Immune checkpoint inhibitor-based therapy for advanced clear cell renal cell carcinoma: A narrative review

Prognosis and biological function of SGOL1 in clear cell renal cell carcinoma: a multiomics analysis

BACKGROUND

Shugoshin-1 (SGOL1) is a mammalian ortholog of Shugoshin in yeast and is essential for precise chromosome segregation during mitosis and meiosis. Aberrant SGOL1 expression was reported to be closely correlated with the malignant progression of various tumors. However, the expression pattern and biological function of SGOL1 in clear cell renal cell carcinoma (ccRCC) are unclear.

METHODS

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provide mRNA expression data and outcome information for ccRCC patients. Immunohistochemistry (IHC) of ccRCC tissue chips verified SGOL1 protein expression in ccRCC patients. Data processing and visualization were performed with the UALCAN, TISIDB, TIMER, GSCA, LinkedOmics, and starBase databases. Gene Ontology (GO) annotation and gene set enrichment analysis (GSEA) were used to identify SGOL1-related biological functions and signaling pathways. Immune infiltration analysis was performed using the TISIDB database, ssGSEA algorithm, and TCGA-KIRC cohort. The biological role of SGOL1 in ccRCC was investigated using a series of in vitro cytological assays, including the MTT assay, EdU staining assay, flow cytometry analysis, Transwell assay, and wound healing assay.

RESULTS

SGOL1 was highly expressed in ccRCC and linked to adverse clinicopathological parameters and unfavorable prognosis. Multivariate logistic regression and nomogram calibration suggested that SGOL1 might serve as an independent and reliable prognostic predictor of ccRCC. Functional enrichment analysis indicated that SGOL1 may be involved in the cell cycle, the p53 pathway, DNA replication, and T-cell activation. Furthermore, tumor microenvironment (TME) analysis suggested that SGOL1 was positively associated with Treg infiltration and immune checkpoint upregulation. In addition, we identified a potential SNHG17/PVT1/ZMIZ1-AS1-miR-23b-3p-SGOL1 axis correlated with ccRCC carcinogenesis and progression. Finally, we demonstrated that SGOL1 promoted ccRCC cell proliferation, migratory capacity, and invasion in vitro.

CONCLUSIONS

SGOL1 potentially functions as an oncogene in ccRCC progression and might contribute to the immunosuppressive TME by increasing Treg infiltration and checkpoint expression, suggesting that targeting SGOL1 could be a novel therapeutic strategy for the treatment of ccRCC patients.

Mechanisms of tyrosine kinase inhibitor resistance in renal cell carcinoma

Renal cell carcinoma (RCC), the most prevalent type of kidney cancer, is a significant cause of cancer morbidity and mortality worldwide. Antiangiogenic tyrosine kinase inhibitors (TKIs), in combination with immune checkpoint inhibitors (ICIs), are among the first-line treatment options for patients with advanced RCC. These therapies target the vascular endothelial growth factor receptor (VEGFR) tyrosine kinase pathway and other kinases crucial to cancer proliferation, survival, and metastasis. TKIs have yielded substantial improvements in progression-free survival (PFS) and overall survival (OS) for patients with advanced RCC. However, nearly all patients eventually progress on these drugs as resistance develops. This review provides an overview of TKI resistance in RCC and explores different mechanisms of resistance, including upregulation of alternative proangiogenic pathways, epithelial-mesenchymal transition (EMT), decreased intracellular drug concentrations due to efflux pumps and lysosomal sequestration, alterations in the tumor microenvironment including bone marrow-derived cells (BMDCs) and tumor-associated fibroblasts (TAFs), and genetic factors such as single nucleotide polymorphisms (SNPs). A comprehensive understanding of these mechanisms opens the door to the development of innovative therapeutic approaches that can effectively overcome TKI resistance, thereby improving outcomes for patients with advanced RCC.

Cuproptosis-related gene DLAT serves as a prognostic biomarker for immunotherapy in clear cell renal cell carcinoma: multi-database and experimental verification

OBJECTIVE

Renal clear cell carcinoma (ccRCC) is the most common type of renal cancer. Here we aim to explore the prognosis and immunotherapeutic value of copper death-related gene Dihydrolipoamide S-acetyltransferase (DLAT) in ccRCC.

METHODS

The mRNA and protein expressions and methylation level of DLAT, as well as the relation of DLAT to survival prognosis, clinical characteristics, biological function, and immune microenvironment and responses in patients with ccRCC were evaluated using multiple databases. In addition, 75 paired ccRCC tissue samples and 3 kinds of cell lines were tested for experimental validation.

RESULTS

Bioinformatics analysis of multiple databases, qRT-PCR, and western blot verified that DLAT expression in ccRCC was lower than that in paracancerous tissues. Patients with low expression of DLAT had a lower survival rate, worse clinical prognosis, stronger immune cell infiltration and expression of immunosuppressive points, and higher tumor immune dysfunction and exclusion (TIDE) scores.

CONCLUSIONS

DLAT was identified as an independent prognostic factor in ccRCC and was closely related to the prognosis and immune responses of patients with ccRCC.

Systematic analysis of RNASET2 gene as a potential prognostic and immunological biomarker in clear cell renal cell carcinoma

BACKGROUND

RNASET2 has been identified as an oncogene with anti-angiogenic and immunomodulatory effects in a variety of cancers, but its function in clear cell renal cell carcinoma (ccRCC) is still not well understood.

METHODS

The RNASET2 expression matrix was extracted from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets and analyzed for diagnostic and prognostic value. RNASET2 mRNA expression was detected by quantitative polymerase chain reaction (qPCR) in ccRCC patients and renal cancer cell lines. Wound healing assay, transwell assay, western blotting, and tube formation assays were used to evaluate the function of RNASET2 in renal cancer in vitro. In addition, transcriptome sequencing was performed on knockdown RNASET2 kidney cancer cells to analyze their potential signaling pathways. Moreover, the immune microenvironment and mutational status were evaluated to predict the potential mechanisms of RNASET2 involvement in renal cancer progression. Sensitivity to common chemotherapeutic and targeted agents was assessed according to the Genomics of Drug Sensitivity in Cancer (GDSC) database.

RESULTS

RNASET2 expression was significantly upregulated in ccRCC tissues and renal cancer cell lines, predicting poor prognosis for patients. In vitro experiments showed that silencing RNASET2 inhibited the migration and pro-angiogenic ability of renal cancer cells. Transcriptome sequencing suggested its possible involvement in the remodeling of the immune microenvironment in renal cell carcinoma. Furthermore, bioinformatics analysis and immunohistochemical staining showed that RNASET2 was positively correlated with the infiltration abundance of regulatory T cells. Finally, we mapped the mutational landscape of RNASET2 in ccRCC and found its predictive value for drug sensitivity.

CONCLUSIONS

Our results suggest that RNASET2 is a promising biomarker and therapeutic target in ccRCC.

Prognostic values of tissue-resident CD8+T cells in human hepatocellular carcinoma and intrahepatic cholangiocarcinoma

BACKGROUND

Tissue-resident CD8⁺T cells (CD103⁺CD8⁺T cells) are the essential effector cell population of anti-tumor immune response in tissue regional immunity. And we have reported that IL-33 can promote the proliferation and effector function of tissue-resident CD103⁺CD8⁺T cells. As of now, the immunolocalization and the prognostic values of tissue-resident CD8⁺T cells in human hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) still remain to be illustrated.

METHODS

In our present study, we used the tissue microarrays of HCC and ICC, the multicolor immunohistochemistry (mIHC), and imaging analysis to characterize the tissue-resident CD8⁺T cells in HCC and ICC tissues. The prognostic values and clinical associations were also analyzed. We also studied the biological functions and the cell-cell communication between tumor-infiltrating CD103⁺CD8⁺T cells and other cell types in HCC and ICC based on the published single-cell RNA sequencing (scRNA-seq) data.

RESULTS

Our work unveiled the expressions of CD8 and CD103 and immunolocalization of tissue-resident CD8⁺T cells in human HCC and ICC. Elevated CD8⁺T cells indicated a better overall survival (OS) rate, implying that tumor-infiltrating CD8⁺T cells in HCC and ICC could serve as an independent prognostic factor. Moreover, the number of CD103⁺CD8⁺T cells was increased in HCC and ICC tissues compared with adjacent normal tissues. HCC patients defined as CD8^highCD103^high had a better OS, and the CD8^lowCD103^low group tended to have a poorer prognosis in ICC. Evaluation of the CD103⁺CD8⁺T-cell ratio in CD8⁺T cells could also be a prognostic predictor for HCC and ICC patients. A higher ratio of CD103⁺CD8⁺T cells over total CD8⁺T cells in HCC tissues was negatively and significantly associated with the advanced pathological stage. The percentage of higher numbers of CD103⁺CD8⁺T cells in ICC tissues was negatively and significantly associated with the advanced pathological stage. In contrast, the higher ratio of CD103⁺CD8⁺T cells over total CD8⁺T cells in ICC tissues was negatively and significantly associated with the advanced pathological stage. In addition, single-cell transcriptomics revealed that CD103⁺CD8⁺T cells were enriched in genes associated with T-cell activation, proliferation, cytokine function, and T-cell exhaustion.

CONCLUSION

The CD103⁺ tumor-specific T cells signified an important prognostic marker with improved OS, and the evaluation of the tissue-resident CD103⁺CD8⁺T cells might be helpful in assessing the on-treatment response of liver cancer.

Immune Checkpoint Inhibitors in Renal Cell Carcinoma: Molecular Basis and Rationale for Their Use in Clinical Practice

Renal cell carcinoma (RCC) is the seventh most common cancer in men and the ninth most common cancer in women worldwide. There is plenty of evidence about the role of the immune system in surveillance against tumors. Thanks to a better understanding of immunosurveillance mechanisms, immunotherapy has been introduced as a promising cancer treatment in recent years. Renal cell carcinoma (RCC) has long been thought chemoresistant but highly immunogenic. Considering that up to 30% of the patients present metastatic disease at diagnosis, and around 20–30% of patients undergoing surgery will suffer recurrence, we need to identify novel therapeutic targets. The introduction of immune checkpoint inhibitors (ICIs) in the clinical management of RCC has revolutionized the therapeutic approach against this tumor. Several clinical trials have shown that therapy with ICIs in combination or ICIs and the tyrosine kinase inhibitor has a very good response rate. In this review article we summarize the mechanisms of immunity modulation and immune checkpoints in RCC and discuss the potential therapeutic strategies in renal cancer treatment.

SLC9A1 Binding mTOR Signaling Pathway-Derived Risk Score Predicting Survival and Immune in Clear Cell Renal Cell Carcinoma

Objective. Clear cell renal cell carcinoma (ccRCC) is one of the common renal cell carcinomas (RCC) with a high risk of recurrence. Considering that SLC9A1 is involved in various cellular physiological processes and probably mediates the course of mTOR signaling in tumors, this study constructed a risk model for SLC9A1 combined with mTOR signaling in ccRCC, aiming at better predicting the prognosis of patients. Methods. ccRCC expression matrices were downloaded from TCGA and ICGC databases to compare the expression of SLC9A1 in TCGA, and qRT-PCR was adopted to validate the SLC9A1 expression in different RCC cells and normal kidney cells. The CIBERSORT and ESTIMATE algorithms were used to assess samples for immunity. mTOR signaling-associated genes were downloaded from the KEGG website, and then the genes were adopted to screen genes associated with SLC9A1 expression and mTOR signaling pathway colleagues, based on which univariate COX regression and lasso regression Cox analyses were conducted to construct a ccRCC prognostic risk model. ROC curves and nomograms were used to assess the validity of the models. Results. ccRCC tumor samples showed lower SLC9A1 expression than normal samples, as also evidenced by qRT-PCR. The SLC9A1 expression was highly correlated with tumor immunity. Totally, 564 key genes associated with both SLC9A1 expression and mTOR signaling were screened out, and the risk model consisting of 11 gene signatures was constructed in ccRCC based on the 564 genes. Since patients at a high risk had poorer survival outcomes, the high-risk group presented poorer immunotherapy outcomes. Moreover, a higher clinical grade of patients suggested a higher risk score. The risk score can serve as one independent prognostic factor for the prognosis prediction of ccRCC patients. Conclusion. An extremely promising prognostic indicator for ccRCC based on SLCA9A1 and mTOR signaling has been constructed to provide reference for clinical treatment.

N6-methyladenosine (m6A) reader IGF2BP1 facilitates clear-cell renal cell carcinoma aerobic glycolysis

Emerging articles have reported that N⁶-methyladenosine (m⁶A) modification is mainly involved in clear-cell renal cell carcinoma (ccRCC) tumorigenesis. However, the regulatory mechanisms of m⁶A reader IGF2BP1 involved in ccRCC tumor energy metabolism are currently unknown. Results showed that the m⁶A reader IGF2BP1 exhibited significantly higher expression in ccRCC cells. Functionally, results by gain/loss functional assays indicated that IGF2BP1 promoted the glycolytic characteristics, including glucose uptake, lactate production and extracellular acidification rate (ECAR). Mechanistically, IGF2BP1 recognized the m⁶A modified sites on LDHA mRNA and enhanced its mRNA stability, thereby accelerating tumor energy metabolism. Thus, our work reveals a novel facet of the m⁶A that promoted mRNA stability and highlighted the functional importance of IGF2BP1 as m⁶A readers in post-transcriptional gene regulation.

Upregulation of CENPM is associated with poor clinical outcome and suppression of immune profile in clear cell renal cell carcinoma

BACKGROUND

The response of advanced clear cell renal cell carcinoma (ccRCC) to immunotherapy is still not durable, suggesting that the immune landscape of ccRCC still needs to be refined, especially as some molecules that have synergistic effects with immune checkpoint genes need to be explored.

METHODS

The expression levels of CENPM and its relationship with clinicopathological features were explored using the ccRCC dataset from TCGA and GEO databases. Quantitative polymerase chain reaction (qPCR) analysis was performed to validate the expression of CENPM in renal cancer cell lines. Kaplan-Meier analysis, COX regression analysis and Nomogram construction were used to systematically evaluate the prognostic potential of CENPM in ccRCC. Besides, single gene correlation analysis, protein-protein interaction (PPI) network, genetic ontology (GO), kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to predict the biological behaviour of CENPM and the possible signalling pathways involved. Finally, a comprehensive analysis of the crosstalk between CENPM and immune features in the tumor microenvironment was performed based on the ssGSEA algorithm, the tumor immune dysfunction and exclusion (TIDE) algorithm, the TIMER2.0 database and the TISIDB database.

RESULTS

CENPM was significantly upregulated in ccRCC tissues and renal cancer cell lines and was closely associated with poor clinicopathological features and prognosis. Pathway enrichment analysis revealed that CENPM may be involved in the regulation of the cell cycle in ccRCC and may have some crosstalk with the immune microenvironment in tumors. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. Furthermore, the TISIDB database provides evidence that not only CENPM is positively associated with immune checkpoint genes such as CTLA4, PDCD1, LAG3, TIGIT, but also chemokines and receptors (such as CCL5, CXCL13, CXCR3, CXCR5) may be responsible for the malignant phenotype of CENPM in ccRCC. Meanwhile, predictions based on the TIDE algorithm support that patients with high CENPM expression have a worse response to immunotherapy.

CONCLUSIONS

The upregulation of CENPM in ccRCC predicts a poor clinical outcome, and this malignant phenotype may be associated with its exacerbation of the immunosuppressive state in the tumor microenvironment.

Construction and Validation of a Novel Immune Checkpoint-Related Model in Clear Cell Renal Cell Carcinoma

Background

With the highest mortality and metastasis rate, kidney renal clear cell carcinoma (KIRC) is one of the most common urological malignant tumors and not sensitive to chemotherapy and radiotherapy. Immunotherapy, which proves to be effective and a big progression, such as PD-1/PD-L1 inhibitors, is not sensitive to all KIRC patients. To predict prognosis and immunotherapy response, a novel immune checkpoint gene- (ICG-) related model is essential in clinics.

Methods

From the public database-downloaded dataset, a novel ICG-related model for predicting prognosis and immunotherapy response in KIRC patients was built up and verified with R packages and Cox regression analysis. The Kaplan-Meier curve was plotted.

Results

39 ICGs were identified to have different expression in KIRC patients and enriched in immune-related biological pathways and activities. Three ICGs (CTLA4, TNFSF14, and HHLA2) were screened to generate KIRC-ICG model. The KIRC-ICG model was verified to be effective. With conducting KIRC-SYS model, KIRC-ICGscore was verified to be an independent factor regardless of age, gender, stage, grade, and TNM stage. Compared to the ICG-low subgroup, the ICG-high subgroup had more immune activities. KIRC-ICGscore was significantly positively correlated with the expression of Treg markers. KIRC-ICG model could also be reliable to predict immunotherapy response.

Conclusion

The KIRC-ICG model was reliable to predict prognosis and immunotherapy response for KIRC patients and could be an independent factor regardless of clinical characteristics.

Construction of a novel prognostic signature based on the composition of tumor-infiltrating immune cells in clear cell renal cell carcinoma

Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research. The ImmuCellAI tool was employed to estimate the abundance of 24 TIICs and further survival analysis explored the prognostic values of TIICs in ccRCC. In addition, the expression levels of immunosuppressive molecules (PDL1, PD1, LAG3, and CTLA4) in the high- and low-risk groups were explored. Various subtypes of TIICs had distinct infiltrating features and most TIICs exhibited dysregulated abundance between normal and tumor tissues. Moreover, specific kinds of TIICs had encouraging prognostic values in ccRCC. Further analysis constructed a 4-TIICs signature to evaluate the prognosis of ccRCC patients. Cox regression analyses confirmed the independent prognostic role of the signature in ccRCC. Moreover, immunosuppressive molecules, including PD1, LAG3, and CTLA4, were significantly upregulated in the high-risk group and predicted poor prognosis. However, PDL1 was not changed between high- and low-risk groups and could not predict poor prognosis. To sum up, our research explored the landscape of TIICs in ccRCC and established a novel 4-TIIC prognostic signature, which could effectively predict the prognosis for patients with ccRCC. Based on this signature, we also concluded that PDL1 may not predict prognosis in ccRCC.