Identification and validation of dichotomous immune subtypes based on intratumoral immune cells infiltration in clear cell renal cell carcinoma patients

Comprehensive multi-omics analysis of histone acetylation modulators identifies ASH1L as a novel aggressive marker for osteosarcoma

BACKGROUND

Osteosarcoma, a highly malignant bone tumor prevalent in children and adolescents, continues to have poor long-term survival rates, particularly in metastatic cases. While histone acetylation dysregulation has been implicated in cancer progression, the role of histone acetylation modification-related proteins (HAMRPs) in osteosarcoma immune infiltration and prognosis remains unclear.

METHODS

The expression patterns, prognostic implications, and clinical correlations of HAMRPs in osteosarcoma were analyzed using the TARGET, GEO, TISCH, and HPA databases. The effectiveness of HAMRPs in predicting the immune landscape of osteosarcoma was confirmed using CIBERSORT, ssGSEA, and ESTIMATE algorithms. The study employed GSEA analysis, wound healing assay, Transwell, and western blot to explore the role and regulatory mechanism of the key gene ASH1L in osteosarcoma progression.

RESULTS

Two distinct histone acetylation modification patterns were identified, showing significant differences in survival, clinical features, and immune landscape. Comprehensive clinical correlation analysis and Kaplan-Meier analysis of all HAMRPs used for two subtypes revealed that higher ASH1L expression was found in metastatic osteosarcoma cases and indicated poorer survival outcomes. In vitro experiments confirmed that ASH1L promoted osteosarcoma metastasis and epithelial-mesenchymal transition via the AKT/mTOR pathway. Additionally, an ASH1L-derived risk model was developed to aid personalized clinical decisions.

CONCLUSIONS

This study elucidates the prognostic and immunological significance of HAMRPs and highlights ASH1L as a novel aggressive marker in osteosarcoma.

Combined protein and transcriptomics identifies DCTPP1 as a putative biomarkers for predicting immunotherapy responsiveness in gastric cancer patients

This study aimed to screen the changes after overexpression of dCTP pyrophosphatase 1 (DCTPP1) in human gastric adenocarcinoma cells (AGS) cells by proteome and transcriptome sequencing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to explore the functional significance of the differentially expressed DCTPP1 in gastric cancer (GC). Cell Counting Kit-8 (CCK-8) assay was used to detect the proliferation of cells. Western blot was used to detect the expression of proteins. A total of 28 genes that were significantly associated with DCTPP1 overexpression and had prognostic value were screened by Cox regression analysis. The results of gene set enrichment analysis showed that the genomes of patients with subtype A exhibited significant enrichment in pathways such as DNA repair, pyrimidine synthesis, and glucose metabolism. The tumor immune dysfunction and exclusion and The Cancer Immunome Atlas databases showed that patients with type A GC were better candidates for immunotherapy than patients with type B GC. Furthermore, the CCK-8 assay indicated significantly enhanced proliferative activity after overexpressing DCTPP1 in AGS cells, corroborating the findings from the bioinformatic analysis. The data suggest a potential association between DCTPP1 expression and both the prognosis of GC patients and the efficacy of immunotherapy. These findings offer valuable insights for the potential optimization of therapeutic strategies in gastric cancer.

Disulfidptosis, a novel regulated cell death to predict survival and therapeutic response in kidney renal clear cell carcinoma

BACKGROUND

Metabolic regulation of cell death has become a potential therapeutic target for kidney renal clear cell carcinoma (KIRC), which is distinguished by notable heterogeneity and significant immune infiltration. Disulfidptosis, a recently identified form of cell death, has gained prominence in antitumor immunity. This research aims to investigate the correlation between disulfidptosis and prognosis of KIRC, while also exploring the possibility of predicting therapeutic response by disulfidptosis-associated genes (DAGs).

METHODS

We sourced clinical data and RNA sequence of KIRC from the Cancer Genome Atlas Database. Employing unsupervised clustering based on 23 DAGs, we further identified key differentially expressed genes (DEGs) between clusters to construct a DAG prognostic signature. A nomogram was developed and validated to predict clinical outcome of KIRC. Finally, we examined immune cell infiltration, tumor mutational burden, immunotherapy response, and sensitivity to drugs in high and low-risk groups.

RESULTS

Two distinct KIRC patient clusters were successfully stratified using the 23-DAG-related prognostic signature, comprising 11 key genes. This resulted in a robust risk model with strong predictive accuracy for overall survival. The nomogram, incorporating DAG-based risk scores, age, and pM stage, exhibited excellent predictive performance. The high-risk group displayed increased immune cell infiltration and tumor mutational burden, while the low-risk group showed heightened sensitivity to immunotherapies and targeted treatments.

CONCLUSION

This study established a robust DAG-based risk model for KIRC, highlighting its significant correlation with the immune landscape and therapeutic responses. Novel disulfidptosis-related biomarkers revealed distinct immune profiles, drug sensitivities, and immunotherapy potentials among KIRC patients.

A Comprehensive Analysis Revealing BUB1B as a Potential Prognostic and Immunological Biomarker in Lung Adenocarcinoma

BUB1B, a member of the spindle assembly checkpoint family known as BUB1 mitotic checkpoint serine/threonine kinase B, has been associated with the promotion of tumor progression. Nevertheless, its specific contributions to tumorigenesis remain largely unexplored. This study seeks to offer a systematic and comprehensive analysis of the role of BUB1B in the progression of various cancers, with a particular focus on lung adenocarcinoma, utilizing a range of databases. We investigated BUB1B's role in pan-cancer using TCGA data, analyzing it with platforms like HPA, TIMER, TISIDB, GEPIA, cBioPortal, GDC, LinkedOmics, and CancerSEA. Additionally, we assessed BUB1B's impact on lung adenocarcinoma proliferation and migration through CCK-8, wound healing, transwell assays and Western blot analysis. This study found that BUB1B was upregulated in most cancers and was significantly linked to patient prognosis. Its expression correlated with immune cell infiltration and genetic markers of immunomodulators across different cancers. BUB1B was involved in the acute inflammatory response and IgA production pathways but negatively correlated with inflammation in lung adenocarcinoma. Moreover, the siRNA-mediated knockdown of BUB1B resulted in the inhibition of proliferation and migration of lung cancer cells in vitro. This study underscores the potential of BUB1B as a biomarker and a promising therapeutic target for patients with lung adenocarcinoma.

VHL missense mutation delineate aggressive clear cell renal cell carcinoma subtype with favorable immunotherapeutic response

BACKGROUND

von Hippel-Lindau (VHL) harbors the highest mutational frequency in clear cell renal cell carcinoma (ccRCC). Although VHL mutational subtypes exert diverse impacts on the functionality of the VHL protein, the clinical significance of VHL mutational heterogeneity remains largely obscure.

METHODS

This study included a total of 1331 patients with ccRCC from localized data sets, including our localized Zhongshan Hospital (ZSHS) cohort (n=1270) and Zhongshan immune checkpoint blockade cohort (n=61), as well as 525 patients with ccRCC from two publicly available data sets with matched clinical annotation and multidimensional data. According to the putative biological effect, we subclassified VHL mutation into VHL Trunc and VHL Miss. The association of VHL status with clinical outcomes, genomic, oncogenic and immunologic characteristics was further depicted.

RESULTS

VHL Miss ccRCC was associated with reduced survival in the localized ZSHS and The Cancer Genome Atlas cohorts. Clinical benefit from immunotherapy was observed in VHL Miss patients in all immunotherapy cohorts. VHL Miss ccRCC exhibited hyper-activated cell cycle and nuclear factor kappa B (NF-κB) instead of canonical hypoxia inducible factor pathways, which might contribute to its proliferative morphology. Meanwhile, VHL Miss ccRCC featured an inflamed microenvironment with enriched tertiary lymphoid structures.

CONCLUSIONS

VHL Miss mutations delineate an aggressive ccRCC subtype with distinct clinical outcomes, likely attributed to its specific oncogenic, morphologic and immunologic features.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma

BACKGROUND

Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers.

METHODS

10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray.

RESULTS

A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment.

CONCLUSIONS

This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.

Dual-loss of PBRM1 and RAD51 identifies hyper-sensitive subset patients to immunotherapy in clear cell renal cell carcinoma

BACKGROUND

Homologous recombination deficiency (HRD), though largely uncharacterized in clear cell renal cell carcinoma (ccRCC), was found associated with RAD51 loss of expression. PBRM1 is the second most common mutated genes in ccRCC. Here, we introduce a HRD function-based PBRM1-RAD51 ccRCC classification endowed with diverse immune checkpoint blockade (ICB) responses.

METHODS

Totally 1542 patients from four independent cohorts were enrolled, including our localized Zhongshan hospital (ZSHS) cohort and Zhongshan hospital metastatic RCC (ZSHS-mRCC) cohort, The Cancer Genome Atlas (TCGA) cohort and CheckMate cohort. The genomic profile and immune microenvironment were depicted by genomic, transcriptome data and immunohistochemistry.

RESULTS

We observed that PBRM1-loss ccRCC harbored enriched HRD-associated mutational signature 3 and loss of RAD51. Dual-loss of PBRM1 and RAD51 identified patients hyper-sensitive to immunotherapy. This dual-loss subtype was featured by M1 macrophage infiltration. Dual-loss was, albeit homologous recombination defective, with high chromosomal stability.

CONCLUSIONS

PBRM1 and RAD51 dual-loss ccRCC indicates superior responses to immunotherapy. Dual-loss ccRCC harbors an immune-desert microenvironment but enriched with M1 macrophages. Dual-loss ccRCC is susceptible to defective homologous recombination but possesses high chromosomal stability.

BAG3 as a novel prognostic biomarker in kidney renal clear cell carcinoma correlating with immune infiltrates

PURPOSE

BCL-2-associated athanogene 3 (BAG3) is an anti-apoptotic protein that plays an essential role in the onset and progression of multiple cancer types. However, the clinical significance of BAG3 in kidney renal clear cell carcinoma (KIRC) remains unclear.

METHODS

Using Tumor IMmune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) database, we explored the expression, prognostic value, and clinical correlations of BAG3 in KIRC. In addition, immunohistochemistry (IHC) of HKH cohort further validated the expression of BAG3 in KIRC and its impact on prognosis. Gene Set Cancer Analysis (GSCA) was utilized to scrutinize the prognostic value of BAG3 methylation. Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to identify potential biological functions of BAG3 in KIRC. Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between BAG3 expression and immune cell infiltration.

RESULTS

BAG3 mRNA expression and protein expression were significantly downregulated in KIRC tissues compared to normal kidney tissues, associated with adverse clinical-pathological factors and poor clinical prognosis. Multivariate Cox regression analysis indicated that low expression of BAG3 was an independent prognostic factor in KIRC patients. GSEA analysis showed that BAG3 is mainly involved in DNA methylation and the immune-related pathways in KIRC. In addition, the expression of BAG3 is closely related to immune cell infiltration and immune cell marker set.

CONCLUSION

BAG3 might be a potential therapeutic target and valuable prognostic biomarker of KIRC and is closely related to immune cell infiltration.

Identifying endoplasmic reticulum stress-related genes as new diagnostic and prognostic biomarkers in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide, and its incidence is increasing every year. Endoplasmic reticulum stress (ERS) caused by protein misfolding has broad and profound effects on the progression and metastasis of various cancers. Accumulating evidence suggests that ERS is closely related to the occurrence and progression of ccRCC. This study aimed to identify ERS-related genes for evaluating the prognosis of ccRCC.

Methods

Transcriptomic expression profiles were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), and clinical data were downloaded from the TCGA. First, the differentially expressed genes (DEGs) were analyzed using the limma package, and the DEGs related to ERS (ERS-DEGs) were identified from the GeneCards database. Second, a function and pathway enrichment analysis and a Gene Set Enrichment Analysis (GSEA) were performed. Third, a protein-protein interaction (PPI) network was constructed to identify the hub genes, and a gene-micro RNA (miRNA) network and gene-transcription factor (TF) network were established using the hub genes. Finally, a least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to establish a diagnostic model, and a Cox analysis was used to analyze the correlations between the expression of the characteristic genes and the clinical characteristics.

Results

We identified 11 signature genes and established a diagnostic model. Further, the Cox analysis results revealed a correlation between the expression levels of the signature genes and the clinical characteristics. Ultimately, five signature genes (i.e., TNFSF13B, APOL1, COL5A3, and CDH5) were found to be associated with a poor prognosis.

Conclusions

This study suggests that TNFSF13B, APOL1, COL5A3, and CDH5 may have potential as prognostic biomarkers in ccRCC and may provide new evidence to support targeted therapy in ccRCC.

A five-protein prognostic signature with GBP2 functioning in immune cell infiltration of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is of poor clinical outcomes, and currently lacks reliable prognostic biomarkers. By analyzing the datasets of the Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), we established a five-protein prognostic signature containing GBP2, HLA-DRA, ISG15, ISG20 and ITGAX. Our data indicate that this signature was closely correlated with advanced stage, higher pathological grade, and unfavorable survivals in patients with ccRCC. We further functionally characterized GBP2. Overexpression of GBP2 enhanced the phosphorylation of STAT2 and STAT3 to trigger JAK-STAT signaling and promote cell migration and invasion in ccRCC. Treatment of Ruxolitinib, a specific inhibitor of JAK/STAT, attenuated the GBP2-mediated phenotypes. Patients with high GBP2 expression were accompanied with more infiltration of immune cells positively stained with CD3, CD8, CD68, and immune checkpoint markers PD-1 and CTLA4, which was validated by Opal multiplex immunohistochemistry in ccRCC tissues. More CD8 + T cells and CD68 + macrophages were observed in patients expressing high GBP2. Taken together, a five-protein prognostic signature was constructed in our study. GBP2 has an oncogenic role via modulating JAK-STAT signaling and tumor immune infiltration, and thus may serve as a potential therapeutic target in ccRCC.

Dissection of pyroptosis-related prognostic signature and CASP6-mediated regulation in pancreatic adenocarcinoma: new sights to clinical decision-making

Recent studies have indicated that pyroptosis may participate in the regulation of tumorigenesis and immune microenvironment. However, the role of pyroptosis-related genes (PRGs) in pancreatic adenocarcinoma (PAAD) remains unclear. Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA network. The correlation between PRGs and prognosis, immune infiltration, immune checkpoints, and tumor mutational burden was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in PAAD patients. The qRT-PCR, Western blotting, CCK-8, Wound healing, and Transwell assay were applied to examine the role of CASP6 in PANC-1 cell. Thirty-one PRGs were upregulated in PAAD. Functional enrichment analysis revealed that the PRGs were mainly involved in pyroptosis, NOD-like receptor signaling pathway, and response to bacteria. We established a novel 4-gene signature related to PRGs for evaluating the prognosis of PAAD patients. Patients with PAAD in the low-risk group had a better prognosis than those in the high-risk group. The nomogram suggested that the 1-, 3-, and 5-years survival probability exhibited robust predictive performance. Significant correlation was observed between prognostic PRGs and immune infiltration, immune checkpoints, and tumor mutational burden. We first identified the potential competing endogenous RNA regulatory axis in PAAD: lncRNA PVT1/hsa-miR-16-5p/CASP6/CASP8. Moreover, knockdown of CASP6 dramatically inhibited the proliferation, migration, and invasion ability of PANC-1 cell in vitro. In conclusion, CASP6 could be a potential biomarker, promoting the occurrence and progression in PAAD. The lncRNA PVT1/hsa-miR-16-5p/CASP6/CASP8 regulatory axis plays an vital role in regulating the anti-tumor immune responses for PAAD.

Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor, and investigating the immunorelated genes is essential. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, an immunoprognosis model was constructed to identify four hub genes with moderate predictive values for the prognosis of ccRCC patients. These four genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltration could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of three hub genes were associated with tumor progression (P<0.1). In conclusion, four genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

Interaction of RARRES1 with ICAM1 modulates macrophages to suppress the progression of kidney renal clear cell carcinoma

Background

RARRES1 is a tumor suppressor protein, and its expression is suppressed in various tumor cells. However, whether it participates in the immune response in kidney renal clear cell carcinoma (KIRC) is unknown, and the defined mechanism is not clear. Therefore, the mechanism of RARRES1 in KIRC is worthy of investigation.

Methods

We analysed the expression and function of RARRES1 with The Cancer Genome Atlas (TCGA) database. The Kaplan–Meier curve was adopted to estimate survival. RARRES1-correlated genes were obtained from the UALCAN database and subjected to Gene Ontology (GO) enrichment and protein–protein interaction (PPI) network analyses. The correlation analysis between tumor-infiltrating immune cells and selected genes were performed with TIMER database. We also investigated the possible function of RARRES1 in KIRC by coculturing Caki-1 cells with THP-1 cells. Immunofluorescence assay was performed to study the RARRES1 expression in difference grade KIRC tissues.

Results

The expression of RARRES1 was negatively correlated with survival in KIRC patients. The GO biological process term most significantly enriched with the RARRES1-correlated genes was regulation of cell adhesion. ICAM1, which exhibited a relatively highest correlation with RARRES1, is positively correlated with the infiltration level of macrophages. RARRES1 could enhance the expression of ICAM1 in Caki-1 cells and then induce the activation of M1 THP-1 cells to decrease the viability and induce the apoptosis of Caki-1 cells.

Conclusion

RARRES1 plays an antitumor role by promoting ICAM1 expression and inducing the activation of M1 macrophages. We offer insights into the molecular mechanism of KIRC and reveal a potential therapeutic target.

Calreticulin as a prognostic biomarker and correlated with immune infiltrate in kidney renal clear cell carcinoma

Background: Calreticulin (CALR) has been investigated in several malignant diseases and is associated with immune-cell infiltration. However, the prognostic value of CALR in kidney renal clear cell carcinoma (KIRC) is still unknown. Methods: Based on the computational analysis, data from 530 KIRC cases and 72 normal kidney samples from The Cancer Genome Atlas (TGCA-KIRC) database were analyzed in this study. The expression of CALR mRNA in pan-cancer and immune infiltrates was analyzed using the Tumor Immune Estimation Resource (TIMER) database. The CALR protein expression was obtained from the UALCAN and Human Protein Atlas (HPA) databases. Survival, functional, and statistical analyses were conducted using R software. Results: The CALR expression was higher in KIRC cases than in normal kidneys. A high CALR expression was correlated with TNM stage, pathological stage, and histological grade. Kaplan-Meier survival analysis showed that a high CALR expression was associated with poor overall survival, disease-specific survival, and progression-free interval. Gene set enrichment analysis (GSEA) indicated that CALR was enriched in IL-6 and IL-2 signaling, interferon signaling, TNF signaling, inflammatory response, apoptosis, and the p53 pathway. CALR is correlated with immune-infiltrating cells. A significant correlation was observed between CALR expression and immunomodulators. Conclusion: We identified CALR as a prognostic biomarker of KIRC. Meanwhile, the CALR expression associated with immune infiltration indicated that CALR might be a potential immunotherapy target for patients with KIRC.

A comprehensive analysis of the prognostic value and immune infiltration of low expression DBT in clear cell renal cell carcinoma

Background: Although DBT is strongly associated with human tumorigenesis and progression through a variety of pathways, the role of DBT in clear cell renal cell carcinoma (ccRCC) has not been well established.

Materials and methods: The Cancer Genome Atlas (TCGA)-Kidney renal clear cell carcinoma (KIRC) databset provides RNA sequencing data and clinicopathological information on ccRCC. The Gene Expression Omnibus (GEO) database was used to validate the DBT expression levels, and qPCR was used to examine the DBT expression in renal cancer cell lines and ccRCC tissue samples from our centre. In parallel, DBT protein expression was explored in the Human Protein Atlas (HPA) database, and western blotting and immunohistochemistry of renal cancer cell lines and ccRCC tissues validated the results. Additionally, the diagnostic and prognostic value of DBT was comprehensively evaluated by receiver operating characteristic (ROC) curves, univariate and multivariate Cox regression analyses, and Kaplan‒Meier survival analysis. The protein‒protein interaction (PPI) network based on the STRING website, Gene Ontology (GO) analysis, Kyoto Gene and Genome Encyclopedia (KEGG) analysis and gene set enrichment analysis (GSEA) further provided a landscape of the molecular mechanisms of DBT in ccRCC. Finally, the TIMER 2.0, GEPIA and TISIDB websites were used to understand the relationship between DBT and immune characteristics.

Results: The mRNA expression and protein expression of DBT were significantly downregulated in ccRCC tissues relative to normal tissues, which was associated with poor clinical outcomes. DBT has an encouraging discriminatory power for ccRCC and is an independent prognostic factor for ccRCC patients. Mechanistically, DBT is mainly involved in the regulation of immune-related signalling pathways in ccRCC; it is associated with a variety of immune infiltrating cells and immune checkpoints.

Conclusion: DBT is a tumour suppressor gene in ccRCC and could be used as a new biomarker for diagnostic and prognostic purposes, and it is associated with immune infiltration in ccRCC.

DHRS7 is an immune-related prognostic biomarker of KIRC and pan-cancer

Renal clear cell carcinoma (KIRC) is one malignancy whose development and prognosis have been associated with aberrant DHRS7 expression. However, the catalytic activity and pathophysiology of KIRC are poorly understood, and no sensitive tumor biomarkers have yet been discovered. In our study, we examined the significant influence of DHRS7 on the tumor microenvironment (TME) and tumor progression using an overall predictable and prognostic evaluation approach. We found novel cancer staging, particularly in KIRC, as well as potential therapeutic drugs out of 27 drug sensitivity tests. Using Perl scripts, it was possible to determine the number of somatic mutations present in 33 tumors, as well as the relative scores of 22 immune cells using CIBERSORT, the relationship between immune infiltration and differential expression using TCGA data, and the immune microenvironment score using the estimate technique. Our results show that DHRS7 is abnormally expressed in pan-cancer patients, which influences their survival. Low DHRS7 expression was associated with late clinical stages and a low survival rate in KIRC patients, suggesting a poor prognosis and course of treatment, in HNSG, MESO, and KIRC patients. We also found that DHRS7 was associated with TMB and MSI in certain tumors. Using KIRC as an example, we discovered a negative correlation between DHRS7 expression and immunological assessments, suggesting that this substance might be used as a tumor biomarker.

Construction and validation of a ferroptosis-related long noncoding RNA signature in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is characterized by the accumulation of lipid-reactive oxygen species. Ferroptosis, due to the lipid peroxidation, has been reported to be strongly correlated with tumorigenesis and progression. However, the functions of the ferroptosis process in ccRCC remain unclear.

Methods

After sample cleaning, data integration, and batch effect removal, we used the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases to screen out the expression and prognostic value of ferroptosis-related lncRNAs and then performed the molecular subtyping using the K-means method. Then, the functional pathway enrichment and immune microenvironment infiltration between the different clusters were carried out. The results showed a significant difference in immune cell infiltration between the two clusters and the associated marker responded to individualized differences in treatment. Then, least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a prognostic signature based on 5 lncRNAs. This signature could accurately predicted patient prognosis and served as an independent clinical risk factor. We then combined significant clinical parameters in multivariate Cox regression and the prognostic signature to construct a clinical predictive nomogram, which provides appropriate guidance for predicting the overall survival of ccRCC patients.

Results

The prognostic differentially expressed ferroptosis-related LncRNAs (DEFRlncRNAs) were found, and 5 lncRNAs were finally used to establish the prognostic signature in the TCGA cohort, with subsequently validation in the internal and external cohorts. Moreover, we conducted the molecular subtyping and divided the patients in the TCGA cohort into two clusters showing differences in Hallmark pathways, immune infiltration, immune target expression, and drug therapies. Differences between clusters contributed to individualizing treatment. Furthermore, a nomogram was established to better predict the clinical outcomes of the ccRCC patients.

Conclusions

Our study conducted molecular subtyping and established a novel predictive signature based on the ferroptosis-related lncRNAs, which contributed to the prognostic prediction and individualizing treatment of ccRCC patients.

Endoplasmic Reticulum Stress-Related Signature Predicts Prognosis and Drug Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. The maximum number of deaths associated with kidney cancer can be attributed to ccRCC. Disruption of cellular proteostasis results in endoplasmic reticulum (ER) stress, which is associated with various aspects of cancer. It is noteworthy that the role of ER stress in the progression of ccRCC remains unclear. We classified 526 ccRCC samples identified from the TCGA database into the C1 and C2 subtypes by consensus clustering of the 295 ER stress-related genes. The ccRCC samples belonging to subtype C2 were in their advanced tumor stage and grade. These samples were characterized by poor prognosis and malignancy immune microenvironment. The upregulation of the inhibitory immune checkpoint gene expression and unique drug sensitivity were also observed. The differentially expressed genes between the two clusters were explored. An 11-gene ER stress-related prognostic risk model was constructed following the LASSO regression and Cox regression analyses. In addition, a nomogram was constructed by integrating the clinical parameters and risk scores. The calibration curves, ROC curves, and DCA curves helped validate the accuracy of the prediction when both the TCGA dataset and the external E-MTAB-1980 dataset were considered. Moreover, we analyzed the differentially expressed genes common to the E-MTAB-1980 and TCGA datasets to screen out new therapeutic compounds. In summary, our study can potentially help in the comprehensive understanding of ER stress in ccRCC and serve as a reference for future studies on novel prognostic biomarkers and treatments.

Identification of a differentiation-related prognostic nomogram based on single-cell RNA sequencing in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is a kidney cancer that is originated from the lined proximal convoluted tubule, and its major histological subtype is clear cell RCC (ccRCC). This study aimed to retrospectively analyze single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, to explore the correlation among the evolution of tumor microenvironment (TME), clinical outcomes, and potential immunotherapeutic responses in combination with bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database, and to construct a differentiation-related genes (DRG)-based prognostic risk signature (PRS) and a nomogram to predict the prognosis of ccRCC patients. First, scRNA-seq data of ccRCC samples were systematically analyzed, and three subsets with distinct differentiation trajectories were identified. Then, ccRCC samples from TCGA database were divided into four DRG-based molecular subtypes, and it was revealed that the molecular subtypes were significantly correlated with prognosis, clinicopathological features, TME, and the expression levels of immune checkpoint genes (ICGs). A DRG-based PRS was constructed, and it was an independent prognostic factor, which could well predict the prognosis of ccRCC patients. Finally, we constructed a prognostic nomogram based on the PRS and clinicopathological characteristics, which exhibited a high accuracy and a robust predictive performance. This study highlighted the significance of trajectory differentiation of ccRCC cells and TME evolution in predicting clinical outcomes and potential immunotherapeutic responses of ccRCC patients, and the nomogram provided an intuitive and accurate method for predicting the prognosis of such patients.

Pan-Cancer Analysis Predicts the Immunological and Prognostic Role of ZC3H12C in KIRC

ZC3H12C is an important member of the CCCH-zinc finger protein family and is mainly involved in host immune and inflammatory diseases. However, its abnormal expression and prognostic value in cancer have not yet been established. Through comparative analysis of the Cancer Genome Atlas (TCGA) database, we found that ZC3H12C is the most relevant to the prognosis, grade, and stage of renal clear cell carcinoma (ccRCC) across 33 cancers. With the help of patient transcription and clinical data from the TCGA and GEO (GSE53757, GSE36895) databases, we determined that in the immune environment of patients with ccRCC, ZC3H12C was clearly negatively correlated with Tregs and was significantly positively correlated with monocytes. In addition, protein phosphorylation and DNA methylation analysis also showed that ZC3H12C negatively regulates the role of cancer in ccRCC. Our research may provide new insights into ccRCC immunotherapy and bring forth novel biomarkers and therapeutic targets.

ASCL2 Affects the Efficacy of Immunotherapy in Colon Adenocarcinoma Based on Single-Cell RNA Sequencing Analysis

Colon adenocarcinoma (COAD) is one of the leading causes of cancer-associated deaths worldwide. Patients with microsatellite instability-high (MSI-H) tumors were shown to highly benefit from immune checkpoint inhibitors (ICIs) than patients with microsatellite stable (MSS) tumors. Furthermore, the infiltration of immune cells and the expression of cancer stem cells (CSCs) in COAD were associated with the anti-tumor immune response. However, the potential mechanisms showing the relationship between microsatellite instability and CSCs or tumor-infiltrating immune cells (TIICs) have not been elucidated. Accumulating evidence reveals that achaete-scute family bHLH transcription factor 2 (ASCL2) plays a crucial role in the initiation and progression of COAD and drug resistance. However, the specific biological functions of ASCL2 in COAD remain unknown. In this study, we performed weighted gene co-expression network analysis (WGCNA) between MSS and MSI-H subsets of COAD. The results revealed that ASCL2 was a potential key candidate in COAD. Subsequently, the single-cell RNA-seq revealed that ASCL2 was positively associated with CSCs. Further, ASCL2 was shown to indirectly affect tumor immune cell infiltration by negatively regulating the expression of DUSP4. Finally, we inferred that the immunotherapy-sensitive role of ASCL2/DUSP4 axis on COAD is partly attributed to the activation of WNT/β-catenin pathway. In conclusion, this study revealed that ASCL2 was positively correlated to CSCs and tumor immune infiltration in COAD. Therefore, ASCL2 is a promising predictor of clinical responsiveness to anti-PD-1/PD-L1 therapy in COAD.

OIP5 Is a Novel Prognostic Biomarker in Clear Cell Renal Cell Cancer Correlating With Immune Infiltrates

Opa interacting protein 5 (OIP5), overexpressed in some types of human cancers, has been reported to be associated with the carcinogenesis of human cancer. However, its contribution to cancer immunity remains unknown. Furthermore, the relationship between OIP5 and cancer immunity remains uncertain. In our research, we explored the different expression of OIP5 between 539 ccRCC and 72 normal renal tissues base on TCGA data set. We analyzed the associations between OIP5 expression with ccRCC progression and survival. Next, we compared immune cell profiles in cancer tissues and normal tissues in the Cancer Genome Atlas (TCGA) ccRCC cohort. We found that the level of immune cell infiltration was correlated with the copy number of OIP5 gene in ccRCC. The effect of OIP5 on immune activity was verified by Gene Set Enrichment Analysis of RNA-seq data from 32 ccRCC cell lines in the public database. Moreover, a pathway enrichment analysis of 49 OIP5-associated immunomodulators demonstrated the involvement of the T cell receptor signaling pathway, the JAK-STAT signaling pathway, the NF-kappa B signaling pathway and the primary immunodeficiency pathway. In addition, using OIP5-associated immunomodulators, we constructed multiple-gene risk prediction signatures using the Cox regression model. Our results provided insights into the role of OIP5 in tumor immunity and revealed that OIP5 may be a potential immunotherapeutic target for ccRCC. Designated immune signature is a promising prognostic biomarker in ccRCC.

m6A Methylation Patterns and Tumor Microenvironment Infiltration Characterization in Clear-Cell Renal Cell Carcinoma

Increasing evidence suggests the essential regulation of RNA N6-methyladenosine (m6A) modification in carcinogenesis and immune response. Nevertheless, the potential impacts of these modifications on the tumor microenvironment (TME) immune cell infiltration characteristics in clear-cell renal cell carcinoma (ccRCC) remain unclear. Utilizing a consensus clustering algorithm, we determined three m6A modification patterns and identified three m6A-related gene clusters among 569 ccRCC samples, which were associated with different biological functions and clinical outcomes. Thereafter, the m6A score was constructed using m6A-associated signature genes to accurately exploit the m6A modification patterns within individual tumors. The m6A score was further demonstrated to be noticeably related to ccRCC prognosis. In addition, the m6A score was found to be strongly correlated with tumor mutational burden (TMB), microsatellite instability, immune infiltration, immune checkpoint expression, and immunotherapy response, which was also validated in the pan-cancer analyses. Our findings thoroughly elucidated that m6A modification contributes to tumor microenvironment immune-infiltrating characteristics and prognosis in ccRCC. Assessing the m6A modification patterns of individual patients with ccRCC will offer novel insights into TME infiltration and help develop more effective treatment strategies.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8⁺ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8⁺ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8⁺ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8⁺ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8⁺ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8⁺ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.

Identification of a competing endogenous RNA network related to immune signature in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a fatal cancer of the urinary system. Long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) involving the ccRCC progression. However, the relationship between the ceRNA network and immune signature is largely unknown. In this study, the ccRCC-related gene expression profiles retrieved from the TCGA database were used first to identify the differentially expressed genes through differential gene expression analysis and weighted gene co-expression network analysis. The interaction among differentially expressed lncRNAs, miRNAs, and mRNAs were matched using public databases. As a result, a ceRNA network was developed that contained 144 lncRNAs, 23 miRNAs, as well as 62 mRNAs. Four of 144 lncRNAs including LINC00943, SRD5A3-AS1, LINC02345, and U62317.3 were identified through LASSO regression and Cox regression analyses, and were used to create a prognostic risk model. Then, the ccRCC samples were divided into the high- and low-risk groups depending on their risk scores. ROC curves, Kaplan-Meier survival analysis, and the survival risk plots indicated that the predictive performance of our developed risk model was accurate. Moreover, the CIBERSORT algorithm was used to measure the infiltration levels of immune cells in the ccRCC samples. The further genomic analysis illustrated a positive correlation between most immune checkpoint blockade-related genes and the risk score. In conclusion, the present findings effectually contribute to the comprehensive understanding of the ccRCC pathogenesis, and may offer a reference for developing novel therapeutic and prognostic biomarkers.

TNFSF13B and PPARGC1A expression is associated with tumor-infiltrating immune cell abundance and prognosis in clear cell renal cell carcinoma

Growing evidence suggests that the tumor microenvironment (TME) plays crucial roles in tumor progression and treatment efficacy in clear cell renal cell carcinoma (ccRCC), which typically has a poor prognosis due to high relapse and metastasis rates. We comprehensively analyzed ccRCC RNA-sequencing data from The Cancer Genome Atlas (TCGA) database to identify candidate prognostic TME-related genes involved in ccRCC. We used the ESTIMATE and CIBERSORT algorithms to estimate the proportions of immune cells, stromal cells, and tumor-infiltrating immune cells (TICs) in the TME in ccRCC samples from 539 patients. By examining the intersection of the differentially expressed genes (DEGs) obtained by Cox regression analysis and protein-protein interaction network, we identified five overlapping DEGs (IGLL5, MZB1, HSD11B1, TNFSF13B, and PPARGC1A). Further analysis revealed that TNFSF13B expression was elevated in ccRCC tumor tissues and negatively associated with overall survival. PPARGC1A expression exhibited the opposite patterns. Immunohistochemical analysis of 35 paired ccRCC and adjacent normal tissues confirmed the in-silico results. Gene set enrichment analysis revealed that genes in the groups with high TNFSF13B and PPARGC1A expression were enriched mainly in immune-related activities. In the group with low PPARGC1A expression, genes were enriched in metabolic pathways. CIBERSORT analysis of TIC proportions revealed that Tregs and CD8 T-cell abundance correlated positively with TNFSF13B expression, but negatively with PPARGC1A expression. These findings demonstrate that TNFSF13B and PPARGC1A are prognostic predictors and possible therapeutic targets in ccRCC.

N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| > 0.7, p < 0.001) and univariable Cox regression analysis (p < 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients.

Methods

The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics.

Results

According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage.

Conclusion

We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

TLR3 Serves as a Prognostic Biomarker and Associates with Immune Infiltration in the Renal Clear Cell Carcinoma Microenvironment

Background

Clear cell renal cancer (KIRC) is one of the most common cancers globally, with a poor prognosis. TLRs play a vital role in anticancer immunity and the regulation of the biological progress of tumour cells. However, the precise role of TLRs in KIRC is still ambiguous.

Methods

Various bioinformatics analysis and clinical validation of tissues were performed to evaluate the prognostic value of TLRs and their correlation with immune infiltration in KIRC.

Results

The expression of TLR2/3/7/8 was increased at both mRNA and protein levels in KIRC. TLRs in KIRC were involved in the activation of apoptosis, EMT, RAS/MAPK, and RTK pathways, as well as the inhibition of the cell cycle and the hormone AR pathway. Drug sensitivity analysis revealed that high expression of TLR3 and low expression of TLR7/9/10 were resistant to most of the small molecules or drugs from CTRP. Enrichment analyses showed that TLRs were mainly involved in innate immune response, toll-like receptor signalling pathway, NF-kappa B signalling pathway, and TNF signalling pathway. Furthermore, a high-level TLR3 expression was associated with a favourable prognosis in KIRC. Validation research further confirmed that TLR3 expression was increased in KIRC tissues, and high TLR3 levels were associated with poor overall survival. Moreover, TLR3 in KIRC showed a positive association with an abundance of immune cells, including B-cells, CD4+ T-cells, CD8+ T-cells, macrophage, neutrophils, and dendritic cells, and the expression of the immune biomarker sets. Several TLR3-associated kinase, miRNA, or transcription factor targets were also identified in KIRC.

Conclusion

Our results indicate that TLR3 serves as a prognostic biomarker and associated with immune infiltration in KIRC. This work lays a foundation for further studies on the role of TLR3 in the carcinogenesis and progression of KIRC.

Identification of the Prognosis Value and Potential Mechanism of Immune Checkpoints in Renal Clear Cell Carcinoma Microenvironment

Background

Kidney Renal Clear Cell Carcinoma (KIRC) is one of the most prevalent types of cancer worldwide. KIRC has a poor prognosis and, to date, immunotherapy based on immune checkpoints is the most promising treatment. However, the role of immune checkpoints in KIRC remains ambiguous.

Methods

Bioinformatics analyses and qRT-PCR were performed to explore and further confirm the prognostic value of immune checkpoint genes and their correlation with immune infiltration in KIRC samples.

Results

The expression of the immune checkpoint genes CD274, PDCD1LG2, HAVCR2, CTLA4, TIGFT, LAG3, and PDCD1 was upregulated in KIRC tissues. These genes were involved in the activation of the apoptosis pathway in KIRC. Low expression of CD274 and HAVCR2 and high expression of CTLA4 were associated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of KIRC patients. The univariate and multivariate analyses revealed that CTLA4, HAVCR2, age, pTNM stage, and tumor grade were independent factors affecting the prognosis of KIRC patients. A predictive nomogram demonstrated that the calibration plots for the 3‐year and 5‐year OS probabilities showed good agreement compared to the actual OS of KIRC patients. The expression of CTLA4 and HAVCR2 were positively associated with immune cell infiltration, immune biomarkers, chemokines, and chemokine receptors. Moreover, miR-20b-5p was identified as a potential miRNA target of CTLA4 in KIRC.

Conclusion

Our study clarified the prognostic value of several immune checkpoint regulators in KIRC, revealing a CTLA4/miR-20b-5p axis in the control of immune cell infiltration in the tumor microenvironment.

Accumulation of CD45RO+CD8+ T cells is a diagnostic and prognostic biomarker for clear cell renal cell carcinoma

Renal cell carcinoma is characterized by high immunogenicity and infiltration of immune cells. CD45RO+CD8+ T cells are well known as a critical role in host defense of the immune environment. However, their role in clear cell renal carcinoma (ccRCC) remains unknown. To elucidate the clinical importance of CD45RO+CD8+ T cells in ccRCC as well as its underlying mechanism, we analyzed several types of peripheral immune cells from 274 patients with ccRCC who have received radical or partial nephrectomy and 350 healthy people. Flow cytomety assays showed there was no significant difference in the proportions of CD8+ T cells and its subtypes other than CD45RO+/CD45RA+CD8+ cells. Both gene and protein expression levels of CD45RO in ccRCC tissues were decreased. CD45RO+CD8+ T cells showed increased proliferative abilities but decreased apoptotic abilities through MAPK signaling activation in ccRCC. High expression level of CD45RO+CD8+ T cells inhibited ccRCC progression, including proliferation, invasion, as well as autophagy of ccRCC through many signaling pathways. Bioinformatics and immunohistochemical chip analysis measured gene and protein levels of CD45RO and other related proteins. The combination of UCHL1, HMGB3, and CD36 has diagnostic value in ccRCC and is able to predict prognosis. Collectively, CD45RO+CD8+ T cells play a critical role in ccRCC progression and may be regarded as clinical indicators.

TYK2 is a prognostic biomarker and associated with immune infiltration in the lung adenocarcinoma microenvironment

BACKGROUND

Lung adenocarcinoma (LUAD) remains a major disease with high morbidity and mortality. The Janus kinases (JAKs) play a significant part in cellular biological process, inflammation and immunity. The role of JAK family in LUAD is still ambiguous.

METHODS

Various bioinformatics web portals were applied to explore the prognostic value of JAK family and their correlation with immune infiltration in LUAD.

RESULTS

JAK1/2 was downregulated, whereas JAK3/TYK2 was upregulated in patients with LUAD compared with the healthy controls in subgroup analyses based on gender, age, smoking habits, cancer stage, TP53 mutation status, and nodal metastasis status. Drug sensitivity indicated that low expression of JAK3 and TYK2 were resistant to most of the small molecules or drugs. High TYK2 expression was associated with favorable overall survival and relapse free survival in LUAD. Moreover, univariate and multivariate analysis revealed that clinical stage, lymphatic node metastasis and TYK2 expression were the independent factors affecting the prognosis of LUAD patients. TYK2 expression in LUAD patients was positively associated with the abundance of immune cells (B cells, CD8+ T cells, CD4+ T cells, neutrophils, and dendritic cells) and immune biomarker sets. Moreover, TYK2 was mainly involved in RNA binding, transcriptional mis-regulation in cancer and cell cycles. We also identified several TYK2-associated miRNA or transcription factor targets in LUAD.

CONCLUSION

Our results indicated that TYK2 was a biomarker and associated with prognosis and immune infiltration in LUAD, laying a foundation for further study about the role of TYK2 in the carcinogenesis and progression of LUAD.

Identification of molecular heterogeneity of hepatocellular carcinoma based on immune gene expression signatures

Although various molecular subtypes of hepatocellular carcinoma (HCC) have been investigated, most of these studies identify HCC subtype based on genomic profiling. Few studies have investigated the classification based on immune signatures, and none have classified HCC based on Immune activation and immunosuppressive. We performed immune gene expression of tumor tissue in 374 HCC patients from The Cancer Genome Atlas (TCGA) database and used unsupervised consensus clustering to stratify tumors. We then used HCC patients from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) as replication datasets. Based on the expression of 782 immune-related genes, HCC was stratified into four distinct immune subtypes. Tumors in one cluster (high immune activation; high-IA) indicate a higher level of Immune activation, which was characterized by higher anti-tumor immunity, higher pro-tumor immune-suppressive cell types, higher fractions of CD8+ T cells and M0 Macrophages compared with other subtypes. The high-IA also presents higher cancer-related hallmark signatures, such as epithelial-mesenchymal transition (EMT), angiogenesis, and apoptosis. We also found subpopulations of regulatory and exhaustion T lymphocyte were characterized by an opposite trend in high-IA, though samples in high-IA response to immunotherapy with better survival. The comparison of the immune profile in tumor and normal tissue indicates the activation of immune responses which only occurred in high-IA patients, while we conducted comparison of cirrhosis and non-cirrhosis tumor immune signatures, immune response activation was almost occurred in high-IA, but some of immune responses occurred in low-IA (low immune activation).

Immune classification of clear cell renal cell carcinoma

Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01) compared to the patients with tumors for all groups of tumors except group 3.

Immune classification of clear cell renal cell carcinoma

Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value [Formula: see text]). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value [Formula: see text]), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value [Formula: see text]). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value [Formula: see text]) compared to the patients with tumors for all groups of tumors except group 3.

Identification of subtype specific biomarkers of clear cell renal cell carcinoma using random forest and greedy algorithm

Suitable biomarkers can be good indicator for cancer subtype. To find biomarkers that can accurately distinguish clear cell renal cell carcinoma (ccRCC) subtypes, we first determined ccRCC subtypes based on the expression of mRNA, miRNA and lncRNA, named clear cell type 1 (ccluster1) and 2 (ccluster2), using three unsupervised clustering algorithms. Besides being associated with the expression pattern derived from the single type of RNA, the differences between subtypes are relevant to the interactions between RNAs. Then, based on ceRNA network, the optimal combination features are selected using random forest and greedy algorithm. Further, in survival-related sub-ceRNA, competing gene pairs centering on miR-106a, miR-192, miR-193b, miR-454, miR-32, miR-98, miR-143, miR-145, miR-204, miR-424 and miR-1271 can also well identify ccluster1 and ccluster2 with prediction accuracy over 92%. These subtype-specific features potentially enhance the accuracy with which machine learning methods predict specific ccRCC subtypes. Simultaneously, the changes of miR-106 and OIP5-AS1 affect cell proliferation and the prognosis of ccluster1. The changes of miR-145 and FAM13A-AS1 in ccluster2 have an effect on cell invasion, apoptosis, migration and metabolism function. Here miR-192 displays a unique characteristic in both subtypes. Two subtypes also display notable differences in diverse pathways. Tumors belonging to ccluster1 are characterized by Fc gamma R-mediated phagocytosis pathway that affects tissue remodeling and repair, whereas those belonging to ccluster2 are characterized by EGFR tyrosine kinase inhibitor resistance pathway that participates in regulation of cell homeostasis. In conclusion, identifying these gene pairs can shed light on therapeutic mechanisms of ccRCC subtypes.

IGLL5 is correlated with tumor-infiltrating immune cells in clear cell renal cell carcinoma

Renal cell carcinomas (RCCs) account for about 90% of renal tumors, and their major histological subtype is ccRCC (clear cell RCC). Increasing evidence has indicated that the tumor microenvironment plays a significant role in the occurrence and development of ccRCC. In this study, we used ESTIMATE and CIBERSORT computational methods to calculate the proportion of immune and stromal components and the rate of TICs (tumor‐infiltrating immune cells) in 539 ccRCC samples from The Cancer Genome Atlas database. By examining the intersection of the differentially expressed genes obtained by the protein–protein interaction network and Cox regression analysis, we identified only one overlapping gene: IGLL5 (immunoglobulin lambda‐like polypeptide 5). We report that IGLL5 expression is correlated with TICs. Furthermore, our immunoinfiltration analyses revealed that three types of TIC are positively correlated with IGLL5 expression. IGLL5 may have potential as a prognostic biomarker of ccRCC.

ACE2 Is a Prognostic Biomarker and Associated with Immune Infiltration in Kidney Renal Clear Cell Carcinoma: Implication for COVID-19

Background

KIRC is one of the most common cancers with a poor prognosis. ACE2 was involved in tumor angiogenesis and progression in many malignancies. The role of ACE2 in KIRC is still ambiguous.

Methods

Various bioinformatics analysis tools were investigated to evaluate the prognostic value of ACE2 and its association with immune infiltration in KIRC.

Results

ACE2 was shown to be downregulated in KIRC at the mRNA and protein level. Low expression of ACE2 protein in KIRC patients was observed in subgroup analyses based on gender, age, weight, tumor grade, and cancer stage. Upregulation of ACE2 in KIRC was associated with a favorable prognosis. ACE2 mRNA expression showed a positive correlation with the abundance of immune cells (B cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells) and the level of immune markers of different immune cells in KIRC. ACE2 expression could affect, in part, the immune infiltration and the advanced cancer stage. Moreover, enrichment analysis revealed that ACE2 in KIRC were mainly involved in translation factor activity, immunoglobulin binding, metabolic pathways, transcriptional misregulation in cancerous cells, cell cycle, and ribosomal activity. Several ACE2-associated kinases, miRNA, and transcription factor targets in KIRC were also identified.

Conclusion

ACE2 was downregulated in KIRC and served as a prognostic biomarker. It was also shown to be associated with immune infiltration.

The Clinical Relevance and Function of Krüppel-Like Factor 16 in Breast Cancer

Background

Krüppel-like factor 16 (KLF16), a member of the KLF family, is involved in metabolism and regulation of the endocrine system and has emerging roles in tumor progression. However, the expression of KLF16 and its role in breast cancer are elusive.

Methods

We investigated the expression and prognostic value of KLFs in breast cancer using data acquired from the TCGA BRCA dataset and the Kaplan–Meier plotter dataset. The protein levels of KLF16 in breast specimens were detected by immunohistochemistry (IHC). KLF16 silencing using shRNAs was performed to explore the effects of KLF16 on breast cancer cell growth, migration, and invasion. The expression of EMT markers in cells manipulated for KLF16 expression was assessed by Western blotting.

Results

Using publicly available dataset and specimens from breast cancer patients, we found that the expression levels of KLF16 were significantly higher in tumor tissues and that high levels of KLF16 were associated with poor prognosis in breast cancer patients. Moreover, KLF16 expression levels had relation to several clinicopathological parameters of breast cancer, including the molecular subtype and histological grade. Importantly, knockdown of KLF16 dramatically suppressed cell proliferation both in vitro and in vivo. Also, KLF16 deletion impaired migration, and invasion in breast cancer cells, and suppressed epithelial–mesenchymal transition (EMT).

Conclusion

Our results suggest that KLF16 has important oncogenic functions in breast cancer and that the expression levels of KLF16 are associated with prognosis in breast cancer patients. Our findings also suggest that KLF16 is involved in proliferation, migration, and invasion in breast cancer cells. Thus, KLF16 might be a promising prognostic marker and a therapeutic target for breast cancer.