ccRCC Microenvironment Research Articles

PTX3 modulates the immunoflogosis in tumor microenvironment and is a prognostic factor for patients with clear cell renal cell carcinoma.

Pentraxin-3 (PTX3) belongs to the pentraxine family, innate immune regulators involved in angiogenesis, proliferation and immune escape in cancer. Here, we evaluated PTX3 tissue expression and serum levels as biomarkers of clear cell renal cell carcinoma (ccRCC) and analyzed the possible role of complement system activation on tumor site. A 10-year retrospective cohort study including patients undergoing nephrectomy for ccRCC was also performed. PTX3 expression was elevated in both neoplastic renal cell lines and tissues, while it was absent in both normal renal proximal tubular cells (HK2) and normal renal tissues. Analysis of complement system activation on tumor tissues showed the co-expression of PTX3 with C1q, C3aR, C5R1 and CD59, but not with C5b-9 terminal complex. RCC patients showed higher serum PTX3 levels as compared to non-neoplastic patients (p<0.0001). Higher PTX3 serum levels were observed in patients with higher Fuhrman grade (p<0.01), lymph node (p<0.0001), and visceral metastases (p<0.001). Patients with higher PTX3 levels also showed significantly lower survival rates (p=0.002). Our results suggest that expression of PTX3 can affect the immunoflogosis in the ccRCC microenvironment, by activating the classical pathway of CS (C1q) and releasing pro-angiogenic factors (C3a, C5a). The up-regulation of CD59 also inhibits the complement-mediated cellular lysis.

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells. We found that the immune scores revealed more prognostic significance in overall survival and positive associations with risk clinical factors than stromal scores. We carried out differential expression analysis between Immunescore and stromalscore groups to obtain the 72 intersect genes. Protein to protein interaction (PPI) network and functional analysis was performed to indicate potential altered pathways. Additionally, we further conducted multivariate Cox analysis to identify 12 hub genes associated highly with TME of ccRCC using a stepwise regression procedure. Accordingly, risk score was constructed from the multivariate Cox results and Receiver Operating Characteristic (ROC) curve was used to assess the predictive value (AUC = 0.781). The ccRCC patients with high risk scores suffered poor survival outcomes than that with low risk scores. In the validation cohort from GSE53757, TNFSF13B, CASP5, and GJB6 correlated positively with tumor stages, while FREM1 negatively correlated with tumor stages. Importantly, we further observed that TNFSF13B, CASP5 and XCR1 showed the remarkable correlations with tumor‐infiltrating immune cells. Taken together, our research identified specific signatures that related to the infiltration of stromal and immune cells in TME of ccRCC using the transciptome profiles, which reached a comprehensive understanding of tumor microenvironment in ccRCC.

Identification of genes of prognostic value in the ccRCC microenvironment from TCGA database.

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma. Bioinformatics analyses were used to screen candidate genes associated with the prognosis and microenvironment of ccRCC and elucidate the underlying molecular mechanisms of action.MethodsThe gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. The ESTIMATE algorithm was used to compute the immune and stromal scores of patients. Based on the median immune/stromal scores, all patients were sorted into low‐ and high‐immune/stromal score groups. Differentially expressed genes (DEGs) were extracted from high‐ versus low‐immune/stromal score groups and were described using functional annotations and protein‒protein interaction (PPI) network.ResultsPatients in the high‐immune/stromal score group had poorer survival outcome. In total, 95 DEGs (48 upregulated and 47 downregulated genes) were screened from the gene expression profiles of patients with high immune and stromal scores. The genes were primarily involved in six signaling pathways. Among the 95 DEGs, 43 were markedly related to overall survival of patients. The PPI network identified the top 10 hub genes—CD19, CD79A, IL10, IGLL5, POU2AF1, CCL19, AMBP, CCL18, CCL21, and IGJ—and four modules. Enrichment analyses revealed that the genes in the most important module were involved in the B‐cell receptor signaling pathway.ConclusionThis study mainly revealed the relationship between the ccRCC microenvironment and prognosis of patients. These results also increase the understanding of how gene expression patterns can impact the prognosis and development of ccRCC by modulating the tumor microenvironment. The results could contribute to the search for ccRCC biomarkers and therapeutic targets.

HHLA2 and PD-L1 co-expression predicts poor prognosis in patients with clear cell renal cell carcinoma

BackgroundAlthough clear cell renal cell carcinoma (ccRCC) is well known as a highly immunogenic tumor, only a small subset of patients could benefit from current immunotherapy, which might be due...

The immune infiltration in clear cell Renal Cell Carcinoma and their clinical implications: A study based on TCGA and GEO databases.

The tumor immune microenvironment in clear cell Renal Cell Carcinoma (ccRCC) still remains poorly understood. Previous methods to study the tumor immune microenvironment have a limitation when accounting for the functionally distinct cell types. In this study, we investigated the differently infiltrated immune cells and their clinical significance in ccRCC for the purpose of shedding some important light on the complex immune microenvironment in ccRCC. The devolution algorithm (CIBERSORT) was applied to infer the proportion of 22 immune infiltrating cells based on gene expression profiles of ccRCC bulk tissue, which were downloaded from TCGA and GEO databases. As a result, we observed considerable differences in immune cells percentage between ccRCC tumor tissue and paired normal tissue; meanwhile, we uncovered their internal correlations and associations with Fuhrman grade. Moreover, dendritic cells resting, dendritic cells activated, mast cells resting, mast cells activated and eosinophils were associated with favorable prognosis, whereas B cells memory, T cells follicular helper and T cells regulatory (Tregs) were correlated with poorer outcome.

&lt;i&gt;PBRM1&lt;/i&gt; Mutation Recruits More Mast Cells by Upregulating CCL5 in a Clear Cell Renal Cell Carcinoma Tumor Microenvironment

Background: PBRM1 (Polybromo-1) is the second most frequently mutated gene in ccRCC (clear cell renal cell carcinoma), and loss of PBRM1 was correlated with advanced tumor and tyrosine kinase inhibitor or immune checkpoint inhibitor clinical therapy in previously reported studies. However, the mechanisms of PBRM1 mutation in tumor microenvironment characterization are poorly understood. Methods: We investigated the tumor microenvironment in ccRCC by estimating immune cells in malignant tumors using CIBERSORT and estimating stromal and immune cells in malignant tumors using an expression data (ESTIMATE) algorithm. Gene set enrichment analysis hierarchical clustering and weighted correlation network analysis were used to analyze the characteristics and clinicopathologic features of ccRCC. Mast cell recruitment assay, colony formation assay, cell cycle assay, ELISA, and tube formation assay were applied to test PBRM1 function in vitro. Findings: We discovered that ccRCC patients with PBRM1 mutations were associated with inhibited CD8 T-cell infiltration but more resting mast cells in the tumor microenvironment. Silenced PBRM1 improved mast cell recruitment, angiogenesis, and cell proliferation among ccRCC cells. The molecular mechanism involved the upregulation ofCCL5 levels through PBRM1 mutations. CCL5 evoked immune-related pathways [including interferon-inflammatory signaling, interferon-gamma signaling, and IL-6-JAK- STAT3 (interleukin-6-Janus kinase-signal transducers and activators of transcription 3)] and recruited more mast cells to the tumor microenvironment. Furthermore, we confirmed that vascular endothelial growth factor family genes are overexpressed and that hypoxia-inducible factor-related processes are activated. Interpretation: These results demonstrated that PBRM1 mutation-CCL5-mast cell infiltration plays a key role in ccRCC clinical therapy. Funding Statement: This study was supported by the National Natural Science Foundation of China (NSFC No. 81602244 to Shan Xu) and Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2017JM8018 to Shan Xu). Declaration of Interests: The authors stated: None. Ethics Approval Statement: Not required.

Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.