Project description:BackgroundRecently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).MethodsWe used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.ResultThrough LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0-21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2-7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9-10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.ConclusionsOur study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.
Project description:Renal inflammation is an initial pathological process during progressive renal injury regardless of the initial cause. Macrophage migration inhibitory factor (MIF) is a truly proinflammatory stress mediator that is highly expressed in a variety of both inflammatory cells and intrinsic kidney cells. MIF is released from the diseased kidney immediately upon stimulation to trigger renal inflammation by activating macrophages and T cells, and promoting the production of proinflammatory cytokines, chemokines, and stress molecules via signaling pathways involving the CD74/CD44 and chemokine receptors CXCR2, CXCR4, and CXCR7 signaling. In addition, MIF can function as a stress molecule to counter-regulate the immunosuppressive effect of glucocorticoid in renal inflammation. Given the critical position of MIF in the upstream inflammatory cascade, this review focuses on the regulatory role and molecular mechanisms of MIF in kidney diseases. The therapeutic potential of targeting MIF signaling to treat kidney diseases is also discussed.
Project description:Detailed genetic profiling of clear cell Renal Cell Carcinoma (ccRCC) has shown that these tumors are characterized by large genetic heterogeneity with some genomic regions commonly affected by structural changes. Loss on chromosomes 3p and 14q, and gain on 5q and 7 are examples of alterations commonly reported in ccRCC. However, there is no consensus regarding the potential prognostic information carried by the identified alterations. We report on poorer outcome for patients with gain on 5q and 7, and loss on 9p, 9q and 14q. These aberrations were in addition found more frequently in metastasized tumors, suggesting that they are markers for advanced disease. Furthermore, the presence of M-bM-^IM-% 4 common aberrations was associated with decreased survival time. Shorter relative telomere length (RTL) has been associated with loss of chromosomal regions in ccRCC tumors, but we found no significant associations between tumor RTL and chromosomal deletions. However, significantly lower tumor-to-nontumor (T/N) RTL ratio was detected for patients with loss on 4q and 9p. Finally, we found a minimum region (MR) of genetic loss of 1.4 Mbp on chromosome 9p and this region contains only one gene, the tumor suppressor candidate 1 gene (TUSC1). TUSC1 has been implicated in lung carcinogenesis and our result further strengthens its role in tumorigenesis. Seventy-four ccRCC tumors and 22 paired normal kidney cortex and blood samples were genotyped on Illuminas HumanCytoSNP-12 bead chips.
Project description:Detailed genetic profiling of clear cell Renal Cell Carcinoma (ccRCC) has shown that these tumors are characterized by large genetic heterogeneity with some genomic regions commonly affected by structural changes. Loss on chromosomes 3p and 14q, and gain on 5q and 7 are examples of alterations commonly reported in ccRCC. However, there is no consensus regarding the potential prognostic information carried by the identified alterations. We report on poorer outcome for patients with gain on 5q and 7, and loss on 9p, 9q and 14q. These aberrations were in addition found more frequently in metastasized tumors, suggesting that they are markers for advanced disease. Furthermore, the presence of ≥ 4 common aberrations was associated with decreased survival time. Shorter relative telomere length (RTL) has been associated with loss of chromosomal regions in ccRCC tumors, but we found no significant associations between tumor RTL and chromosomal deletions. However, significantly lower tumor-to-nontumor (T/N) RTL ratio was detected for patients with loss on 4q and 9p. Finally, we found a minimum region (MR) of genetic loss of 1.4 Mbp on chromosome 9p and this region contains only one gene, the tumor suppressor candidate 1 gene (TUSC1). TUSC1 has been implicated in lung carcinogenesis and our result further strengthens its role in tumorigenesis.
Project description:While concurrent diagnoses of Merkel cell carcinoma (MCC) and other cancers, like Chronic lymphocytic leukemia (CLL), are rare, patients with MCC have a 30-fold higher incidence of CLL. While these increases have been attributed to the ability of CLL to suppress immune responses allowing for the emergence of MCC, here we found evidence that MCC could support the persistence of CLL. Using single cell sequencing approaches and computational analyses of MCC and CLL from a patient where both cancers were present in the same lymph node, we found that production of macrophage migration inhibitory factor (MIF) by MCC could promote the persistence of CLL through stimulation of CD74 and CXCR4. These results may explain why blood cell counts rapidly normalized after treatment for MCC and were maintained at normal levels despite the absence of treatment for CLL.
Project description:Background: Cuprotosis is a new form of programmed cell death induced by copper. We explored the correlation of cuprotosis with clear cell renal cell carcinoma (ccRCC) and constructed a cuprotosis-related signature to predict the prognosis of patients with ccRCC. Methods: The clinical and transcriptomic data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA), cBioPortal, and GEO databases, and cuprotosis-related gene sets were contained in the previous study. A cuprotosis-related signature was developed based on data from TCGA and verified by data from cBioPortal and GEO databases. The immune cell infiltrates and the corresponding signature risk scores were investigated. Two independent cohorts of clinical trials were analyzed to explore the correlation of the signature risk score with immune therapy response. Results: A signature containing six cuprotosis-related genes was identified and can accurately predict the prognosis of ccRCC patients. Patients with downregulated copper-induced programmed death had a worse overall survival (hazard ratio: 1.90, 95% CI: 1.39-2.59, p < 0.001). The higher signature risk score was significantly associated with male gender (p = 0.026), higher tumor stage (p < 0.001), and higher histological grade (p < 0.001). Furthermore, the signature risk score was positively correlated with the infiltration of B cells, CD8+ T cells, NK cells, Tregs, and T cells, whereas it was negatively correlated with eosinophils, mast cells, and neutrophils. However, no correlation between cuprotosis and response to anti-PD-1 therapy was found. Conclusion: We established a cuprotosis signature, which can predict the prognosis of patients with ccRCC. Cuprotosis was significantly correlated with immune cell infiltrates in ccRCC.
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we use fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors reveals a distinct transcriptional signature that is predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrates vascular remodeling within the endothelial cells. An in silico cell-to-cell interaction analysis highlights the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment.
Project description:Clear-cell renal-cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma (RCC), accounting for about 80% of RCC. In order to find potential prognostic biomarkers in ccRCC, we presented a four-gene signature to evaluate the prognosis of ccRCC. SurvExpress and immunohistochemical (IHC) staining of tissue microarrays were used to analyze the association between the four genes and the prognosis of ccRCC. Data from TCGA dataset revealed a prognostic prompt function of the four genes (PTEN, PIK3C2A, ITPA and BCL3). Further discovery suggested that the four-gene signature predicted survival better than any of the four genes alone. Moreover, IHC staining demonstrated a consistent result with TCGA, indicating that the signature was an independent prognostic factor of survival in ccRCC. Univariate and multivariate Cox proportional hazard regression analysis were conducted to verify the association of clinicopathological variables and the four genes' expression levels with survival. The results further testified that the risk (four-gene signature) was an independent prognostic factors of both Overall Survival (OS) and Disease-free Survival (DFS) (P<0.05). In conclusion, the four-gene signature was correlated with the survival of ccRCC, and therefore, may help to provide significant clinical implications for predicting the prognosis of patients.
Project description:Clear-cell renal cell carcinoma (ccRCC) is the major renal cell carcinoma subtype, but its postsurgical prognosis varies among individual patients.We used gene expression, machine learning (random forest variable hunting), and Cox regression analysis to develop a risk score model based on 15 genes to predict survival of patients with ccRCC in the The Cancer Genome Atlas dataset (N?=?533). We validated this model in another cohort, and analyzed correlations between risk score and other clinical indicators.Patients in the high-risk group had significantly worse overall survival (OS) than did those in the low-risk group (P?=?5.6e-16); recurrence-free survival showed a similar pattern. This result was reproducible in another dataset, E-MTAB-1980 (N?=?101, P?=?.00029). We evaluated correlations between risk score and other clinical indicators. Risk was independent of age and sex, but was significantly associated with hemoglobin level, primary tumor size, and grade. Radiation therapy also had no effect on the prognostic value of the risk score. Cox multivariate regression showed risk score to be an important indicator for ccRCC prognosis. We plotted a nomogram for 3-year OS to facilitate use of risk score and other indicators.The risk score model based on expression of the 15 selected genes can predict survival of patients with ccRCC.
Project description:In this retrospective analysis, we evaluated associations between albumin to globulin ratio (AGR), clinicopathological characteristics, and survival in 592 patients with localized or locally advanced clear cell renal cell carcinoma (CCRCC) prior to nephrectomy. We found that low AGR was associated with more aggressive tumor behavior; patients with low AGR had poorer overall survival (OS) and cancer-specific survival (CSS) in Kaplan-Meier survival analyses both before and after propensity score matching, which was used to compensate for differences in baseline clinicopathological characteristics. AGR was an independent prognostic factor for both OS (HR: 6.799; 95% CI: 3.215-14.377; P < 0.001) and CSS (HR: 8.806; 95% CI: 3.891-19.928; P < 0.001), and its prognostic value was higher than that of other established inflammation-based prognostic scores. When AGR was incorporated into a prognostic model that included T stage, neutrophil to lymphocyte ratio (NLR), and monocyte to lymphocyte ratio (MLR), the resulting nomogram predicted 3- and 5-year OS in the patients more accurately than when AGR was not included. In conclusion, AGR may be particularly useful for improving clinical outcome predictions for patients with localized or locally advanced CCRCC.