Determinants of anti-PD-1 response and resistance in clear cell renal cell carcinoma

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

The cuproptosis-associated 13 gene signature as a robust predictor for outcome and response to immune- and targeted-therapies in clear cell renal cell carcinoma

Cuproptosis, the newly identified form of regulatory cell death (RCD), results from mitochondrial proteotoxic stress mediated by copper and FDX1. Little is known about significances of cuproptosis in oncogenesis. Here we determined clinical implications of cuproptosis in clear cell renal cell carcinoma (ccRCC). Based on the correlation and survival analyses of cuproptosis-correlated genes in TCGA ccRCC cohort, we constructed a cuproptosis-associated 13 gene signature (CuAGS-13) score system. In both TCGA training and two validation cohorts, when patients were categorized into high- and low-risk groups according to a median score as the cutoff, the CuAGS-13 high-risk group was significantly associated with shorter overall survival (OS) and/or progression-free survival (PFS) independently (P<0.001 for all). The CuAGS-13 score assessment could also predict recurrence and recurrence-free survival of patients at stage I - III with a high accuracy, which outperformed the ccAccB/ClearCode34 model, a well-established molecular predictor for ccRCC prognosis. Moreover, patients treated with immune checkpoint inhibitors (ICIs) acquired complete/partial remissions up to 3-time higher coupled with significantly longer PFS in the CuAGS-13 low- than high-risk groups in both training and validation cohorts of ccRCCs (7.2 - 14.1 vs. 2.1 - 3.0 months, P<0.001). The combination of ICI with anti-angiogenic agent Bevacizumab doubled remission rates in CuAGS-13 high-risk patients while did not improve the efficacy in the low-risk group. Further analyses showed a positive correlation between CuAGS-13 and TIDE scores. We also observed that the CuAGS-13 score assessment accurately predicted patient response to Sunitinib, and higher remission rates in the low-risk group led to longer PFS (Low- vs. high-risk, 13.9 vs. 5.8 months, P = 5.0e-12). Taken together, the CuAGS-13 score assessment serves as a robust predictor for survival, recurrence, and response to ICIs, ICI plus anti-angiogenic drugs and Sunitinib in ccRCC patients, which significantly improves patient stratifications for precision medicine of ccRCC.

TMEM92 acts as an immune-resistance and prognostic marker in pancreatic cancer from the perspective of predictive, preventive, and personalized medicine

Background

Pancreatic cancer presents extremely poor prognosis due to the difficulty of early diagnosis, low resection rate, and high rates of recurrence and metastasis. Immune checkpoint blockades have been widely used in many cancer types but showed limited efficacy in pancreatic cancer. The current study aimed to evaluate the landscape of tumor microenvironment (TME) of pancreatic cancer and identify the potential markers of prognosis and immunotherapy efficacy which might contribute to improve the targeted therapy strategy and efficacy in pancreatic cancer in the context of predictive, preventive, and personalized medicine (PPPM).

Methods

In the current study, a total of 382 pancreatic samples from the datasets of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were selected. LM22 gene signature matrix was applied to quantify the fraction of immune cells based on "CIBERSORT" algorithm. Weighted Gene Co-expression Network Analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm was applied to confirm the hub-network of immune-resistance phenotype. A nomogram model based on COX and Logistic regression was constructed to evaluate the prognostic value and the predictive value of hub-gene in immune-response. The role of transmembrane protein 92 (TMEM92) in regulating cell proliferation was evaluated by MTS assay. Western blot and Real-time PCR were applied to assess the biological effects of PD-L1 inhibition by TMEM92. Moreover, the effect of TMEM92 in immunotherapy was evaluated with PBMC co-culture and by MTS assay.

Results

Two tumor-infiltrating immune cell (TIIC) phenotypes were identified and a weighted gene co-expression network was constructed to confirm the 167 gene signatures correlated with immune-resistance TIIC subtype. TMEM92 was further identified as a core gene of 167 gene signature network based on MCODE algorithm. High TMEM92 expression was significantly correlated with unfavorable prognosis, characterizing by immune resistance. A nomogram model and external validation confirmed that TMEM92 was an independent prognostic factor in pancreatic cancer. An elevated tumor mutation burden (TMB), mostly is consistent with commonly mutations of KRAS and TP53, was found in the high TMEM92 group. The predictive role of TMEM92 in immunotherapeutic response was also confirmed by IMvigor210 datasets. In addition, the specific biological roles of TMEM92 in cancer was explored in vitro. The results showed that abnormal overexpression of TMEM92 was significantly associated with the poor survival rate of pancreatic cancer. Moreover, we demonstrated that TMEM92 inhibit tumour immune responses of the anti-PD-1 antibody with PBMC co-culture.

Conclusion

The current study explored for the first time the immune-resistance phenotype of pancreatic cancer and identified TMEM92 as an innovative marker in predicting clinical outcomes and immunotherapeutic efficacy. These findings not only help to recognize high-risk and immune-resistance population which could be supplied targeted prevention, but also provide personalized medical services by intervening TMEM92 function to improve the prognosis of pancreatic cancer. In addition, the biological role of TMEM92 might reveal the potential molecular mechanisms of pancreatic cancer and lead to a novel sight for development of a PPPM approach for pancreatic cancer management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00287-0.

An immunotherapy response prediction model derived from proliferative CD4+ T cells and antigen-presenting monocytes in ccRCC

Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4⁺ T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.

Aging-based molecular classification and score system in ccRCC uncovers distinct prognosis, tumor immunogenicity, and treatment sensitivity

Objective

Aging is a complex biological process and a major risk factor for cancer development. This study was conducted to develop a novel aging-based molecular classification and score system in clear cell renal cell carcinoma (ccRCC).

Methods

Integrative analysis of aging-associated genes was performed among ccRCC patients in the TCGA and E-MTAB-1980 cohorts. In accordance with the transcriptional expression matrix of 173 prognostic aging-associated genes, aging phenotypes were clustered with the consensus clustering approach. The agingScore was generated to quantify aging phenotypes with principal component analysis. Tumor-infiltrating immune cells and the cancer immunity cycle were quantified with the ssGSEA approach. Immunotherapy response was estimated through the TIDE algorithm, and a series of tumor immunogenicity indicators were computed. Drug sensitivity analysis was separately conducted based on the GDSC, CTRP, and PRISM analyses.

Results

Three aging phenotypes were established for ccRCC, with diverse prognosis, clinical features, immune cell infiltration, tumor immunogenicity, immunotherapeutic response, and sensitivity to targeted drugs. The agingScore was developed, which enabled to reliably and independently predict ccRCC prognosis. Low agingScore patients presented more undesirable survival outcomes. Several small molecular compounds and three therapeutic targets, namely, CYP11A1, SAA1, and GRIK4, were determined for the low agingScore patients. Additionally, the high agingScore patients were more likely to respond to immunotherapy.

Conclusion

Overall, our findings introduced an aging-based molecular classification and agingScore system into the risk stratification and treatment decision-making in ccRCC.

What We Have Learnt from CARMENA and SURTIME and What Should Be Done Differently in Future Trials on Cytoreductive Nephrectomy

Upfront cytoreductive nephrectomy (CN) was the standard treatment for selected patients with metastatic Renal Cell Carcinoma (RCC) in the cytokine era for many years. In the recent ‘targeted therapy era’ it has been re-challenged by both the CARMENA and SURTIME trials. As first-line therapy for treatment-naive metastatic clear-cell RCC has now changed to immune checkpoint inhibitor combination therapy (ICI), and previous studies concerning CN were built in the targeted therapy era, the role and sequence of CN needs to be revisited. Here we address what we have learnt from both trials and how future trials should be designed to investigate CN.

Development of a Novel Sphingolipid Signaling Pathway-Related Risk Assessment Model to Predict Prognosis in Kidney Renal Clear Cell Carcinoma

This study aimed to explore underlying mechanisms by which sphingolipid-related genes play a role in kidney renal clear cell carcinoma (KIRC) and construct a new prognosis-related risk model. We used a variety of bioinformatics methods and databases to complete our exploration. Based on the TCGA database, we used multiple R-based extension packages for data transformation, processing, and statistical analyses. First, on analyzing the CNV, SNV, and mRNA expression of 29 sphingolipid-related genes in various types of cancers, we found that the vast majority were protective in KIRC. Subsequently, we performed cluster analysis of patients with KIRC using sphingolipid-related genes and successfully classified them into the following three clusters with significant prognostic differences: Cluster 1, Cluster 2, and Cluster 3. We performed differential analyses of transcription factor activity, drug sensitivity, immune cell infiltration, and classical oncogenes to elucidate the unique roles of sphingolipid-related genes in cancer, especially KIRC, and provide a reference for clinical treatment. After analyzing the risk rates of sphingolipid-related genes in KIRC, we successfully established a risk model composed of seven genes using LASSO regression analysis, including SPHK1, CERS5, PLPP1, SGMS1, SGMS2, SERINC1, and KDSR. Previous studies have suggested that these genes play important biological roles in sphingolipid metabolism. ROC curve analysis results showed that the risk model provided good prediction accuracy. Based on this risk model, we successfully classified patients with KIRC into high- and low-risk groups with significant prognostic differences. In addition, we performed correlation analyses combined with clinicopathological data and found a significant correlation between the risk model and patient’s M, T, stage, grade, and fustat. Finally, we developed a nomogram that predicted the 5-, 7-, and 10-year survival in patients with KIRC. The model we constructed had strong predictive ability. In conclusion, we believe that this study provides valuable data and clues for future studies on sphingolipid-related genes in KIRC.

SIGIRR Downregulation and Interleukin-1 Signaling Intrinsic to Renal Cell Carcinoma

Renal cell carcinoma is highly inflamed, and tumor cells are embedded into a microenvironment enriched with IL1. While inflammatory pathways are well characterized in the immune system, less is known about these same pathways in epithelial cells; it is unclear if and how innate immune signals directly impact on cancer cells, and if we could we manipulate these for therapeutic purposes. To address these questions, we first focused on the inflammatory receptors belonging to the IL1- and Toll-like receptor family including negative regulators in a small cohort of 12 clear cell RCC (ccRCC) patients’ samples as compared to their coupled adjacent normal tissues. Our data demonstrated that renal epithelial cancer cells showed a specific and distinctive pattern of inflammatory receptor expression marked by a consistent downregulation of the inhibitory receptor SIGIRR mRNA. This repression was confirmed at the protein level in both cancer cell lines and primary tissues. When we analyzed in silico data of different kidney cancer histotypes, we identified the clear cell subtype as the one where SIGIRR was mostly downregulated; nonetheless, papillary and chromophobe tumor types also showed low levels as compared to their normal counterpart. RNA-sequencing analysis demonstrated that IL1 stimulation of the ccRCC cell line A498 triggered an intrinsic signature of inflammatory pathway activation characterized by the induction of distinct “pro-tumor” genes including several chemokines, the autocrine growth factor IL6, the atypical co-transcription factor NFKBIZ, and the checkpoint inhibitor PD-L1. When we looked for the macroareas most represented among the differentially expressed genes, additional clusters emerged including pathways involved in cell differentiation, angiogenesis, and wound healing. To note, SIGIRR overexpression in A498 cells dampened IL1 signaling as assessed by a reduced induction of NFKBIZ. Our results suggest that SIGIRR downregulation unleashes IL1 signaling intrinsic to tumor cells and that manipulating this pathway may be beneficial in ccRCC.

Next-generation sequencing: unraveling genetic mechanisms that shape cancer immunotherapy efficacy

Immunity is governed by fundamental genetic processes. These processes shape the nature of immune cells and set the rules that dictate the myriad complex cellular interactions that power immune systems. Everything from the generation of T cell receptors and antibodies, control of epitope presentation, and recognition of pathogens by the immunoediting of cancer cells is, in large part, made possible by core genetic mechanisms and the cellular machinery that they encode. In the last decade, next-generation sequencing has been used to dissect the complexities of cancer immunity with potent effect. Sequencing of exomes and genomes has begun to reveal how the immune system recognizes “foreign” entities and distinguishes self from non-self, especially in the setting of cancer. High-throughput analyses of transcriptomes have revealed deep insights into how the tumor microenvironment affects immunotherapy efficacy. In this Review, we discuss how high-throughput sequencing has added to our understanding of how immune systems interact with cancer cells and how cancer immunotherapies work.

Advances in Renal Cell Carcinoma Drug Resistance Models

Renal cell carcinoma (RCC) is the most common form of kidney cancer. Systemic therapy is the preferred method to eliminate residual cancer cells after surgery and prolong the survival of patients with inoperable RCC. A variety of molecular targeted and immunological therapies have been developed to improve the survival rate and prognosis of RCC patients based on their chemotherapy-resistant properties. However, owing to tumor heterogeneity and drug resistance, targeted and immunological therapies lack complete and durable anti-tumor responses; therefore, understanding the mechanisms of systemic therapy resistance and improving clinical curative effects in the treatment of RCC remain challenging. In vitro models with traditional RCC cell lines or primary cell culture, as well as in vivo models with cell or patient-derived xenografts, are used to explore the drug resistance mechanisms of RCC and screen new targeted therapeutic drugs. Here, we review the established methods and applications of in vivo and in vitro RCC drug resistance models, with the aim of improving our understanding of its resistance mechanisms, increasing the efficacy of combination medications, and providing a theoretical foundation for the development and application of new drugs, drug screening, and treatment guidelines for RCC patients.

Redistribution of CD8+ T cell subsets in metastatic renal cell carcinoma patients treated with anti-PD-1 therapy

Renal‐cell carcinoma (RCC) is responsible for the majority of tumors arising from the kidney parenchyma. Although a progressive improvement in median overall survival has been observed after the introduction of anti‐PD‐1 therapy, many patients do not benefit from this treatment. Therefore, we have investigated T cell dynamics to find immune modification induced by anti‐PD‐1 therapy. Here, we show that, after therapy, RCC patients (5 responders and 14 nonresponders) are characterized by a redistribution of different subsets across the memory T cell compartment.

The genomic landscape of metastatic clear cell renal cell carcinoma after systemic therapy

Primary clear cell renal cell carcinoma (ccRCC) has been previously characterized, but the genomic landscape of metastatic ccRCC is largely unexplored. Here, we performed whole exome sequencing (WES) in 68 samples from 44 patients with ccRCC, including 52 samples from a metastatic site. SETD2, PBRM1, APC and VHL were the most frequently mutated genes in the metastatic ccRCC cohort. RBM10 and FBXW7 were also among the 10 most frequently mutated genes in metastatic tissues. Recurrent somatic copy number variations (CNV) were observed at the previously identified regions 3p25, 9p21 and 14q25, but also at 6p21 (CDKN1A) and 13q14 (RB1). No statistically significant differences were found between samples from therapy‐naïve and pretreated patients. Clonal evolution analyses with multiple samples from 13 patients suggested that early appearance of CNVs at 3p25, 9p21 and 14q25 may be associated with rapid clinical progression. Overall, the genomic landscapes of primary and metastatic ccRCC seem to share frequent CNVs at 3p25, 9p21 and 14q25. Future work will clarify the implication of RBM10 and FBXW7 mutations and 6p21 and 13q14 CNVs in metastatic ccRCC.

Rules of Engagement: The Lymphocyte Receptor Ecosystem in Renal Cell Carcinoma

Immune receptor repertoires provide insight into the clonal distribution of tumor-infiltrating lymphocytes, yet the clinical implications of T-cell receptor (TCR) and B-cell receptor (BCR) repertoire diversity in cancer are unclear. In this issue of Cancer Research, Ferral-Fairbanks and colleagues reveal the interplay between repertoire diversity, tumor molecular features, and clinical outcome in renal cell carcinoma (RCC). The authors show that aggressive tumors harbor increasingly diverse TCR and BCR repertoires and that both repertoires are altered by common RCC driver mutations. Moreover, the authors demonstrate that high TCR diversity is associated with improved overall survival. This study highlights the contribution of lymphocyte receptor dynamics to the emerging complexity of RCC antitumor immune responses. See related article by Ferral-Fairbanks et al., p. 929.

Histologic-Based Tumor-Associated Immune Cells Status in Clear Cell Renal Cell Carcinoma Correlates with Gene Signatures Related to Cancer Immunity and Clinical Outcomes

The three-tier immunophenotype (desert, excluded, and inflamed) and the four-tier immunophenotype (cold, immunosuppressed, excluded, and hot) have been linked to prognosis and immunotherapy response. This study aims to evaluate whether immunophenotypes of clear cell renal cell carcinoma, identified on hematoxylin and eosin-stained slides, correlate with gene expression signatures related to cancer immunity, and clinical outcomes. We evaluated tumor-associated immune cells (TAICs) status using three methodologies: three-tier immunophenotype based on the location of TAICs, four-tier immunophenotype considering both the location and degree of TAICs and inflammation score focusing only on the degree of TAICs, using a localized clear cell renal cell carcinoma cohort (n = 436) and The Cancer Genome Atlas (TCGA)-KIRC cohort (n = 162). We evaluated the association of the TAICs status assessed by three methodologies with CD8 and PD-L1 immunohistochemistry and immune gene expression signatures by TCGA RNA-sequencing data. All three methodologies correlated with immunohistochemical and immune gene expression signatures. The inflammation score and the four-tier immunophenotype showed similarly higher accuracy in predicting recurrence-free survival and overall survival compared to the three-tier immunophenotype. In conclusion, a simple histologic assessment of TIACs may predict clinical outcomes and immunotherapy responses.

Case Report: Exceptional Response to Nivolumab Plus Ipilimumab in a Young Woman With TFE3-SFPQ Fusion Translocation-Associated Renal Cell Carcinoma

Translocation-associated renal cell carcinoma (tRCC) is a rare, aggressive malignancy that primarily affects children and young adults. There is no clear consensus on the most effective treatment for tRCC and there are no biomarkers of response to treatments in these patients. We present a case of a 23 year-old female with metastatic tRCC to the lungs who was started on treatment with nivolumab and ipilimumab. She had a complete radiographic response to treatment and has been progression-free for over 18 months. Immunofluorescence imaging performed on the baseline primary tumor sample showed significant intratumoral immune infiltration. Importantly, these cells are present in niches characterized by TCF1+ CD8+ T cells. Histopathologic investigation showed the presence of lymphocytes in the fibrovascular septae and foci of lymphovascular invasion. Furthermore, lymphovascular invasion and intratumor niches with TCF1+ CD8+ T cells may predict a favorable response to treatment with nivolumab and ipilimumab. These findings have significant clinical relevance given that immune checkpoint inhibitors are approved for several malignancies and predictive biomarkers for response to treatment are lacking. Importantly, the identification of these TCF1+ CD8+ T cells may guide treatment for patients with tRCC, which is a rare malignancy without a consensus first-line treatment option.

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.