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Identification of a Novel Stem Cell Subtype for Clear Cell Renal Cell Carcinoma Based on Stem Cell Gene Profiling.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and is characterized by high rates of metastasis. Cancer stem cell is a vital cause of renal cancer metastasis and recurrence. However, little is known regarding the change and the roles of stem cells during the development of renal cancer. To clarify this problem, we developed a novel stem cell clustering strategy. Based on The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) genomic datasets, we used 19 stem cell gene sets to classify each dataset. A machine learning method was used to perform the classification. We classified ccRCC into three subtypes-stem cell activated (SC-A), stem cell dormant (SC-D), and stem cell excluded (SC-E)-based on the expressions of stem cell-related genes. Compared with the other subtypes, C2(SC-A) had the highest degree of cancer stem cell concentration, the highest level of immune cell infiltration, a distinct mutation landscape, and the worst prognosis. Moreover, drug sensitivity analysis revealed that subgroup C2(SC-A) had the highest sensitivity to immunotherapy CTLA-4 blockade and the vascular endothelial growth factor receptor (VEGFR) inhibitor sunitinib. The identification of ccRCC subtypes based on cancer stem cell gene sets demonstrated the heterogeneity of ccRCC and provided a new strategy for its treatment.

SUBMITTER: Wang H

PROVIDER: S-EPMC8667732 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Gene expression profiling has been shown to provide prognostic information on patients with solitary sporadic renal cell carcinoma. To our knowledge there is no reliable way to differentiate synchronous renal metastasis from bilateral primary tumors in patients with bilateral renal cell carcinoma. We present data using a custom kidney cancer cDNA array that can predict the outcome in patients with unilateral and bilateral renal cell carcinoma.Fresh frozen tissue from 38 clear cell renal cell carcinomas was analyzed using a cancer cDNA array containing 3,966 genes relevant to cancer or kidney development. Median followup was 5.3 years. Cancer recurred in 12 patients (43%) and 11 (39%) had died by the last followup.Using a training data set of 8 tumors a 44 gene expression profile distinguishing aggressive and indolent clear cell renal cell carcinoma was identified. Of 29 single clear cell renal cell carcinomas 16 and 13 were predicted to be indolent and aggressive, respectively, by the gene expression profile. Recurrence-free survival at 5 years was 68% and 42% in these 2 groups, respectively (p = 0.032). Clear cell renal cell carcinoma classified as indolent or aggressive according to SSIGN (stage, size, grade and necrosis) score showed a 5-year recurrence-free survival rate of 78% and 42%, respectively (p = 0.021). On Cox proportional hazards analysis the gene expression profile was not an independent predictor of recurrence-free survival after accounting for SSIGN score. Gene expression profile classification correlated with cancer specific survival at 5 years in 4 of 4 patients with metachronous clear cell renal cell carcinoma but in only 2 of 4 with bilateral synchronous clear cell renal cell carcinoma.Gene expression profiling using a kidney cancer relevant cDNA array can differentiate between aggressive and indolent clear cell renal cell carcinomas. Gene expression profile results may be most useful for unilateral clear cell renal cell carcinoma when results are discordant with predictions of tumor behavior based on standard clinicopathological features. In addition, gene expression profiling can provide prognostic information that may help characterize tumors of unknown clinical stage, such as bilateral metachronous clear cell renal cell carcinoma.

Project description:BackgroundManagement of clear cell renal cell carcinoma (ccRCC) has changed rapidly in recent years with the advent of immune checkpoint inhibitors (ICIs). However, only a limited number of patients can sustainably respond to immune checkpoint inhibitors and many patients develop resistance to therapy, creating an additional need for therapeutic strategies to improve the efficacy of systemic therapies.MethodsBinding probability and target genes prediction using online databases, invasion, migration, and apoptosis assays as well as the inhibition of cancer stem cells (CSCs) markers in ccRCC cell lines were used to select the most promising phytochemicals (PTCs). Mixed lymphocyte tumor cell culture (MLTC) system and flow cytometry were performed to confirm the potential combination strategy. The potential immunotherapeutic targets and novel CSC markers were identified via the NanoString analysis. The mRNA and protein expression, immune signatures as well as survival characteristics of the marker in ccRCC were analyzed via bioinformation analysis.ResultsShikonin was selected as the most promising beneficial combination partner among 11 PTCs for ipilimumab for the treatment of ccRCC patients due to its strong inhibitory effect on CSCs, the significant reduction of FoxP3+ Treg cells in peripheral blood mononuclear cells (PBMCs) of patients and activation of the endogenous effector CD3+CD8+ and CD3+CD4+ T cells in response to the recognition of tumor specific antigens. Based on NanoString analysis VCAM1, CXCL1 and IL8 were explored as potential immunotherapeutic targets and novel CSC markers in ccRCC. The expression of VCAM1 was higher in the tumor tissue both at mRNA and protein levels in ccRCC compared with normal tissue, and was significantly positively correlated with immune signatures and survival characteristics in ccRCC patients.ConclusionWe propose that a combination of shikonin and ipilimumab could be a promising treatment strategy and VCAM1 a novel immunotherapeutic target for the treatment of ccRCC.

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Identification of a Novel Stem Cell Subtype for Clear Cell Renal Cell Carcinoma Based on Stem Cell Gene Profiling.

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