Update on the most promising biomarkers of response to immune checkpoint inhibitors in clear cell renal cell carcinoma

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.

Silencing of genes by promoter hypermethylation shapes tumor microenvironment and resistance to immunotherapy in clear-cell renal cell carcinomas

The efficacy of immune checkpoint inhibitors varies in clear-cell renal cell carcinoma (ccRCC), with notable primary resistance among patients. Here, we integrate epigenetic (DNA methylation) and transcriptome data to identify a ccRCC subtype characterized by cancer-specific promoter hypermethylation and epigenetic silencing of Polycomb targets. We develop and validate an index of methylation-based epigenetic silencing (iMES) that predicts primary resistance to immune checkpoint inhibition (ICI) in the BIONIKK trial. High iMES is associated with VEGF pathway silencing, endothelial cell depletion, immune activation/suppression, EZH2 activation, BAP1/SETD2 deficiency, and resistance to ICI. Combination therapy with hypomethylating agents or tyrosine kinase inhibitors may benefit patients with high iMES. Intriguingly, tumors with low iMES exhibit increased endothelial cells and improved ICI response, suggesting the importance of angiogenesis in ICI treatment. We also develop a transcriptome-based analogous system for extended applicability of iMES. Our study underscores the interplay between epigenetic alterations and tumor microenvironment in determining immunotherapy response.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

Validation of the Meet-URO score in patients with metastatic renal cell carcinoma receiving first-line nivolumab and ipilimumab in the Italian Expanded Access Program

BACKGROUND

The Meet-URO score allowed a more accurate prognostication than the International Metastatic RCC Database Consortium (IMDC) for patients with pre-treated metastatic renal cell carcinoma (mRCC) by adding the pre-treatment neutrophil-to-lymphocyte ratio and presence of bone metastases.

MATERIALS AND METHODS

A post hoc analysis was carried out to validate the Meet-URO score on the overall survival (OS) of patients with IMDC intermediate-poor-risk mRCC treated with first-line nivolumab plus ipilimumab within the prospective Italian Expanded Access Programme (EAP). We additionally considered progression-free survival (PFS) and disease response rates. Harrell's c-index was calculated to compare the accuracy of survival prediction.

RESULTS

Overall the EAP included 306 patients, with a median follow-up of 12.2 months, median OS was not reached, 1-year OS was 66.8% and median PFS was 7.9 months. By univariable analysis, both the IMDC score and the two additional variables of the Meet-URO score were associated with either OS or PFS (P < 0.001 for all comparisons). The four Meet-URO risk groups (G) had 1-year OS of 92%, 72%, 50% and 21% for G2 (29.1% of patients), G3 (28.8%), G4 (33.0%) and G5 (9.1%), respectively. OS was significantly shorter in each consecutive G (P = 0.001 for G3, P < 0.001 for both G4 and G5 compared to G2). Similarly, Meet-URO Gs 2-5 showed decreasing median PFS and response rates. The Meet-URO score showed the highest c-index for both OS (0.73) and PFS (0.67). Limitations include the post hoc nature of this analysis and the lack of a comparative arm to assess predictive value.

CONCLUSION

The Meet-URO score appeared to show better prognostic classification than the IMDC alone in patients with mRCC at IMDC intermediate-poor risk treated with first-line nivolumab and ipilimumab.

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.

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.

Radiogenomics in Clear Cell Renal Cell Carcinoma: A Review of the Current Status and Future Directions

Radiogenomics is a field of translational radiology that aims to associate a disease's radiologic phenotype with its underlying genotype, thus offering a novel class of non-invasive biomarkers with diagnostic, prognostic, and therapeutic potential. We herein review current radiogenomics literature in clear cell renal cell carcinoma (ccRCC), the most common renal malignancy. A literature review was performed by querying PubMed, Medline, Cochrane Library, Google Scholar, and Web of Science databases, identifying all relevant articles using the following search terms: "radiogenomics", "renal cell carcinoma", and "clear cell renal cell carcinoma". Articles included were limited to the English language and published between 2009-2021. Of 141 retrieved articles, 16 fit our inclusion criteria. Most studies used computed tomography (CT) images from open-source and institutional databases to extract radiomic features that were then modeled against common genomic mutations in ccRCC using a variety of machine learning algorithms. In more recent studies, we noted a shift towards the prediction of transcriptomic and/or epigenetic disease profiles, as well as downstream clinical outcomes. Radiogenomics offers a platform for the development of non-invasive biomarkers for ccRCC, with promising results in small-scale retrospective studies. However, more research is needed to identify and validate robust radiogenomic biomarkers before integration into clinical practice.

[Biomarkers for renal cell tumours]

During the last three decades, renal tumours have become increasingly well differentiated on the basis of their histopathological and molecular features. This subtyping has increasingly impacted clinical practice because more therapeutic options are available in organ-confined and metastatic renal cell tumours. The knowledge of the underlying molecular alterations is essential to develop molecular targeted therapies and to select the most effective systemic therapy for each patient. This manuscript gives an overview of the molecular differentiation on the one hand, and on diagnostic, prognostic and predictive biomarkers on the other hand.

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.

MicroRNAs Targeting HIF-2α, VEGFR1 and/or VEGFR2 as Potential Predictive Biomarkers for VEGFR Tyrosine Kinase and HIF-2α Inhibitors in Metastatic Clear-Cell Renal Cell Carcinoma

Metastatic clear-cell renal cell carcinoma (m-ccRCC) is characterized by increased hypoxia-induced factor (HIF)-2α and vascular endothelial growth factor receptor (VEGFR)-dependent angiogenesis through loss of function of the von Hippel-Lindau protein. VEGFR tyrosine kinase inhibitors (VEGFR-TKIs) are a cornerstone of m-ccRCC treatment, and new treatments targeting HIF-2α are currently under investigation. However, predictive biomarkers for these treatments are lacking. In this retrospective cohort study including 109 patients treated with VEGFR-targeted therapies as first-line treatment, we aimed to study the possible predictive function of microRNAs (miRNAs) targeting HIF-2α, VEGFR1 and VEGFR2. We selected miRNAs inversely correlated with HIF-2α, VEGFR1 and/or VEGFR2 expression and with predicted target sites in the respective genes and subsequently studied their impact on therapeutic outcomes. We identified four miRNAs (miR-34c-5p, miR-221-3p, miR-222-3p and miR-3529-3p) inversely correlated with VEGFR1 and/or VEGFR2 expression and associated with tumor shrinkage and progression-free survival (PFS) upon treatment with VEGFR-TKIs, highlighting the potential predictive value of these miRNAs. Moreover, we identified three miRNAs (miR-185-5p, miR-223-3p and miR-3529-3p) inversely correlated with HIF-2α expression and associated with tumor shrinkage and PFS upon treatment with VEGFR-TKIs. These three miRNAs can have a predictive value not only upon treatment with VEGFR-TKIs but possibly also upon treatment with the upcoming HIF-2α inhibitor belzutifan.

Individualizing renal cell carcinoma treatment through biomarkers discovery in the era of immune checkpoint inhibitors: where do we stand?

PURPOSE OF REVIEW

The treatment landscape of metastatic renal cell carcinoma has greatly evolved over the past fifteen years, leading to a significant improvement in the outcome of our patients. However, there is still an urgent need for predictive biomarkers that could guide our treatment selection, especially in the present era of immune-based treatments.

RECENT FINDINGS

A number of putative biomarkers of immunotherapy activity have been proposed over the past few years, including PD-L1 immunohistochemical expression, tumor mutational burden, neoantigens load, insertions and deletions, complex gene signatures, as well as lymphocytic subpopulations (either circulating or tumor-infiltrating). However, despite preliminary intriguing findings, no biomarker for immune checkpoint activity has emerged so far, that could be used in everyday clinical practice, mainly due to preliminary, or frankly, conflicting results.

SUMMARY

The quest for an 'ideal' biomarker, which should be characterized by adequate specificity, sensibility, predictive (and not just prognostic) value, robustness, reproducibility, ease of evaluation and low cost, is still ongoing.

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.