Current Status and Future Directions of Immunotherapy in Renal Cell Carcinoma

An ultraconserved snoRNA-like element in long noncoding RNA CRNDE promotes ribosome biogenesis and cell proliferation

Cancer cells frequently upregulate ribosome production to support tumorigenesis. While small nucleolar RNAs (snoRNAs) are critical for ribosome biogenesis, the roles of other classes of noncoding RNAs in this process remain largely unknown. Here, we performed CRISPR interference (CRISPRi) screens to identify essential long noncoding RNAs (lncRNAs) in renal cell carcinoma (RCC) cells. This revealed that an alternatively spliced isoform of lncRNA colorectal neoplasia differentially expressed (CRNDE) containing an ultraconserved element (UCE), referred to as CRNDEUCE, is required for RCC cell proliferation. CRNDEUCE localizes to the nucleolus and promotes 60S ribosomal subunit biogenesis. The UCE of CRNDE functions as an unprocessed C/D box snoRNA that directly interacts with ribosomal RNA precursors. This facilitates delivery of eukaryotic initiation factor 6 (eIF6), a key 60S biogenesis factor, which binds to CRNDEUCE through a sequence element adjacent to the UCE. These findings highlight the functional versatility of snoRNA sequences and expand the known mechanisms through which noncoding RNAs orchestrate ribosome biogenesis.

Dysregulation of ubiquitination modification in renal cell carcinoma

Renal cell carcinoma (RCC) is a malignant tumor of the renal tubular epithelial cells with a relatively high incidence rate worldwide. A large number of studies have indicated that dysregulation of the ubiquitination, including ubiquitination and dysregulation, is associated with the occurrence and development of RCC. This review focuses on several abnormal signaling pathways caused by E3 ligases and deubiquitinases. Additionally, we discuss research progress in RCC treatment by targeting key enzymes related to ubiquitination modifications.

An ultraconserved snoRNA-like element in long noncoding RNA CRNDE promotes ribosome biogenesis and cell proliferation

Cancer cells frequently upregulate ribosome production to support tumorigenesis. While small nucleolar RNAs (snoRNAs) are critical for ribosome biogenesis, the roles of other classes of noncoding RNAs in this process remain largely unknown. Here we performed CRISPRi screens to identify essential long noncoding RNAs (lncRNAs) in renal cell carcinoma (RCC) cells. This revealed that an alternatively-spliced isoform of lncRNA Colorectal Neoplasia Differentially Expressed containing an ultraconserved element (UCE), referred to as CRNDE UCE, is required for RCC cell proliferation. CRNDE UCE localizes to the nucleolus and promotes 60S ribosomal subunit biogenesis. The UCE of CRNDE functions as an unprocessed C/D box snoRNA that directly interacts with ribosomal RNA precursors. This facilitates delivery of eIF6, a key 60S biogenesis factor, which binds to CRNDE UCE through a sequence element adjacent to the UCE. These findings highlight the functional versatility of snoRNA sequences and expand the known mechanisms through which noncoding RNAs orchestrate ribosome biogenesis.

Von-Hipple Lindau syndrome with family history: a case report and seventeen years follow-up study

Background

Von-Hipple Lindau syndrome is an uncommon autosomal dominant disorder. 17 years ago we diagnosed a young woman with VHL syndrome validated by Sanger sequencing, her family members were genetically tested as well, and 187 healthy people were randomly selected for VHL genetic testing as controls. We analyze the clinical and genetic characteristics of VHL syndrome in a Chinese lineage and with 17-year follow-up.

Case presentation

A woman was finally diagnosed with VHL syndrome due to the detection of a missense mutation c.353T > C in exon 2 of the short arm of chromosome 3, which resulted in a leucine substitution at amino acid 118 of the encoded protein by a proline, which may be thought the main cause of the disease. The same mutation was observed in two other family members, their clinical symptoms are not entirely identical. However, this mutation was not found in other family members or 187 healthy controls. She clinically presented with central nervous system hemangioblastomas, clear renal cell carcinoma, and pancreatic neuroendocrine neoplasms, despite the multi-organ involvement and several relapses during the disease, the patients survive well for she was treated with aggressive surgery early in the course of the plaguing symptoms, whereas patients who are not aggressively treated have a poorer prognosis.

Conclusion

The clinical presentation of VHL syndrome is atypical, and early identification and treatment of VHL syndrome is possible by genetic testing techniques. Multiple relapses occurred during the course of the disease, but early diagnosis and aggressive treatment allowed the patients to survive well.

Molecular characteristics and prognostic significances of lysosomal-dependent cell death in kidney renal clear cell carcinoma

Lysosomal-dependent cell death (LDCD) has an excellent therapeutic effect on apoptosis-resistant and drug-resistant tumors; however, the important role of LDCD-related genes (LDCD-RGs) in kidney renal clear cell carcinoma (KIRC) has not been reported. Initially, single-cell atlas of LDCD signal in KIRC was comprehensively depicted. We also emphasized the molecular characteristics of LDCD-RGs in various human neoplasms. Predicated upon the expressive quotients of LDCD-RGs, we stratified KIRC patients into tripartite cohorts denoted as C1, C2, and C3. Those allocated to the ambit of C1 evinced the most sanguine prognosis within the KIRC cohort, underscored by the acme of LDCD-RGs scores. This further confirms the significant role that LDCD-RGs play in both the pathophysiological foundation and clinical implications of KIRC. In culmination, by virtue of employing the LASSO-Cox analytical modality, we have ushered in an innovative and avant-garde prognostic framework tailored for KIRC, predicated on the bedrock of LDCD-RGs. The assemblage of KIRC instances was arbitrarily apportioned into constituents inclusive of a didactic cohort, an internally wielded validation cadre, and an externally administered validation cohort. Concurrently, patients were dichotomized into strata connoting elevated jeopardy synonymous with adverse prognostic trajectories, and conversely, diminished risk tantamount to favorable prognoses, contingent on the calibrated expressions of LDCD-RGs. Succinctly, our investigative findings serve to underscore the cardinal capacity harbored by LDCD-RGs within the KIRC milieu, concurrently birthing a pioneering prognostic schema intrinsically linked to the trajectory of KIRC and its attendant prognoses.

An automatic texture feature analysis framework of renal tumor: surgical, pathological, and molecular evaluation based on multi-phase abdominal CT

OBJECTIVES

To determine whether the texture feature analysis of multi-phase abdominal CT can provide a robust prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor.

METHODS

A total of 1051 participants with renal tumor were split into the internal cohort (850 patients from four different hospitals) and the external testing cohort (201 patients from another local hospital). The proposed framework comprised a 3D-kidney and tumor segmentation model by 3D-UNet, a feature extractor for the regions of interest based on radiomics and image dimension reduction, and the six classifiers by XGBoost. A quantitative model interpretation method called SHAP was used to explore the contribution of each feature.

RESULTS

The proposed multi-phase abdominal CT model provides robust prediction for benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in the internal validation set, with the AUROC values of 0.88 ± 0.1, 0.90 ± 0.1, 0.91 ± 0.1, 0.89 ± 0.1, 0.84 ± 0.1, and 0.88 ± 0.1, respectively. The external testing set also showed impressive results, with AUROC values of 0.83 ± 0.1, 0.83 ± 0.1, 0.85 ± 0.1, 0.81 ± 0.1, 0.79 ± 0.1, and 0.81 ± 0.1, respectively. The radiomics feature including the first-order statistics, the tumor size-related morphology, and the shape-related tumor features contributed most to the model predictions.

CONCLUSIONS

Automatic texture feature analysis of abdominal multi-phase CT provides reliable predictions for multi-tasks, suggesting the potential usage of clinical application.

CLINICAL RELEVANCE STATEMENT

The automatic texture feature analysis framework, based on multi-phase abdominal CT, provides robust and reliable predictions for multi-tasks. These valuable insights can serve as a guiding tool for clinical diagnosis and treatment, making medical imaging an essential component in the process.

KEY POINTS

• The automatic texture feature analysis framework based on multi-phase abdominal CT can provide more accurate prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. • The quantitative decomposition of the prediction model was conducted to explore the contribution of the extracted feature. • The study involving 1051 patients from 5 medical centers, along with a heterogeneous external data testing strategy, can be seamlessly transferred to various tasks involving new datasets.

Mathematical and Machine Learning Models of Renal Cell Carcinoma: A Review

This review explores the multifaceted landscape of renal cell carcinoma (RCC) by delving into both mechanistic and machine learning models. While machine learning models leverage patients' gene expression and clinical data through a variety of techniques to predict patients' outcomes, mechanistic models focus on investigating cells' and molecules' interactions within RCC tumors. These interactions are notably centered around immune cells, cytokines, tumor cells, and the development of lung metastases. The insights gained from both machine learning and mechanistic models encompass critical aspects such as signature gene identification, sensitive interactions in the tumors' microenvironments, metastasis development in other organs, and the assessment of survival probabilities. By reviewing the models of RCC, this study aims to shed light on opportunities for the integration of machine learning and mechanistic modeling approaches for treatment optimization and the identification of specific targets, all of which are essential for enhancing patient outcomes.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

Reigniting hope in cancer treatment: the promise and pitfalls of IL-2 and IL-2R targeting strategies

Interleukin-2 (IL-2) and its receptor (IL-2R) are essential in orchestrating immune responses. Their function and expression in the tumor microenvironment make them attractive targets for immunotherapy, leading to the development of IL-2/IL-2R-targeted therapeutic strategies. However, the dynamic interplay between IL-2/IL-2R and various immune cells and their dual roles in promoting immune activation and tolerance presents a complex landscape for clinical exploitation. This review discusses the pivotal roles of IL-2 and IL-2R in tumorigenesis, shedding light on their potential as diagnostic and prognostic markers and their therapeutic manipulation in cancer. It underlines the necessity to balance the anti-tumor activity with regulatory T-cell expansion and evaluates strategies such as dose optimization and selective targeting for enhanced therapeutic effectiveness. The article explores recent advancements in the field, including developing genetically engineered IL-2 variants, combining IL-2/IL-2R-targeted therapies with other cancer treatments, and the potential benefits of a multidimensional approach integrating molecular profiling, immunological analyses, and clinical data. The review concludes that a deeper understanding of IL-2/IL-2R interactions within the tumor microenvironment is crucial for realizing the full potential of IL-2-based therapies, heralding the promise of improved outcomes for cancer patients.

Automatic analysis framework based on 3D-CT multi-scale features for accurate prediction of Ki67 expression levels in substantial renal cell carcinoma

PURPOSE

To investigate the effectiveness of an automatic analysis framework based on 3D-CT multi-scale features in predicting Ki67 expression levels in substantial renal cell carcinoma (RCC).

METHODS

This retrospective study was conducted using multi-center cohorts consisting of 588 participants with pathologically confirmed RCC. The participants were divided into an internal training set (n = 485) and an external testing set (n = 103) from four and one local hospitals, respectively. The proposed automatic analytic framework comprised a 3D kidney and tumor segmentation model constructed by 3D UNet, a 3D-CT multi-scale features extractor based on the renal-tumor feature, and a low or high Ki67 prediction classifier using XGBoost. The framework was validated using a fivefold cross-validation strategy. The Shapley additive explanation (SHAP) method was used to determine the contribution of each feature.

RESULTS

In the prediction of low or high Ki67, the combination of renal and tumor features achieved better performance than any single features. Internal validation using a fivefold cross-validation strategy yielded AUROC values of 0.75 ± 0.1, 0.75 ± 0.1, 0.83 ± 0.1, 0.77 ± 0.1, and 0.87 ± 0.1, respectively. The optimal model achieved an AUROC of 0.87 ± 0.1 and 0.82 ± 0.1 for low vs. high Ki67 prediction in the internal validation and external testing sets, respectively. Notably, the tumor first-order-10P was identified as the most influential feature in the model decision.

CONCLUSIONS

Our study suggests that the proposed automatic analysis framework based on 3D-CT multi-scale features has great potential for accurately predicting Ki67 expression levels in substantial RCC.

CRITICAL RELEVANCE STATEMENT

Automatic analysis framework based on 3D-CT multi-scale features provides reliable predictions for Ki67 expression levels in substantial RCC, indicating the potential usage of clinical applications.

Development of an Immune Prognostic Model for Clear Cell Renal Cell Carcinoma Based on Tumor Microenvironment

Immune infiltration remains at a high level in clear cell renal cell carcinoma (ccRCC). It has been confirmed that immune cell infiltration in tumor microenvironment (TME) is intimately bound up with the progression and the clinical outcome of ccRCC. The prognostic model, developed based on different immune subtypes of ccRCC, has a predictive value in patients' prognosis. RNA sequencing data, somatic mutation data of ccRCC and clinical information were acquired from the cancer genome atlas (TCGA) database. The key immune-related genes (IRGs) were selected and by univariate Cox, LASSO, and multivariate Cox regression analyses. Then the ccRCC prognostic model was developed. The applicability of this model was verified in the independent dataset GSE29609. Thirteen IRGs including CCL7, ATP6V1C2, ATP2B3, ELAVL2, SLC22A8, DPP6, EREG, SERPINA7, PAGE2B, ADCYAP1, ZNF560, MUC20, and ANKRD30A were finally selected and a 13-IRGs prognostic model was developed. Survival analysis demonstrated that when compared with the low-risk group, patients in the high-risk group had a lower overall survival (p<0.05). AUC values based on the 13-IRGs prognostic model used to predict 3- and 5-year survival of ccRCC patients were greater than 0.70. And risk score was an independent prognostic factor (p<0.001). In addition, nomogram could accurately predict ccRCC patient's prognosis. This 13-IRGs model can effectively evaluate the prognosis of ccRCC patients, and also provide guidance for the treatment and prognosis of ccRCC patients.

Immunotherapy and Immune Infiltration in Patients with Clear Cell Renal Cell Carcinoma: A Comprehensive Analysis

On a global scale, renal cell carcinoma (RCC) is the second most common form of cancer and the 10th leading cause of cancer-related deaths. There are about 70% of cases of RCC that are clear cell renal cell carcinomas (ccRCCs). This study explores possible targets for immune therapy in patients with RCC. In the recent years, immunotherapy has been applied to RCC patients. In order to identify genes that are closely associated with immune cells, a weighted gene coexpression network analysis (WGCNA) was conducted. A close association was found between genes involved in MEred and M0 macrophages, M1 macrophages, and M2 macrophages. A prognostic prediction model is subsequently developed by incorporating the OS and the expression level of key genes from the RCC cohort into a univariate COX regression analysis, a multivariate COX regression analysis, and a combined COX regression analysis. We finally discovered that 6 genes are closely associated with the prognosis of RCC patients, including SLC16A12, SLC2A9, IGF2BP2, EMX2, ANK3, and METTL7A. The survival analysis proved the prognostic prediction value of the model. The 1-year, 3-year, and 5-year AUC of ROC curves are 0.759, 0.723, and 0.733, respectively. For clinical ROC curves, the AUC score for risk score, stage, grade, and T stage is 0.759, 0.824, 0722, and 0.736, respectively. The nomogram was constructed for better prognosis prediction of RCC patients. In addition, GSVA and GO enrichment analysis was performed to explore the potential pathways that are closely associated with genes involved in the prognostic prediction model. Accordingly, our study demonstrates that immune cells play a crucial role in RCC infiltration. The development of a prognostic prediction model is a potential new prognostic biomarker and potential immunotherapy target for tumors.

A novel natural killer cell-related signatures to predict prognosis and chemotherapy response of pancreatic cancer patients

Background: Natural killer (NK) cells are involved in monitoring and eliminating cancers. The purpose of this study was to develop a NK cell-related genes (NKGs) in pancreatic cancer (PC) and establish a novel prognostic signature for PC patients. Methods: Omic data were downloaded from The Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and used to generate NKG-based molecular subtypes and construct a prognostic signature of PC. NKGs were downloaded from the ImmPort database. The differences in prognosis, immunotherapy response, and drug sensitivity among subtypes were compared. 12 programmed cell death (PCD) patterns were acquired from previous study. A decision tree and nomogram model were constructed for the prognostic prediction of PC. Results: Thirty-two prognostic NKGs were identified in PC patients, and were used to generate three clusters with distinct characteristics. PCD patterns were more likely to occur at C1 or C3. Four prognostic DEGs, including MET, EMP1, MYEOV, and NGFR, were found among the clusters and applied to construct a risk signature in TCGA dataset, which was successfully validated in PACA-CA and GSE57495 cohorts. The four gene expressions were negatively correlated with methylation level. PC patients were divided into high and low risk groups, which exerts significantly different prognosis, clinicopathological features, immune infiltration, immunotherapy response and drug sensitivity. Age, N stage, and the risk signature were identified as independent factors of PC prognosis. Low group was more easily to happened on PCD. A decision tree and nomogram model were successfully built for the prognosis prediction of PC patients. ROC curves and DCA curves demonstrated the favorable and robust predictive capability of the nomogram model. Conclusion: We characterized NKGs-derived molecular subtypes of PC patients, and established favorable prognostic models for the prediction of PC prognosis, which may serve as a potential tool for prognosis prediction and making personalized treatment in PC.

Kinase inhibitors: Opportunities for small molecule anticancer immunotherapies

As the fifth pillar of cancer treatment, immunotherapy has dramatically changed the paradigm of therapeutic strategies by focusing on the host's immune system. In the long road of immunotherapy development, the identification of immune-modulatory effects for kinase inhibitors opened a new chapter in this therapeutic approach. These small molecule inhibitors not only directly eradicate tumors by targeting essential proteins of cell survival and proliferation but can also drive immune responses against malignant cells. This review summarizes the current standings and challenges of kinase inhibitors in immunotherapy, either as a single agent or in a combined modality.

Identification and experimental validation of a tumor-infiltrating lymphocytes-related long noncoding RNA signature for prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common aggressive malignant tumor of the urinary system. Given the heterogeneity of the tumor microenvironment, immunotherapy may not fully exert its role in the treatment of advanced patients. Long noncoding RNA (lncRNA) has been reported to be critically associated with the differentiation and maturation of tumor-infiltrating lymphocytes (TILs), which work against tumor cells. In this study, we identified 10 TIL-related lncRNAs (AL590094.1, LINC02027, LINC00460, AC147651.1, AC026401.3, LINC00944, LINC01615, AP000439.2, AL162586.1, and AC084876.1) by Pearson correlation, univariate Cox regression, Lasso regression, and multivariate Cox regression based on The Cancer Genome Atlas (TCGA) database. A risk score model was established based on these lncRNAs. Next, a nomogram was constructed to predict the overall survival. By employing differentially expressed genes (DEGs) between groups with high and low risk scores, gene ontology (GO) enrichment analysis was performed to identify the major biological processes (BP) related to immune DEGs. We analyzed the mutation data of the groups and demonstrated that SETD2 and BAP1 had the highest mutation frequency in the high-risk group. The "CIBERSORT" R package was used to detect the abundance of TILs in the groups. The expression of lymphocyte markers was compared. We also determined the expression of two lncRNAs (AC084876.1 and AC026401.3) and their relationship with lymphocyte markers in the kidney tissue of ccRCC patients and showed that there was a positive correlation between AC084876.1 and FoxP3. Proliferation, migration, and invasion of AC084876.1-downregulated ccRCC cell lines were inhibited, and the expression of PD-L1 and TGF-β secretion decreased. To our knowledge, this is the first bioinformatics study to establish a prognostic model for ccRCC using TIL-related lncRNAs. These lncRNAs were associated with T-cell activities and may serve as biomarkers of disease prognosis.

Molecular subtypes based on cuproptosis regulators and immune infiltration in kidney renal clear cell carcinoma

Copper toxicity involves the destruction of mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death called cuproptosis, which proposes a novel approach using copper toxicity to treat cancer. However, the biological function of cuproptosis has not been fully elucidated in kidney renal clear cell carcinoma (KIRC). Using the expression profile of 13 cuproptosis regulators, we first identified two molecular subtypes related to cuproptosis defined as "hot tumor" and "cold tumor", having different levels of biological function, clinical prognosis, and immune cell infiltration. We obtained three gene clusters using the differentially expressed genes between the two cuproptosis-related subtypes, which were associated with different molecular activities and clinical characteristics. Next, we developed and validated a cuproptosis prognostic model that included two genes (FDX1 and DBT). The calculated risk score could divide patients into high- and low-risk groups. The high-risk group had a poorer prognosis, lower level of immune infiltration, higher frequency of gene alterations, and greater levels of FDX1 methylation and limited DBT methylation. The risk score was also an independent predictive factor for overall survival in KIRC. The established nomogram calculating the risk score achieved a high predictive ability for the prognosis of individual patients (area under the curve: 0.860). We then identified small molecular inhibitors as potential treatments and analyzed the sensitivity to chemotherapy of the signature genes. Tumor immune dysfunction and exclusion (TIDE) showed that the high-risk group had a higher level of TIDE, exclusion and dysfunction that was lower than the low-risk group, while the microsatellite instability of the high-risk group was significantly lower. The results of two independent immunotherapy datasets indicated that cuproptosis regulators could influence the response and efficacy of immunotherapy in KIRC. Our study provides new insights for individualized and comprehensive therapy of KIRC.

A novel necroptosis-related lncRNAs signature for survival prediction in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common kind of kidney cancer with poor prognosis. Necroptosis is a newly observed type of programmed cell death in recent years. However, the effects of necroptosis-related lncRNAs (NRlncRNAs) on ccRCC have not been widely explored. The transcription profile and clinical information were obtained from The Cancer Genome Atlas. Necroptosis-related lncRNAs were identified by utilizing a co-expression network of necroptosis-related genes and lncRNAs. Univariate Cox regression, least absolute shrinkage, and selection operator regression and multivariate Cox regression were performed to screen out ideal prognostic necroptosis-related lncRNAss and develop a multi-lncRNA signature. Finally, 6 necroptosis-related lncRNA markers were established. Patients were separated into high- and low-risk groups based on the performance value of the median risk score. Kaplan-Meier analysis identified that high-risk patients had poorer prognosis than low-risk patients. Furthermore, the area under time-dependent receiver operating characteristic curve reached 0.743 at 1 year, 0.719 at 3 years, and 0.742 at 5 years, which indicating that they can be used to predict ccRCC prognosis. In addition, the proposed signature was related to immunocyte infiltration. A nomogram model was also established to provide a more beneficial prognostic indicator for the clinic. Altogether, in the present study, the 6-lncRNA prognostic risk signature are trustworthy and effective indicators for predicting the prognosis of ccRCC.

Comprehensive assessments of immuno-oncology drug-based combination therapies as first-line treatment for advanced renal cell carcinoma

Over the last decade, there have been substantial progress in the field of systemic therapy for advanced renal cell carcinoma. Through the transition from treatment with cytokines to molecular-targeted agents, and currently to immuno-oncology drugs, the prognostic outcomes of patients with advanced renal cell carcinoma have been markedly improved. In particular, based on the promising outcomes of recently conducted pivotal randomized clinical trials, immuno-oncology drug-based combination therapy by either dual immune checkpoint inhibition or combined inhibition of an immune checkpoint and tyrosine kinase, is currently regarded as a standard of care for treatment-naïve advanced renal cell carcinoma patients. However, insufficient data are available with respect to the selection of optimal systemic therapies for advanced renal cell carcinoma in the first-line setting due to the lack of a head-to-head comparison between approved immuno-oncology drug-based combination therapies. In this review, therefore, we summarize interesting findings associated with first-line combination therapies for advanced renal cell carcinoma obtained from both randomized clinical trials and real-world clinical practices, in order to present useful guidance to help make treatment decisions for patients with treatment-naïve advanced renal cell carcinoma.

The value measurement of emerging therapeutics in renal cell carcinoma: ASCO value framework and ESMO-MCBS

Purpose

Rapid development of novel therapeutics in renal cell carcinoma (RCC) has led to financial burden for patients and society. Value including clinical benefit, toxicity affecting quality of life and cost-effectiveness are a concern, prompting the need for tools to facilitate value assessment of therapeutics. This study reviews the value assessment tools, and evaluates the value of emerging therapeutics in RCC.

Materials and methods

Two medical oncologists used American Society of Clinical Oncology value framework (ASCO VF) v2.0 and European Society for Medical Oncology-magnitude of clinical benefit scale (ESMO-MCBS) v1.1 to phase 3 trials evaluating first-line therapy in patients with metastatic RCC. Follow-up (FU) reports and extended survival data were included. Equivocal aspects and limitations of the tools were discussed.

Results

Six trials (COMPARZ, CheckMate 214, JAVELIN renal 101, Keynote 426, CLEAR, and CheckMate 9ER) were assessed. The control arm was standard-of-care sunitinib in all trials. ASCO VF’s net health benefit, calculated as clinical benefit, toxicity and other bonus point was 11 in pazopanib, 41.9 in nivolumab plus ipilimumab, 22.4 in axitinib plus avelumab, 48.7 in axitinib plus pembrolizumab, 35.2 in lenvatinib plus pembrolizumab, and 50.8 in cabozantinib plus nivolumab. A higher score means a greater treatment benefit. ESMO-MCBS gave grade 5 to nivolumab plus ipilimumab, 4 to pazopanib, lenvatinib plus pembrolizumab and cabozantinib plus nivolumab, 3 to axitinib plus avelumab or pembrolizumab. Both tools had unclear aspects to be applied to clinical practice, and should be more clearly defined, such as endpoint for determining survival benefits or how to standardize quality of life and toxicity.

Conclusions

ASCO VF and ESMO-MCBS were applied to evaluate the newly emerging drugs in RCC and assessed their value. In-depth discussion by experts in various fields is required for appropriate clinical application in a real-world setting.

F18-FDG PET/CT imaging early predicts pathologic complete response to induction chemoimmunotherapy of locally advanced head and neck cancer: preliminary single-center analysis of the checkrad-cd8 trial

Aim

In the CheckRad-CD8 trial patients with locally advanced head and neck squamous cell cancer are treated with a single cycle of induction chemo-immunotherapy (ICIT). Patients with pathological complete response (pCR) in the re-biopsy enter radioimmunotherapy. Our goal was to study the value of F-18-FDG PET/CT in the prediction of pCR after induction therapy.

Methods

Patients treated within the CheckRad-CD8 trial that additionally received FDG- PET/CT imaging at the following two time points were included: 3–14 days before (pre-ICIT) and 21–28 days after (post-ICIT) receiving ICIT. Tracer uptake in primary tumors (PT) and suspicious cervical lymph nodes (LN +) was measured using different quantitative parameters on EANM Research Ltd (EARL) accredited PET reconstructions. In addition, mean FDG uptake levels in lymphatic and hematopoietic organs were examined. Percent decrease (Δ) in FDG uptake was calculated for all parameters. Biopsy of the PT post-ICIT acquired after FDG-PET/CT served as reference. The cohort was divided in patients with pCR and residual tumor (ReTu).

Results

Thirty-one patients were included. In ROC analysis, ΔSUVmax PT performed best (AUC = 0.89) in predicting pCR (n = 17), with a decline of at least 60% (sensitivity, 0.77; specificity, 0.93). Residual SUVmax PT post-ICIT performed best in predicting ReTu (n = 14), at a cutpoint of 6.0 (AUC = 0.91; sensitivity, 0.86; specificity, 0.88). Combining two quantitative parameters (ΔSUVmax ≥ 50% and SUVmax PT post-ICIT ≤ 6.0) conferred a sensitivity of 0.81 and a specificity of 0.93 for determining pCR. Background activity in lymphatic organs or uptake in suspected cervical lymph node metastases lacked significant predictive value.

Conclusion

FDG-PET/CT can identify patients with pCR after ICIT via residual FDG uptake levels in primary tumors and the related changes compared to baseline. FDG-uptake in LN + had no predictive value.

Trial registry

ClinicalTrials.gov identifier: NCT03426657.

Key Players of the Immunosuppressive Tumor Microenvironment and Emerging Therapeutic Strategies

The tumor microenvironment (TME) is a complex, dynamic battlefield for both immune cells and tumor cells. The advent of the immune checkpoint inhibitors (ICI) since 2011, such as the anti-cytotoxic T-lymphocyte associated protein (CTLA)-4 and anti-programmed cell death receptor (PD)-(L)1 antibodies, provided powerful weapons in the arsenal of cancer treatments, demonstrating unprecedented durable responses for patients with many types of advanced cancers. However, the response rate is generally low across tumor types and a substantial number of patients develop acquired resistance. These primary or acquired resistance are attributed to various immunosuppressive elements (soluble and cellular factors) and alternative immune checkpoints in the TME. Therefore, a better understanding of the TME is absolutely essential to develop therapeutic strategies to overcome resistance. Numerous clinical studies are underway using ICIs and additional agents that are tailored to the characteristics of the tumor or the TME. Some of the combination treatments are already approved by the Food and Drug Administration (FDA), such as platinum-doublet chemotherapy, tyrosine kinase inhibitor (TKI) -targeting vascular endothelial growth factor (VEGF) combined with anti-PD-(L)1 antibodies or immuno-immuno combinations (anti-CTLA-4 and anti-PD-1). In this review, we will discuss the key immunosuppressive cells, metabolites, cytokines or chemokines, and hypoxic conditions in the TME that contribute to tumor immune escape and the prospect of relevant clinical trials by targeting these elements in combination with ICIs.

Anti-4-1BB antibody-based combination therapy augments antitumor immunity by enhancing CD11c+CD8+ T cells in renal cell carcinoma

To improve the potential treatment strategies of incurable renal cell carcinoma (RCC), which is highly resistant to chemotherapy and radiotherapy, the present study established a combination therapy with immunostimulatory factor (ISTF) and anti-4-1BB monoclonal antibodies (mAbs) to augment the antitumor response in a murine RCC model. ISTF isolated from Actinobacillus actinomycetemcomitans stimulates macrophages, dendritic cells and B cells to produce IL-6, TNF-α, nitric oxide and major histocompatibility complex class II expression. 4-1BB (CD137) is expressed in activated immune cells, including activated T cells, and is a promising target for cancer immunotherapy. The administration of anti-4-1BB mAbs promoted antitumor immunity via enhancing CD11c⁺CD8⁺ T cells. The CD11c⁺CD8⁺ T cells were characterized by high killing activity and IFN-γ-producing ability, representing a phenotype of active effector cytotoxic T lymphocytes. The present study showed that combination therapy with ISTF and anti-4-1BB mAbs promoted partial tumor regression with established RCC, but monotherapy with ISTF or anti-4-1BB mAbs did not. These effects were speculated to be caused by the increase in CD11c⁺CD8⁺ T cells in the spleen and tumor, and IFN-γ production. These insights into the effector mechanisms of the combination of ISTF and anti-4-1BB mAbs may be useful for targeting incurable RCC.

Von Hippel-Lindau disease-associated renal cell carcinoma: a call to action

PURPOSE OF REVIEW

While the molecular and genetic bases of Von Hippel-Lindau (VHL) disease have been extensively investigated, limited evidence is available to guide diagnosis, local or systemic therapy, and follow-up. The aim of the current review is to summarize the ongoing trials both in preclinical and clinical setting regarding VHL disease management.

RECENT FINDINGS

Although genotype/phenotype correlations have been described, there is considerable inter and intra-familiar heterogeneity in VHL disease. Genetic anticipation has been reported in VHL disease. From a clinical point of view, expert-opinion-based protocols suggest testing those patients with any blood relative of an individual diagnosed with VHL disease, those with at least 1 or more suggestive neoplasms or patients presenting with clear cell renal cell carcinoma (ccRCC) diagnosed at a less than 40 years old, and/or multiple ccRCC. Clinical research is focused on safety and efficacy of systemic agents for patients with VHL-related ccRCC, with the aim to possibly preserve kidney function and improve patient survival.

SUMMARY

To date, preclinical and clinical research on the topic is scarce and clinical guidelines are not supported by strong validation studies.

Molecular mechanisms underlying the role of hypoxia-inducible factor-1 α in metabolic reprogramming in renal fibrosis

Renal fibrosis is the result of renal tissue damage and repair response disorders. If fibrosis is not effectively blocked, it causes loss of renal function, leading to chronic renal failure. Metabolic reprogramming, which promotes cell proliferation by regulating cellular energy metabolism, is considered a unique tumor cell marker. The transition from oxidative phosphorylation to aerobic glycolysis is a major feature of renal fibrosis. Hypoxia-inducible factor-1 α (HIF-1α), a vital transcription factor, senses oxygen status, induces adaptive changes in cell metabolism, and plays an important role in renal fibrosis and glucose metabolism. This review focuses on the regulation of proteins related to aerobic glycolysis by HIF-1α and attempts to elucidate the possible regulatory mechanism underlying the effects of HIF-1α on glucose metabolism during renal fibrosis, aiming to provide new ideas for targeted metabolic pathway intervention in renal fibrosis.

Downregulation of FXYD2 Is Associated with Poor Prognosis and Increased Regulatory T Cell Infiltration in Clear Cell Renal Cell Carcinoma

BACKGROUND

FXYD2, a gene coding for the γ subunit of Na⁺/K⁺-ATPase, was demonstrated to involve in carcinogenesis recently. However, the specific role of FXYD2 in clear cell renal cell carcinoma (ccRCC) remains unknown. The current study was conducted to investigate the expression, biological function, and potentially immune-related mechanisms of FXYD2 in ccRCC. Materials and methods. The data from TCGA-KIRC, ICGC, GEO, Oncomine, ArrayExpress, TIMER, HPA datasets, and our clinical samples were used to determine and validate the expression level, prognostic roles, and potentially immune-related mechanisms in ccRCC. Cell function assays were performed to investigate the biological role of FXYD2 in vitro.

RESULTS

FXYD2 was identified to be downregulated in ccRCC tissue compared to normal tissue, which was confirmed by our RT-PCR, WB, and IHC analyses. Kaplan-Meier survival analysis and Cox regression analysis suggested that downregulated FXYD2 could independently predict poor survival of ccRCC patients. Through the ESTIMATE algorithm, ssGSEA algorithm, CIBERSORT algorithm, TIMER database, and our laboratory experiment, FXYD2 was found to correlate with the immune landscape, especially regulatory T cells (Treg), in ccRCC. Gain-of-function experiment revealed that FXYD2 could restrain cell proliferation, migration, and invasion in vitro. Functional enrichment analysis illustrated that TGF-β-SMAD2/3, Notch, and PI3K-Akt-mTOR signaling pathways may be potential signaling pathways of FXYD2 in ccRCC.

CONCLUSIONS

Downregulation of FXYD2 is associated with ccRCC tumorigenesis, poor prognosis, and increased Treg infiltration in ccRCC, which may be related to TGF-β-SMAD2/3, Notch, and PI3K-Akt-mTOR signaling pathways. This will probably provide a novel prognostic marker and potential therapeutic target for ccRCC.

The construction and analysis of a ferroptosis-related gene prognostic signature for pancreatic cancer

Ferroptosis is a regulated cell death nexus linking metabolism, redox biology and diseases including cancer. The aim of the present study was to identify a ferroptosis-related gene prognostic signature for pancreatic cancer (PCa) by systematic analysis of transcriptional profiles from Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Altogether 14 ferroptosis-relevant genes with potential prognostic values were identified, based on which a risk score formula was constructed. According to the risk scores, we classified the patients into a high- and a low-risk score group. It was verified in Gene Expression Omnibus (GEO) and ICGC (International Cancer Genome Consortium) datasets. The Kaplan-Meier survival curves demonstrated that patients with lower risk scores had significantly favorable overall survival (OS) (P < 0.0001). The area under the receiver operating curve (ROC) for 12, 18 and 24 months was about 0.8 in all patients. The result of immune status analysis revealed that the signature significantly associated with the immune infiltration and immune checkpoint blockade (ICB) proteins. In addition, we used quantitative real time PCR (q-rtPCR) and Human Protein Atlas (HPA) to validate the expression of the key genes. Collectively, the signature is valuable for survival prediction of PCa patients. As the signature also has relevance with the immune characteristics, it may help improve the efficacy of personalized immunotherapy.

Molecular and Metabolic Subtypes in Sporadic and Inherited Clear Cell Renal Cell Carcinoma

The promise of personalized medicine is a therapeutic advance where tumor signatures obtained from different omics platforms, such as genomics, transcriptomics, proteomics, and metabolomics, in addition to environmental factors including metals and metalloids, are used to guide the treatments. Clear cell renal carcinoma (ccRCC), the most common type of kidney cancer, can be sporadic (frequently) or genetic (rare), both characterized by loss of the von Hippel-Lindau (VHL) gene that controls hypoxia inducible factors. Recently, several genomic subtypes were identified with different prognoses. Transcriptomics, proteomics, metabolomics and metallomic data converge on altered metabolism as the principal feature of the disease. However, in view of multiple biochemical alterations and high level of tumor heterogeneity, identification of clearly defined subtypes is necessary for further improvement of treatments. In the future, single-cell combined multi-omics approaches will be the next generation of analyses gaining deeper insights into ccRCC progression and allowing for design of specific signatures, with better prognostic/predictive clinical applications.

Immune classification of clear cell renal cell carcinoma

Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<0.01$$\end{document}<0.01) compared to the patients with tumors for all groups of tumors except group 3.

Immune classification of clear cell renal cell carcinoma

Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value [Formula: see text]). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value [Formula: see text]), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value [Formula: see text]). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value [Formula: see text]) compared to the patients with tumors for all groups of tumors except group 3.

Characterization of the expression and immunological impact of the transcriptional activator CREB in renal cell carcinoma

Background

The non-classical human leukocyte antigen (HLA)-G is a strong immunomodulatory molecule. Under physiological conditions, HLA-G induces immunological tolerance in immune privileged tissues, while under pathophysiological situations it contributes to immune escape mechanisms. Therefore, HLA-G could act as a potential immune checkpoint for future anti-cancer immunotherapies. Recent data suggest an aberrant expression of the cAMP response element binding protein (CREB) in clear cell renal cell carcinoma (ccRCC), which is correlated with tumor grade and stage. Furthermore, preliminary reports demonstrated a connection of CREB as a control variable of HLA-G transcription due to CREB binding sites in the HLA-G promoter region. This study investigates the interaction between CREB and HLA-G in different renal cell carcinoma (RCC) subtypes and its correlation to clinical parameters.

Methods

The direct interaction of CREB with the HLA-G promoter was investigated by chromatin immunoprecipitation in RCC cell systems. Furthermore, the expression of CREB and HLA-G was determined by immunohistochemistry using a tissue microarray (TMA) consisting of 453 RCC samples of distinct subtypes. Staining results were assessed for correlations to clinical parameters as well as to the composition of the immune cell infiltrate.

Results

There exists a distinct expression pattern of HLA-G and CREB in the three main RCC subtypes. HLA-G and CREB expression were the lowest in chromophobe RCC lesions. However, the clinical relevance of CREB and HLA-G expression differed. Unlike HLA-G, high levels of CREB expression were positively associated to the overall survival of RCC patients. A slightly, but significantly elevated number of tumor infiltrating regulatory T cells was observed in tumors of high CREB expression. Whether this small increase is of clinical relevance has to be further investigated.

Conclusions

An interaction of CREB with the HLA-G promoter could be validated in RCC cell lines. Thus, for the first time the expression of CREB and its interaction with the HLA-G in human RCCs has been shown, which might be of clinical relevance.

The immunology of renal cell carcinoma

Renal cell carcinoma (RCC) is the most common type of kidney cancer and comprises several subtypes with unique characteristics. The most common subtype (~70% of cases) is clear-cell RCC. RCC is considered to be an immunogenic tumour but is known to mediate immune dysfunction in large part by eliciting the infiltration of immune-inhibitory cells, such as regulatory T cells and myeloid-derived suppressor cells, into the tumour microenvironment. Several possible mechanisms have been proposed to explain how these multiple tumour-infiltrating cell types block the development of an effective anti-tumour immune response, including inhibition of the activity of effector T cells and of antigen presenting cells via upregulation of suppressive factors such as checkpoint molecules. Targeting immune suppression using checkpoint inhibition has resulted in clinical responses in some patients with RCC and combinatorial approaches involving checkpoint blockade are now standard of care in patients with advanced RCC. However, a substantial proportion of patients do not benefit from checkpoint blockade. The identification of reliable biomarkers of response to checkpoint blockade is crucial to facilitate improvements in the clinical efficacy of these therapies. In addition, there is a need for the development of other immune-based strategies that address the shortcomings of checkpoint blockade, such as adoptive cell therapies.

Significance of tumor microenvironment in acquiring resistance to vascular endothelial growth factor-tyrosine kinase inhibitor and recent advance of systemic treatment of clear cell renal cell carcinoma

The development of systemic therapies, including vascular endothelial growth factor-tyrosine kinase inhibitors (VEGF-TKI) and mammalian target of rapamycin (mTOR) inhibitors, represents a major breakthrough in the treatment of patients with renal cell carcinoma (RCC). However, inherent resistance is observed in some patients and acquired resistance commonly develops in many patients within several months of the initiation of systemic therapies. Since these treatments rarely cure patients, their aim is to suppress tumor progression and prolong survival. Therefore, the establishment of dependable criteria that predict responses and resistance to systemic therapies is clinically important, and the underlying molecular mechanisms also need to be elucidated for the future development of more effective therapies. We herein review recent advances in research on the molecular mechanisms underlying resistance, with a focus on morphological characteristics, tumor angiogenesis, and the tumor immune microenvironment in RCC and their relationships with VEGF-TKI treatments. Recent therapies using immune checkpoint inhibitors (ICI) and newly developed VEGF-TKI also appear to be effective for advanced RCC, with stable and durable responses to ICI being observed in some RCC patients. These new drugs and their outcomes have been briefly described.

Efficacy of an Oncolytic Adenovirus Driven by a Chimeric Promoter and Armed with Decorin Against Renal Cell Carcinoma

Virus-targeted therapy for tumors can effectively prolong the survival rate of patients and has become a new trend for cancer biotherapy. Oncolytic adenovirus (OAd) can specifically replicate in tumor cells, allowing the therapeutic genes carried to be rapidly copied. As known, solid tumors are always hypoxic, and researchers often overlook a key point, the replication of OAd depends not only on its own activity but also on the cellular hypoxic environment in which the virus replicates. In this study, we constructed an OAd carrying Decorin, HRE-Ki67-Decorin, combining the Ki67 promoter upstreamed with hypoxia-response element (HRE) sequences to drive adenoviral E1A. The OAd HRE-Ki67-Decorin had better replication ability under hypoxic conditions, downregulated cellular immunosuppressed growth factor TGF-β. In addition, HRE-Ki67-Decorin was potent in suppressing tumor growth and participated in the assembly of tumor extracellular matrix by expressing Decorin in subcutaneous renal cancer cell tumor models. Tumor sections from HRE-Ki67-Decorin-treated tissues had less collagen fibers and more spread of virus among tumor tissues. These results indicated that chimeric HRE-Ki67 promoter-regulated OAd carrying Decorin might be an effective anticancer treatment strategy.

Identification of biomarkers related to CD8+ T cell infiltration with gene co-expression network in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an extremely common kind of kidney cancer in adults. Immunotherapy and targeted therapy are particularly effective at treating ccRCC. In this study, weighted gene co-expression network analysis and a deconvolution algorithm that quantifies the cellular composition of immune cells were used to analyze ccRCC expression data from the Gene Expression Omnibus database, and identify modules related to CD8⁺ T cells. Ten hub genes (LCK, CD2, CD3D, CD3G, IRF1, IFNG, CCR5, CD8A, CCL5, and CXCL9) were identified by co-expression network and protein-protein interactions network analysis. Datasets obtained from The Cancer Genome Atlas were analyzed and the data revealed that the hub genes were meaningfully up-regulated in tumor tissues and correlated with promotion of tumor progression. After Kaplan-Meier analysis and Oncomine meta-analysis, CCL5 was selected as a prognostic biomarker. Finally, the experimental results show that reduced expression of CCL5 decreased cell proliferation and invasion in the ccRCC cell line. Various analyses were performed and verified, CCL5 is a potential biomarker and therapeutic target which related to CD8⁺ T cell infiltration in ccRCC.

6-Gingerol induces cell-cycle G1-phase arrest through AKT-GSK 3β-cyclin D1 pathway in renal-cell carcinoma

Purpose

6-Gingerol, a major biochemical and pharmacological active ingredient of ginger, has shown anti-inflammatory and antitumor activities against various cancers. Searching for natural products with fewer side effects for developing adjunctive therapeutic options is necessary.

Methods

The effects of 6-gingerol on proliferation, colony formation, and cell cycle in RCC cells were detected by a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, colony formation assay, and propidium iodide (PI) staining, respectively. Western blotting, an immunofluorescence assay, and immunohistochemical staining were performed to assess the expression of relevant proteins. A subcutaneous tumor model was set up to investigate the 6-gingerol effects on tumor growth in vivo, and the pharmacokinetics of 6-gingerol in mice were detected by LC/MS assays.

Results

6-Gingerol treatment exerted time- and dose-dependent inhibition of the growth and colony formation of ACHN, 786-O, and 769-P cells, leading to a concomitant induction of cell-cycle G1-phase arrest and decrease in Ki-67 expression in the cell nucleus. Western-blotting results showed that 6-gingerol reduces phosphorylation of protein kinase B (AKT) Ser 473, cyclin-dependent kinases (CDK4), and cyclin D1 and, meanwhile, increases glycogen synthase kinase (GSK 3β) protein amount. Furthermore, the efficacy of 6-gingerol was demonstrated in an in vivo murine model of 786-O.

Conclusion

The above results indicate that 6-gingerol can induce cell-cycle arrest and cell-growth inhibition through the AKT–GSK 3β–cyclin D1 signaling pathway in vitro and in vivo, suggesting that 6-gingerol should be useful for renal-cell carcinoma treatment.

Electronic supplementary material

The online version of this article (10.1007/s00280-019-03999-9) contains supplementary material, which is available to authorized users.

Profiles of tumor-infiltrating immune cells in renal cell carcinoma and their clinical implications

Tumor-infiltrating immune cells (TIICs) are crucial for the clinical outcome of renal cell carcinoma (RCC), as they regulate cancer progression. TIICs have therefore the potential to become novel targets of immunotherapies. The present study used CIBERSORT analytical tool, which is a deconvolution algorithm, to comprehensively analyze the composition of immune cells in RCC and normal tissues from The Cancer Genome Atlas (TCGA) cohort, and to determine the prognostic value of TIICs in RCC. A landscape of infiltrating immune cells was determined as containing 13 subpopulations of immune cells, with significant differences between normal and tumor tissues. Subsequently, Kaplan-Meier analysis and log-rank test were used to estimate the prognostic value of TIICs in RCC. The results demonstrated that a higher proportion of regulatory T cells (Tregs) [hazard ratio (HR)=1.596; 95% confidence interval (CI), 1.147–2.222; P=0.006] and follicular helper T cells (HR=1.516; 95% CI, 1.089–2.111; P=0.014) were associated with poor outcome in patients with RCC. Conversely, resting mast cells (HR=0.678; 95% CI, 0.487–0.943; P=0.021) and monocytes (HR=0.701; 95% CI, 0.503–0.977; P=0.036) were associated with a favorable prognosis in patients with RCC. Furthermore, the results from multivariate Cox regression analysis indicated that Tregs and monocytes represented independent risk factors for prognosis in patients with RCC. These findings demonstrated that gene profiling deconvolution by CIBERSORT served to determine the composition of immune cells infiltrated in RCC and may provide some crucial information for the development of immunotherapies.

The role of cancer-associated fibroblasts in renal cell carcinoma. An example of tumor modulation through tumor/non-tumor cell interactions

Cancer-associated fibroblasts (CAF) are a cellular compartment of the tumor microenvironment (TME) with critical roles in tumor development. Fibroblast activation protein-α (FAP) is one of the proteins expressed by CAF and its immunohistochemical detection in routine practice is associated with tumor aggressiveness and shorter patient survival. For these reasons, FAP seems a good prognostic marker in many malignant neoplasms, including renal cell carcinoma (RCC). The start point of this Perspective paper is to review the role of CAF in the modulation of renal cell carcinoma evolution. In this sense, CAF have demonstrated to develop important protumor and/or antitumor activities. This apparent paradox suggests that some type of temporally or spatially-related specialization is present in this cellular compartment during tumor evolution. The end point is to remark that tumor/non-tumor cell interactions, in particular the symbiotic tumor/CAF connections, are permanent and ever-changing crucial phenomena along tumor lifetime. Interestingly, these interactions may be responsible of many therapeutic failures.

Role of immune checkpoint inhibitor-based therapies for metastatic renal cell carcinoma in the first-line setting: A Bayesian network analysis

BACKGROUND

Several novel immune checkpoint inhibitor (ICI)-based treatments exhibited promising survival benefits for metastatic renal cell carcinoma (mRCC), yet there is no current guidance regarding the optimum first-line regimen. We performed this network analysis to compare the efficacy and safety of all available treatments for mRCC.

METHODS

A systematic search of literature was conducted up to April 30, 2019, and the analysis was done on a Bayesian fixed-effect model.

FINDINGS

Twenty-five randomized clinical trials (RCTs) involving 13,010 patients were included in this study. The results showed that for overall survival, pembrolizumab plus axitinib (hazard ratio [HR]: 0.53; 95% credible interval [CrI]: 0.38-0.73) and nivolumab plus ipilimumab (HR: 0.63; 95% CrI: 0.50-0.79) were significantly more effective than sunitinib, and pembrolizumab plus axitinib was probably (68%) to be the best choice. For progression-free survival, cabozantinib (HR: 0.66; 95% CrI: 0.46-0.94), pembrolizumab plus axitinib (HR: 0.69; 95% CrI: 0.57-0.84), avelumab plus axitinib (HR: 0.69; 95% CrI: 0.56-0.85), nivolumab plus ipilimumab (HR: 0.82; 95% CrI: 0.68-0.99), and atezolizumab plus bevacizumab (HR: 0.86; 95% CrI: 0.74-0.99) were statistically superior to sunitinib, and cabozantinib was likely (43%) to be the preferred options. Nivolumab plus ipilimumab (OR: 0.50; 95% CrI: 0.28-0.84), and atezolizumab plus bevacizumab (OR: 0.56; 95% CrI: 0.36-0.83) were associated with significantly lower rate of high-grade adverse events than sunitinib.

INTERPRETATION

Our findings demonstrate that pembrolizumab plus axitinib might be the best treatment for mRCC, while nivolumab plus ipilimumab has the most favorable balance between efficacy and acceptability, and may provide new guidance to make treatment decisions. FUND: This research was supported by the Henan Provincial Scientific and Technological Research Project (Grant No. 192102310036).