Predicting Response to Immunotherapy in Metastatic Renal Cell Carcinoma

Research progress on the impact of intratumoral microbiota on the immune microenvironment of malignant tumors and its role in immunotherapy

Microbiota has been closely related to human beings, whose role in tumor development has also been widely investigated. However, previous studies have mainly focused on the gut, oral, and/or skin microbiota. In recent years, the study of intratumoral microbiota has become a hot topic in tumor-concerning studies. Intratumoral microbiota plays an important role in the occurrence, development, and response to treatment of malignant tumors. In fact, increasing evidence has suggested that intratumoral microbiota is associated with malignant tumors in various ways, such as promoting the tumor development and affecting the efficacy of chemotherapy and immunotherapy. In this review, the impact of intratumoral microbiota on the immune microenvironment of malignant tumors has been analyzed, as well as its role in tumor immunotherapy, with the hope that it may contribute to the development of diagnostic tools and treatments for related tumors in the future.

Radiomics to predict immunotherapy efficacy in advanced renal cell carcinoma: A retrospective study

Immunotherapy has become a cornerstone for the treatment of renal cell carcinoma. Nevertheless, some patients are resistant to immune checkpoint inhibitors. The possibility to identify patients who cannot benefit from immunotherapy is a relevant clinical challenge. We analyzed the association between several radiomics features and response to immunotherapy in 53 patients treated with checkpoint inhibitors for advanced renal cell carcinoma. We found that the following features are associated with progression of disease as best tumor response: F_stat.range (p < .0004), F_stat.max (p < .0007), F_stat.var (p < .0016), F_stat.uniformity (p < .0020), F_stat.90thpercentile (p < .0050). Gross tumor volumes characterized by high values of F_stat.var and F_stat.max (greater than 60,000 and greater than 300, respectively) are most likely related to a high risk of progression. Further analyses are warranted to confirm these results. Radiomics, together with other potential predictive factors, such as gut microbiota, genetic features or circulating immune molecules, could allow a personalized treatment for patients with advanced renal cell carcinoma.

Treatment Landscape of Renal Cell Carcinoma

OPINION STATEMENT

The treatment landscape of renal cell carcinoma (RCC) has evolved significantly over the past three decades. Active surveillance and tumor ablation are alternatives to extirpative therapy in appropriately selected patients. Stereotactic body radiation therapy (SBRT) is an emerging noninvasive alternative to treat primary RCC tumors. The advent of immune checkpoint inhibitors (ICIs) has greatly improved the overall survival of advanced RCC, and now the ICI-based doublet (dual ICI-ICI doublet; or ICI in combination with a vascular endothelial growth factor tyrosine kinase inhibitor, ICI-TKI doublet) has become the standard frontline therapy. Based on unprecedented outcomes in the metastatic with ICIs, they are also being explored in the neoadjuvant and adjuvant setting for patients with high-risk disease. Adjuvant pembrolizumab has proven efficacy to reduce the risk of RCC recurrence after nephrectomy. Historically considered a radioresistant tumor, SBRT occupies an expanding role to treat RCC with oligometastasis or oligoprogression in combination with systemic therapy. Furthermore, SBRT is being investigated in combination with ICI-doublet in the advanced disease setting. Lastly, given the treatment paradigm is shifting to adopt ICIs at earlier disease course, the prospective studies guiding treatment sequencing in the post-ICI setting is maturing. The effort is ongoing in search of predictive biomarkers to guide optimal treatment option in RCC.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment

Background

Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates.

Results

21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1-ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. In CPTAC, collagen IV protein was more abundant in advanced stages of disease.

Conclusions

On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Comprehensive analyses of immune tumor microenvironment in papillary renal cell carcinoma

BACKGROUND

Papillary renal cell carcinoma (pRCC) is the most common non-clear cell RCC, and associated with poor outcomes in the metastatic setting. In this study, we aimed to comprehensively evaluate the immune tumor microenvironment (TME), largely unknown, of patients with metastatic pRCC and identify potential therapeutic targets.

METHODS

We performed quantitative gene expression analysis of TME using Microenvironment Cell Populations-counter (MCP-counter) methodology, on two independent cohorts of localized pRCC (n=271 and n=98). We then characterized the TME, using immunohistochemistry (n=38) and RNA-sequencing (RNA-seq) (n=30) on metastatic pRCC from the prospective AXIPAP trial cohort.

RESULTS

Unsupervised clustering identified two "TME subtypes", in each of the cohorts: the "immune-enriched" and the "immune-low". Within AXIPAP trial cohort, the "immune-enriched" cluster was significantly associated with a worse prognosis according to the median overall survival to 8 months (95% CI, 6 to 29) versus 37 months (95% CI, 20 to NA, p=0.001). The two immune signatures, Teff and JAVELIN Renal 101 Immuno signature, predictive of response to immune checkpoint inhibitors (CPI) in clear cell RCC, were significantly higher in the "immune-enriched" group (adjusted p<0.05). Finally, five differentially overexpressed genes were identified, corresponding mainly to B lymphocyte populations.

CONCLUSION

For the first time, using RNA-seq and immunohistochemistry, we have highlighted a specific immune TME subtype of metastatic pRCC, significantly more infiltrated with T and B immune population. This "immune-enriched" group appears to have a worse prognosis and could have a potential predictive value for response to immunotherapy, justifying the confirmation of these results in a cohort of metastatic pRCC treated with CPI and in combination with targeted therapies.

TRIAL REGISTRATION NUMBER

NCT02489695.

The role of spleen volume change in predicting immunotherapy response in metastatic renal cell carcinoma

INTRODUCTION

Resistance to immune checkpoint inhibitors (ICI) is a significant issue in metastatic renal cell carcinoma (mRCC), as it is in the majority of cancer types. An important deficiency in immunooncology today is the lack of a predictive factor to identify this patient group. Myeloid-derived suppressor cells (MDSC) are a type of cell that contributes to immunotherapy resistance by inhibiting T cell activity. While it accumulates in the tumor microenvironment and blood, it can also accumulate in lymphoid organs such as the spleen and cause splenomegaly. Therefore we aimed to evaluate the effect of increase in splenic volume, which can be considered as an indirect indicator of increased MDSC cells, on survival outcomes in mRCC patients.

METHODS

We analyzed 45 patients with mRCC who received nivolumab as a second-line or subsequent therapy. Splenic volume was analyzed from baseline imaging before starting nivolumab and from control imaging performed within the first 6 months of treatment initiation. Additionally, we analyzed how patients' body mass index (BMI), IMDC risk score, ECOG performance status, nephrectomy status, neutrophil-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR) and sites of metastasis.

RESULTS

Median splenic volume change was 10% (ranging from - 22% to + 117%) during follow-up. Change in splenic volume was found to be associated with overall survival (OS) and progression-free survival (PFS) (p = 0.025, 0.04). The median PFS in patients with increased splenic volume was 5 months, while it was 17 months in patients without increased splenic volume. (HR 2.1, 95% CI (1-4), p = 0.04). The median OS in patients with increased splenic volume was 9 months, while it was 35 months in patients without increased splenic volume (HR 2.7, 95% CI (1.1-6.2), p = 0.025). In four patients with decreased splenic volume, neither PFS nor OS could reach the median value. Log-rank p value in respectively (0.015, 0.035), The group in which an increase in volume was accompanied by a high NLR had the shortest survival rate. Basal splenic volume was analyzed separately. However, neither PFS nor OS differed significantly.

CONCLUSION

Our findings suggest that the change in splenic volume throughout immunotherapy regimens may be utilized to predict PFS and OS in mRCC patients undergoing treatment.

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.

Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature

It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature was generated to assess the effect of MRGs on the prognosis of ccRCC patients. Important module MRGs were selected by differentially expressed analysis and WGCNA. Subsequently, the hub MRGs were screened via univariate cox regression as well as LASSO regression. A new metabolism-related signature of 6 hub MRGs (PAFAH2, ACADSB, ACADM, HADH, PYCR1 and ITPKA) was constructed, with a good prognostic prediction ability in the TCGA cohort. The prediction accuracy of this signature was further confirmed in both GSE22541 and FAHWMU cohort. Interestingly, this MRG risk signature was highly correlated with tumor mutation burden and immune infiltration in ccRCC. Notably, lower PAFAH2, a member of 6 MRGs, was found in ccRCC. Knockdown of PAFAH2 contributed to renal cancer cell proliferation and migration. Collectively, a 6-MRG prognostic risk signature is generated to estimate the prognostic status of ccRCC patients, providing a novel insight in the prognosis prediction and treatment of ccRCC.

Artificial Intelligence in Renal Cell Carcinoma Histopathology: Current Applications and Future Perspectives

Renal cell carcinoma (RCC) is characterized by its diverse histopathological features, which pose possible challenges to accurate diagnosis and prognosis. A comprehensive literature review was conducted to explore recent advancements in the field of artificial intelligence (AI) in RCC pathology. The aim of this paper is to assess whether these advancements hold promise in improving the precision, efficiency, and objectivity of histopathological analysis for RCC, while also reducing costs and interobserver variability and potentially alleviating the labor and time burden experienced by pathologists. The reviewed AI-powered approaches demonstrate effective identification and classification abilities regarding several histopathological features associated with RCC, facilitating accurate diagnosis, grading, and prognosis prediction and enabling precise and reliable assessments. Nevertheless, implementing AI in renal cell carcinoma generates challenges concerning standardization, generalizability, benchmarking performance, and integration of data into clinical workflows. Developing methodologies that enable pathologists to interpret AI decisions accurately is imperative. Moreover, establishing more robust and standardized validation workflows is crucial to instill confidence in AI-powered systems' outcomes. These efforts are vital for advancing current state-of-the-art practices and enhancing patient care in the future.

Potential role of gut microbes in the efficacy and toxicity of immune checkpoints inhibitors

In recent years, Immune checkpoint inhibitors have been extensively used in the treatment of a variety of cancers. However, the response rates ranging from 13% to 69% depending on the tumor type and the emergence of immune-related adverse events have posed significant challenges for clinical treatment. As a key environmental factor, gut microbes have a variety of important physiological functions such as regulating intestinal nutrient metabolism, promoting intestinal mucosal renewal, and maintaining intestinal mucosal immune activity. A growing number of studies have revealed that gut microbes further influence the anticancer effects of tumor patients through modulation of the efficacy and toxicity of immune checkpoint inhibitors. Currently, faecal microbiota transplantation (FMT) have been developed relatively mature and suggested as an important regulator in order to enhance the efficacy of treatment. This review is dedicated to exploring the impact of differences in flora composition on the efficacy and toxicity of immune checkpoint inhibitors as well as to summarizing the current progress of FMT.

BAP1-related signature predicts benefits from immunotherapy over VEGFR/mTOR inhibitors in ccRCC: a retrospective analysis of JAVELIN Renal 101 and checkmate-009/010/025 trials

BACKGROUND

In patients with advanced clear cell renal cell carcinoma, despite the undoubted benefits from immune checkpoint inhibitor (ICI)-based therapies over monotherapies of angiogenic/mTOR inhibitors in the intention-to-treat population, approximately a quarter of the patients can scarcely gain advantage from ICIs, prompting the search for predictive biomarkers for patient selection.

METHODS

Clinical and multi-omic data of 2428 ccRCC patients were obtained from The Cancer Genome Atlas (TCGA, n = 537), JAVELIN Renal 101 (avelumab plus axitinib vs. sunitinib, n = 885), and CheckMate-009/010/025 (nivolumab vs. everolimus, n = 1006).

RESULTS

BAP1 mutations were associated with large progression-free survival (PFS) benefits from ICI-based immunotherapies over sunitinib/everolimus (pooled estimate of interaction HR = 0.71, 95% CI 0.51-0.99, P = 0.045). Using the top 20 BAP1 mutation-associated differentially expressed genes (DEGs) generated from the TCGA cohort, we developed the BAP1-score, negatively correlated with angiogenesis and positively correlated with multiple immune-related signatures concerning immune cell infiltration, antigen presentation, B/T cell receptor, interleukin, programmed death-1, and interferon. A high BAP1-score indicated remarkable PFS benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors (avelumab plus axitinib vs. sunitinib: HR = 0.55, 95% CI 0.43-0.70, P < 0.001; nivolumab vs. everolimus: HR = 0.72, 95% CI 0.52-1.00, P = 0.045), while these benefits were negligible in the low BAP1-score subgroup (HR = 1.16 and 1.02, respectively).

CONCLUSION

In advanced ccRCCs, the BAP1-score is a biologically and clinically significant predictor of immune microenvironment and the clinical benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors, demonstrating its potential utility in optimizing the personalized therapeutic strategies in patients with advanced ccRCC.

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.

Can Molecular Classifications Help Tailor First-line Treatment of Metastatic Renal Cell Carcinoma? A Systematic Review of Available Models

Context

The advent of immune check inhibitors (ICIs) has tremendously changed the prognosis of metastatic renal cell carcinoma (mRCC), adding an unseen substantial overall survival benefit. These agents could be administered alone or in combination with anti-vascular endothelial growth factor (anti-VEGF) therapies. So far, treatment allocation is based only on clinical stratification risk models.

Objective

Herein, we aimed to report the different molecular classifications reported in the first-line treatment of mRCC and discuss the awaited clinical implications in terms of treatment selection.

Evidence acquisition

Medline database as well as European Society for Medical Oncology (ESMO)/American Society of Clinical Oncology (ASCO) conference proceedings were searched to identify biomarker studies. Inclusion criteria comprised randomized and nonrandomized clinical trials that included patients treated in the first line of mRCC setting, patients treated with anti-VEGF therapies or ICIs, biological modeling, and available survival outcomes.

Evidence synthesis

Four classification models were identified with subsequent clinical implications: Beuselinck model (34 gene signatures), IMmotion150, Hakimi, and JAVELIN 101 model. Tumor profiling shows distinct outcomes when treated with one or other combination. Patients are clustered into two gene signatures: angiogenic and proinflammatory (as per JAVELIN). The first is more likely to respond to therapy that includes anti-VEGF agents, while the best outcomes are obtained with an ICI combination with the second.

Conclusions

The findings presented here were mostly derived from ancillary registered studies of new drugs in the setting of mRCC. Further validation is needed, which sets new paradigms for investigation in clinical research based on tumor biology for treatment allocation and not only on clinical stratification tools.

Patient summary

First-line treatment of metastatic kidney includes immunotherapy alone or in combination with antiangiogenic therapy. However, clinical practice demonstrated that the "one treatment fits all" strategy might not be the best approach. In fact, recent studies showed that the addition of immunotherapy agents will not benefit all patients equally, and some still respond either equally to or better than anti-vascular endothelial growth factor alone. This review revealed biomarker modeling that impacts treatment selection. Recent tumor profiling into "angiogenic signature" more sensitive to angiogenic agents versus "immune signature" more likely to achieve the best response with immunotherapy should be validated. Tumor biology features might be more powerful than clinical classification for a tailored treatment approach.

Current Options for Second-Line Systemic Therapy in Metastatic Renal Cell Carcinoma

Standard systemic therapy of advanced renal cell carcinoma (RCC) involves targeting angiogenesis, mainly through tyrosine kinase inhibitors (TKI) against the vascular endothelial growth factor receptor (VEGFR) pathway and targeting the immune checkpoints, namely, programmed death-1 (PD-1) or its ligand (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA4). With current strategies of combining these two approaches in the front-line setting, less is known about optimal selection of therapy upon development of resistance in the second and later lines of treatment for progressive disease. This review discusses currently available therapeutic options in patients who have progressive RCC after prior treatment with double immune check-point inhibitors (ICIs) or ICI-TKI combinations.

Prognosis-related genes participate in immunotherapy of renal clear cell carcinoma possibly by targeting dendritic cells

Tumor immunotherapy has become one of the most promising approaches to tumor treatment. This study aimed to screen genes involved in the response of clear cell renal cell carcinoma (ccRCC) to immunotherapy and analyze their function. Based on the Gene Expression Omnibus and The Cancer Genome Atlas datasets, we screened out nine differentially expressed genes (TYROBP, APOC1, CSTA, LY96, LAPTM5, CD300A, ALOX5, C1QA, and C1QB) associated with clinical traits and prognosis. A risk signature constructed by these nine genes could predict the survival probability for patients at 1 year, 3 years, and 5 years. The immune checkpoint blockade response rate in the high-risk group was significantly higher than in the low-risk group (49.25% vs. 24.72%, p ≤ 0.001). The nine prognosis-related genes were negatively correlated with activated dendritic cells in the low-risk group but not in the high-risk group. qRT-PCR, immunohistochemistry, and immunofluorescence showed that the nine prognosis-related genes were associated with dendritic cell activity and the PD-1 positive staining rate. In conclusion, the nine prognosis-related genes have a high prognostic value. The patients in the high-risk group were more likely to benefit from immunotherapy, and the mechanism might be related to the release of dendritic cell-mediated immunosuppression.

Comprehensive analysis of 7-methylguanosine and immune microenvironment characteristics in clear cell renal cell carcinomas

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. ccRCC has obvious immunological characteristics, and the infiltration of immune cells is related to the prognosis of ccRCC. The effect of immune checkpoint therapy is related to the dynamic changes of the tumor immune microenvironment (TIM). The 7-methylguanosine (m7G) is an additional mRNA modification ability besides m6A, which is closely related to the TIM and affects the occurrence and development of tumors. At present, the correlations between m7G and the immune microenvironment, treatment, and prognosis of ccRCC are not clear. As far as we know, there was no study on the relationship between m7G and the immune microenvironment and survival of clear cell renal cell carcinomas. A comprehensive analysis of the correlations between them and the construction of a prognosis model are helpful to improve the treatment strategy. Two different molecular subtypes were identified in 539 ccRCC samples by describing the differences of 29 m7G-related genes. It was found that the clinical features, TIM, and prognosis of ccRCC patients were correlated with the m7G-related genes. We found that there were significant differences in the expression of PD-1, CTLA4, and PD-L1 between high- and low-risk groups. To sum up, m7G-related genes play a potential role in the TIM, treatment, and prognosis of ccRCC. Our results provide new findings for ccRCC and help to improve the immunotherapy strategies and prognosis of patients.

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

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

Hematological prognosticators in metastatic renal cell cancer treated with immune checkpoint inhibitors: a meta-analysis

Aim: We aimed to assess the prognostic value of pretreatment hematological biomarkers in patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs). Methods: PubMed, Web of Science and Scopus databases were searched for articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Results: Fifteen studies comprising 1530 patients were eligible for meta-analysis. High levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein and lactate dehydrogenase were significantly associated with worse progression-free survival. High NLR and PLR were significantly associated with worse overall survival. Conclusion: High pretreatment NLR and PLR appear to be hematological prognostic factors of progression and overall mortality in mRCC patients treated with ICIs. These findings might help in the design of correlative biomarker studies to guide the clinical decision-making in the immune checkpoint inhibitor era.

Approaches to First-Line Therapy for Metastatic Clear Cell Renal Cell Carcinoma

PURPOSE OF REVIEW

Four immuno-oncology (IO)-based combinations have demonstrated overall survival benefit as frontline treatment of metastatic clear cell renal cell carcinoma (mccRCC). Choosing among the available combinations depends on treating physician's interpretation of existing data without level I evidence to inform choice of therapy. Landmark trials of mccRCC are reviewed and perspective on treatment options is provided.

RECENT FINDINGS

The four IO-based combinations reviewed are ipilimumab/nivolumab (IO/IO), pembrolizumab/axitinib (IO/TKI), nivolumab/cabozantinib (IO/TKI), and pembrolizumab/lenvatinib (IO/TKI). The ipilimumab/nivolumab combination is notable for durable efficacy after extended 4-year follow-up. IO/TKI combinations have clinical efficacy across all IMDC risk groups with higher response rates and longer progression-free survival (PFS) but also had higher ≥ grade 3 adverse events rate. Patient tumor burden, performance status, and IMDC risk group are factors in choosing an IO-based treatment. IO/IO and IO/TKI combinations for mccRCC have distinct efficacy and toxicity profiles. Future studies are needed to identify biomarkers to optimize patient outcomes.

Determining programmed cell death ligand 1 expression in circulating tumor cells of patients with clear cell renal cell carcinoma and its correlation with response to programmed cell death protein 1 inhibitors

OBJECTIVE

There is a great interest in determining whether the expression of the programmed cell death ligand 1 is correlated with the efficacy of immune checkpoint inhibitors in patients with clear cell renal cell carcinoma; however, primary tumor biopsies can only provide limited information. Therefore, we explored the expression of programmed cell death ligand 1 on circulating tumor cells, which is a potential predictor of therapeutic response.

METHODS

Circulating tumor cells were isolated from 20 clear cell renal cell carcinoma patients based on cell surface markers targeting clear cell renal cell carcinoma using IsoFlux device, followed by identification according to cell morphology and immunofluorescence studies. Programmed cell death ligand 1 expression status and clinical correlations were also analyzed.

RESULTS

Before treatment with programmed cell death protein 1 inhibitors, circulating tumor cells were detected in all patients, ranging from 1 to 22 (median 7), with 75% (15/20) of the patients having programmed cell death ligand 1 + circulating tumor cells. Circulating tumor cell programmed cell death ligand 1 expression did not correlate with the immunohistochemical staining of programmed cell death ligand 1 in primary tumors. During treatment with programmed cell death protein 1 inhibitors, the disease control rate was much higher in the patients harboring programmed cell death ligand 1 + circulating tumor cells (73%, 11/15) than others (20%, 1/5). We also found that changes in total circulating tumor cell numbers and programmed cell death ligand 1 + circulating tumor cell counts correlated well with the disease outcome.

CONCLUSION

We showed that the presence of programmed cell death ligand 1 + circulating tumor cells before programmed cell death protein 1 inhibition treatment could be a prognosis predictive factor and that the dynamic changes in circulating tumor cell numbers may be used to monitor the therapeutic response. Our study confirms the possibility of programmed cell death ligand 1 + circulating tumor cell detection in clear cell renal cell carcinoma patients' blood samples, which can potentially be used as an individualized immunotherapy molecular biomarker for real-time exploration.

Body Mass Index, Sarcopenia, and Their Variations in Predicting Outcomes for Patients Treated with Nivolumab for Metastatic Renal Cell Carcinoma

INTRODUCTION

The advent of immune checkpoint inhibitors (ICIs) such as nivolumab has enabled outcomes for metastatic renal cell carcinoma (mRCC) to be improved. However, only around 25% of patients respond to these therapies without being able to formally identify them. Data on relevant predictive markers are still lacking. The obesity paradox has been shown as a relevant prognostic marker in mRCC with better outcomes for obese patients. Nevertheless, the impact of weight variation and the presence of sarcopenia during ICI treatment is not known for now.

METHODS

In a retrospective study, weight and its variations were collected at first day of ICI and at 6 weeks of treatment. Scanographic imagery was used to define the skeletal muscle index (SMI) as a reflect of sarcopenia. The impact of these parameters as predictive and prognostic factors for mRCC with nivolumab was evaluated.

RESULTS

A higher body mass index (BMI) at baseline was significantly associated with response at the first scan (p = 0.036). Longer overall survival (OS) was observed for patients with a weight gain compared to the group with weight loss (p = 0.00028). Median OS for sarcopenic patients was 17.2 months and 31.6 months for the non-sarcopenic group of patients, but there was no statistical difference.

CONCLUSION

This trial showed that a higher BMI and weight gain during nivolumab treatment were good predictive markers for outcomes in mRCC with nivolumab. Sarcopenia and variations in SMI could thus be of interest, but further studies are required.

Association of baseline neutrophil-to-eosinophil ratio with response to nivolumab plus ipilimumab in patients with metastatic renal cell carcinoma

BACKGROUND

The identification of biomarkers to select patients with metastatic renal cell carcinoma (mRCC) most likely to respond to combination immunotherapy (IO) is needed. We sought to investigate an association of the baseline neutrophil-to-eosinophil ratio (NER) with outcomes to nivolumab plus ipilimumab for patients with mRCC.

METHODS

We performed a retrospective review of patients with clear cell mRCC treated with nivolumab plus ipilimumab from Vanderbilt-Ingram Cancer Center and Duke Cancer Institute. Patients with prior receipt of immunotherapy and those without available baseline complete blood count with differential were excluded. Patients were divided into groups by the median baseline NER and analyzed for overall survival (OS), progression free survival (PFS), and objective response rate (ORR). Patients were also divided by median baseline neutrophil-to-lymphocyte ratio (NLR) and analyzed for clinical outcome. Further analyses of patients above/below the median NER and NLR were performed in subgroups of IMDC intermediate/poor risk, IMDC favorable risk, and treatment naïve patients.

RESULTS

A total of 110 patients were included: median age was 61 years and 75% were treatment naïve. The median NER (mNER) at baseline was 26.4. The ORR was 40% for patients with <mNER compared to 21.8% among patients with >mNER (OR 2.39, p = 0.04). The median PFS for patients with <mNER was significantly longer at 8.6 months (mo) compared to 3.2 mo for patients with >mNER (HR 0.50, p < 0.01). Median OS was not reached (NR) for patients with <mNER compared with 27.3 mo for patients with >mNER (HR 0.31, p < 0.01). The median NLR (mNLR) was 3.42. While patients with <mNLR showed improvement in OS (HR 0.42, p = 0.02), PFS and ORR did not differ compared with patients in the >mNLR group.

CONCLUSIONS

A lower baseline NER was associated with improved clinical outcomes (PFS, OS, and ORR) in patients with mRCC treated with nivolumab plus ipilimumab, and prospective validation of the baseline NER as a predictive biomarker for response to immunotherapy-based combinations in mRCC is warranted.

PD-1/PD-L1 inhibitors-based treatment for advanced renal cell carcinoma: Mechanisms affecting efficacy and combination therapies

With the widespread use of PD-1/PD-L1 monoclonal antibodies (mAbs) in the treatment of multiple malignant tumors, they were also gradually applied to advanced renal cell carcinoma (aRCC). Nowadays, multiple PD-1/PD-L1 mAbs, such as nivolumab, avelumab, and pembrolizumab, have achieved considerable efficacy in clinical trials. However, due to the primary, adaptive, and acquired resistance to these mAbs, the efficacy of this immunotherapy is not satisfactory. Theories also vary as to why the difference in efficacy occurs. The alterations of PD-L1 expression and the interference of cellular immunity may affect the efficacy. These mechanisms demand to be revealed to achieve a sustained and complete objective response in patients with aRCC. Tyrosine kinase inhibitors have been proven to have synergistic mechanisms with PD-1/PD-L1 mAb in the treatment of aRCC, and CTLA-4 mAb has been shown to have a non-redundant effect with PD-1/PD-L1 mAb to enhance efficacy. Although combinations with targeted agents or other checkpoint mAbs have yielded enhanced clinical outcomes in multiple clinical trials nowadays, the potential of PD-1/PD-L1 mAbs still has a large development space. More potential mechanisms that affect the efficacy demand to be developed and transformed into the clinical treatment of aRCC to search for possible combination regimens. We elucidate these mechanisms in RCC and present existing combination therapies applied in clinical trials. This may help physicians' select treatment options for patients with refractory kidney cancer.

Eosinophil counts as a relevant prognostic marker for response to nivolumab in the management of renal cell carcinoma: a retrospective study

Background

Despite improvements in the management of renal cell carcinomas (RCC) with the advent of immunotherapy, only a few patients respond to these treatments. Predictors of response to nivolumab are currently being investigated but are still lacking.

Aim of the study

To evaluate eosinophil levels and their variations during treatment as an accurate biomarker for outcome in metastatic RCC treated with nivolumab.

Methods

A retrospective analysis was carried out for patients with metastatic RCC treated with nivolumab. Absolute eosinophil counts, their variation, and relative change were evaluated at six weeks. Relative eosinophil change was categorized in three groups (≥10%‐decrease, no change, ≥10%‐increase). Univariable and multivariable analyses were performed to determine whether eosinophils and their variations were prognostic markers for response at the first scan evaluation, progression‐free survival, and overall survival.

Results

Sixty‐five patients aged on average 66 years, 68% men, and 77% with good or intermediate International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk group were included. The median follow‐up was 16.6 months. Median overall survival (OS) was not reached for good prognosis and was 22.5 and 6.5 months for intermediate and poor prognosis, respectively. An increase in eosinophils and relative eosinophil change at six weeks of nivolumab was associated with a good response to immunotherapy (p = 0.012 and p = 0.024 respectively). In the group of patients with a 10%‐decrease in relative change, PFS reduced significantly compared to the other groups (p = 0.0044 with the 10%‐increase group and p = 0.03 with the no‐change group). This relative increase was independent of IMDC risks factors for better OS (HR = 3.3 [1.45–7.4]; p = 0.004). The eosinophil baseline level was not associated with response to treatment.

Conclusion

Eosinophil levels and relative eosinophil change at 6 weeks might be good prognostic markers for response to nivolumab for metastatic RCC, and were associated with better PFS and OS.

Clearing up Clear Cell: Clarifying the Immuno-Oncology Treatment Landscape for Metastatic Clear Cell RCC

Patients with advanced or malignant renal cell carcinoma at the time of diagnosis have historically had a poor prognosis. Immunonologic agents have significantly altered the therapeutic landscape and clinical outcomes of these patients. In this review, we highlight recent and upcoming clinical trials investigating the role of immunotherapies in clear cell RCC. In particular, we emphasize immunotherapy-based combinations, including immune checkpoint inhibitor (ICI) combinations, neoadjuvant, and adjuvant ICI, and ICI agents combined with anti-VEGF therapy.

Co-immunization with L-Myc enhances CD8+ or CD103+ DCs mediated tumor-specific multi-functional CD8+ T cell responses

Renal carcinoma shows a high risk of invasion and metastasis without effective treatment. Herein, we developed a chitosan (CS) nanoparticle-mediated DNA vaccine containing an activated factor L-Myc and a tumor-specific antigen CAIX for renal carcinoma treatment. The subcutaneous tumor models were intramuscularly immunized with CS-pL-Myc/pCAIX or control vaccine, respectively. Compared with single immunization group, the tumor growth was significantly suppressed in CS-pL-Myc/pCAIX co-immunization group. The increased proportion and mature of CD11c⁺ DCs, CD8⁺ CD11c⁺ DCs and CD103⁺ CD11c⁺ DCs were observed in the splenocytes from CS-pL-Myc/pCAIX co-immunized mice. Furthermore, the enhanced antigen-specific CD8⁺ T lymphocyte proliferation, cytotoxic T lymphocyte (CTL) responses, and multi-functional CD8⁺ T cell induction were detected in CS-pL-Myc/pCAIX co-immunization group compared with CS-pCAIX immunization group. Of note, the depletion of CD8 T cells resulted in the reduction of CD8⁺ T cells or CD8⁺ CD11c⁺ DCs and the loss of anti-tumor efficacy induced by CS-pL-Myc/pCAIX vaccine, suggesting the therapeutic efficacy of the vaccine was required for CD8⁺ DCs and CD103⁺ DCs mediated CD8⁺ T cells responses. Likewise, CS-pL-Myc/pCAIX co-immunization also significantly inhibited the lung metastasis of renal carcinoma models accompanied with the increased induction of multi-functional CD8⁺ T cell responses. Therefore, these results indicated that CS-pL-Myc/pCAIX vaccine could effectively induce CD8⁺ DCs and CD103⁺ DCs mediated tumor-specific multi-functional CD8⁺ T cell responses and exert the anti-tumor efficacy. This vaccine strategy offers a potential and promising approach for solid or metastatic tumor treatment.

First-line Immunotherapy-based Combinations for Metastatic Renal Cell Carcinoma: A Systematic Review and Network Meta-analysis

CONTEXT

There have been substantial changes in the management of patients with metastatic renal cell carcinoma (mRCC) over the past decade, with upfront immunotherapy-based combinations replacing targeted therapies. A broad range of combinations have been approved, and comparisons of their efficacy and safety are needed to guide the optimal choice of first-line therapy.

OBJECTIVE

To perform indirect comparisons of efficacy and safety of first-line immune checkpoint inhibitor (ICI)-based combination therapies for mRCC.

EVIDENCE ACQUISITION

We searched multiple databases and abstracts of major scientific meetings up to February 2021 to identify phase III randomized controlled trials of patients receiving first-line ICI-based combination therapies for mRCC. Progression-free survival (PFS) and overall survival (OS) were the primary endpoints. The secondary endpoints included complete response rates (CRRs), objective response rates (ORRs), grade ≥3 treatment-related adverse events (TRAEs), and rates of treatment discontinuation due to adverse events (AEs). Subgroup network meta-analyses were performed based on patients' risk group categories and programmed death ligand 1 (PD-L1) expression status.

EVIDENCE SYNTHESIS

Six trials were included in our network meta-analyses comprising 5121 patients. Nivolumab plus cabozantinib had the highest likelihood of providing the maximal OS (P score: 0.7573). Lenvatinib plus pembrolizumab demonstrated the highest likelihood of PFS (P score: 0.9906) and ORR (P score: 0.9564). CRRs were more likely to be associated with nivolumab plus ipilimumab (P score: 0.8682). In patients with ≥1% PD-L1 expression, the highest likelihood of better PFS was associated with lenvatinib plus pembrolizumab and nivolumab plus ipilimumab. Nivolumab plus ipilimumab was also associated with the lowest rates of grade ≥3 TRAEs; while the highest likelihood of AE-related treatment discontinuation was associated with lenvatinib plus pembrolizumab and nivolumab plus ipilimumab.

CONCLUSIONS

Our network meta-analysis suggests that combinations of ICIs and tyrosine kinase inhibitors (TKIs) provide superior PFS, ORR, and OS to ICI-ICI combinations, regardless of the on International mRCC Database Consortium risk group. However, an ICI-ICI combination could be the optimal treatment for tumors with increased PD-L1 expression. The newly introduced ICI-TKI combinations, nivolumab plus cabozantinib and lenvatinib plus pembrolizumab, showed promising activity and are likely to have an important role in the mRCC treatment strategy.

PATIENT SUMMARY

The use of immune checkpoint inhibitor (ICI)-based combinations (ICI plus tyrosine kinase inhibitor and ICI-ICI) improved oncological outcomes of metastatic renal cell carcinoma. Programmed death ligand 1 (PD-L1) expression status could help guide physicians and patients to select the appropriate treatment strategy.

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.

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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).

Uncovering the microbiota in renal cell carcinoma tissue using 16S rRNA gene sequencing

INTRODUCTION

Increasing evidence indicates an important role of microbiota in cancer development and progression, while little is known about the correlation between microbiota and renal cell carcinoma (RCC). Thus, we performed this study to profile the intratumoral microbiota possibly associated with RCC.

MATERIALS AND METHODS

Paired RCC and adjacent normal tissue samples were collected from 24 patients with RCC. V3-V4 variable region of microbial 16S rRNA gene was sequenced using Illumina MiSeq. Sequencing reads were processed using QIIME. Differentially abundant bacterial taxa between groups were identified by LEfSe, and their potential functions were inferred by PICRUSt.

RESULTS

Decreased species diversity was presented in RCC tissues (Simpson index, P = 0.0340), and the composition of the bacterial community in RCC tissues was significantly distinct from that in normal tissues (unweighted UniFrac distance, P = 0.026; weighted UniFrac distance, P = 0.017). Compared with normal tissues, 25 taxa increased and 47 reduced taxa were identified in RCC tissues. Among these taxa, the class Chloroplast (AUC = 0.91, P < 0.0001) and the order Streptophyta (AUC = 0.89, P < 0.0001) showed high indication accuracy to discriminate RCC tissues from normal tissues. Furthermore, nine altered pathways were identified in RCC tissues to reveal the potential microbial function.

CONCLUSIONS

Our results have uncovered the presence of distinct microbiota in RCC and adjacent normal tissues and provided a better understanding of the possible role of the intratumoral microbiota in RCC. Further studies are required to confirm our results and determine the real correlation between microbiota and RCC.

Targeting the Deterministic Evolutionary Trajectories of Clear Cell Renal Cell Carcinoma

The emergence of clinical resistance to currently available systemic therapies forces us to rethink our approach to clear cell renal cell carcinoma (ccRCC). The ability to influence ccRCC evolution by inhibiting processes that propel it or manipulating its course may be an adequate strategy. There are seven deterministic evolutionary trajectories of ccRCC, which correlate with clinical phenotypes. We suspect that each trajectory has its own unique weaknesses that could be exploited. In this review, we have summarized recent advances in the treatment of ccRCC and demonstrated how to improve systemic therapies from the evolutionary perspective. Since there are only a few evolutionary trajectories in ccRCC, it appears feasible to use them as potential biomarkers for guiding intervention and surveillance. We believe that the presented patient stratification could help predict future steps of malignant progression, thereby informing optimal and personalized clinical decisions.