elevated of NDUFA4L2 expression in colon adenocarcinoma is correlated with an unfavorable prognosis and increased immune cell infiltration.

Background: Colon adenocarcinoma (COAD) is a prevalent malignancy worldwide, yet, its underlying pathogenesis and genetic characteristics are still unclear. Previous studies have suggested that NADH dehydrogenase 1 alpha subcomplex subunit 4-like 2 (NDUFA4L2) may affect tumor progression across various cancers. However, this effect on COAD has rarely been reported. Thus, this study investigated NDUFA4L2's prognostic and diagnostic relevance and explored its potential connection with immune cell infiltration in COAD. Methods: To achieve this, RNA sequencing data from Cancer Genome Atlas (TCGA) was analyzed to assess NDUFA4L2's prognostic value in COAD, and factors relevant to the prognosis of COAD, including NDUFA4L2, were scrutinized using Kaplan-Meier analyses as well as univariate and multivariate Cox regression. A nomogram model was created to project prognosis based on the results of multivariate Cox analysis. Furthermore, gene set enrichment analysis (GSEA) was employed to pinpoint key NDUFA4L2-related pathways, and single-sample GSEA (ssGSEA) on TCGA data was employed to investigate the connections of NDUFA4L2 with cancer immune infiltrations. Results: Our findings revealed significant associations of high NDUFA4L2 expression with poor overall survival, progression-free interval, and disease-specific survival of COAD patients. GSEA indicated close links of NDUFA4L2 with several signaling pathways implicated in tumorigenesis, including extracellular matrix receptor interaction, the intestinal immune network for immunoglobulin A production, natural killer (NK) cell-mediated cytotoxicity, pathways in cancer, cell adhesion molecules, mitogen-activated protein kinase signaling pathway, Hedgehog signaling pathway, transforming growth factor beta signaling pathway, and chemokine signaling pathway. Additionally, ssGSEA identified a positive link between increased NDUFA4L2 expression and higher infiltration degree of various immune cells, such as immature dendritic cells, macrophages, NK cells and dendritic cells. Conclusions: Collectively, our findings demonstrate the association of increased NDUFA4L2 expression with adverse prognosis and heightened immune cell infiltration in COAD patients.

MRI-based Machine Learning Radiomics Can Predict CSF1R Expression Level and Prognosis in High-grade Gliomas.

The purpose of this study is to predict the mRNA expression of CSF1R in HGG non-invasively using MRI (magnetic resonance imaging) omics technology and to evaluate the correlation between the established radiomics model and prognosis. We investigated the predictive value of CSF1R in the Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) database. The Support vector machine (SVM) and the Logistic regression (LR) algorithms were used to create a radiomics_score (Rad_score), respectively. The effectiveness and performance of the radiomics model was assessed in the training (n = 89) and tenfold cross-validation sets. We further analyzed the correlation between Rad_score and macrophage-related genes using Spearman correlation analysis. A radiomics nomogram combining the clinical factors and Rad_score was constructed to validate the radiomic signatures for individualized survival estimation and risk stratification. The results showed that CSF1R expression was markedly elevated in HGG tissues, which was related to worse prognosis. CSF1R expression was closely related to the abundance of infiltrating immune cells, such as macrophages. We identified nine features for establishing a radiomics model. The radiomics model predicting CSF1R achieved high AUC in training (0.768 in SVM and 0.792 in LR) and tenfold cross-validation sets (0.706 in SVM and 0.717 in LR). Rad_score was highly associated with tumor-related macrophage genes. A radiomics nomogram combining the Rad_score and clinical factors was constructed and revealed satisfactory performance. MRI-based Rad_score is a novel way to predict CSF1R expression and prognosis in high-grade glioma patients. The radiomics nomogram could optimize individualized survival estimation for HGG patients.

MDM4 was associated with poor prognosis and tumor-immune infiltration of cancers.

MDM4 is one of the MDM protein family and is generally recognized as the key negative regulator of p53. As a cancer-promoting factor, it plays a non-negligible role in tumorigenesis and development. In this article, we analyzed the expression levels of MDM4 in pan-cancer through multiple databases. We also investigated the correlations between MDM4 expression and prognostic value, immune features, genetic mutation, and tumor-related pathways. We found that MDM4 overexpression is often accompanied by adverse clinical features, poor prognosis, oncogenic mutations, tumor-immune infiltration and aberrant activation of oncogenic signaling pathways. We also conducted transcriptomic sequencing to investigate the effect of MDM4 on transcript levels in colon cancer and performed qPCR to verify this. Finally, we carried out some in vitro experiments including colony formation assay, chemoresistance and senescence-associated ß-galactosidase activity assay to study the anti-tumor treatment effect of small molecule MDM4 inhibitor, NSC146109. Our research confirmed that MDM4 is a prognostic biomarker and potential therapeutic target for a variety of malignancies.

Exploration of Key Genes Combining with Immune Infiltration Level andTumor Mutational Burden in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a lethal malignancy due to its heterogeneity and aggressive behavior. Recently, somatic mutations and tumor cell interactions with the surrounding tumor immune microenvironment (TIME) have been reported to participate in HCC carcinogenesis and predict HCC progression. In this study, we aimed to investigate the association between tumor mutational burden (TMB) and TIME in HCC. Additionally, we sought to identify differentially expressed genes (DEGs) associated with HCC prognosis and progression. METHODS: The expression, clinical, and mutational data were downloaded from the cancer genome atlas (TCGA) database. The immune infiltration levels and TMB levels of the HCC samples were estimated and the samples were divided into immune cluster (ICR)-1 and 2 based on immune infiltration score and high and low TMB groups based on TMB score. Thereafter, differential gene expression analysis was conducted to identify the DEGs in the ICR1/2 and high/low TMB groups, and the intersecting DEGs were selected. Thereafter, Cox regression analysis was performed on 89 significant DEGs, among which 19 were associated with prognosis. These 19 DEGs were then used to construct a prognostic model based on their expression levels and regression coefficients. Thereafter, we analyzed the DEGs in mutant and wildtype TP53 HCC samples and identified high BCL10 and TRAF3 expression in the mutant TP53 samples. BCL10 and TRAF3 expression was detected by real-time quantitative reverse transcription PCR and immunohistochemistry, and their clinical correlation, biological function, and immune infiltration levels were analyzed by chi-square analyses, Gene Set Enrichment Analysis (GSEA), and "ssGSEA", respectively. RESULTS: The results of our study revealed that immune infiltration level was correlated with TMB and that they synergistically predicted poor prognosis of HCC patients. DEGs enriched in immune-related pathways could serve as indicators of immunotherapy response in HCC. Among these DEGs, BCL10 and TRAF3 were highly expressed in HCC tissues, especially in the mutant TP53 group, and they co-operatively exhibited immunological function, thereby affecting HCC progression and prognosis. CONCLUSION: In this study, we identified BCL10 and TRAF3 as potential prognostic indicators in HCC patients. Additionally, we found that BCL10 and TRAF3 influence TMB and TIME in HCC patients and can be used for the development of immune-based therapies for improving the long-term survival of HCC patients.

[High expression of ANKRD6 is an indicator for poor prognosis of colon adenocarcinoma].

OBJECTIVE: To explore the expression of ANKRD6 in colon adenocarcinoma (COAD) and its implications for prognosis and treatment of COAD. METHODS: We investigated the differential expression of ANKRD6 in 20 pairs of COAD and adjacent tissues using immunohistochemistry and in colon cancer cell lines and normal colon cells using real-time quantitative PCR. Gene expression matrices, immune infiltration data, and clinical information of 521 COAD patients and 41 normal tissues were obtained from the TCGA database for analyzing the association of ANKRD6 expression with clinicopathological features, gene set enrichment, and immune infiltration in COAD using R software. The prognostic factors of COAD were evaluated using univariate and multivariate Cox regression and Kaplan-Meier analyses, and a prognostic nomogram containing ANKRD6 was constructed. Western blotting, CCK-8 assay, scratch assay and Transwell assay were performed to assess the effects of ANKRD6 knockdown on biological activities of COAD cells. RESULTS: ANKRD6 was highly expressed in COAD cell lines and upregulated in COAD tissues with higher malignancy (P<0.05). Increased ANKRD6 expression was significantly correlated with decreased overall survival and disease-free survival of COAD patients (P<0.05). Univariate and multivariate Cox regression analyses indicated that ANKRD6 expression was significantly correlated with the overall survival rate of COAD patients (P<0.05). The constructed prognostic nomogram showed a C-index value of 0.739 and effectively predicted the 1-, 3-, and 5-year survival of the patients. ANKRD6 expression was positively correlated with immune infiltration of macrophages (P<0.05) and negatively correlated with Th17 cells and other immune cell infiltration (P<0.05). Bioinformatic analysis suggested that ANKRD6 was mainly enriched in Wnt, vascular endothelial growth factor receptor, and calcium signaling pathways in COAD. In cultured COAD cells, ANKRD6 knockdown significantly suppressed cell proliferation, migration, and invasion (P<0.05). CONCLUSION: High ANKRD6 expression is an indicator for poor prognosis of COAD, and ANKRD6 may serve as a potential biomarker as well as a therapeutic target for diagnosis and treatment of COAD.

HAGLR, A Long Non-coding RNA of Potential Tumor Suppressive Function in Clear Cell Renal Cell Carcinoma: Diagnostic and Prognostic Implications.

Research works suggested the role of long non-coding RNAs (lncRNAs) in pathogenesis of clear cell renal cell carcinoma (ccRCC). lncRNA HAGLR is studied in several malignancies, but not in ccRCC. From The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset, we analyzed molecular alterations of HAGLR and constructed a competitive endogenous RNA (ceRNA) network with related miRNAs and mRNAs. Gene Ontology analysis was done to identify important pathways enriched with HAGLR recovered mRNAs. Clinical importance of HAGLR and related mRNAs was assessed and, the impact of selected mRNA-encoding genes on tumor immune infiltration was studied using TIMER. HAGLR expression was reduced in ccRCC than in normal kidneys, and correlated significantly with gene promoter methylation. Low HAGLR level in tumors showed diagnostic potency, and was associated with clinicopathological parameters (stage/grade/metastasis) and poor patient survival. The HAGLR-associated ceRNA network constituted 13 miRNAs and 23 mRNAs differentially expressed in the TCGA-KIRC dataset. From HAGLR recovered mRNA-encoding genes, we developed a 5-gene (PAQR5, ARHGAP24, HABP4, PDLIM5, and RPS6KA2) prognostic signature in the training dataset and validated it in testing as well as entire datasets. The expression level of signature genes showed negative correlation with tumor infiltration of immune cells having adverse impact on ccRCC prognosis and also with tumor derived chemokines facilitating the infiltration. In conclusion, HAGLR seemed to play a tumor suppressive role in ccRCC. HAGLR and associated gene signature may have implementation in improving existing prognostic measure and developing effective immunotherapeutic strategies for ccRCC.

PIK3CD correlates with prognosis, epithelial-mesenchymal transition and tumor immune infiltration in breast carcinoma.

BACKGROUND: Breast carcinoma (BRCA) is one of the most common, fatal, and aggressive cancers, with increasing morbidity that has a major impact on human health. PIK3CD appears to have important roles in the beginning and advancement of various forms of human cancer, according to mounting data. However,the particular role and mechanism of PIK3CD in BRCA remains not fully identified. METHODOLOGY: The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/ ), Genotype-Tissue Expression (GTEx) data and the UCSC Xena browser ( https://xenabrowser.net ) data were used in this study's initial pan-cancer analysis of PIK3CD expression and prognosis. Circular RNAs (circRNAs) that regulated the expression of PIK3CD were subsequently found using a combination of in silico investigations of expression, correlation, and survival. Measurements of PIK3CD expression and an analysis of the in vitro function of PIK3CD in BRCA cells were performed using real-time RT-PCR, Western blotting and Transwell assays. RESULTS: In BRCA GLI2, RAB32, LAMB1, MGAT2, ITGA8, CHF, COL6A3 and PRRX1-miR-30b-5p axis was identified as the most likely upstream CircRNA-related route of PIK3CD. PIK3CD was correlated with the expression of EMT markers. The PIK3CD cDNA improved the capacity for invasion and migration. The expression of PIK3CD was linked to some of the m1A/m5C/m6A regulators. Additionally, it was discovered that the expression of PIK3CD was found to be highly connected to the expression of immunological checkpoints, immune cell biomarkers, and tumor immune cell invasion. CONCLUSIONS: Our findings reveal that PIK3CD expression is associated with prognosis, EMT, and tumor immune infiltration in BRCA patients.

Integrative analysis of TROAP with molecular features, carcinogenesis, and related immune and pharmacogenomic characteristics in soft tissue sarcoma.

Soft tissue sarcoma (STS) is an uncommon malignancy that often carries a grim prognosis. Trophinin-associated protein (TROAP) is augmented in a variety of tumors and can affect tumor proliferation. Nevertheless, the prognostic value and specific functions of TROAP in STS are still vague. Herein, we display that TROAP exhibits an augmented trend in STS, and its elevation correlates with a poor prognosis of STS. Furthermore, its reduction is related to increased immune cell infiltration, enhanced stroma, and elevation of immune activation. Meanwhile, the TROAP-derived genomic signature is validated to predict patient prognosis, immunotherapy, and drug response reliably. A nomogram constructed based on age, metastatic status, and a TROAP-derived risk score of an STS individual could be used to quantify the survival probability of STS. In addition, in vitro experiments have demonstrated that TROAP is overexpressed in STS, and the downregulation of TROAP could affect the proliferation, migration, metastasis, and cell cycle of STS cells. In summary, the TROAP expression is elevated in STS tissues and cells, which is related to the poor prognosis and malignant biological behaviors of STS. It could act as a potential prognostic biomarker for diagnosis and treatment of STS.