Single-Cell RNA-seq Identification of the Cellular Molecular Characteristics of Sporadic Bilateral Clear Cell Renal Cell Carcinoma

Distinct molecular profiles and shared drug vulnerabilities in pancreatic metastases of renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is the most common origin of pancreatic metastases (PM). Distinct genomic aberrations, favorable prognosis, and clinical observations on high angiogenesis, and succeeding tyrosine kinase inhibitor (TKI) sensitivity have been reported in PM-ccRCC. However, no functional or single-cell studies have been conducted thus far. We recruited five PM-ccRCC patients and investigated the genomic, single-cell transcriptomic, and drug sensitivity profiles of their patient-derived cells (PDCs). The PM depicted both expected and novel genomic alterations. Further, the transcriptomics differed from both primary and metastatic ccRCC, with upregulations of the PI3K/mTOR and - supporting the clinical observations - angiogenesis pathways. Data integration at pathway level showed that transcriptomics explained drug sensitivities the best. Accordingly, PM-ccRCC PDCs shared sensitivity to many PI3K/mTOR inhibitors. Altogether, we show distinct genomic and transcriptomic signatures in PM-ccRCC, highlight the superiority of transcriptomics in interpreting drug sensitivities, and encourage the use of TKIs and PI3K/mTOR inhibitors in PM-ccRCC.

Potential protumor function of CD74 in clear cell renal cell carcinoma

CD74 is a transmembrane protein that functions as a specialized chaperone of HLA class II and CD74 in tumor cells was suggested to be involved in cell proliferation in several kinds of malignant tumors. CD74 is also known to be expressed in macrophages, therefore, we investigated the CD74 expression in clear cell renal cell carcinoma (ccRCC). Immunohistochemistry of CD74 indicated that CD74 was expressed not only in cancer cells but also macrophages. CD74 was detected in surface membrane and cytoplasm of cancer cells in 92 of 94 cases (98%) and of 87 of 94 cases (93%). CD74 was expressed both in cancer cells and TAMs in 86 of 94 cases (91%). In vitro studies using cancer cell lines and monocyte-derived macrophages stimulated by anti-CD74 antibodies showed that CD74 signal accelerated cancer cell proliferation and macrophage activation. However, macrophage activation via CD74 signal did not influence macrophage-mediated cancer cell growth. RNA-sequence of macrophages stimulated by anti-CD74 antibodies indicated that CD74 signal was associated to inflammatory responses in macrophages. In conclusion, we examined the expression and functional significance of CD74 in ccRCC using tissue specimens and cell culture studies. The function of CD74 was suggested to be different in cancer cells and in macrophages, and further studies are necessary to clarify the functional significance of CD74 in ccRCC.

Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma

BACKGROUND

The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded.

METHODS

A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays.

RESULTS

The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays.

CONCLUSION

The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.

MMPs-related risk model identification and SAA1 promotes clear cell renal cell carcinoma migration via ERK-AP1-MMPs axis

Matrix Metalloproteinases (MMPs) have been demonstrated to be essential in facilitating the migration and metastasis of clear cell renal cell carcinoma (ccRCC). However, the ability of the MMP family to predict clinical outcomes and guide optimal therapeutic strategies for ccRCC patients remains incompletely understood. In this investigation, we initially conducted a thorough examination of the MMP family in pan-cancer. Notably, MMPs exhibited distinctive significance in ccRCC. Following this, we undertook an extensive analysis to evaluate the clinical value of MMPs and potential mechanisms by which MMPs contribute to the progression of ccRCC. A novel stratification method and prognostic model were developed based on MMPs in order to enhance the accuracy of prognosis prediction for ccRCC patients and facilitate personalized treatment. By conducting multi-omics analysis and transcriptional regulation analysis, it was hypothesized that SAA1 plays a crucial role in promoting ccRCC migration through MMPs. Subsequently, in vitro experiments confirmed that SAA1 regulates ccRCC cell migration via the ERK-AP1-MMPs axis. In conclusion, our study has explored the potential value of the MMP family as prognostic markers for ccRCC and as guides for medication regimens. Additionally, we have identified SAA1 as a crucial factor in the migration of ccRCC.

A new insight of immunosuppressive microenvironment in osteosarcoma lung metastasis

The lung is the primary organ for the metastasis of osteosarcoma. Although the application of neoadjuvant chemotherapy and surgery has remarkably improved the survival rate of patients with osteosarcoma, prognosis is still poor for those patients with metastasis. In this study, we performed further bioinformatics analysis on single-cell RNA sequencing (scRNA-seq) data published before, containing 75,317 cells from two osteosarcoma lung metastasis and five normal lung tissues. First, we classified 17 clusters, including macrophages, T cells, endothelial cells, and so on, indicating highly intratumoral heterogeneity in osteosarcoma lung metastasis. Next, we found macrophages in osteosarcoma lung metastasis did not have significant M1 or M2 polarizations. Then, we identified that T cells occupied the most abundant among all cell clusters, and found CD8+ T cells exhibited a low expression level of immune checkpoints in osteosarcoma lung metastasis. What is more, we identified C2_Malignant cells, and found CD63 might play vital roles in determining the infiltration of T cells and malignant cells in conventional-type osteosarcoma lung metastasis. Finally, we unveiled C1_Therapeutic cluster, a subcluster of malignant cells, was sensitive to oxfendazole and mevastatin, and the potential hydrogen-bond position and binding energy of oxfendazole-KIAA0907 and mevastatin-KIAA0907 were unveiled, respectively. Our results highlighted the power of scRNA-seq technique in identifying the complex tumor microenvironment of osteosarcoma lung metastasis, making it possible to devise precision therapeutic approaches.

Integrative Single-Cell Analysis Reveals Transcriptional and Epigenetic Regulatory Features of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC.

SIGNIFICANCE

A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

A novel lipid metabolism gene signature for clear cell renal cell carcinoma using integrated bioinformatics analysis

Background: Clear cell renal cell carcinoma (ccRCC), which is the most prevalent type of renal cell carcinoma, has a high mortality rate. Lipid metabolism reprogramming is a hallmark of ccRCC progression, but its specific mechanism remains unclear. Here, the relationship between dysregulated lipid metabolism genes (LMGs) and ccRCC progression was investigated. Methods: The ccRCC transcriptome data and patients' clinical traits were obtained from several databases. A list of LMGs was selected, differentially expressed gene screening performed to detect differential LMGs, survival analysis performed, a prognostic model established, and immune landscape evaluated using the CIBERSORT algorithm. Gene Set Variation Analysis and Gene set enrichment analysis were conducted to explore the mechanism by which LMGs affect ccRCC progression. Single-cell RNA-sequencing data were obtained from relevant datasets. Immunohistochemistry and RT-PCR were used to validate the expression of prognostic LMGs. Results: Seventy-one differential LMGs were identified between ccRCC and control samples, and a novel risk score model established comprising 11 LMGs (ABCB4, DPEP1, IL4I1, ENO2, PLD4, CEL, HSD11B2, ACADSB, ELOVL2, LPA, and PIK3R6); this risk model could predict ccRCC survival. The high-risk group had worse prognoses and higher immune pathway activation and cancer development. Conclusion: Our results showed that this prognostic model can affect ccRCC progression.

The Infiltration of Neutrophil Granulocytes Due to Loss of PTEN Was Associated with Poor Response to Immunotherapy in Renal Cell Carcinoma

Introduction

A primary impediment to the efficacy of immune checkpoint inhibitors is the lack of biomarkers for therapeutic responses and prognosis. Although patients with clear cell renal cell carcinoma (ccRCC) could be precisely selected for targeted therapy based on somatic mutations, it remains controversial to choose the suitable patients with a high response rate to immune checkpoint inhibitors (ICIs). The immune-dependent roles of tumor suppressor PTEN in the formation of tumor immune microenvironment remain elusive.

Methods

We comprehensively analyzed the genomic and transcriptomic data from multiple ccRCC datasets, including bulk-RNA sequencing and single-cell RNA sequencing data. In vitro, immunoblotting, qRT-PCR, and RNA sequencing were conducted in ccRCC cell lines upon PTEN depletion. Gene ontology and gene set enrichment analysis were performed to screen the critical pathway and molecules in response to PTEN deletion. Immunohistochemistry staining and further bioinformatic analysis were used to validate our data.

Results

Based on multi-omics analysis of public datasets of renal cancer, the frequently mutated or deleted PTEN was found to be correlated with a suppressive tumor immune microenvironment in ccRCC. Furthermore, we depleted PTEN via CRISPR-Cas9 in Caki-1 cells, which led to the upregulation of multiple neutrophil chemokines, particularly CXCL1, CXCL2, CXCL5, CXCL6, and CXCL8. The roles of neutrophil chemokines and neutrophil markers were further validated and investigated for the association with prognosis in vitro, clinical samples, and the publicly available databases. The expression of CXCL1, CXCL8, and neutrophil markers, S100A9 and BCL2A1, were significantly associated with a poor immunotherapy-related prognosis in public dataset of renal cancer patients receiving ICIs treatment.

Conclusion

These results add a new layer to understanding the association between PTEN status and the role of neutrophil infiltration in ccRCC. Moreover, our findings propose low expression of PTEN as candidate factor of resistance to anti-PD-1-based immunotherapy in ccRCC.

Single-Cell RNA Sequencing of Metastatic Testicular Seminoma Reveals the Cellular and Molecular Characteristics of Metastatic Cell Lineage

Background

Testicular cancer is the most common solid malignancy in young men. Given the many histological classifications of testicular tumors, seminoma is one of the most treatable cancers. The survival rate in early-stage disease was more than 90%. Thus, seminoma at the cellular and molecular levels, especially at the single-cell level, is worth studying.

Methods

We performed a single-cell RNA sequencing (scRNA-seq) study on a patient who was diagnosed with testicular seminoma with lymph node metastasis. This study presented tumor tissue, PBMC, pelvic and renal hilus lymph node in a total of 18,206 high-quality single-cell transcriptome information. The characteristics of metastatic cell lineage were revealed by the comparison between different tumor cell subtypes at the scRNA level.

Results

A single-cell map of testicular seminoma with lymph node metastasis was constructed by scRNA-seq. We discovered the gene expression characteristics of the tumor cells in testicular seminoma, especially metastatic tumor cells. KRT8 and KRT18 were commonly expressed in the three tumor cell subtypes. However, TCF7L1, SCG3 and SV2C were the specifically expressed genes of tumor cell subtypes in primary tumor sites. Some molecular markers specifically expressed by the metastatic cell lineage, such as POU5F1, were identified.

Conclusions

We revealed the molecular characteristics of testicular seminoma at the single-cell level, especially the metastatic tumor cells. This study could provide new insights into the diagnosis and treatment of testicular seminoma.

Updates on Immunotherapy and Immune Landscape in Renal Clear Cell Carcinoma

Several clinicopathological features of clear cell renal cell carcinomas (ccRCC) contribute to make an "atypical" cancer, including resistance to chemotherapy, sensitivity to anti-angiogenesis therapy and ICIs despite a low mutational burden, and CD8+ T cell infiltration being the predictor for poor prognosis-normally CD8+ T cell infiltration is a good prognostic factor in cancer patients. These "atypical" features have brought researchers to investigate the molecular and immunological mechanisms that lead to the increased T cell infiltrates despite relatively low molecular burdens, as well as to decipher the immune landscape that leads to better response to ICIs. In the present study, we summarize the past and ongoing pivotal clinical trials of immunotherapies for ccRCC, emphasizing the potential molecular and cellular mechanisms that lead to the success or failure of ICI therapy. Single-cell analysis of ccRCC has provided a more thorough and detailed understanding of the tumor immune microenvironment and has facilitated the discovery of molecular biomarkers from the tumor-infiltrating immune cells. We herein will focus on the discussion of some major immune cells, including T cells and tumor-associated macrophages (TAM) in ccRCC. We will further provide some perspectives of using molecular and cellular biomarkers derived from these immune cell types to potentially improve the response rate to ICIs in ccRCC patients.

Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers

Background

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq).

Methods

We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level.

Results

Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC.

Conclusions

Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.

Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches.

METHODS

Transcriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets.

RESULTS

In the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of ALDOB, EFHD1, and ESRRG in different cell types of ccRCC.

CONCLUSIONS

The present results demonstrated that ALDOB, EFHD1, and ESRRG may act as potential targets for medical therapy and could serve as diagnostic biomarkers for ccRCC.