Predictive Biomarkers of Response to Immunotherapy in Metastatic Renal Cell Cancer

A machine learning-based analysis for the definition of an optimal renal biopsy for kidney cancer

OBJECTIVE

Renal Tumor biopsy (RTB) can assist clinicians in determining the most suitable approach for treatment of renal cancer. However, RTB's limitations in accurately determining histology and grading have hindered its broader adoption and data on the concordance rate between RTB results and final pathology after surgery are unavailable. Therefore, we aimed to develop a machine learning algorithm to optimize RTB technique and to investigate the degree of concordance between RTB and surgical pathology reports.

MATERIALS AND METHODS

Within a prospectively maintained database, patients with indeterminate renal masses who underwent RTB at a single tertiary center were identified. We recorded and analyzed the approach (US vs. CT), the number of biopsy cores (NoC), and total core tissue length (LoC) to evaluate their impact on diagnostic outcomes. The K-Nearest Neighbors (KNN), a non-parametric supervised machine learning model, predicted the probability of obtaining pathological characterization and grading. In surgical patients, final pathology reports were compared with RTB results.

RESULTS

Overall, 197 patients underwent RTB. Overall, 89.8% (n=177) and 44.7% (n=88) of biopsies were informative in terms of histology and grading, respectively. The discrepancy rate between the pathology results from renal tissue biopsy (RTB) and the final pathology report following surgery was 3.6% (n=7) for histology and 5.0% (n=10) for grading. According to the machine learning model, a minimum of 2 cores providing at least 0.8 cm of total tissue should be obtained to achieve the best accuracy in characterizing the cancer. Alternatively, in cases of RTB with more than two cores, no specific minimum tissue threshold is required.

CONCLUSIONS

The discordance rates between RTB pathology and final surgical pathology are notably minimal. We defined an optimal renal biopsy strategy based on at least 2 cores and at least 0.8 cm of tissue or at least 3 cores and no minimum tissue threshold.

PATIENTS SUMMARY

RTB is a useful test for kidney cancer, but it's not always perfect. Our study shows that it usually matches up well with what doctors find during surgery. Using machine learning can make RTB even better by helping doctors know how many samples to take. This helps doctors treat kidney cancer more accurately.

Lessons learned from spatial transcriptomic analyses in clear-cell renal cell carcinoma

Spatial transcriptomics has emerged as a powerful tool for discerning the heterogeneity of the tumour microenvironment across various cancers, including renal cell carcinoma (RCC). Spatial transcriptomics-based studies conducted in clear-cell RCC (the only RCC subtype studied using this technique to date) have given insights into spatial interactions within this disease. These insights include the role of epithelial-to-mesenchymal transitioning, revealing proximity-dependent interactions between tumour cells, fibroblasts, interleukin-2-expressing macrophages and hyalinized regions. Investigations into metabolic programmes have shown high transcriptional heterogeneity within tumours, with a tendency of increased metabolic activity towards the tumour centre. T cell infiltration has been shown to be independent of neoantigen burden, although T cell activity correlates with both metabolic states and various transcripts expressed by tumour cells, fibroblasts and monocytes. The role of tertiary lymphoid structures in both plasma cell maturation and their infiltration of the tumour has been shown through tracks of fibroblasts. Collectively, these findings indicate the potential of spatial transcriptomics to reveal predictive spatial features, supporting its promise in the development of biomarkers for clear-cell RCC management.

Immunotherapy Applications for Thymine Dimers and WT1 Antigen in Renal Cancers: A Comparative Statistical Analysis

Renal cell carcinoma (RCC) remains incurable in advanced stages. Biomarkers have proven to be quite useful in cancer therapeutics. Herein, we provide a comparative/integrative statistical analysis of seminal immunohistochemistry (IHC) findings for Wilms' Tumor 1 antigen (WT1) and thymine dimers (TDs), emerging as atypical, yet promising, potential biomarkers for RCCs. We assessed WT1/TD reactivity in adult RCC tumor cells, tumor microenvironment (TME), and tumor-adjacent healthy renal tissue (HRT). WT1 positivity was scarce and strictly nuclear in tumor cells, whereas TD-reactive tumor tissues were prevalent. We report statistically significant positive correlations between the density of reactive RCC cellularity and the intensity of nuclear staining for both biomarkers (WT1 - rho = 0.341, p-value = 0.036; TDs - rho = 0.379, p-value = 0.002). RCC stromal TME TD-positivity was much more frequent than WT1 reactivity, apparently proportional to that of the proper RCC cellularity and facilitated by extensive RCC inflammatory infiltration. TDs exhibited nuclear reactivity for most TME cell lines, while RCC TME WT1 expression was rare and inconsistent. In HRTs, TDs were entirely restricted to renal tubular cells, the likely cellular progenitor of most conventional RCC subtypes. In lieu of proper validation, these early findings have significant implications regarding the origins/biology of RCCs and may inform RCC therapeutics, both accounting for the high frequency of immunotherapy-permissive frameshift indels in RCCs, but also hinting at novel predictive clinical tools for WT1-targeted immunotherapy. Overall, the current study represents a meek yet hopefully significant step towards understanding the molecular biology and potential therapeutic targets of RCCs.

Circulating microRNA-155-3p levels predicts response to first line immunotherapy in patients with metastatic renal cell carcinoma

Predictive biomarkers of response to immune checkpoint-based therapies (ICI) remain a critically unmet need in the management of advanced renal cell carcinoma (RCC). The complex interplay of the tumour microenvironment (TME) and the circulating immune response has proven to be challenging to decipher. MicroRNAs have gained increasing attention for their role in post-transcriptional gene expression regulation, particularly because they can have immunomodulatory properties. We evaluated the presence of immune-specific extracellular vesicle (EV) microRNAs in the plasma of patients with metastatic RCC (mRCC) prior to initiation of ICI. We found significantly lower levels of microRNA155-3p (miR155) in responders to ICI, when compared to non-responders. This microRNA has unique immunomodulatory properties, thus providing potential biological rationale for our findings. Our results support further work in exploring microRNAs as potential biomarkers of response to immunotherapy.

Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques

The advent of Surface-Enhanced Raman Scattering (SERS) has enabled the exploration and detection of small molecules, particularly in biological fluids such as serum, blood plasma, urine, saliva, and tears. SERS has been proposed as a simple diagnostic technique for various diseases, including cancer. Renal cell carcinoma (RCC) ranks as the sixth most commonly diagnosed cancer in men and is often asymptomatic, with detection occurring incidentally. The onset of symptoms typically aligns with advanced disease, aggressive histology, and unfavorable prognosis, and therefore new methods for an early diagnosis are needed. In this study, we investigated the utility of label-free SERS in urine, coupled with two multivariate analysis approaches: Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM), to discriminate between 50 RCC patients and 44 healthy donors. Employing LDA-PCA, we achieved a discrimination accuracy of 100% using 13 principal components, and an 88% accuracy in discriminating between different RCC stages. The SVM approach yielded a training accuracy of 100%, a validation accuracy of 99% for discriminating between RCC and controls, and an 80% accuracy for discriminating between stages. The comparative analysis of raw and normalized SERS spectral data shows that while raw data disclose relative concentration variations in urine metabolites between the two classes, the normalization of spectral data significantly improves the accuracy of discrimination. Moreover, the selection of principal components with markedly distinct scores between the two classes serves to alleviate overfitting risks and reduces the number of components employed for discrimination. We obtained the accuracy of the discrimination between the RCC patients cases and healthy donors of 90% for three PCs and a linear discrimination function, and a 88% accuracy of discrimination between stages using six PCs, mitigating practically the risk of overfitting and increasing the robustness of our analysis. Our findings underscore the potential of label-free SERS of urine in conjunction with chemometrics for non-invasive and early RCC detection.

Impact of Tumor Grade Distribution on Genetic Alterations in Clear Cell Renal Cell Carcinoma and Prostate Cancer

BACKGROUND/AIM

A genomic analysis based on next-generation sequencing is important for deciding cancer treatment strategies. Cancer tissue sometimes displays intratumor heterogeneity and a pathologic specimen may contain more than two tumor grades. Although tumor grades are very important for the cancer prognosis, the impact of higher tumor grade distribution in a specimen used for a genomic analysis is unknown.

PATIENTS AND METHODS

We retrospectively analyzed the data of 61 clear cell carcinoma and 46 prostate cancer patients that were diagnosed between December 2018 and August 2022 using the GeneRead Human Comprehensive Cancer Panel or SureSelect PrePool custom Tier2. Genome annotation and curation were performed using the GenomeJack software.

RESULTS

Tumor mutation burden (TMB) was increased in proportion to the higher tumor grade distribution in grade 2 clear cell renal cell carcinoma (ccRCC). In PC, Grade Group 3/4 specimens that included an increased distribution of Gleason pattern 4 had more frequent gene mutations.

CONCLUSION

Our results suggest the importance of selecting the maximum distribution of higher tumor grade areas to obtain results on the precise gene alterations for genomics-focused treatments.

Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic

The incidence of renal cell carcinoma (RCC) is increasing worldwide, yet research within this field is lagging behind other cancers. Despite increased detection of early disease as a consequence of the widespread use of diagnostic CT scans, 25% of patients have disseminated disease at diagnosis. Similarly, around 25% progress to metastatic disease following curatively intended surgery. Surgery is the cornerstone in the treatment of RCC; however, when the disease is disseminated, immunotherapy or immunotherapy in combination with a tyrosine kinase inhibitor is the patient's best option. Immunotherapy is a potent treatment, with durable treatment responses and potential to cure the patient, but only half of the patients benefit from the administered treatment, and there are currently no methods that can identify which patients will respond to immunotherapy. Moreover, there is a need to identify the patients in greatest risk of relapsing after surgery for localized disease and direct adjuvant treatment there. Even though several molecular biomarkers have been published to date, we are still lacking routinely used biomarkers to guide optimal clinical management. The purpose of this review is to highlight some of the most promising biomarkers, discuss the efforts made within this field to date, and describe the barriers needed to be overcome to have reliable and robust predictive and prognostic biomarkers in the clinic for renal cancer.

Clinical Importance of Cannabinoid Type 1 Receptor (CB1R) and Cannabinoid Type 2 Receptor (CB2R) Expression in Renal Cell Carcinoma

Background and objective The purpose of our study was to assess the expression of cannabinoid type 1 receptor (CB1R) and cannabinoid type 2 receptor (CB2R), including positivity, intensity, percentage, site of distribution, and immunohistochemical score, in renal cell carcinomas (RCCs) and explore their correlation with various clinicopathological aspects. Methodology We retrospectively obtained data and specimens from 87 patients diagnosed with RCC after partial or radical nephrectomy, and the CB1R and CB2R expression was assessed immunohistochemically on paraffin-embedded tissues. The results were statistically analyzed uni- and multi-factorial along with clinicopathological parameters. Results CB1R was not expressed at all, and CB2R was highly expressed in 78 (89.7%) patients with RCC. In unifactorial analysis, no statistical significance was found in any of the analyzed parameters. However, in the multifactorial analysis, we found that patients with a papillary histologic type (P < 0.0005) were associated with a lower likelihood of expression of the CB2R in the membranous compared with those with clear-cell and were also associated with a higher likelihood of moderate or strong expression of CB2R immunohistochemical score compared with those with clear-cell (P = 0.03). Patients with stage T2 (P = 0.010) had more enhanced expression (grade 3 CB2R intensity) compared with those with stage T1. Males (beta coefficient ± standard error [SE] 13.70 ± 7.04; P = 0.056) and patients with chromophobe histologic type (beta coefficient ± SE 23.45 ± 9.86; P = 0.020) were associated with a higher percentage of CB2R expression. Conclusions Our data suggest that although the CB1R was not expressed in RCCs, CB2R was expressed in almost every patient and enhanced expression was noted in correlation with specific clinicopathological aspects of the patients. Thus, following well-designed studies, especially CB2R could be used as a prognostic marker or even as a potential therapeutic target in RCC.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Identifying the Needs of Health Care Providers in Advanced First-Line Renal Cell Carcinoma: A Mixed-Methods Research

INTRODUCTION

Systemic treatments for metastatic or unresectable renal cell carcinoma (mRCC) are rapidly evolving. This study aimed at investigating challenges in the care of mRCC to inform future educational interventions for health care providers (HCPs).

MATERIALS AND METHODS

The sequential mixed-method design consisted of a qualitative phase (semistructured interviews) followed by a quantitative phase (online surveys). Participants included US-based medical oncologists, nephrologists, physician assistants, nurse practitioners, and registered nurses. Interview transcripts were thematically analyzed. Survey data was descriptively and inferentially analyzed.

RESULTS

Forty interviews and 265 surveys were completed. Analysis revealed four challenges in the care of mRCC patients. A challenge in staying current with emerging evidence and treatment recommendations was found with 33% of surveyed HCPs reporting suboptimal skills interpreting published evidence on the efficacy and safety of emerging agents. A challenge weighing patient health and preferences in treatment decisions was found, especially among HCPs with 3 to 10 years of practice (37%) who reported suboptimal skills in assessing patients' tolerance to side effects. Promoting a collaborative care approach to the management of immune-related adverse events was a challenge, specifically related to barriers involving nephrologists (eg, diverging treatment goals). Breakdowns in communication were reported (46% of HCPs), especially in the monitoring of side effects and treatment adherence.

CONCLUSION

This study revealed key challenges faced by HCPs when treating and managing patients with mRCC across multiple providers. Future interventions (eg, community of practice) should aim to address the identified gaps and promote a team-based approach to care that strengthens the complementary competencies of HCPs involved.

Axitinib Rechallenge Restores the Anticancer Effect after Nivolumab: A Case Report

The immune checkpoint inhibitor/tyrosine kinase inhibitor (ICI/TKI) combination treatment is currently the first-line treatment for metastatic renal cell carcinoma (mRCC). However, its efficacy beyond the third-line setting is expected to be relatively poor, and high-grade toxicities can develop by prior exposure to multiple drugs, resulting in a relatively poor performance in patients. Determining the best treatment regimen and sequence remains difficult and requires further investigation in patients with mRCC. In this study, two cases of mRCC, who failed several lines of TKI and nivolumab but exhibited a good anticancer effect after rechallenging with axitinib, are described. Both patients had a faster time to best response and better progression-free survival (PFS) than during previous treatments. Moreover, the axitinib dose could be reduced to 2.5 mg daily when used in combination with nivolumab while continuing to exert an impressive anticancer effect. To determine the cytotoxic effect, we performed a lymphocyte activation test and found that the level of granzyme B released by cytotoxic T lymphocytes and natural killer cells was higher when axitinib was combined with nivolumab. To evaluate this result, a bioinformatics approach was used to analyze the PRISM database. In conclusion, based on the results of a lymphocyte activation test and PD-1 expression, our findings indicate that sequential therapy with axitinib rechallenge after nivolumab resistance is reasonable for the treatment of mRCC.

Biomarkers for Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.

Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy.

METHODS

Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein-protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan-Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients.

RESULTS

Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan-Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan-Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored.

CONCLUSIONS

Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches.

Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time

Renal Cell Carcinoma (RCC) is a fatal urological cancer, with one third of patients diagnosed with metastasis, resulting in a 5-year survival of only 12%. Recent advancements in therapies have increased survival in mRCC, but lack efficacy in subtypes, due to treatment resistance and toxic side effects. Currently, white blood cells, hemoglobin, and platelets are limitedly used as blood based biomarkers to help determine RCC prognosis. Cancer associated macrophage-like cells (CAMLs) are a potential mRCC biomarker which have been identified in peripheral blood of patients with malignant tumors and have been shown to predict poor clinical patient outcomes based on their number and size. In this study, blood samples from 40 RCC patients were obtained to evaluate the clinical utility of CAMLs. CAML changes were monitored during treatment regimens to evaluate their ability to predict treatment efficacy. It was observed that patients with smaller CAMLs had better progression free survival (HR = 2.84, 95% CI 1.22-6.60, p = 0.0273) and overall survival (HR = 3.95, 95% CI 1.45-10.78, p = 0.0154) versus patients with larger CAMLs. These findings suggest that CAMLs can be used as a diagnostic, prognostic, and predictive biomarker for patients with RCC which may help improve management of advanced RCC.

Tumor microenvironment in renal cell carcinoma: what is the current impact?

Tweetable abstract Tumor microenvironment plays a critical role in tumor progression and response to therapy. Recent studies show the potential of gene expression signatures and T cells to predict response to immunotherapy in renal cell carcinoma.

Anti-programmed death-1 inhibitor nivolumab-induced immune-related adverse events: hepatitis, renal insufficiency, myositis, vitiligo, and hypothyroidism: a case-based review

Nivolumab (NIVO) is a monoclonal antibody used to treat renal cell cancer. It is an anti-programmed death-1 (anti-PD-1) inhibitor, enhancing the tumor-targeted immune response of T lymphocytes, resulting in immune-mediated adverse events (AEs). We present five immunological AEs in a single patient treated with NIVO. A 68-year-old male patient with metastatic renal cell carcinoma and right-sided nephrectomy received NIVO after pazopanib and sunitinib treatment. Two and a half months after starting NIVO, hepatocellular enzymes and creatinine were elevated. Concomitantly, the patient noticed hypopigmentation of the hand skin and a change in voice and speech. Due to hepatitis, he has been treated with dexamethasone 16 mg daily for 22 days, after which hypothyroidism and increased creatine kinase were found without muscle pain and functional impairment. Dexamethasone was continued, and a rapid decline in all parameters except thyroid-stimulating hormone (TSH) and vitiligo was observed. Myositis was initially considered a part of hypothyroidism and elevated renal parameters due to hypohydration. The rapid regression on glucocorticoid treatment and a longer time for creatinine normalization than expected with hydration were noticed. Nivolumab likely induced those side effects as assessed by Naranjo Adverse Drug Reaction Probability Scale. The literature review shows that the consequences of PD-1 inhibition are not uniform. Side effects of checkpoint inhibitors should be monitored carefully in the early and later treatment schedules evaluating subclinical manifestations like myositis and worsening of kidney parameters. Early administered higher doses of glucocorticoids can stop drug toxicity and reverse-induced tissue damage.

Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma

The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.

Baseline and Dynamic Changes in Hemoglobin Levels Predict Treatment Response and Prognosis in Metastatic Renal Cell Carcinoma: A Multicenter Retrospective Study

INTRODUCTION

Clinical markers of response in metastatic renal cell carcinoma (mRCC) are lacking. Low hemoglobin (Hb) is associated with poor outcomes in the IMDC risk score. This study evaluates the role of Hb as a marker of treatment outcomes in mRCC.

PATIENTS AND METHODS

This multicenter retrospective study evaluated 276 patients with mRCC treated with frontline immune checkpoint inhibitor (ICI) therapy, ICI and vascular endothelial growth factor (VEGF) inhibitor (VEGFI) combinations (ICI/VEGFI), or VEGFI monotherapy between 2014 and 2021. Hb levels at baseline, week 6 and 12 and at disease progression or death were recorded. Patients were categorized as responders (CR+PR) or nonresponders (SD+PD) using cross-sectional imaging at week 12. The association between baseline and dynamic changes in Hb and oncological outcomes was assessed.

RESULTS

Thirty-seven percent, 40% and 22% of patients received ICIs, ICI/VEGFI and VEGFI respectively. In patients receiving ICIs, there was a significant increase in Hb amongst responders from baseline to week 12 (P= .02). Amongst patients receiving ICI/VEGFI, there was an increase in Hb from baseline to week 12 which was greater in responders (P< .001). In patients receiving VEGFI monotherapy, responders had a higher Hb at baseline (P= .01), week 6 (P= .04), and week 12 (P= .003). An increase in Hb was a significant independent predictor of progression-free survival amongst patients receiving ICIs (HR 0.40, 95%CI, 0.19-0.83, P= .009).

CONCLUSION

Baseline and dynamic changes in Hb are associated with first-line treatment outcomes in patients with mRCC and represent a pragmatic early serological marker.

Clear Cell Renal Cell Carcinoma: From Biology to Treatment

The majority of kidney cancers are detected incidentally and typically diagnosed at a localized stage, however, the development of regional or distant disease occurs in one-third of patients. Over 90% of kidney tumors are renal cell carcinomas, of which, clear cell is the most predominate histologic subtype. Von Hippel Lindau (VHL) gene alterations result in the overexpression of growth factors that are central to the pathogenesis of clear cell carcinoma. The therapeutic strategies have revolved around this tumor suppressor gene and have led to the approval of tyrosine kinase inhibitors (TKI) targeting the vascular endothelial growth factor (VEGF) axis. The treatment paradigm shifted with the introduction of immune checkpoint inhibitors (ICI) and programed death-1 (PD-1) inhibition, leading to durable response rates and improved survival. Combinations of TKI and/or ICIs have become the standard of care for advanced clear cell renal cell carcinoma (ccRCC), changing the outlook for patients, with several new and promising therapeutic targets under development.

A new label-free optical imaging method for the lymphatic system enhanced by deep learning

Our understanding of the lymphatic vascular system lags far behind that of the blood vascular system, limited by available imaging technologies. We present a label-free optical imaging method that visualizes the lymphatic system with high contrast. We developed an orthogonal polarization imaging (OPI) in the shortwave infrared range (SWIR) and imaged both lymph nodes and lymphatic vessels of mice and rats in vivo through intact skin, as well as human mesenteric lymph nodes in colectomy specimens. By integrating SWIR-OPI with U-Net, a deep learning image segmentation algorithm, we automated the lymph node size measurement process. Changes in lymph nodes in response to cancer progression were monitored in two separate mouse cancer models, through which we obtained insights into pre-metastatic niches and correlation between lymph node masses and many important biomarkers. In a human pilot study, we demonstrated the effectiveness of SWIR-OPI to detect human lymph nodes in real time with clinical colectomy specimens.

One Sentence Summary

We develop a real-time high contrast optical technique for imaging the lymphatic system, and apply it to anatomical pathology gross examination in a clinical setting, as well as real-time monitoring of tumor microenvironment in animal studies.

Contemporary Clinical Definitions, Differential Diagnosis, and Novel Predictive Tools for Renal Cell Carcinoma

Despite significant progress regarding clinical detection/imaging evaluation modalities and genetic/molecular characterization of pathogenesis, advanced renal cell carcinoma (RCC) remains an incurable disease and overall RCC mortality has been steadily rising for decades. Concomitantly, clinical definitions have been greatly nuanced and refined. RCCs are currently viewed as a heterogeneous series of cancers, with the same anatomical origin, but fundamentally different metabolisms and clinical behaviors. Thus, RCC pathological diagnosis/subtyping guidelines have become increasingly intricate and cumbersome, routinely requiring ancillary studies, mainly immunohistochemistry. Meanwhile, RCC-associated-antigen targeted systemic therapy has been greatly diversified and emerging, novel clinical applications for RCC immunotherapy have already reported significant survival benefits, at least in the adjuvant setting. Even so, systemically disseminated RCCs still associate very poor clinical outcomes, with currently available therapeutic modalities only being able to prolong survival. In lack of a definitive cure for advanced RCCs, integration of the amounting scientific knowledge regarding RCC pathogenesis into RCC clinical management has been paramount for improving patient outcomes. The current review aims to offer an integrative perspective regarding contemporary RCC clinical definitions, proper RCC clinical work-up at initial diagnosis (semiology and multimodal imaging), RCC pathological evaluation, differential diagnosis/subtyping protocols, and novel clinical tools for RCC screening, risk stratification and therapeutic response prediction.

The prognostic value of baseline and early variations of peripheral blood inflammatory ratios and their cellular components in patients with metastatic renal cell carcinoma treated with nivolumab: The Δ-Meet-URO analysis

BACKGROUND

Treatment choice for metastatic renal cell carcinoma (mRCC) patients is still based on baseline clinical and laboratory factors.

METHODS

By a pre-specified analysis of the Meet-URO 15 multicentric retrospective study enrolling 571 pretreated mRCC patients receiving nivolumab, baseline and early dynamic variations (Δ) of neutrophil, lymphocyte, and platelet absolute cell counts (ACC) and their inflammatory ratios (IR) were evaluated alongside their association with the best disease response and overall (OS) and progression-free survival (PFS). Multivariable analyses on OS and PFS between baseline and Δ ACC and IR values were investigated with receiving operating curves-based cut-offs.

RESULTS

The analysis included 422 mRCC patients. Neutrophil-to-lymphocyte ratio (NLR) increased over time due to consistent neutrophil increase (p < 0.001). Higher baseline platelets (p = 0.044) and lower lymphocytes (p = 0.018), increasing neutrophil Δ (p for time-group interaction <0.001), higher baseline IR values (NLR: p = 0.012, SII: p = 0.003, PLR: p = 0.003), increasing NLR and systemic immune-inflammatory index (SII) (i.e., NLR x platelets) Δ (p for interaction time-group = 0.0053 and 0.0435, respectively) were associated with disease progression. OS and PFS were significantly shorter in patients with baseline lower lymphocytes (p < 0.001 for both) and higher platelets (p = 0.004 and p < 0.001, respectively) alongside early neutrophils Δ (p = 0.046 and p = 0.033, respectively). Early neutrophils and NLR Δ were independent prognostic factors for both OS (p = 0.014 and p = 0.011, respectively) and PFS (p = 0.023 and p = 0.001, respectively), alongside baseline NLR (p < 0.001 for both) and other known prognostic variables.

CONCLUSIONS

Early neutrophils and NLR Δ may represent new dynamic prognostic factors with clinical utility for on-treatment decisions.

A Randomized Phase II Study of MEDI0680 in Combination with Durvalumab versus Nivolumab Monotherapy in Patients with Advanced or Metastatic Clear-cell Renal Cell Carcinoma

PURPOSE

MEDI0680 is a humanized anti-programmed cell death-1 (PD-1) antibody, and durvalumab is an anti-PD-L1 antibody. Combining treatment using these antibodies may improve efficacy versus blockade of PD-1 alone. This phase II study evaluated antitumor activity and safety of MEDI0680 plus durvalumab versus nivolumab monotherapy in immunotherapy-naïve patients with advanced clear-cell renal cell carcinoma who received at least one prior line of antiangiogenic therapy.

PATIENTS AND METHODS

Patients received either MEDI0680 (20 mg/kg) with durvalumab (750 mg) or nivolumab (240 mg), all intravenous, every 2 weeks. The primary endpoint was investigator-assessed objective response rate (ORR). Secondary endpoints included best overall response, progression-free survival (PFS), safety, overall survival (OS), and immunogenicity. Exploratory endpoints included changes in circulating tumor DNA (ctDNA), baseline tumor mutational burden, and tumor-infiltrated immune cell profiles.

RESULTS

Sixty-three patients were randomized (combination, n = 42; nivolumab, n = 21). ORR was 16.7% [7/42; 95% confidence interval (CI), 7.0-31.4] with combination treatment and 23.8% (5/21; 95% CI, 8.2-47.2) with nivolumab. Median PFS was 3.6 months in both arms; median OS was not reached in either arm. Because of adverse events, 23.8% of patients discontinued MEDI0680 and durvalumab and 14.3% of patients discontinued nivolumab. In the combination arm, reduction in ctDNA fraction was associated with longer PFS. ctDNA mutational analysis did not demonstrate an association with response in either arm. Tumor-infiltrated immune profiles showed an association between immune cell activation and response in the combination arm.

CONCLUSIONS

MEDI0680 combined with durvalumab was safe and tolerable; however, it did not improve efficacy versus nivolumab monotherapy.

Transmembrane Transporter Sema3D Serves as a Tumor Suppressor in Localized Clear Cell Renal Cell Carcinoma

Background

The transmembrane transporter Sema3D is a vital molecule involved in axon guidance and carcinogenesis of variant malignancies. However, the relationship between Sema3D and clear cell renal cell carcinoma (ccRCC) is barely reported and remains unclear.

Methods

Sema3D expression and the connection of clinical and histological characteristics were first analyzed with transcriptome data in the TCGA repository. We then located and examined the Sema3D expression in ccRCC patients by using immunofluorescence staining in the tissue microarray. The prognostic value of Sema3D in localized ccRCC was evaluated by Cox proportional hazard analysis. Functional and gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to describe the potential mechanisms of Sema3D in ccRCC. Correlation analysis between Sema3D and tumor-infiltrating lymphocytes was calculated by ssGSEA.

Results

In 86 ccRCC patients, Sema3D mRNA and protein expression were downregulated in tumor tissues than the para-tumor tissues, and Sema3D was dominantly expressed in the extracellular space. Low expression of Sema3D was associated with advanced tumor stage, advanced histological grade, and poor prognosis in ccRCC. In the subgroup analysis of 81 localized ccRCC patients, Sema3D expression level was an independent protective prognostic factor for overall survival (OS) (HR = 0.125, p=0.043). Coagulation, complement, estrogen response, and KRAS signaling hallmark gene sets were identified as Sema3D-related signaling pathways. The expression level of Sema3D was significantly correlated with a high abundance of several immune cells (neutrophils, eosinophils, and T helper cells).

Conclusions

Transmembrane transporter Sema3D is an efficient prognostic biomarker for localized ccRCC patients, by playing the role of tumor suppressor in ccRCC. Sema3D can be a novel therapeutic target for ccRCC.

Precision Medicine: An Optimal Approach to Patient Care in Renal Cell Carcinoma

Renal cell cancer (RCC) is a heterogeneous tumor that shows both intra- and inter-heterogeneity. Heterogeneity is displayed not only in different patients but also among RCC cells in the same tumor, which makes treatment difficult because of varying degrees of responses generated in RCC heterogeneous tumor cells even with targeted treatment. In that context, precision medicine (PM), in terms of individualized treatment catered for a specific patient or groups of patients, can shift the paradigm of treatment in the clinical management of RCC. Recent progress in the biochemical, molecular, and histological characteristics of RCC has thrown light on many deregulated pathways involved in the pathogenesis of RCC. As PM-based therapies are rapidly evolving and few are already in current clinical practice in oncology, one can expect that PM will expand its way toward the robust treatment of patients with RCC. This article provides a comprehensive background on recent strategies and breakthroughs of PM in oncology and provides an overview of the potential applicability of PM in RCC. The article also highlights the drawbacks of PM and provides a holistic approach that goes beyond the involvement of clinicians and encompasses appropriate legislative and administrative care imparted by the healthcare system and insurance providers. It is anticipated that combined efforts from all sectors involved will make PM accessible to RCC and other patients with cancer, making a tremendous positive leap on individualized treatment strategies. This will subsequently enhance the quality of life of patients.

Hypermutation as a potential predictive biomarker of immunotherapy efficacy in high-grade gliomas: a broken dream?

A high tumor mutational burden and mismatch repair deficiency are observed in 'hypermutated' high-grade gliomas (HGGs); however, the molecular characterization of this distinct subtype and whether it predicts the response to immune checkpoint inhibitors (ICIs) are largely unknown. Pembrolizumab is a valid therapeutic option for the treatment of hypermutated cancers of diverse origin, but only a few clinical trials have explored the activity of ICIs in hypermutated HGGs. HGGs appear to differ from other cancers, likely due to the prevalence of subclonal versus clonal neoantigens, which are unable to elicit an immune response with ICIs. The main aim of this review is to summarize the current knowledge on hypermutation in HGGs, focusing on the broken promises of tumor mutational burden and mismatch repair deficiency as potential biomarkers of response to ICIs.

A Retrospective Study of First-Line Therapy Involving Immune Checkpoint Inhibitors in Patients With Poor Risk Metastatic Renal Cell Carcinoma

Purpose

Patients with International Metastatic RCC Database Consortium (IMDC) poor risk metastatic renal cell carcinoma (mRCC) rarely respond to first-line tyrosine kinase inhibitors (TKIs) including sunitinib, and carries a very poor prognosis. In recent years, combination therapy involving immune checkpoint inhibitors (ICIs) have demonstrated superior efficacy to sunitinib in poor risk disease.

Materials and Methods

In a retrospective study using a cancer chemotherapy registry, 206 consecutive patients with mRCC in the first-line setting were identified between Oct 2019 and Dec 2020. Sixty-one patients had a poor risk mRCC, and were treated with TKI monotherapy (n=36), nivolumab plus ipilimumab (n=16), or pembrolizumab plus axitinib (n=9). Endpoints included overall survival (OS), progression-free survival (PFS), response rate (RR), and safety.

Results

Patients’ median age was 61 years and the median number of risk factors was 3 (range, 3-5). During a median 23.0 months of follow-up, the median OS was 24.3 months with ICI-based combinations and 14.8 months with TKI monotherapy, and the median PFS periods were 9.3 months and 3.4 months, respectively. An objective response occurred in 60% of the patients receiving ICI-based combinations and in 19% of those receiving TKI monotherapy (P=0.001). In the multivariate regression model, number of IMDC risk factors and the ICI-based combination therapy were independent prognostic factors for PFS. All-causality grade 3 or 4 adverse events were 44% for ICI-based combinations and 50% for TKI monotherapy.

Conclusions

Among patients with poor risk mRCC, first-line ICI-based therapy showed significantly longer OS and PFS, as well as a higher RR, than TKI monotherapy.

Tumor immunotherapies by immune checkpoint inhibitors (ICIs); the pros and cons

The main breakthrough in tumor immunotherapy was the discovery of immune checkpoint (IC) proteins, which act as a potent suppressor of the immune system by a myriad of mechanisms. After that, scientists focused on the immune checkpoint molecules mainly. Thereby, much effort was spent to progress novel strategies for suppressing these inhibitory axes, resulting in the evolution of immune checkpoint inhibitors (ICIs). Then, ICIs have become a promising approach and shaped a paradigm shift in tumor immunotherapies. CTLA-4 plays an influential role in attenuation of the induction of naïve and memory T cells by engagement with its responding ligands like B7-1 (CD80) and B7-2 (CD86). Besides, PD-1 is predominantly implicated in adjusting T cell function in peripheral tissues through its interaction with programmed death-ligand 1 (PD-L1) and PD-L2. Given their suppressive effects on anti-tumor immunity, it has firmly been documented that ICIs based therapies can be practical and rational therapeutic approaches to treat cancer patients. Nonetheless, tumor inherent or acquired resistance to ICI and some treatment-related toxicities restrict their application in the clinic. The current review will deliver a comprehensive overview of the ICI application to treat human tumors alone or in combination with other modalities to support more desired outcomes and lower toxicities in cancer patients. Video Abstract.

Reviewing Treatment Options for Advanced Renal Cell Carcinoma: Is There Still a Place for Tyrosine Kinase Inhibitor (TKI) Monotherapy?

Renal cell carcinoma (RCC) comprises a highly heterogeneous group of kidney tumours built upon distinct genetic- and epigenetic-driven mechanisms and molecular pathways. Therefore, responsiveness to treatment is considerably variable across patients, adding an extra layer of complexity to the already challenging therapeutic decision process. The last decade brought an unprecedented shift in the medical approach to advanced or metastatic RCC; in fact, immunotherapy-based combinations have significantly transformed the therapeutic arsenal and clinical outcomes of these patients. These strategies were quickly adopted by international guidelines committees as the new standards of care. However, this enhanced efficacy comes at the expense of tolerability, with a predictable negative impact on patients' quality of life. Moreover, subgroup and post hoc analyses of the major clinical trials have shown that not all patients benefit equally from these innovative approaches. In this context, a group of experts on kidney cancer met and discussed the state of the art in the field, with a special emphasis on the appropriateness of using monotherapy with an anti-angiogenesis tyrosine kinase inhibitor (TKI) to treat specific subgroups of patients with RCC. This article reviews the main topics that were considered to be pertinent for that discussion and establishes the profile of patients for whom TKI monotherapy remains a sensible frontline option by avoiding overtreatment and an unnecessary exposure to treatment-related toxicity.

piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers

piRNAs (PIWI-interacting RNAs) are small non-coding RNAs capable of regulation of transposon and gene expression. piRNAs utilise multiple mechanisms to affect gene expression, which makes them potentially more powerful regulators than microRNAs. The mechanisms by which piRNAs regulate transposon and gene expression include DNA methylation, histone modifications, and mRNA degradation. Genitourinary cancers (GC) are a large group of neoplasms that differ by their incidence, clinical course, biology, and prognosis for patients. Regardless of the GC type, metastatic disease remains a key therapeutic challenge, largely affecting patients’ survival rates. Recent studies indicate that piRNAs could serve as potentially useful biomarkers allowing for early cancer detection and therapeutic interventions at the stage of non-advanced tumour, improving patient’s outcomes. Furthermore, studies in prostate cancer show that piRNAs contribute to cancer progression by affecting key oncogenic pathways such as PI3K/AKT. Here, we discuss recent findings on biogenesis, mechanisms of action and the role of piRNAs and the associated PIWI proteins in GC. We also present tools that may be useful for studies on the functioning of piRNAs in cancers.

Genomics of Clear-cell Renal Cell Carcinoma: A Systematic Review and Meta-analysis

CONTEXT

Although antiangiogenic treatments and immunotherapies have significantly improved the prognosis of metastatic renal cell carcinoma (RCC), many patients will develop resistance, leading to treatment failure. Genetic tumor heterogeneity is a major cause of this resistance.

OBJECTIVE

To perform a meta-analysis of genomic data for clear-cell RCC obtained from primary tumors and metastases to assess the prevalence of gene mutations and copy number alterations (CNAs).

EVIDENCE ACQUISITION

Articles were selected from Medline and Embase libraries using the search algorithm ("Kidney Neoplasms"[Mesh] OR "Renal Cell Carcinoma") AND ("Genomics"[Mesh] OR "Mutation") from January 1999 to February 2021. A critical review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. Ninety-three publications were selected for inclusion in this meta-analysis.

EVIDENCE SYNTHESIS

Our meta-analysis included a total 14 696 patients, 14 299 primary tumor samples, and 969 metastatic samples. We evaluated the overall and subgroup prevalence of gene mutations and CNAs, including comparisons between primary tumors and metastases. In particular, for metastases we observed that the mutation prevalence was significantly more marked for ten genes compared to primary tumors, with no or little heterogeneity across studies. The VHL mutation prevalence increased significantly from 64% in primary tumors to 75% in metastases (p < 0.001). There was a significant increase in CNA prevalence from primary tumors to metastases for chromosomes 1p36.11, 9p21.3, and 18 in terms of losses, and for chromosomes 1q21.3, 7q36.3, 8q, and 20q11.21 in terms of gains. CDKN2A, also called p16 and involved in cell-cycle progression, is located at the 9p21.3 locus and was lost in 76% of metastatic samples. ASXL1, located on 20p11.21 and amplified in 50% of metastatic RCCs compared to 21% of primary tumors (p < 0.001), is closely linked to BAP1 function.

CONCLUSIONS

Our results underline the added value of preferential biopsies on RCC metastases to fully explore the biology of metastatic disease for therapeutic purposes.

PATIENT SUMMARY

We reviewed the literature on genetic mutations in primary tumors and metastatic lesions in kidney cancer. Our pooled results for all the relevant studies show a higher level of mutations in metastases than in primary tumors. This highlights the importance of taking biopsies of metastases to analyze genetic mutations and potentially guide selection of the most suitable treatment strategy.

Combination therapy with immune checkpoint inhibitors (ICIs); a new frontier

Recently, immune checkpoint inhibitors (ICIs) therapy has become a promising therapeutic strategy with encouraging therapeutic outcomes due to their durable anti-tumor effects. Though, tumor inherent or acquired resistance to ICIs accompanied with treatment-related toxicities hamper their clinical utility. Overall, about 60-70% of patients (e.g., melanoma and lung cancer) who received ICIs show no objective response to intervention. The resistance to ICIs mainly caused by alterations in the tumor microenvironment (TME), which in turn, supports angiogenesis and also blocks immune cell antitumor activities, facilitating tumor cells' evasion from host immunosurveillance. Thereby, it has been supposed and also validated that combination therapy with ICIs and other therapeutic means, ranging from chemoradiotherapy to targeted therapies as well as cancer vaccines, can capably compromise tumor resistance to immune checkpoint blocked therapy. Herein, we have focused on the therapeutic benefits of ICIs as a groundbreaking approach in the context of tumor immunotherapy and also deliver an overview concerning the therapeutic influences of the addition of ICIs to other modalities to circumvent tumor resistance to ICIs.

Assessment of prognostic factors in previously treated Japanese patients with metastatic renal cell carcinoma who received nivolumab: An observational multi-institute study

The aim of the present study was to evaluate the prognosis of Japanese patients with metastatic renal cell carcinoma (mRCC) receiving nivolumab and to identify factors predicting the overall survival (OS) in this cohort of patients. This study retrospectively assessed the outcomes of 77 consecutive Japanese patients with mRCC who were treated using either 1 or 2 molecular-targeted agents followed by nivolumab in routine clinical practice. The best responses to nivolumab observed were as follows: Complete response in 3 patients, partial response in 27, stable disease in 33 and progressive disease in 14; therefore, the objective response rate in the 77 patients was 39.0%. During the median follow-up period of 11 months after the introduction of nivolumab, the median progression-free survival and OS were 7 months and not reached, respectively. On multivariate analysis of several parameters, age, Karnofsky Performance Status (KPS) and neutrophil counts were demonstrated to be independently associated with OS in the 77 patients. By dividing these patients into 3 groups according to 3 risk factors, it was possible to stratify the OS; however, the International Metastatic Renal Cell Carcinoma Database Consortium model was unable to classify the OS. These results suggested that age, KPS and neutrophil counts were useful predictors of OS in previously treated patients with mRCC who received nivolumab.

Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma

Urothelial cancer (UC) is one of the common refractory tumors and chemotherapy is the primary treatment for it. The advent of immune checkpoint inhibitors (ICI) has facilitated the development of treatment strategies for UC patients. To screen out UC patients sensitive to ICI, researchers have proposed that PD-L1, tumor mutation burden and TCGA molecular subtypes can be used as predictors of ICI efficacy. However, the performance of these predictors needs further validation. We need to identify novel biomarkers to screen out UC patients sensitive to ICI. In our study, we collected the data of two clinical cohorts: the ICI cohort and the TCGA cohort. The result of the multivariate Cox regression analysis showed that glycogen metabolism score (GMS) (HR = 1.26, p = 0.017) was the negative predictor of prognosis for UC patients receiving ICI treatment. Low-GMS patients had a higher proportion of patients achieving complete response or partial response to ICI. After the comparison of gene mutation status between high-GMS and low-GMS patients, we identified six genes with significant differences in mutation frequencies, which may provide new directions for potential drug targets. Moreover, we analyzed the immune infiltration status and immune-related genes expression between high-GMS and low-GMS patients. A reduced proportion of tumor-associated fibroblasts and elevated proportion of CD8⁺ T cells can be observed in low-GMS patients while several immunosuppressive molecules were elevated in the high-GMS patients. Using the sequencing data of the GSE164042 dataset, we also found that myeloid-derived suppressor cell and neutrophil related signature scores were lower in α-glucosidase knockout bladder carcinoma cells when compared to the control group. In addition, angiogenesis, classic carcinogenic pathways, immunosuppressive cells related pathways and immunosuppressive cytokine secretion were mainly enriched in high-GMS patients and cell samples from the control group. Finally, we suspected that the combination treatment of ICI and histone deacetylase inhibitors may achieve better clinical responses in UC patients based on the analysis of drug sensitivity data. In conclusion, our study revealed the predictive value of GMS for ICI efficacy of UC patients, providing a novel perspective for the exploration of new drug targets and potential treatment strategies.

Clinical outcome of renal cancer patients who early interrupted immunotherapy due to serious immune-related adverse events. Meet-Uro 13 trial on behalf of the MeetUro investigators

BACKGROUND

Severe immune-related Adverse Events (irAEs) develop in 10-27% of patients treated with Immune-Oncology (IO) [Powles (Lancet 391:748-757, 2018); Galsky (Lancet 395:1547-1557, 2020); Haanen (Ann Oncol 28:119-142, 2017)]. The aim of our study was to evaluate efficacy and clinical outcome of metastatic renal cell carcinoma (mRCC) patients who stopped Immune Checkpoint Inhibitors (ICIs) due to early Grade (G) 3-G4 irAEs.

METHODS

We retrospectively collected data from 204 mRCC patients treated with ICIs in 6 Italian referral centers adhering to the Meet-Uro group, between February 2017 and January 2020. To properly weight the results, patients who did not report early G3-G4 toxicities have been included as control group. Primary endpoint was to evaluate 6 months Progression Free Survival (PFS) after early treatment interruption for Grade (G) 3-4 toxicities compared to the control group. Secondary endpoints were to evaluate Time to treatment failure (TTF) and overall survival (OS) in both groups. All statistical analyses were performed using SPSS software (version 19.00, SPSS, Chicago).

RESULTS

18/204 (8.8%) patients had early treatment interruption for serious (G3-G4) irAEs. Early was defined as interruption of IO after only one or two administrations. Immune related nephritis and pancreatitis were the most common irAE that lead to treatment interruption. 6/18 patients received IO-IO combination whereas 12/18 patients antiPD1. In the study group, 12/18 (66.6%) were free from progression at 6 months since IO interruption, TTF was 1.6 months (95% CI 1.6-2.1), mPFS was 7.4 months (95% CI 3.16-11.6) and mOS was 15.5 months (5.1-25.8). In the control group 111/184 (60.3%) patients were free from progression at 6 months, TTF was 4.6 months (95% CI 3.5-5.6), mPFS was 4.6 months (95% CI 3.5-5.6) and mOS was 19.6 months (95% CI 15.1-24.0). In the overall population, mPFS was 5.0 months (95% CI 4.0-5.9) and mOS was 19.6 months (95% CI 15.1-24.0).

CONCLUSIONS

ICIs seem to maintain efficacy even after early interruption due to severe irAE.

Pembrolizumab for the treatment of renal cell carcinoma

INTRODUCTION

The acquisition of resistance to VEGF-inhibiting therapies has prompted research toward immunotherapy for the treatment of metastatic renal cell carcinoma (mRCC). Among several, checkpoint inhibitors including PD-1 and PD-L1 inhibitors are the most promising approach.

AREAS COVERED

This review addresses the clinical efficacy of the anti-PD-1 monoclonal antibody pembrolizumab in first- and second-line treatment for mRCC regarding the most recent and significant published and ongoing studies. Attention is also given to its pharmacological characteristics as well as adverse events and its impact on patients' quality of life.

EXPERT OPINION

Immunotherapy has become the backbone for the treatment of advanced RCC. With the approval of several therapeutic options, research needs now to focus on defining the appropriate therapy for each patient. Axitinib plus pembrolizumab belongs to the combinations of tyrosine kinase inhibitors (TKI) plus immune checkpoint inhibitors for the first-line treatment of metastatic RCC. New combinations of pembrolizumab plus TKI for the evaluation in first- and second-line treatment of mRCC available. However, studies directly comparing the various treatment regimens using predictive biomarkers and long-term endpoints, including treatment-free survival, are lacking.

Mechanisms of Neoantigen-Targeted Induction of Pyroptosis and Ferroptosis: From Basic Research to Clinical Applications

Neoantigens are tumor-specific antigens (TSAs) that are only expressed in tumor cells. They are ideal targets enabling T cells to recognize tumor cells and stimulate a potent antitumor immune response. Pyroptosis and ferroptosis are newly discovered types of programmed cell death (PCD) that are different from apoptosis, cell necrosis, and autophagy. Studies of ferroptosis and pyroptosis of cancer cells are increasing, and strategies to modify the tumor microenvironment (TME) through ferroptosis to inhibit the occurrence and development of cancer, improve prognosis, and increase the survival rate are popular research topics. In addition, adoptive T cell therapy (ACT), including chimeric antigen receptor T cell (CAR-T) technology and T cell receptor engineered T cell (TCR-T) technology, and checkpoint blocking tumor immunotherapies (such as anti-PD- 1 and anti-PD-L1 agents), tumor vaccines and other therapeutic technologies that rely on tumor neoantigens are rapidly being developed. In this article, the relationship between neoantigens and pyroptosis and ferroptosis as well as the clinical role of neoantigens is reviewed.

TERT promoter mutations and other prognostic factors in patients with advanced urothelial carcinoma treated with an immune checkpoint inhibitor

BACKGROUND

Immune checkpoint inhibitors (ICI) can achieve durable responses in a subset of patients with locally advanced or metastatic urothelial carcinoma (aUC). The use of tumor genomic profiling in clinical practice may help suggest biomarkers to identify patients most likely to benefit from ICI.

METHODS

We undertook a retrospective analysis of patients treated with an ICI for aUC at a large academic medical center. Patient clinical and histopathological variables were collected. Responses to treatment were assessed for all patients with at least one post-baseline scan or clear evidence of clinical progression following treatment start. Genomic profiling information was also collected for patients when available. Associations between patient clinical/genomic characteristics and objective response were assessed by logistic regression; associations between the characteristics and progression-free survival (PFS) and overall survival (OS) were examined by Cox regression. Multivariable analyses were performed to identify independent prognostic factors.

RESULTS

We identified 119 aUC patients treated with an ICI from December 2014 to January 2020. Genomic profiling was available for 78 patients. Overall response rate to ICI was 29%, and median OS (mOS) was 13.4 months. Favorable performance status at the start of therapy was associated with improved OS (HR 0.46, p=0.025) after accounting for other covariates. Similarly, the presence of a TERT promoter mutation was an independent predictor of improved PFS (HR 0.38, p=0.012) and OS (HR 0.32, p=0.037) among patients who had genomic profiling available. Patients with both a favorable performance status and a TERT promoter mutation had a particularly good prognosis with mOS of 21.1 months as compared with 7.5 months in all other patients (p=0.03).

CONCLUSIONS

The presence of a TERT promoter mutation was an independent predictor of improved OS in a cohort of aUC patients treated with an ICI who had genomic data available. Most of the clinical and laboratory variables previously shown to be prognostic in aUC patients treated with chemotherapy did not have prognostic value among patients treated with an ICI. Genomic profiling may provide important prognostic information and affect clinical decision making in this patient population. Validation of these findings in prospective patient cohorts is needed.

Biomarkers in renal cell carcinoma: Towards a more selective immune checkpoint inhibition

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Multiple prognostic markers are capable of predicting prognosis in mRCC.

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Biomarkers capable of predicting immune treatment efficacy in mRCC are needed.

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TIM-3 can have both a prognostic and predictive value.

•

Integrating biomarkers to the trials of combination therapies is essential.

Immune checkpoint inhibitors such as programmed death protein 1/programmed death-ligand 1 and cytotoxic T-lymphocyte–associated protein 4 inhibitors are already playing a central role in the treatment of metastatic renal cell carcinoma. However, they seem to be only effective in a subset of patients, with a high risk of innate and adaptive tumor resistance. Consequently, biomarkers capable of predicting immune treatment efficacy in advanced renal cancer are needed both in the clinical and the experimental setting. We hereby present a brief summary of evidence on the most studied biomarkers in metastatic renal cell carcinoma with a focus on the possible future place of T cell immunoglobulin and mucin domain-3 (TIM-3).

Identification of a Novel Glycolysis-Related Gene Signature Correlates With the Prognosis and Therapeutic Responses in Patients With Clear Cell Renal Cell Carcinoma

Background

Accumulating evidences indicate significant alterations in the aerobic glycolysis in clear cell renal cell carcinoma (ccRCC). We aim to develop and validate a glycolysis-related genes signature for predicting the clinical outcomes of patients with ccRCC.

Methods

mRNA expression profiling of ccRCC was obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. The protein expression levels of the core genes were obtained from the Human Protein Atlas database. We used four external independent data sets to verify the predictive power of the model for prognosis, tyrosine kinase inhibitor (TKI) therapy, and immunotherapy responses, respectively. Finally, we explored the potential mechanism of this signature through gene set enrichment analysis (GSEA).

Results

Through the GSEA, glycolysis-related gene sets were significantly different between ccRCC tissues and normal tissues. Next, we identified and constructed a seven-mRNA signature (GALM, TGFA, RBCK1, CD44, HK3, KIF20A, and IDUA), which was significantly correlated with worse survival outcome and was an independent prognostic indicator for ccRCC patients. Furthermore, the expression levels of hub genes were validated based on the Human Protein Atlas databases. More importantly, the model can predict patients’ response to TKI therapy and immunotherapy. These findings were successfully validated in the external independent ccRCC cohorts. The mechanism exploration showed that the model may influence the prognosis by influencing tumor proliferation, base mismatch repair system and immune status of patients.

Conclusions

Our study has built up a robust glycolysis-based molecular signature that predicts the prognosis and TKI therapy and immunotherapy responses of patients with ccRCC with high accuracy, which might provide important guidance for clinical assessment. Also, clinical investigations in large ccRCC cohorts are greatly needed to validate our findings.

Investigating T Cell Immunity in Cancer: Achievements and Prospects

T cells play a key role in tumour surveillance, both identifying and eliminating transformed cells. However, as tumours become established they form their own suppressive microenvironments capable of shutting down T cell function, and allowing tumours to persist and grow. To further understand the tumour microenvironment, including the interplay between different immune cells and their role in anti-tumour immune responses, a number of studies from mouse models to clinical trials have been performed. In this review, we examine mechanisms utilized by tumour cells to reduce their visibility to CD8⁺ Cytotoxic T lymphocytes (CTL), as well as therapeutic strategies trialled to overcome these tumour-evasion mechanisms. Next, we summarize recent advances in approaches to enhance CAR T cell activity and persistence over the past 10 years, including bispecific CAR T cell design and early evidence of efficacy. Lastly, we examine mechanisms of T cell infiltration and tumour regression, and discuss the strengths and weaknesses of different strategies to investigate T cell function in murine tumour models.

Soluble PD-L1 Is an Independent Prognostic Factor in Clear Cell Renal Cell Carcinoma

Simple Summary

Renal cell carcinoma (RCC) is a heterogeneous and complex disease with almost no response to chemotherapy. Immune checkpoint inhibitors have achieved great clinical success but no interesting circulating markers of clinical use have developed so far in clear cell renal cell carcinoma (CCRCC). We investigate the diagnostic and prognostic role of plasma PD-1 (sPD-1) and PD-L1 (sPD-L1) proteins for the first time together with the immunohistochemical expression counterpart of these proteins within the tumor front and tumor center in the same sample of patients with renal cancer undergoing surgery. We also investigate these plasma and tissue markers in the population of metastatic patients according to International mRCC Database Consortium (IMDC) prognostic groups and the response to systemic therapy. The independent role of sPD-L1 as a predictor of prognosis and treatment response is demonstrated.

Abstract

(1). Background: Immunohistochemical (IHC) evaluation of programmed death-1 (PD-1) and its ligand (PD-L1) is being used to evaluate advanced malignancies with potential response to immune checkpoint inhibitors. We evaluated both plasma and tissue expression of PD-1 and PD-L1 in the same cohort of patients, including non-metastatic and metastatic clear cell renal cell carcinoma (CCRCC). Concomitant plasma and tissue expression of PD-1 and PD-L1 was evaluated with emphasis on diagnostic and prognostic implications. (2) Methods: we analyzed PD-1 and PD-L1 IHC expression in tumor tissues and soluble forms (sPD-1 and sPD-L1) in plasma from 89 patients with CCRCC, of which 23 were metastatic and 16 received systemic therapy. The primary endpoint was evaluation of overall survival using Kaplan-Meier analysis and the Cox regression model. Plasma samples from healthy volunteers were also evaluated. (3) Results: Interestingly, sPD-1 and sPD-L1 levels were lower in cancer patients than in controls. sPD-1 and sPD-L1 levels and their counterpart tissue expression both at the tumor center and infiltrating front were not associated. Higher expression of both PD-1 and PD-L1 were associated with tumor grade, necrosis and tumor size. PD-1 was associated to tumor stage (pT) and PD-L1 to metastases. sPD-1 and sPD-L1 were not associated with clinico-pathological parameters, although both were higher in patients with synchronous metastases compared to metachronous ones and sPD-L1 was also higher for metastatic patients compared to non-metastatic patients. sPD-1 was also associated with the International Metastatic Renal Cell Cancer Database Consortium (IMDC) prognostic groups in metastatic CCRCC and also to the Morphology, Attenuation, Size and Structure (MASS) response criteria in metastatic patients treated with systemic therapy, mainly tyrosine-kinase inhibitors. Regarding prognosis, PD-L1 immunostaining at the tumor center with and without the tumor front was associated with worse survival, and so was sPD-L1 at a cut-off >793 ng/mL. Combination of positivity at both the tissue and plasma level increased the level of significance to predict prognosis. (4) Conclusions: Our findings corroborate the role of PD-L1 IHC to evaluate prognosis in CCRCC and present novel data on the usefulness of plasma sPD-L1 as a promising biomarker of survival in this neoplasia.

Finding predictive factors for immunotherapy in metastatic renal-cell carcinoma: What are we looking for?

A major breakthrough in cancer immunotherapy was the development of monoclonal antibodies targeting inhibitory immune checkpoint proteins. This approach demonstrated significant antitumor activity and efficacy in different cancer types, including metastatic renal cell carcinoma (mRCC). In the majority of patients, this drug is able to restore the patient's tumour-specific T-cell-mediated response thus improving both overall survival and objective response rate. However, a lack of clinical response occurs in a number of patients, raising questions about how to predict and increase the number of patients who receive long-term clinical benefit from immune checkpoint therapy or not. The aim of this review is to summarize available data about immune biomarkers in patients with mRCC treated with immunotherapy.