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Single-cell deconvolution of a specific malignant cell population as a poor prognostic biomarker in low-risk clear cell renal cell carcinoma patients

ABSTRACT: BACKGROUND: Intra-tumor heterogeneity (ITH) is a key feature in clear-cell renal cell carcinomas (ccRCCs) which impacts outcomes such as aggressiveness, response to treatments or recurrence. In particular, it may explain tumor relapse after surgery in clinically low-risk patients who did not benefit from adjuvant therapy. Recently, single-cell RNA-seq (scRNA-seq) has emerged as a powerful tool to unravel expression intra-tumor heterogeneity (eITH) and might enable better assessment of clinical outcomes in ccRCC. OBJECTIVE: To explore eITH in ccRCC with a focus on malignant cells (MCs), and assess its relevance to improve prognosis for low-risk patients. RESULTS AND LIMITATIONS: We analyzed 54,812 cells and identified 35 cell subpopulations. The eITH analysis revealed that each tumor contained various degrees of clonal diversity. The transcriptomic signatures of MCs in one particularly heterogeneous sample were used to design a deconvolution-based strategy which allowed to risk-stratify 310 low-risk ccRCC patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE224630 | GEO | 2023/02/09

REPOSITORIES: GEO

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Quantitative proteomics identifies secreted diagnostic biomarkers as well as tumor-dependent prognostic targets for clear cell Renal Cell Carcinoma

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Expression data from spatially separated samples of different ccRCC patients

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2015-08-01 | E-GEOD-66741 | biostudies-arrayexpress

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2014-01-06 | E-GEOD-53000 | biostudies-arrayexpress

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Project description:Here we characterize an association between disease progression and DNA methylation in Diffuse Large B cell Lymphoma (DLBCL). By profiling genome-wide DNA methylation at single base-pair resolution in thirteen DLBCL diagnosis-relapse sample pairs, we show DLBCL patients exhibit heterogeneous evolution of tumor methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse–associated methylation signature converging on key pathways such as transforming growth factor beta (TGF-beta) receptor activity. We also observe decreased intra-tumor methylation heterogeneity from diagnosis to relapsed tumor samples. Relapse-free patients display lower intra-tumor methylation heterogeneity at diagnosis compared to relapsed patients in an independent validation cohort. Furthermore, intra-tumor methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse. Using ERRBS, we profiled genome-wide DNA methylation patterns of non-relapse DLBCL tumor samples at diagnosis, relaspe DLBCL patient samples at diagnosis and relaspe.

2015-04-14 | E-GEOD-66329 | biostudies-arrayexpress

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Global and targeted microRNA expression profiling in clear cell renal cell carcinoma tissues potentially links miR-155-5p and miR-210-3p to both tumorigenesis and recurrence [discovery phase]

Project description:About 30% of renal cell carcinoma (RCC) patients undergoing nephrectomy experience disease recurrence. This study aimed to profile microRNAs (miRNAs) that are dysregulated in clear cell RCC (ccRCC) tumor tissues and predictive of recurrence. The expression levels of 800 miRNAs were assessed in paired tumor and normal tissues from a discovery cohort of 18 ccRCC patients via the NanoString assay platform. MiRNAs found to be differentially expressed were further examined in a validation set of 205 patients using quantitative real-time PCR. Tumor-normal data from 64 patients in The Cancer Genome Atlas were used for external validation. Results showed 28 miRNAs were consistently dysregulated in tumor tissues. Dichotomized analyses indicated patients with high levels of miR-155-5p and miR-210-3p displayed increased risk of ccRCC recurrence (HR, 2.64; 95% CI, 1.49-4.70; P=0.0009 and HR, 1.8; 95% CI, 1.04-3.12; P=0.036, respectively) and shorter median recurrence-free survival times than patients with low levels (log rank test P<0.01). A risk score was generated based on expression levels of miR-155-5p and miR-210-3p, and the trend test was significant (P for trend=0.005). Pathway analysis revealed target genes regulated by miR-155-5p and miR-210-3p were mainly enriched in inflammation-related pathways. In summary, we identified and validated multiple miRNAs dysregulated in ccRCC tissues. MiR-155-5p and miR-210-3p were predictive of ccRCC recurrence pointing to potential utility as biomarkers and underlying biological mechanisms.

2018-10-04 | GSE116251 | GEO

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Project description:Purpose: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Thirty percent of patients with localized ccRCC develop metastases during follow-up. Although current scoring methods correctly identify patients at low progression risk, a small subgroup still experiences metastatization. We therefore aimed to identify ccRCC progression biomarkers in “low-risk” patients, potentially eligible for adjuvant treatments. Methods: We performed next-generation sequencing of RNA from formalin-fixed samples obtained at initial surgery from 8 “low-risk” patients with progressing tumours and 16 patients with similar Leibovich score, tumour stage and size, creatinine levels and surgical treatment, not progressing to recurrence with metastasis. Key results were confirmed with qPCR, immunohistochemistry and in external data. Results: Principal component analysis indicates that systematic transcriptomic differences are detectable at the time of initial surgery. 1167 genes, related to cancer and immune-related pathways, were differentially expressed between progressors and non-progressors. Search for a classifier revealed that overexpression of AGAP2-AS1, an antisense long non-coding RNA, alone, correctly classified 23 of 24 samples without requiring larger gene panels. AGAP2-AS1 gene overexpression was confirmed by qPCR (p <0.05) and correlated with shorter progression-free survival (p: <0.0005). Immunohistochemistry confirmed upregulation at the protein level of AGAP2. Conclusion: AGAP2-AS1 may represent a novel biomarker identifying high risk patients currently classified as “low risk” at the time of surgery.

2021-12-29 | GSE171955 | GEO

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