CD31, EDNRB and TSPAN7 are promising prognostic markers in clear-cell renal cell carcinoma revealed by genome-wide expression analyses of primary tumors and metastases

Comprehensive analysis of MAPK genes in the prognosis, immune characteristics, and drug treatment of renal clear cell carcinoma using bioinformatic analysis and Mendelian randomization

Mitogen-activated protein kinase (MAPK) signalling is vitally important in tumour development and progression. This study is the first to comprehensively analyse the role of MAPK-family genes in the progression, prognosis, immune-cell infiltration, methylation, and potential therapeutic value drug candidates in ccRCC. We identified a novel prognostic panel of six MAPK-signature genes (MAP3K12, MAP3K1, MAP3K5, MAPK1, MAPK8, MAPK9), and introduced a robust MAPK-signature risk model for predicting ccRCC prognosis. Model construction, evaluation, and external validation using datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database demonstrated its stability, as well as high sensitivity and specificity. Enrichment analysis suggested the participation of immune-mediated mechanism in MAPK dysregulation in ccRCC. Immune-infiltration analysis confirmed the relationship and revealed that the MAPK-signature risk model might stratify immunotherapy response in ccRCC, which was verified in drug sensitivity analysis and validated in external ccRCC immunotherapy dataset (GSE67501). Potential therapeutic drug predictions for key MAPKs using DSigDB, Network Analyst, CTD, and DGIdb were subsequently verified by molecular docking with AutoDock Vina and PyMol. Mendelian randomization further demonstrated the possibilities of the MAPK-signature genes as targets for therapeutic drugs in ccRCC. Methylation analysis using UALCAN and MethSurv revealed the participation of epigenetic modifications in dysregulation and survival difference of MAPK pathway in ccRCC. Among the key MAPKs, MAP3K12 exhibited the highest significance, indicating its independent prognostic value as single gene in ccRCC. Knockout and overexpression validation experiments in vitro and in vivo found that MAP3K12 acted as a promoter of tumour progression in RCC, suggesting a pivotal role for MAP3K12 in the proliferation, migration, and invasion of RCC cells. Our findings proposed the potential of MAPK-signature genes as biomarkers for prognosis and therapy response, as well as targets for therapeutic drugs in ccRCC.

Unveiling the unique role of TSPAN7 across tumors: a pan-cancer study incorporating retrospective clinical research and bioinformatic analysis

BACKGROUND

TSPAN7 is an important factor in tumor progression. However, the precise function of TSPAN7 and its role in pan-cancer are not clear.

METHODS

Based on Xinhua cohort incorporating 370 patients with kidney neoplasm, we conducted differential expression analysis by immunohistochemistry between tumor and normal tissues, and explored correlations of TSPAN7 with patients' survival. Subsequently, we conducted a pan-cancer study, and successively employed differential expression analysis, competing endogenous RNA (ceRNA) analysis, protein-protein interaction (PPI) analysis, correlation analysis of TSPAN7 with clinical characteristics, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. Last but not least, gene set enrichment analysis was applied to identify enriched pathways of TSPAN7.

RESULTS

In Xinhua cohort, TSPAN7 expression was significantly up-regulated (P-value = 0.0019) in tumor tissues of kidney neoplasm patients. High TSPAN7 expression was associated with decreases in overall survival (OS) (P-value = 0.009) and progression-free survival (P-value = 0.009), and it was further revealed as an independent risk factor for OS (P-value = 0.0326, HR = 5.66, 95%CI = 1.155-27.8). In pan-cancer analysis, TSPAN7 expression was down-regulated in most tumors, and it was associated with patients' survival, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. The ceRNA network and PPI network of TSPAN7 were also constructed. Last but not least, the top five enriched pathways of TSPAN7 in various tumors were identified.

CONCLUSION

TSPAN7 served as a promising biomarker of various tumors, especially kidney neoplasms, and it was closely associated with tumor purity, tumor genomics, tumor immunology, and drug sensitivity in pan-cancer level.

Prognostic Significance of VAV3 Gene Variants and Expression in Renal Cell Carcinoma

Renal cell carcinoma (RCC) is characterized by high mortality and morbidity rates. Vav guanine nucleotide exchange factors (VAVs), crucial for signal transduction between cell membrane receptors and intracellular mediators, have been implicated in carcinogenesis. However, their potential prognostic value in RCC remains unclear. The impact of 150 common VAV polymorphisms on RCC risk and survival was investigated in a cohort of 630 individuals. Publicly available gene expression datasets were utilized to analyze VAV gene expression in relation to patient outcomes. The VAV3 rs17019888 polymorphism was significantly associated with RCC risk and overall survival after adjusting for false discovery rates. Expression quantitative trait loci analysis revealed that the risk allele of rs17019888 is linked to reduced VAV3 expression. Analysis of 19 kidney cancer gene expression datasets revealed lower VAV3 expression in RCC tissues compared to normal tissues, with higher expression correlating with better prognosis. Gene set enrichment analysis demonstrated that VAV3 negatively regulates the ubiquitin-proteasome system, extracellular matrix and membrane receptors, inflammatory responses, matrix metalloproteinases, and cell cycle pathways. Furthermore, elevated VAV3 expression was associated with increased infiltration of B cells, macrophages, and neutrophils into the RCC tumor microenvironment. Our findings suggest that VAV3 gene variants influence RCC risk and survival, contributing to a favorable prognosis in RCC.

Single-cell sequencing reveals novel proliferative cell type: a key player in renal cell carcinoma prognosis and therapeutic response

Renal cell carcinoma (RCC) is characterized by a variety of subtypes, each defined by unique genetic and morphological features. This study utilizes single-cell RNA sequencing to explore the molecular heterogeneity of RCC. A highly proliferative cell subset, termed as "Prol," was discovered within RCC tumors, and its increased presence was linked to poorer patient outcomes. An artificial intelligence network, encompassing traditional regression, machine learning, and deep learning algorithms, was employed to develop a Prol signature capable of predicting prognosis. The signature demonstrated superior performance in predicting RCC prognosis compared to other signatures and exhibited pan-cancer prognostic capabilities. RCC patients with high Prol signature scores exhibited resistance to targeted therapies and immunotherapies. Furthermore, the key gene CEP55 from the Prol signature was validated by both proteinomics and quantitative real time polymerase chain reaction. Our findings may provide new insights into the molecular and cellular mechanisms of RCC and facilitate the development of novel biomarkers and therapeutic targets.

Tetraspanin proteins in membrane remodeling processes

Membrane remodeling is a fundamental cellular process that is crucial for physiological functions such as signaling, membrane fusion and cell migration. Tetraspanins (TSPANs) are transmembrane proteins of central importance to membrane remodeling events. During these events, TSPANs are known to interact with themselves and other proteins and lipids; however, their mechanism of action in controlling membrane dynamics is not fully understood. Since these proteins span the membrane, membrane properties such as rigidity, curvature and tension can influence their behavior. In this Review, we summarize recent studies that explore the roles of TSPANs in membrane remodeling processes and highlight the unique structural features of TSPANs that mediate their interactions and localization. Further, we emphasize the influence of membrane curvature on TSPAN distribution and membrane domain formation and describe how these behaviors affect cellular functions. This Review provides a comprehensive perspective on the multifaceted function of TSPANs in membrane remodeling processes and can help readers to understand the intricate molecular mechanisms that govern cellular membrane dynamics.

Development of prognostic signatures and risk index related to lipid metabolism in ccRCC

Background

Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment.

Methods

We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives.

Results

Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens.

Conclusion

Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.

PTK6: An emerging biomarker for prognosis and immunotherapeutic response in clear cell renal carcinoma (KIRC)

Kidney renal clear cell carcinoma (KIRC), one of the most prevalent form of kidney carcinoma, is highly aggressive cancer known for significant immune infiltration and high mortality rates. The absence of sensitivity to traditional therapy has spurred the search for new treatments. Protein Tyrosine Kinase 6 (PTK6) is implicated in promoting cancer growth, spread, and metastasis. Our review of The Cancer Genome Atlas database revealed PTK6 overexpression in KIRC, though its specific role in this cancer type was unclear. We investigated PTK6's cancer-promoting roles in KIRC using the database and confirmed our findings with patient-derived tissues. Our analysis showed that elevated PTK6 expression is linked to worse outcomes and higher levels of immune infiltration. It also correlates positively with neo-antigens (NEO) and DNA ploidy changes in KIRC. This research delves into PTK6's role in KIRC development, suggesting PTK6 as a possible biomarker for prognosis and treatment in KIRC.

The role of Tetraspanins in digestive system tumor development: update and emerging evidence

Digestive system malignancies, including cancers of the esophagus, pancreas, stomach, liver, and colorectum, are the leading causes of cancer-related deaths worldwide due to their high morbidity and poor prognosis. The lack of effective early diagnosis methods is a significant factor contributing to the poor prognosis for these malignancies. Tetraspanins (Tspans) are a superfamily of 4-transmembrane proteins (TM4SF), classified as low-molecular-weight glycoproteins, with 33 Tspan family members identified in humans to date. They interact with other membrane proteins or TM4SF members to form a functional platform on the cytoplasmic membrane called Tspan-enriched microdomain and serve multiple functions including cell adhesion, migration, propagation and signal transduction. In this review, we summarize the various roles of Tspans in the progression of digestive system tumors and the underlying molecular mechanisms in recent years. Generally, the expression of CD9, CD151, Tspan1, Tspan5, Tspan8, Tspan12, Tspan15, and Tspan31 are upregulated, facilitating the migration and invasion of digestive system cancer cells. Conversely, Tspan7, CD82, CD63, Tspan7, and Tspan9 are downregulated, suppressing digestive system tumor cell metastasis. Furthermore, the connection between Tspans and the metastasis of malignant bone tumors is reviewed. We also summarize the potential role of Tspans as novel immunotherapy targets and as an approach to overcome drug resistance. Finally, we discuss the potential clinical value and therapeutic targets of Tspans in the treatments of digestive system malignancies and provide some guidance for future research.

Comprehensive analysis reveals dual biological function roles of EpCAM in kidney renal clear cell carcinoma

Background

Epithelial cell adhesion molecule (EpCAM), a well-established marker for circulating tumor cells, plays a crucial role in the complex process of cancer metastasis. The primary objective of this investigation is to study EpCAM expression in pan-cancer and elucidate its significance in the context of kidney renal clear cell carcinoma (KIRC).

Methods

Data obtained from the public database was harnessed for the comprehensive assessment of the EpCAM expression levels and prognostic and clinicopathological correlations in thirty-three types of cancer. EpCAM was validated in our own KIRC sequencing and immunohistochemical cohorts. Subsequently, an in-depth exploration was conducted to scrutinize the interrelationship between EpCAM and various facets, including immune cells, immune checkpoints, and chemotherapy drugs. We employed Cox regression analysis to identify prognostic immunomodulators associated with EpCAM, which were subsequently utilized in the development of a prognostic model. The model was validated in our own clinical cohort and public datasets, and compared with 137 published models. The role of EpCAM in KIRC was explored by biological function experiments in vitro.

Results

While EpCAM exhibited pronounced overexpression across a wide spectrum of cancer types, a notable reduction was observed in KIRC tissues. As grade increased, EpCAM expression decreased. EpCAM expression decreased in patients without metastasis. EpCAM mRNA and protein levels were used as independent, favorable prognostic factors in patients with KIRC in our own cohort. The expression of EpCAM exhibited strong associations with immune-related pathways, demonstrating an inverse correlation with the majority of immune cell types. Immune checkpoint inhibitors exert better therapeutic effects on patients with low EpCAM expression. In addition, EpCAM can be used as a drug resistance indicator and guide the clinical medication of patients with KIRC. A robust model, which had good predictive accuracy and applicability, showed significant superiority over other models. Importantly, EpCAM played the dual roles of promoting proliferation and resisting metastasis in KIRC.

Conclusion

In the context of KIRC, EpCAM assumes a surprising dual role, where it not only facilitates cell proliferation but also exerts resistance against the metastatic process. EpCAM serves as a standalone prognostic marker for patients with KIRC, and related models can also effectively predict prognosis. These discoveries offer novel perspectives on the functional significance of EpCAM in the context of KIRC.

USP31 serves as a potential biomarker for predicting prognosis and immune responses for clear cell renal cell carcinoma via single-cell and bulk RNA-sequencing

BACKGROUND

Currently, there is no research available on the prognosis, potential effect and therapeutic value of USP31 in clear cell renal cell carcinoma (ccRCC). To address this gap, the present study aimed to shed light on its potential roles and possible mechanisms in ccRCC.

METHODS

R software was utilized to conduct bioinformatics analyses with the data derived from The Cancer Genome Atlas (i.e. KIRC) and Gene Expression Omnibus datasets. The expression of USP31 in ccRCC was validated by a PCR. The independent prognostic ability of USP31 was evaluated by Cox regression analysis. We conducted gene set enrichment analysis (GSEA) to explore the potential USP31-related pathways. We also discussed the relationships between USP31 and immunity, by predicting its possible upstream transcription factors (TFs) by ChEA3.

RESULTS

In ccRCC, USP31 demonstrated a high level of expression and this increased expression was correlated with a poor prognosis (p < 0.05). Through univariate and multivariate Cox regression analysis, USP31 was identified as an independent prognostic factor for ccRCC (p < 0.05). Furthermore, eight USP31-related pathways were identified by GSEA (p < 0.05). Moreover, USP31 was found to be associated with microsatellite instability, tumor microenvironment, a variety of immune cells and immune checkpoints and immune infiltration (p < 0.05). Additionally, Patients with high USP31 expression in ccRCC were shown to have better curative effects after immunotherapy (p < 0.05). Finally, we found that AR, USF1, MXI1 and CLOCK could be the potential upstream TFs of USP31.

CONCLUSIONS

USP31 could serve as a potential biomarker for predicting both prognosis and immune responses, revealing its potential mechanisms of TF-USP31 mRNA networks in ccRCC.

Construction and validation of a metabolism-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer

Tumor Metabolism is strongly correlated with prognosis. Nevertheless, the prognostic and therapeutic value of metabolic-associated genes in BCa patients has not been fully elucidated. First, in this study, metabolism-related differential expressed genes DEGs with prognostic value in BCa were determined. Through the consensus clustering algorithm, we identified two molecular clusters with significantly different clinicopathological features and survival prognosis. Next, a novel metabolism-related prognostic model was established. Its reliable predictive performance in BCa was verified by multiple external datasets. Multivariate Cox analysis exhibited that risk score were independent prognostic factors. Interestingly, GSEA enrichment analysis of GO, KEGG, and Hallmark gene sets showed that the biological processes and pathways associated with ECM and collagen binding in the high-risk group were significantly enriched. Notely, the model was also significantly correlated with drug sensitivity, immune cell infiltration, and immunotherapy efficacy prediction by the wilcox rank test and chi-square test. Based on the 7 immune infiltration algorithm, we found that Neutrophils, Myeloid dendritic cells, M2 macrophages, Cancer-associated fibroblasts, etc., were more concentrated in the high-risk group. Additionally, in the IMvigor210, GSE111636, GSE176307, or our Truce01 (registration number NCT04730219) cohorts, the expression levels of multiple model genes were significantly correlated with objective responses to anti-PD-1/anti-PD-L1 immunotherapy. Finally, the expression of interested model genes were verified in 10 pairs of BCa tissues and para-carcinoma tissues by the HPA and real-time fluorescent quantitative PCR. Altogether, the signature established and validated by us has high predictive power for the prognosis, immunotherapy responsiveness, and chemotherapy sensitivity of BCa.

Spatial heterogeneity of tumor microenvironment influences the prognosis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is an immunologically and histologically diverse tumor. However, how the structural heterogeneity of tumor microenvironment (TME) affects cancer progression and treatment response remains unclear. Hence, we characterized the TME architectures of ccRCC tissues using imaging mass cytometry (IMC) and explored their associations with clinical outcome and therapeutic response.

METHODS

Using IMC, we profiled the TME landscape of ccRCC and paracancerous tissue by measuring 17 markers involved in tissue architecture, immune cell and immune activation. In the ccRCC tissue, we identified distinct immune architectures of ccRCC tissue based on the mix score and performed cellular neighborhood (CN) analysis to subdivide TME phenotypes. Moreover, we assessed the relationship between the different TME phenotypes and ccRCC patient survival, clinical features and treatment response.

RESULTS

We found that ccRCC tissues had higher levels of CD8⁺ T cells, CD163^- macrophages, Treg cells, endothelial cells, and fibroblasts than paracancerous tissues. Immune infiltrates in ccRCC tissues distinctly showed clustered and scattered patterns. Within the clustered pattern, we identified two subtypes with different clinical outcomes based on CN analysis. The TLS-like phenotype had cell communities resembling tertiary lymphoid structures, characterized by cell-cell interactions of CD8⁺ T cells-B cells and GZMB⁺CD8⁺ T cells-B cells, which exhibited anti-tumor features and favorable outcomes, while the Macrophage/T-clustered phenotype with macrophage- or T cell-dominated cell communities had a poor prognosis. Patients with scattered immune architecture could be further divided into scattered-CN-hot and scattered-CN-cold phenotypes based on the presence or absence of immune CNs, but both had a better prognosis than the macrophage/T-clustered phenotype. We further analyzed the relationship between the TME phenotypes and treatment response in five metastatic ccRCC patients treated with sunitinib, and found that all three responders were scattered-CN-hot phenotype while both non-responders were macrophage/T-clustered phenotype.

CONCLUSION

Our study revealed the structural heterogeneity of TME in ccRCC and its impact on clinical outcome and personalized treatment. These findings highlight the potential of IMC and CN analysis for characterizing TME structural units in cancer research.

The genomic and transcriptomic landscape of advanced renal cell cancer for individualized treatment strategies

Differences in the clinical course and treatment responses in individual patients with advanced renal cell carcinoma (RCC) can largely be explained by the different genomics of this disease. To improve the personalized treatment strategy and survival outcomes for patients with advanced RCC, the genomic make-up in patients with advanced RCC was investigated to identify putative actionable variants and signatures. In this prospective multicenter study (NCT01855477), whole-genome sequencing (WGS) data of locally advanced and metastatic tissue biopsies and matched whole-blood samples were collected from 91 patients with histopathologically confirmed RCC. WGS data were analyzed for small somatic variants, copy-number alterations and structural variants. For a subgroup of patients, RNA sequencing (RNA-Seq) data could be analyzed. RNA-Seq data were clustered on immunogenic and angiogenic gene expression patterns according to a previously developed angio-immunogenic gene signature. In all patients with papillary and clear cell RCC, putative actionable drug targets were detected by WGS, of which 94% were on-label available. RNA-Seq data of clear cell and papillary RCC were clustered using a previously developed angio-immunogenic gene signature. Analyses of driver mutations and RNA-Seq data revealed clear differences among different RCC subtypes, showing the added value of WGS and RNA-Seq over clinicopathological data. By improving both histological subtyping and the selection of treatment according to actionable targets and immune signatures, WGS and RNA-Seq may improve therapeutic decision making for most patients with advanced RCC, including patients with non-clear cell RCC for whom no standard treatment is available to data. Prospective clinical trials are needed to evaluate the impact of genomic and transcriptomic diagnostics on survival outcome for advanced RCC patients.

Repurposing of the Drug Tezosentan for Cancer Therapy

Tezosentan is a vasodilator drug that was originally developed to treat pulmonary arterial hypertension. It acts by inhibiting endothelin (ET) receptors, which are overexpressed in many types of cancer cells. Endothelin-1 (ET1) is a substance produced by the body that causes blood vessels to narrow. Tezosentan has affinity for both ET_A and ET_B receptors. By blocking the effects of ET1, tezosentan can help to dilate blood vessels, improve the blood flow, and reduce the workload on the heart. Tezosentan has been found to have anticancer properties due to its ability to target the ET receptors, which are involved in promoting cellular processes such as proliferation, survival, neovascularization, immune cell response, and drug resistance. This review intends to demonstrate the potential of this drug in the field of oncology. Drug repurposing can be an excellent way to improve the known profiles of first-line drugs and to solve several resistance problems of these same antineoplastic drugs.

Functional characterization of TSPAN7 as a novel indicator for immunotherapy in glioma

Glioma is the most common primary malignant tumor of the central nervous system in clinical practice. Most adult diffuse gliomas have poor efficacy after standard treatment, especially glioblastoma. With the in-depth understanding of brain immune microenvironment, immunotherapy as a new treatment has attracted much attention. In this study, through analyzing a large number of glioma cohorts, we reported that TSPAN7, a member of the tetraspanin family, decreased in high-grade gliomas and low expression was associated with poor prognosis in glioma patients. Meanwhile, the expression pattern of TSPAN7 was verified in glioma clinical samples and glioma cell lines by qPCR, Western Blotting and immunofluorescence. In addition, functional enrichment analysis showed that cell proliferation, EMT, angiogenesis, DNA repair and MAPK signaling pathways were activated in the TSPAN7 lower expression subgroup. Lentiviral plasmids were used to overexpress TSPAN7 in U87 and LN229 glioma cell lines to explore the anti-tumor role of TSPAN7 in glioma. Moreover, by analyzing the relationship between TSPAN7 expression and immune cell infiltration in multiple datasets, we found that TSPAN7 was significantly negatively correlated with the immune infiltration of tumor-related macrophages, especially M2-type macrophages. Further analysis of immune checkpoints showed that, the expression level of TSPAN7 was negatively correlated with the expression of PD-1, PD-L1 and CTLA-4. Using an independent anti-PD-1 immunotherapy cohorts of GBM, we demonstrated that TSPAN7 expression may had a synergistic effect with PD-L1 on the response to immunotherapy. Based on the above findings, we speculate that TSPAN7 can serve as a biomarker for prognosis and a potential immunotherapy target in glioma patients.

PIMREG is a prognostic biomarker involved in immune microenvironment of clear cell renal cell carcinoma and associated with the transition from G1 phase to S phase

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the world and affects human health seriously. PIMREG is a mitotic regulator which is essential to the metaphase-to-anaphase transition in cell cycle. Although PIMREG plays a crucial role in the malignant progression of tumors, there are few reports on its role in ccRCC.

Methods

The transcriptional expression profile and clinical data of PIMREG were downloaded from TCGA database and verified by qRT-PCR. Kaplan-Meier plotter was used to analyze the effect of PIMREG on overall survival (OS), disease specific survival (DSS) and progression-free interval (PFI) of patients with ccRCC. Univariable and multivariable Cox regression analysis were used to determine the independent prognostic factors of ccRCC. The effects of PIMREG on cell migration and invasion were detected by wound healing assay and transwell invasion assay, and CCK-8 assay, colony formation assay and cell cycle assay were used to detect the effect of PIMREG on cell proliferation. In addition, the changes in cell cycle related proteins were detected by western blot.

Results

PIMREG was highly expressed in human ccRCC and was positively correlated with pathologic stage, TNM stage and histologic grade. In addition, patients with high expression of PIMREG had a poor prognosis. Univariable and multivariable Cox regression analysis identified that PIMREG was an independent prognostic factor of ccRCC. Additionally, PIMREG was also closely related to immune cell infiltration. Experiments in vitro identified that the knockdown of PIMREG could significantly inhibit the proliferation, migration and invasion abilities of ccRCC. The expression of cyclin D1, CDK4 and CDK6 was also significantly reduced after PIMREG knockdown.

Conclusions

PIMREG plays a vital role in the development of ccRCC and may become a potential therapeutic target in the future.

Multi-omics consensus portfolio to refine the classification of lung adenocarcinoma with prognostic stratification, tumor microenvironment, and unique sensitivity to first-line therapies

BACKGROUND

Molecular classification of lung adenocarcinoma (LUAD) based on transcriptomic features has been widely studied. The complementarity of data obtained from multilayer molecular biology could help the LUAD classification via combining multi-omics information.

METHODS

We successfully divided samples from the The Cancer Genome Atlas (TCGA) (n=437) into four subtypes (CS1, CS2, CS3 and CS4) by 10 comprehensive multi-omics clustering methods in the "movics" R package. Meanwhile, external validation sets from different sequencing technologies proved the robustness of the grouping model. The relationship between subtypes, prognosis, molecular features, tumor microenvironment and response to first-line therapy was further analyzed. Next we used univariate Cox regression analysis and Lasso regression analysis to explore the application of biomarkers in clinical prognosis and constructed a prognostic model.

RESULTS

CS1 showed the worst overall survival (OS) among all four clusters, possibly related to its poor immune infiltration, higher tumor mutation and worse chromosomal stability. Patients in different subtypes differed significantly in cancer stem cell characteristics, activation of cancer-related pathways, sensitivity to chemotherapy and immunotherapy. The prognostic model showed good predictive performance. The 1-, 2- and 3-year areas under the curve of risk score were 0.779, 0.742 and 0.678, respectively. Seven genes (DKK1, TSPAN7, ID1, DLGAP5, HHIPL2, CD40 and SEMA3C) used to build the model may be potential therapeutic targets for LUAD.

CONCLUSIONS

Four LUAD subtypes with different molecular characteristics and clinical implications were identified successfully through bioinformatic analysis. Our results may contribute to precision medicine and inform the development of rational clinical strategies for targeted and immune therapies.

A predictive signature based on enhancer RNA associates with immune infiltration and aids treatment decision in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a prevalent urinary malignancy. Despite the recent development of better diagnostic tools and therapy, the five-year survival rate for individuals with advanced and metastatic ccRCC remains dismal. Unfortunately, ccRCC is less susceptible to radiation and chemotherapy. Consequently, targeted therapy and immunotherapy play a crucial role in the treatment of ccRCC. Enhancer RNAs (eRNAs) are noncoding RNAs transcribed by enhancers. Extensive research has shown that eRNAs are implicated in a variety of cancer signaling pathways. However, the biological functions of eRNAs have not been systematically investigated in ccRCC. In this study, we conducted a comprehensive investigation of the role of eRNAs in the onset and management of ccRCC. Patient prognosis-influencing eRNAs and target genes were chosen to construct a predictive signature. On the basis of the median riskscore, ccRCC patients were split into high- and low-risk subgroups. The prediction efficiency was assessed in several cohorts, and multi-omics analysis was carried out to investigate the differences and underlying mechanisms between the high- and low-risk groups. In addition, we investigated its potential to facilitate clinical treatment choices. The riskscore might be used to forecast a patient’s response to immunotherapy and targeted therapy, giving a revolutionary method for selecting treatment regimens with pinpoint accuracy.

Comprehensive analysis of FRAS1/FREM family as potential biomarkers and therapeutic targets in renal clear cell carcinoma

Background: FRAS1 (Fraser syndrome protein 1), together with FREM1 (the Fras1-related extracellular matrix proteins 1) and FREM2, belonging to the FRAS1/FREM extracellular matrix protein family, are considered to play essential roles in renal organogenesis and cancer progression. However, their roles in kidney renal clear cell carcinoma (KIRC) remain to be elucidated. Methods: FRAS1/FREM RNA expression analysis was performed using TCGA/GTEx databases, and valided using GEO databases and real-time PCR. Protein expression was peformed using CPTAC databases. Herein, we employed an array of bioinformatics methods and online databases to explore the potential oncogenic roles of FRAS1/FREM in KIRC. Results: We found that FRAS1, FREM1 and FREM2 genes and proteins expression levels were significantly decreased in KIRC tissues than in normal tissues. Decreased FRAS1/FREM expression levels were significantly associated with advanced clinicopathological parameters (pathological stage, grade and tumor metastasis status). Notably, the patients with decreased FRAS1/FREM2 expression showed a high propensity for metastasis and poor prognosis. FRAS1/FREM were correlated with various immune infiltrating cells, especially CD4+ T cells and its corresponding subsets (Th1, Th2, Tfh and Tregs). FRAS1 and FREM2 had association with DNA methylation and their single CpG methylation levels were associated with prognosis. Moreover, FRAS1/FREM might exert antitumor effects by functioning in key oncogenic signalling pathways and metabolic pathways. Drug sensitivity analysis indicated that high FRAS1 and FREM2 expression can be a reliable predictor of targeted therapeutic drug response, highlighting the potential as anticancer drug targets. Conclusion: Together, our results indicated that FRAS1/FREM family members could be potential therapeutic targets and valuable prognostic biomarkers of KIRC.

LncRNA MILIP links YBX1 to translational activation of Snai1 and promotes metastasis in clear cell renal cell carcinoma

Background

Distant metastasis is the major cause of clear cell renal cell carcinoma (ccRCC)-associated mortality. However, molecular mechanisms involved in ccRCC metastasis remain to be fully understood. With the increasing appreciation of the role of long non-coding RNAs (lncRNAs) in cancer development, progression, and treatment resistance, the list of aberrantly expressed lncRNAs contributing to ccRCC pathogenesis is expanding rapidly.

Methods

Bioinformatics analysis was carried out to interrogate publicly available ccRCC datasets. In situ hybridization and qRT-PCR assays were used to test lncRNA expression in human ccRCC tissues and cell lines, respectively. Chromatin immunoprecipitation and luciferase reporter assays were used to examine transcriptional regulation of gene expression. Wound healing as well as transwell migration and invasion assays were employed to monitor ccRCC cell migration and invasion in vitro. ccRCC metastasis was also examined using mouse models in vivo. RNA pulldown and RNA immunoprecipitation were performed to test RNA–protein associations, whereas RNA-RNA interactions were tested using domain-specific chromatin isolation by RNA purification.

Results

MILIP expression was upregulated in metastatic compared with primary ccRCC tissues. The increased MILIP expression in metastatic ccRCC cells was driven by the transcription factor AP-2 gamma (TFAP2C). Knockdown of MILIP diminished the potential of ccRCC cell migration and invasion in vitro and reduced the formation of ccRCC metastatic lesions in vivo. The effect of MILIP on ccRCC cells was associated with alterations in the expression of epithelial-to-mesenchymal transition (EMT) hallmark genes. Mechanistically, MILIP formed an RNA-RNA duplex with the snail family transcriptional repressor 1 (Snai1) mRNA and bound to Y-box binding protein 1 (YBX1). This promoted the association between the YBX1 protein and the Snai1 mRNA, leading to increased translation of the latter. Snai1 in turn played an important role in MILIP-driven ccRCC metastasis.

Conclusions

The TFAP2C-responsive lncRNA MILIP drives ccRCC metastasis. Targeting MILIP may thus represent a potential avenue for ccRCC treatment.

Definition and verification of novel metastasis and recurrence related signatures of ccRCC: A multicohort study

Background

Cancer metastasis and recurrence remain major challenges in renal carcinoma patient management. There are limited biomarkers to predict the metastatic probability of renal cancer, especially in the early-stage subgroup. Here, our study applied robust machine-learning algorithms to identify metastatic and recurrence-related signatures across multiple renal cancer cohorts, which reached high accuracy in both training and testing cohorts.

Methods

Clear cell renal cell carcinoma (ccRCC) patients with primary or metastatic site sequencing information from eight cohorts, including one out-house cohort, were enrolled in this study. Three robust machine-learning algorithms were applied to identify metastatic signatures. Then, two distinct metastatic-related subtypes were identified and verified; matrix remodeling associated 5 (MXRA5), as a promising diagnostic and therapeutic target, was investigated in vivo and in vitro.

Results

We identified five stable metastasis-related signatures (renin, integrin subunit beta-like 1, MXRA5, mesenchyme homeobox 2, and anoctamin 3) from multicenter cohorts. Additionally, we verified the specificity and sensibility of these signatures in external and out-house cohorts, which displayed a satisfactory consistency. According to these metastatic signatures, patients were grouped into two distinct and heterogeneous ccRCC subtypes named metastatic cancer subtype 1 (MTCS1) and type 2 (MTCS2). MTCS2 exhibited poorer clinical outcomes and metastatic tendencies than MTCS1. In addition, MTCS2 showed higher immune cell infiltration and immune signature expression but a lower response rate to immune blockade therapy than MTCS1. The MTCS2 subgroup was more sensitive to saracatinib, sunitinib, and several molecular targeted drugs. In addition, MTCS2 displayed a higher genome mutation burden and instability. Furthermore, we constructed a prognosis model based on subtype biomarkers, which performed well in training and validation cohorts. Finally, MXRA5, as a promising biomarker, significantly suppressed malignant ability, including the cell migration and proliferation of ccRCC cell lines in vitro and in vivo.

Conclusions

This study identified five robust metastatic signatures and proposed two metastatic probability clusters with stratified prognoses, multiomics landscapes, and treatment options. The current work not only provided new insight into the heterogeneity of renal cancer but also shed light on optimizing decision-making in immunotherapy and chemotherapy.

Integrated bioinformatics analysis to identify the key gene associated with metastatic clear cell renal cell carcinoma

Metastasis of clear cell renal cell carcinoma (ccRCC) is a leading cause of death. The purpose of this research was to investigate the key gene in ccRCC tumor metastasis. Three microarray datasets (GSE22541, GSE85258, and GSE105261), which included primary and metastatic ccRCC tissues, were obtained from the Gene Expression Omnibus (GEO) database. Expression profiling and clinical data of ccRCC were downloaded from The Cancer Genome Atlas (TCGA) dataset. A total of 20 overlapping differentially expressed genes (DEGs) were identified using the R limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the DEGs were mainly enriched in tumor metastasis-related pathways. Gene expression analysis and survival analysis in the GEPIA2 database further identified the key gene HSD11B2. qRT-PCR result manifested that HSD11B2 level was significantly down-regulated in ccRCC tissues compared with adjacent normal tissues. ROC analysis showed that HSD11B2 exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Univariate and multivariate Cox regression analysis showed that HSD11B2 expression was an independent prognostic factor. To establish a nomogram combining HSD11B2 expression and clinical factors, and a new method for predicting the survival probability of ccRCC patients. Gene Set Enrichment Analysis (GSEA) enrichment results showed that low expression of HSD11B2 was mainly enriched in tumor signaling pathways and immune-related pathways. Immune analysis revealed a significant correlation between HSD11B2 and tumor immune infiltrates in ccRCC. This study suggests that HSD11B2 can serve as a potential biomarker and therapeutic target for ccRCC metastasis.

Tetraspanin 7 promotes osteosarcoma cell invasion and metastasis by inducing EMT and activating the FAK-Src-Ras-ERK1/2 signaling pathway

Background

Tetraspanins are members of the 4-transmembrane protein superfamily (TM4SF) that function by recruiting many cell surface receptors and signaling proteins into tetraspanin-enriched microdomains (TEMs) that play vital roles in the regulation of key cellular processes including adhesion, motility, and proliferation. Tetraspanin7 (Tspan7) is a member of this superfamily that plays documented roles in hippocampal neurogenesis, synaptic transmission, and malignant transformation in certain tumor types. How Tspan7 influences the onset or progression of osteosarcoma (OS), however, remains to be defined. Herein, this study aimed to explore the relationship between Tspan7 and the malignant progression of OS, and its underlying mechanism of action.

Methods

In this study, the levels of Tspan7 expression in human OS cell lines were evaluated via qRT-PCR and western blotting. The effect of Tspan7 on proliferation was examined using CCK-8 and colony formation assays, while metastatic role of Tspan7 was assessed by functional assays both in vitro and in vivo. In addition, mass spectrometry and co-immunoprecipitation were performed to verify the interaction between Tspan7 and β1 integrin, and western blotting was used to explore the mechanisms of Tspan7 in OS progresses.

Results

We found that Tspan7 is highly expressed in primary OS tumors and OS cell lines. Downregulation of Tspan7 significantly suppressed OS growth, metastasis, and attenuated epithelial-mesenchymal transition (EMT), while its overexpression had the opposite effects in vitro. Furthermore, it exhibited reduced OS pulmonary metastases in Tspan7-deleted mice comparing control mice in vivo. Additionally, we proved that Tspan7 interacted with β1 integrin to facilitate OS metastasis through the activation of integrin-mediated downstream FAK-Src-Ras-ERK1/2 signaling pathway.

Conclusion

In summary, this study demonstrates for the first time that Tspan7 promotes OS metastasis via interacting with β1 integrin and activating the FAK-Src-Ras-ERK1/2 pathway, which could provide rationale for a new therapeutic strategy for OS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02591-1.

Construction of a Lactate-Related Prognostic Signature for Predicting Prognosis, Tumor Microenvironment, and Immune Response in Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent primary malignancies with high heterogeneity in the urological system. Growing evidence implies that lactate is a significant carbon source for cell metabolism and plays a vital role in tumor development, maintenance, and therapeutic response. However, the global influence of lactate-related genes (LRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response has not been comprehensively elucidated in patients with KIRC. In the present study, we collected RNA sequencing and clinical data of KIRC from The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts. Unsupervised clustering of 17 differentially expressed LRG profiles divided the samples into three clusters with distinct immune characteristics. Three genes (FBP1, HADH, and TYMP) were then identified to construct a lactate-related prognostic signature (LRPS) using the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The novel signature exhibited excellent robustness and predictive ability for the overall survival of patients. In addition, the constructed nomogram based on the LRPS-based risk scores and clinical factors (age, gender, tumor grade, and stage) showed a robust predictive performance. Furthermore, patients classified by risk scores had distinguishable immune status, tumor mutation burden, response to immunotherapy, and sensitivity to drugs. In conclusion, we developed an LRPS for KIRC that was closely related to the immune landscape and therapeutic response. This LRPS may guide clinicians to make more precise and personalized treatment decisions for KIRC patients.

Unique Transcriptomic Changes Underlie Hormonal Interactions During Mammary Histomorphogenesis in Female Pigs

Successful lactation and the risk for developing breast cancer depend on growth and differentiation of the mammary gland (MG) epithelium that is regulated by ovarian steroids (17β-estradiol [E] and progesterone [P]) and pituitary-derived prolactin (PRL). Given that the MG of pigs share histomorphogenic features present in the normal human breast, we sought to define the transcriptional responses within the MG of pigs following exposure to all combinations of these hormones. Hormone-ablated female pigs were administered combinations of E, medroxyprogesterone 17-acetate (source of P), and either haloperidol (to induce PRL) or 2-bromo-α-ergocryptine. We subsequently monitored phenotypic changes in the MG including mitosis, receptors for E and P (ESR1 and PGR), level of phosphorylated STAT5 (pSTAT5), and the frequency of terminal ductal lobular unit (TDLU) subtypes; these changes were then associated with all transcriptomic changes. Estrogen altered the expression of approximately 20% of all genes that were mostly associated with mitosis, whereas PRL stimulated elements of fatty acid metabolism and an inflammatory response. Several outcomes, including increased pSTAT5, highlighted the ability of E to enhance PRL action. Regression of transcriptomic changes against several MG phenotypes revealed 1669 genes correlated with proliferation, among which 29 were E inducible. Additional gene expression signatures were associated with TDLU formation and the frequency of ESR1 or PGR. These data provide a link between the hormone-regulated genome and phenome of the MG in a species having a complex histoarchitecture like that in the human breast, and highlight an underexplored synergy between the actions of E and PRL during MG development.

Key genes associated with prognosis and metastasis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a tumor that frequently shows the hematogenous pathway and tends to be resistant to radiotherapy and chemotherapy. However, the exact mechanism of ccRCC metastasis remains unknown.

METHODS

Differentially expressed genes (DEGs) of three gene expression profiles (GSE85258, GSE105288 and GSE22541) downloaded from the Gene Expression Omnibus (GEO) database were analyzed by GEO2R analysis, and co-expressed DEGs among the datasets were identified using a Venn drawing tool. The co-expressed DEGs were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and hub genes were determined based on the protein-protein interaction network established by STRING. After survival analysis performed on UALCAN website, possible key genes were selected and verified in ccRCC cell lines and ccRCC tissues (n = 44). Statistical analysis was conducted using GraphPad Prism (Version 8.1.1).

RESULTS

A total of 104 co-expressed DEGs were identified in the three datasets. Pathway analysis revealed that these genes were enriched in the extracellular matrix (ECM)-receptor interaction, protein digestion and absorption and focal adhesion. Survival analysis on 17 hub genes revealed that four key genes with a significant impact on survival: procollagen C-endopeptidase enhancer (PCOLCE), prolyl 4-hydroxylase subunit beta (P4HB), collagen type VI alpha 2 (COL6A2) and collagen type VI alpha 3 (COL6A3). Patients with higher expression of these key genes had worse survival than those with lower expression. In vitro experiments revealed that the mRNA expression levels of PCOLCE, P4HB and COL6A2 were three times higher and that of COL6A3 mRNA was 16 times higher in the metastatic ccRCC cell line Caki-1 than the corresponding primary cell line Caki-2. Immunohistochemistry revealed higher expression of the proteins encoded by these four genes in metastatic ccRCC compared with tumors from the corresponding primary sites, with statistical significance.

CONCLUSION

PCOLCE, P4HB, COL6A2 and COL6A3 are upregulated in metastatic ccRCC and might be related to poor prognosis and distant metastases.

Identifying Biomarkers from Transcriptomic Signatures in Renal Allograft Biopsies Using Deceased and Living Donors

The survival of transplant kidneys using deceased donors (DD) is inferior to living donors (LD). In this study, we conducted a whole-transcriptome expression analysis of 24 human kidney biopsies paired at 30 minutes and 3 months post-transplantation using DD and LD. The transcriptome profile was found significantly different between two time points regardless of donor types. There were 446 differentially expressed genes (DEGs) between DD and LD at 30 minutes and 146 DEGs at 3 months, with 25 genes common to both time points. These DEGs reflected donor injury and acute immune responses associated with inflammation and cell death as early as at 30 minutes, which could be a precious window of potential intervention. DEGs at 3 months mainly represented the changes of adaptive immunity, immunosuppressive treatment, remodeling or fibrosis via different networks and signaling pathways. The expression levels of 20 highly DEGs involved in kidney diseases and 10 genes dysregulated at 30 minutes were found correlated with renal function and histology at 12 months, suggesting they could be potential biomarkers. These genes were further validated by quantitative polymerase chain reaction (qPCR) in 24 samples analysed by microarray, as well as in a validation cohort of 33 time point unpaired allograft biopsies. This analysis revealed that SERPINA3, SLPI and CBF were up-regulated at 30 minutes in DD compared to LD, while FTCD and TASPN7 were up-regulated at both time points. At 3 months, SERPINA3 was up-regulated in LD, but down-regulated in DD, with increased VCAN and TIMP1, and decreased FOS, in both donors. Taken together, divergent transcriptomic signatures between DD and LD, and changed by the time post-transplantation, might contribute to different allograft survival of two type kidney donors. Some DEGs including FTCD and TASPN7 could be novel biomarkers not only for timely diagnosis, but also for early precise genetic intervention at donor preservation, implantation and post-transplantation, in particular to effectively improve the quality and survival of DD.

Sexual dimorphism in cancer: insights from transcriptional signatures in kidney tissue and renal cell carcinoma

Sexual dimorphism in cancer incidence and outcome is widespread. Understanding the underlying mechanisms is fundamental to improve cancer prevention and clinical management. Sex disparities are particularly striking in kidney cancer: across diverse populations, men consistently show unexplained 2-fold increased incidence and worse prognosis. We have characterized genome-wide expression and regulatory networks of 609 renal tumors and 256 non-tumor renal tissues. Normal kidney displayed sex-specific transcriptional signatures, including higher expression of X-linked tumor suppressor genes in women. Sex-dependent genotype-phenotype associations unraveled women-specific immune regulation. Sex differences were markedly expanded in tumors, with male-biased expression of key genes implicated in metabolism, non-malignant diseases with male predominance and carcinogenesis, including markers of tumor infiltrating leukocytes. Analysis of sex-dependent RCC progression and survival uncovered prognostic markers involved in immune response and oxygen homeostasis. In summary, human kidney tissues display remarkable sexual dimorphism at the molecular level. Sex-specific transcriptional signatures further shape renal cancer, with relevance for clinical management.

A Novel m6A Gene Signature Associated With Regulatory Immune Function for Prognosis Prediction in Clear-Cell Renal Cell Carcinoma

The important role of N⁶-methyladenosine (m⁶A) RNA methylation regulator in carcinogenesis and progression of clear-cell renal cell carcinoma (ccRCC) is poorly understood by now. In this study, we performed comprehensive analyses of m⁶A RNA methylation regulators in 975 ccRCC samples and 332 adjacent normal tissues and identified ccRCC-related m⁶A regulators. Moreover, the m⁶A diagnostic score based on ccRCC-related m⁶A regulators could accurately distinguish ccRCC from normal tissue in the Meta-cohort, which was further validated in the independent GSE-cohort and The Cancer Genome Atlas-cohort, with an area under the curve of 0.924, 0.867, and 0.795, respectively. Effective survival prediction of ccRCC by m⁶A risk score was also identified in the Cancer Genome Atlas training cohort and verified in the testing cohort and the independent GSE22541 cohort, with hazard ratio values of 3.474, 1.679, and 2.101 in the survival prognosis, respectively. The m⁶A risk score was identified as a risk factor of overall survival in ccRCC patients by the univariate Cox regression analysis, which was further verified in both the training cohort and the independent validation cohort. The integrated nomogram combining m⁶A risk score and predictable clinicopathologic factors could accurately predict the survival status of the ccRCC patients, with an area under the curve values of 85.2, 82.4, and 78.3% for the overall survival prediction in 1-, 3- and 5-year, respectively. Weighted gene co-expression network analysis with functional enrichment analysis indicated that m⁶A RNA methylation might affect clinical prognosis through regulating immune functions in patients with ccRCC.

TSPAN7 Exerts Anti-Tumor Effects in Bladder Cancer Through the PTEN/PI3K/AKT Pathway

The tetraspanin protein superfamily participate in the dynamic regulation of cellular membrane compartments expressed in a variety of tumor types, which may alter the biological properties of cancer cells such as cell development, activation, growth and motility. The role of tetraspanin 7 (TSPAN7) has never been investigated in bladder cancer (BCa). In this study, we aimed to investigate the biological function of TSPAN7 and its therapeutic potential in human BCa. First, via reverse transcription and quantitative real-time PCR (qRT-PCR), we observed downregulation of TSPAN7 in BCa tissues samples and cell lines and found that this downregulation was associated with a relatively high tumor stage and tumor grade. Low expression of TSPAN7 was significantly correlated with a much poorer prognosis for BCa patients than was high expression. Immunohistochemistry (IHC) showed that low TSPAN7 expression was a high-risk predictor of BCa patient overall survival. Furthermore, the inhibitory effects of TSPAN7 on the proliferation and migration of BCa cell lines were detected by CCK-8, wound-healing, colony formation and transwell assays in vitro. Flow cytometry analysis revealed that TSPAN7 induced BCa cell lines apoptosis and cell cycle arrest. In vivo, tumor growth in nude mice bearing tumor xenografts could be obviously affected by overexpression of TSPAN7. Western blotting showed that overexpression of TSPAN7 activated Bax, cleaved caspase-3 and PTEN but inactivated Bcl-2, p-PI3K, and p-AKT to inhibit BCa cell growth via the PTEN/PI3K/AKT pathway. Taken together, our study will help identify a potential marker for BCa diagnosis and supply a target molecule for BCa treatment.

DNA Methylation-Based Panel Predicts Survival of Patients With Clear Cell Renal Cell Carcinoma and Its Correlations With Genomic Metrics and Tumor Immune Cell Infiltration

DNA methylation based prognostic factor for patients with clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, we identified survival-related DNA methylation sites based on the differentially methylated DNA CpG sites between normal renal tissue and ccRCC. Then, these survival-related DNA methylation sites were included into an elastic net regularized Cox proportional hazards regression (CoxPH) model to build a DNA methylation-based panel, which could stratify patients into different survival groups with excellent accuracies in the training set and test set. External validation suggested that the DNA methylation-based panel could effectively distinguish normal controls from tumor samples and classify patients into metastasis group and non-metastasis group. The nomogram containing DNA methylation-based panel was reliable in clinical settings. Higher total mutation number, SCNA level, and MATH score were associated with higher methylation risk. The innate immune, ratio between CD8⁺T cell versus Treg cell as well as Th17 cell versus Th2 cell were significantly decreased in high methylation risk group. In inclusion, we developed a DNA methylation-based panel which might be independent prognostic factor in ccRCC. Patients with higher methylation risk were associated genomic alteration and poor immune microenvironment.

Creation of a Prognostic Risk Prediction Model for Lung Adenocarcinoma Based on Gene Expression, Methylation, and Clinical Characteristics

Background

This study aimed to identify important marker genes in lung adenocarcinoma (LACC) and establish a prognostic risk model to predict the risk of LACC in patients.

Material/Methods

Gene expression and methylation profiles for LACC and clinical information about cases were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between cancer and control groups were selected through meta-analysis. Pearson coefficient correlation analysis was performed to identify intersections between DEGs and DMGs and a functional analysis was performed on the genes that were correlated. Marker genes and clinical factors significantly related to prognosis were identified using univariate and multivariate Cox regression analyses. Risk prediction models were then created based on the marker genes and clinical factors.

Results

In total, 1975 DEGs and 2095 DMGs were identified. After comparison, 16 prognosis-related genes (EFNB2, TSPAN7, INPP5A, VAMP2, CALML5, SNAI2, RHOBTB1, CKB, ATF7IP2, RIMS2, RCBTB2, YBX1, RAB27B, NFATC1, TCEAL4, and SLC16A3) were selected from 265 overlapping genes. Four clinical factors (pathologic N [node], pathologic T [tumor], pathologic stage, and new tumor) were associated with prognosis. The prognostic risk prediction models were constructed and validated with other independent datasets.

Conclusions

An integrated model that combines clinical factors and gene markers is useful for predicting risk of LACC in patients. The 16 genes that were identified, including EFNB2, TSPAN7, INPP5A, VAMP2, and CALML5, may serve as novel biomarkers for diagnosis of LACC and prediction of disease prognosis.

Development and validation of a metastasis-related Gene Signature for predicting the Overall Survival in patients with Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer characterized by invasiveness and metastasis. In this study, we aimed to propose a gene prediction model based on metastasis-related genes (MTGs) to more accurately predict PDAC prognosis.

Methods: Differentially expressed MTGs (DE-MTGs) were identified via integrated analysis of gene expression omnibus (GEO) datasets and Human Cancer Metastasis Database (HCMDB). Overall survival (OS) related DE-MTGs were then identified and a prognostic gene signature was established using Lasso-Cox regression with TCGA-PAAD datasets. Tumor immunity was analyzed using ESTIMATE and CIBERSORT algorithms. Finally, a nomogram predicting 1-year, 2-year, and 3-year OS of PDAC patients was established based on the prognostic gene signature and relevant clinical parameters using a stepwise Cox regression model.

Results: A total of 36 DE-MTGs related to OS were identified in PDAC. Consequently, an MTG-based gene signature comprising of RACGAP1, RARRES3, TPX2, MMP28, GPR87, KIF14, and TSPAN7 was established to predict the OS of PDAC. The MTG-based gene signature was able to distinguish high-risk patients with significantly poorer prognosis and accurately predict OS of PDAC in both the training and external validation datasets. Cox regression analysis indicated that the MTG-based gene signature was an independent prognostic factor in PDAC. The gene set enrichment analysis (GSEA) showed that molecular alterations in the high-risk group were associated with multiple oncological pathways. Moreover, analysis of tumor immunity revealed significantly higher levels of follicular helper T cells and M0 macrophage infiltration, and lower levels of infiltrating naïve B cells, CD8 T cells, monocytes, and resting dendritic cells in the high-risk group. Immune cell infiltration levels were significantly associated with the expression of the seven DE-MTGs. Finally, a nomogram was established by incorporating the prognostic gene signature and clinical parameters, which was superior to the AJCC staging system in predicting the OS of PDAC patients.

Conclusions: The DE-MTGs we identified were closely associated with the progress and prognosis of PDAC and are potential therapeutic targets. The MTG-based gene signature and nomogram may serve to improve the individualized prediction of survival, assisting in clinical decision-making.

Identification of PDE7B as a Potential Core Gene Involved in the Metastasis of Clear Cell Renal Cell Carcinoma

Background

Metastasis is the main cause of treatment failure in various cancer, including ccRCC. However, the key genes involved in ccRCC metastasis remain largely unknown.

Purpose

The identification of the aberrant gene expression patterns associated with metastatic traits is of great clinical significance. The aim of this study was to investigate the clinical significance and function of PDE7B in ccRCC.

Materials and Methods

Expression profiling data for patient-matched primary and metastatic ccRCC tumors were obtained from GEO Dataset. Limma package was used to identify differentially expressed genes (DEGs) between the metastatic and the primary groups. Gene Ontology, Kyoto Encyclopedia of Genes Genomes (KEGG), and PPI network analysis were used to study the interacting activities and the interconnection of the DEGs. CCK-8 assays and Transwell assays were performed to detect the proliferation and migration of renal cancer cells.

Results

We obtained 163 DEGs, including 132 that were upregulated and 31 that were downregulated in metastatic ccRCC tissues. Both Gene Ontology function and KEGG pathway analysis showed that DEGs were involved in extracellular matrix (ECM) organization and cell adhesion. After utilizing PPI network to explore the interconnection among the DEGs, 22 genes were selected as the hub genes. Subsequently, survival analysis revealed that seven hub genes (SFN, NKX2-1, HP, MAPT, EPHA4, KCNAB1, and PDE7B) were significantly associated with overall survival disease-specific survival, and progression-free interval in ccRCC. Moreover, the low expression of PDE7B was found in clinical ccRCC samples and correlated with TNM stage and histologic grade. We further showed that knockdown of PDE7B increased cell growth and migration of renal cancer cells.

Conclusion

Our results implicated that PDE7B may play a key role in the development of metastatic RCC.

Tetraspanin 7 and its closest paralog tetraspanin 6: membrane organizers with key functions in brain development, viral infection, innate immunity, diabetes and cancer

Tetraspanin (TSPAN) protein family forms a family of transmembrane proteins that act as organizers/scaffold for other proteins. TSPANs are primarily present on plasma membranes although they are also found in other biological membranes. They are organized in tetraspanin-enriched microdomains (TEMs), which allow spatiotemporal tuning of protein functions through the control of their membrane localization. TSPAN6 and TSPAN7 are close paralogs expressed in different tissues, TSPAN7 being highly expressed in the brain. Their functions only started to be unveiled in the late 2000's and are still poorly understood. Here, we introduce how TSPAN7 was first highlighted has a protein mutated in some forms of X-linked mental retardation, which was later proposed to be caused by defects in neuronal morphogenesis and synaptic transmission. We then discuss the impacts TSPAN7 has on cell morphology of dendritic cells and osteoclasts, through rearrangement of actin cytoskeleton and how TSPAN7 was shown to be a target of autoantibody in patients suffering from type 1 diabetes. Finally, we are addressing the double edge sword that is TSPAN7 in cancer. In the second part of this review, we address the known roles of TSPAN6 and how this protein was shown to participate in synaptic transmission and in amyloid precursor protein secretion, which may contribute to Alzheimer's disease pathology. We conclude this review by discussing the anti-inflammatory effect of TSPAN6.

Expression and function of transmembrane 4 superfamily proteins in digestive system cancers

Background

Although the medical level is constantly improving, cancer is still a major disease that threatens human health, and very effective treatments have not been found. In recent years, studies have found that four-transmembrane superfamily proteins are involved in multiple stages of tumorigenesis and development, but their expression and function in tumors have not been systematically studied.

Methods

We used the Oncomine database to analyze the mRNA expression levels of TSPAN family in various cancers. Then differentially expressed genes were screened out and verified by liver cancer, colorectal cancer, and gastric cancer cells by q-PCR and Western blot analysis. CCK8 and EDU analysis are used to detect cell proliferation, Cell wound scrape assay and Cell invasion assay are used to analyze cell invasion and metastasis. Nude tumor formation test used to verify the tumor suppressive effect of TSPAN7 in vivo.

Results

Differential analysis of 33 TSPAN proteins revealed that a total of 11 proteins showed differential expression in 10% of independent analyses, namely TSPAN1, TSPAN3, TSPAN5, TSPAN6, TSPAN7, TSPAN8, TSPAN13, TSPAN25, TSPAN26, TSPAN29, TSPAN30. TSPAN7 is the only four-transmembrane protein with reduced expression in three types of digestive tract tumors, so we chose TSPAN7 to be selected for cellular and molecular level verification. We found that compared with normal cells, the expression of TSPAN7 in liver cancer cells was significantly reduced, while the expression of gastric and colon cancer was not significantly different from that of normal cells. In addition, we also found that the high expression of Tspan7 not only inhibited the proliferation of HCC-LM3 cells, but also inhibited its invasion and metastasis.

Conclusions

Our study evaluated the expression and function of the TSPANs family in digestive cancers and explored TSPAN7 in hepatoma cells in detail. We found some members of the TSPAN family show significant expression differences between cancer and normal tissues, of which TSPAN7 may be a potential biomarker for liver cancer.

Induction of DNMT3B by PGE2 and IL6 at Distant Metastatic Sites Promotes Epigenetic Modification and Breast Cancer Colonization

Current cancer treatments are largely based on the genetic characterization of primary tumors and are ineffective for metastatic disease. Here we report that DNA methyltransferase 3B (DNMT3B) is induced at distant metastatic sites and mediates epigenetic reprogramming of metastatic tumor cells. Multiomics analysis and spontaneous metastatic mouse models revealed that DNMT3B alters multiple pathways including STAT3, NFκB, PI3K/Akt, β-catenin, and Notch signaling, which are critical for cancer cell survival, apoptosis, proliferation, invasion, and colonization. PGE2 and IL6 were identified as critical inflammatory mediators in DNMT3B induction. DNMT3B expression levels positively correlated with human metastatic progression. Targeting IL6 or COX-2 reduced DNMT3B induction and improved chemo or PD1 therapy. We propose a novel mechanism linking the metastatic microenvironment with epigenetic alterations that occur at distant sites. These results caution against the "Achilles heel" in cancer therapies based on primary tumor characterization and suggests targeting DNMT3B induction as new option for treating metastatic disease. SIGNIFICANCE: These findings reveal that DNMT3B epigenetically regulates multiple pro-oncogenic signaling pathways via the inflammatory microenvironment at distant sites, cautioning the clinical approach basing current therapies on genetic characterization of primary tumors.

Endothelin Receptor Antagonists: Status Quo and Future Perspectives for Targeted Therapy

The endothelin axis, recognized for its vasoconstrictive action, plays a central role in the pathology of pulmonary arterial hypertension (PAH). Treatment with approved endothelin receptor antagonists (ERAs), such as bosentan, ambrisentan, or macitentan, slow down PAH progression and relieves symptoms. Several findings have indicated that endothelin is further involved in the pathogenesis of certain other diseases, making ERAs potentially beneficial in the treatment of various conditions. In addition to PAH, this review summarizes the use and perspectives of ERAs in cancer, renal disease, fibrotic disorders, systemic scleroderma, vasospasm, and pain management. Bosentan has proven to be effective in systemic sclerosis PAH and in decreasing the development of vasospasm-related digital ulcers. The selective ERA clazosentan has been shown to be effective in preventing cerebral vasospasm and delaying ischemic neurological deficits and new infarcts. Furthermore, in the SONAR (Study Of Diabetic Nephropathy With Atrasentan) trial, the selective ERA atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease. These data suggest atrasentan as a new therapy in the treatment of diabetic nephropathy and possibly other renal diseases. Preclinical studies regarding heart failure, cancer, and fibrotic diseases have demonstrated promising effects, but clinical trials have not yet produced measurable results. Nevertheless, the potential benefits of ERAs may not be fully realized.

Risk score based on expression of five novel genes predicts survival in soft tissue sarcoma

In this study, The Cancer Genome Atlas and Genotype-Tissue Expression databases were used to identify potential biomarkers of soft tissue sarcoma (STS) and construct a prognostic model. The model was used to calculate risk scores based on the expression of five key genes, among which MYBL2 and FBN2 were upregulated and TSPAN7, GCSH, and DDX39B were downregulated in STS patients. We also examined gene signatures associated with the key genes and evaluated the model’s clinical utility. The key genes were found to be involved in the cell cycle, DNA replication, and various cancer pathways, and gene alterations were associated with a poor prognosis. According to the prognostic model, risk scores negatively correlated with infiltration of six types of immune cells. Furthermore, age, margin status, presence of metastasis, and risk score were independent prognostic factors for STS patients. A nomogram that incorporated the risk score and other independent prognostic factors accurately predicted survival in STS patients. These findings may help to improve prognostic prediction and aid in the identification of effective treatments for STS patients.

The value of endothelin receptor type B promoter methylation as a biomarker for the risk assessment and diagnosis of prostate cancer: A meta-analysis

Previous researches have demonstrated that the methylation status of the EDNRB promoter was associated with the prostate cancer (PCa), but these conclusions remained controversial. Thus, the aim of this meta-analysis was to evaluate the association between EDNRB promoter methylation and the PCa. According to the PRISMA statement, the Web of Science, PubMed, EMBASE, and Cochrane Library databases were retrieved. The ORs and 95 % CIs were analyzed to evaluate the associations between EDNRB promoter methylation and the risk and clinical features of PCa. Heterogeneity among the included studies was estimated by I² statistic and Q test. Publication bias and sensitivity analysis were utilized to test the robustness of our outcomes. In addition, the pooled sensitivity and specificity were calculated to assess the diagnostic value of EDNRB methylation for PCa. Ultimately, 11 eligible studies were included. Under the random-effects model, the pooled OR shown that the frequency of EDNRB methylation was substantially higher in cases compared with controls (OR = 5.42, 95 % CI = 1.98-14.88, P = 0.001). The similar results were also found by the data from TCGA database. Subgroup analysis according to the methylation detection method showed that the heterogeneity in quantitative methylation-specific polymerase chain reaction (qMSP) group was insignificant (I² = 0.0 %, P = 0.669). Moreover, the pooled sensitivity for all-inclusive studies was 0.55 (95 % CI: 0.26-0.81), and the pooled specificity was 0.93 (95 % CI: 0.55-0.99). The methylation of EDNRB promoter might increase the risk of PCa. Meanwhile, EDNRB promoter methylation test combined with PSA testing and/or other biomarkers could be promising diagnostic biomarkers for more accurate detection of PCa.

Gene Selection for the Discrimination of Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Cancer discrimination is a typical application of gene expression analysis using a microarray technique. However, microarray data suffer from the curse of dimensionality and usual imbalanced class distribution between the majority (tumor samples) and minority (normal samples) classes. Feature gene selection is necessary and important for cancer discrimination.

OBJECTIVES

To select feature genes for the discrimination of CRC.

METHODS

We improve the feature selection algorithm based on differential evolution, DEFSw by using RUSBoost classifier and weight accuracy instead of the common classifier and evaluation measure for selecting feature genes from imbalance data. We firstly extract differently expressed genes (DEGs) from the CRC dataset of the TCGA and then select the feature genes from the DEGs using the improved DEFSw algorithm. Finally, we validate the selected feature gene sets using independent datasets and retrieve the cancer related information for these genes based on text mining through the Coremine Medical online database.

RESULTS

We select out 16 single-gene feature sets for colorectal cancer discrimination and 19 single-gene feature sets only for colon cancer discrimination.

CONCLUSIONS

In summary, we find a series of high potential candidate biomarkers or signatures, which can discriminate either or both of colon cancer and rectal cancer with high sensitivity and specificity.

MUDENG Expression Profiling in Cohorts and Brain Tumor Biospecimens to Evaluate Its Role in Cancer

Mu-2-related death-inducing gene (MUDENG, MuD) has been reported to be involved in the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-associated apoptotic pathway of glioblastoma multiforme (GBM) cells; however, its expression level, interactors, and role in tumors are yet to be discovered. To investigate whether MuD expression correlates with cancer progression, we analyzed The Cancer Genome Atlas (TCGA) database using UALCAN and Gene Expression Profiling Interactive Analysis (GEPIA). Differential expression of MuD was detected in 6 and 10 cancer types, respectively. Validation performed using data from the Gene Expression Omnibus database showed that MuD expression is downregulated in KIRC tumor and correlate with higher chance of survival. Upregulation of MuD expression in GBM tumors was detected through GEPIA and high MuD expression correlated with higher survival in proneural GBM, whereas the opposite was observed in classical GBM subtype. GBM biospecimens analysis shows that MuD protein level was upregulated in three of six specimens, whereas mRNA level remained relatively unaltered. Therefore, MuD may exert differential effects according to subtypes, and/or be subjected to post-translational regulation in GBM. Correlation analysis between GBM cohort database and experiments using GBM cell lines revealed its positive effect on regulation of protein phosphatase 2 regulatory subunit B’Epsilon (PPP2R5E) and son of sevenless homolog 2 (SOS2). STRING database analysis indicated that the components of adaptor protein complexes putatively interacted with MuD but showed no correlation in terms of survival of patients with different GBM subtypes. In summary, we analyzed the expression of MuD in publicly available cancer patient data sets, GBM cell lines, and biospecimens to demonstrate its potential role as a biomarker for cancer prognosis and identified its candidate interacting molecules.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan-Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp.

Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma

Background

Competing endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer progression and poor prognosis. In this study, we aimed to identify ceRNAs that may serve as potential biomarkers for early diagnosis of lung adenocarcinoma (LUAD).

Methods

We performed differential gene expression analysis on TCGA-LUAD datasets to identify differentially expressed (DE) mRNAs, lncRNAs, and miRNAs at different tumor stages. Based on the ceRNA hypothesis and considering the synergistic or feedback regulation of ceRNAs, a lncRNA–miRNA–mRNA network was constructed. Functional analysis was performed using gene ontology term and KEGG pathway enrichment analysis and KOBAS 2.0 software. Transcription factor (TF) analysis was carried out to identify direct targets of the TFs associated with LUAD prognosis. Identified DE genes were validated using gene expression omnibus (GEO) datasets.

Results

Based on analysis of TCGA-LUAD datasets, we obtained 2,610 DE mRNAs, 915 lncRNAs, and 125 miRNAs that were common to different tumor stages (|log₂(Fold change)| ≥ 1, false discovery rate < 0.01), respectively. Functional analysis showed that the aberrantly expressed mRNAs were closely related to tumor development. Survival analyses of the constructed ceRNA network modules demonstrated that five of them exhibit prognostic significance. The five ceRNA interaction modules contained one lncRNA (FENDRR), three mRNAs (EPAS1, FOXF1, and EDNRB), and four miRNAs (hsa-miR-148a, hsa-miR-195, hsa-miR-196b, and hsa-miR-301b). The aberrant expression of one lncRNA and three mRNAs was verified in the LUAD GEO dataset. Transcription factor analysis demonstrated that EPAS1 directly targeted 13 DE mRNAs.

Conclusion

Our observations indicate that lncRNA-related ceRNAs and TFs play an important role in LUAD. The present study provides novel insights into the molecular mechanisms underlying LUAD pathogenesis. Furthermore, our study facilitates the identification of potential biomarkers for the early diagnosis and prognosis of LUAD and therapeutic targets for its treatment.

TSPAN7 promotes the migration and proliferation of lung cancer cells via epithelial-to-mesenchymal transition

PURPOSE

To explore the effects and mechanisms of tetraspanin TSPAN7 on the progression of non-small-cell lung cancer (NSCLC) cells.

PATIENTS AND METHODS

All 125 lung cancer specimens and 60 metastatic tissues were obtained from patients diagnosed with NSCLC, and we used immunohistochemistry to detect the expression of TSPAN7 in NSCLC tissues and adjacent normal tissues. Cell proliferation and invasion ability were determined by MTT, colony formation, and cell migration. The relative protein expression level was analyzed by Western blot analysis.

RESULTS

Our clinical data showed that among 125 patients with lung cancer, TSPAN7 was associated with lymph node status, differentiation, tumor size, and poor prognosis. TSPAN7 knockout inhibited cell proliferation and migration. In addition, TSPAN7 increased the expression of N-cadherin in NSCLC cells by reducing the expression of E-cadherin and vimentin and promoting the cell epithelial-mesenchymal transition (EMT) process. Xenograft transplantation model confirmed the role of TSPAN7 in NSCLC metastasis.

CONCLUSION

TSPAN7-mediated EMT is the key to NSCLC migration. TSPAN7 is a potential target for NSCLC therapy.

Comprehensive assessment gene signatures for clear cell renal cell carcinoma prognosis

There are many prognostic gene signature models in clear cell renal cell carcinoma (ccRCC). However, different results from various methods and samples are hard to contribute to clinical practice. It is necessary to develop a robust gene signature for improving clinical practice in ccRCC.A method was proposed to integrate least absolute shrinkage and selection operator and multiple Cox regression to obtain mRNA and microRNA signature from the cancer genomic atlas database for predicting prognosis of ccRCC. The gene signature model consisted by 5 mRNAs and 1 microRNA was identified. Prognosis index (PI) model was constructed from RNA expression and median value of PI is used to classified patients into high- and low-risk groups.The results showed that high-risk patients showed significantly decrease survival comparison with low-risk groups [hazard ratio (HR) =7.13, 95% confidence interval = 3.71-13.70, P < .001]. As the gene signature was mainly consisted by mRNA, the validation data can use transcriptomic data to verify. For comparison of the performance with previous works, other gene signature models and 4 datasets of ccRCC were retrieved from publications and public database. For estimating PI in each model, 3 indicators including HR, concordance index , and the area under the curve of receiver operating characteristic for 3 years were calculated across 4 independent datasets.The comparison results showed that the integrative model from our study was more robust than other models via comprehensive analysis. These findings provide some genes for further study their functions and mechanisms in ccRCC tumorigenesis and malignance, and may be useful for effective clinical decision making of ccRCC patients.

A 44-gene set constructed for predicting the prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most frequent type of renal cell carcinoma (RCC). The present study aimed to examine prognostic markers and construct a prognostic prediction system for ccRCC. The mRNA sequencing data of ccRCC was downloaded from The Cancer Genome Atlas (TCGA) database, and the GSE40435 dataset was obtained from the Gene Expression Omnibus database. Using the Limma package, the differentially expressed genes (DEGs) in the TCGA dataset and GSE40435 dataset were obtained, respectively, and the overlapped DEGs were selected. Subsequently, Cox regression analysis was applied for screening prognosis-associated genes. Following visualization of the co-expression network using Cytoscape software, the network modules were examined using the GraphWeb tool. Functional annotation for genes in the network was performed using the clusterProfiler package. Finally, a prognostic prediction system was constructed through Bayes discriminant analysis and confirmed with the GSE29609 validation dataset. The results revealed a total of 263 overlapped DEGs and 161 prognosis-associated genes. Following construction of the co-expression network, 16 functional terms and three pathways were obtained for genes in the network. In addition, red, yellow (Involving chemokine ligand 10 (CXCL10), CD27 molecule (CD27) and runt-related transcription factor 3 (RUNX3)], green (Involving angiopoietin-like 4 (ANGPTL4), stannio-calcin 2 (STC2), and sperm associated antigen 4 (SPAG4)], and cyan modules were extracted from the co-expression network. Additionally, the prognostic prediction system involving 44 signature genes, including ANGPTL4, STC2, CXCL10, SPAG4, CD27, matrix metalloproteinase (MMP9) and RUNX3, was identified and confirmed. In conclusion, the 44-gene prognostic prediction system involving ANGPTL4, STC2, CXCL10, SPAG4, CD27, MMP9 and RUNX3 may be utilized for predicting the prognosis of patients with ccRCC.

Overexpression of endothelin B receptor in glioblastoma: a prognostic marker and therapeutic target?

Background

Glioblastoma (GBM) is the most common malignant brain tumor with median survival of 12-15 months. Owing to uncertainty in clinical outcome, additional prognostic marker(s) apart from existing markers are needed. Since overexpression of endothelin B receptor (ETBR) has been demonstrated in gliomas, we aimed to test whether ETBR is a useful prognostic marker in GBM and examine if the clinically available endothelin receptor antagonists (ERA) could be useful in the disease treatment.

Methods

Data from The Cancer Genome Atlas and the Gene Expression Omnibus database were analyzed to assess ETBR expression. For survival analysis, glioblastoma samples from 25 Swedish patients were immunostained for ETBR, and the findings were correlated with clinical history. The druggability of ETBR was assessed by protein-protein interaction network analysis. ERAs were analyzed for toxicity in in vitro assays with GBM and breast cancer cells.

Results

By bioinformatics analysis, ETBR was found to be upregulated in glioblastoma patients, and its expression levels were correlated with reduced survival. ETBR interacts with key proteins involved in cancer pathogenesis, suggesting it as a druggable target. In vitro viability assays showed that ERAs may hold promise to treat glioblastoma and breast cancer.

Conclusions

ETBR is overexpressed in glioblastoma and other cancers and may be a prognostic marker in glioblastoma. ERAs may be useful for treating cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4012-7) contains supplementary material, which is available to authorized users.

Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis

In cancer, both histopathologic images and genomic signatures are used for diagnosis, prognosis, and subtyping. However, combining histopathologic images with genomic data for predicting prognosis, as well as the relationships between them, has rarely been explored. In this study, we present an integrative genomics framework for constructing a prognostic model for clear cell renal cell carcinoma. We used patient data from The Cancer Genome Atlas (n = 410), extracting hundreds of cellular morphologic features from digitized whole-slide images and eigengenes from functional genomics data to predict patient outcome. The risk index generated by our model correlated strongly with survival, outperforming predictions based on considering morphologic features or eigengenes separately. The predicted risk index also effectively stratified patients in early-stage (stage I and stage II) tumors, whereas no significant survival difference was observed using staging alone. The prognostic value of our model was independent of other known clinical and molecular prognostic factors for patients with clear cell renal cell carcinoma. Overall, this workflow and the shared software code provide building blocks for applying similar approaches in other cancers. Cancer Res; 77(21); e91-100. ©2017 AACR.

Expression of minichromosome maintenance genes in renal cell carcinoma

Minichromosome maintenance (MCM) proteins play an essential role in DNA replication. They have been shown to be overexpressed in various types of cancer. However, the role of this family in renal cell carcinoma (RCC) is widely unknown. In this study, we have identified a number of RCC datasets in the Gene Expression Omnibus database and also investigated the correlation between the expression levels of MCM genes and clinicopathological parameters. We found that the expression levels of MCM genes are positively correlated with one another. Expression levels of MCM2, MCM5, MCM6, and MCM7, but not of MCM3 and MCM4, were higher in RCC compared to paired adjacent normal tissue. Only the expression level of MCM4, but not of other MCMs, was positively correlated with tumor grade. In addition, a high-level expression of MCM2 in either primary tumor or metastases of RCC predicted a shorter disease-free survival time, while a high-level expression of MCM4 or MCM6 in primary tumor was also associated with poorer disease-free survival. Interestingly, we also demonstrated that patients with their primary RCC overexpressing 2 or more MCM genes had a shorter disease-free survival time, while those with RCC metastases overexpressing 3 or more MCM genes had a shorter disease-free survival. Importantly, we also demonstrated that overexpression of MCM genes is an independent predictor for survival in RCC patients. Our results suggest that MCM2-7 genes may be an important prognostic marker for patients with RCC.