Molecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade

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.

POLD1 as a Prognostic Biomarker Correlated with Cell Proliferation and Immune Infiltration in Clear Cell Renal Cell Carcinoma

DNA polymerase delta 1 catalytic subunit (POLD1) plays a vital role in genomic copy with high fidelity and DNA damage repair processes. However, the prognostic value of POLD1 and its relationship with tumor immunity in clear cell renal cell carcinoma (ccRCC) remains to be further explored. Transcriptional data sets and clinical information were obtained from the TCGA, ICGC, and GEO databases. Differentially expressed genes (DEGs) were derived from the comparison between the low and high POLD1 expression groups in the TCGA–KIRC cohort. KEGG and gene ontology (GO) analyses were performed for those DEGs to explore the potential influence of POLD1 on the biological behaviors of ccRCC. The prognostic clinical value and mutational characteristics of patients were described and analyzed according to the POLD1 expression levels. TIMER and TISIDB databases were utilized to comprehensively investigate the potential relevance between the POLD1 levels and the status of the immune cells, as well as the tumor infiltration of immune cells. In addition, RT-qPCR, Western blot, immunohistochemistry and several functional and animal experiments were performed for clinical, in vitro and in vivo validation. POLD1 was highly expressed in a variety of tumors including ccRCC, and further verified in a validation cohort of 60 ccRCC samples and in vitro cell line experiments. POLD1 expression levels in the ccRCC samples were associated with various clinical characteristics including pathologic tumor stage and histologic grade. ccRCC patients with high POLD1 expression have poor clinical outcomes and exhibit a higher rate of somatic mutations than those with low POLD1 expression. Cox regression analysis also showed that POLD1 could act as a potential independent prognostic biomarker. The DEGs associated with POLD1 were significantly enriched in the immunity-related pathways. Moreover, further immune infiltration analysis indicated that high POLD1 expression was associated with high NK CD56bright cells, Treg cells, and myeloid-derived suppressor cells’ (MDSCs) infiltration scores, as well as their marker gene sets of immune cell status. Meanwhile, POLD1 exhibited resistance to various drugs when highly expressed. Finally, the knockdown of POLD1 inhibited the proliferation and migration, and promoted the apoptosis of ccRCC cells in vitro and in vivo, as well as influenced the activation of oncogenic signaling. Our current study demonstrated that POLD1 is a potential prognostic biomarker for ccRCC patients. It might create a tumor immunosuppressive microenvironment and inhibit the susceptibility to ferroptosis leading to a poor prognosis.

Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

PURPOSE

Patients with resected localized clear-cell renal cell carcinoma (ccRCC) remain at variable risk of recurrence. Incorporation of biomarkers may refine risk prediction and inform adjuvant treatment decisions. We explored the role of tumor genomics in this setting, leveraging the largest cohort to date of localized ccRCC tissues subjected to targeted gene sequencing.

EXPERIMENTAL DESIGN

The somatic mutation status of 12 genes was determined in 943 ccRCC cases from a multinational cohort of patients, and associations to outcomes were examined in a Discovery (n = 469) and Validation (n = 474) framework.

RESULTS

Tumors containing a von-Hippel Lindau (VHL) mutation alone were associated with significantly improved outcomes in comparison with tumors containing a VHL plus additional mutations. Within the Discovery cohort, those with VHL+0, VHL+1, VHL+2, and VHL+≥3 tumors had disease-free survival (DFS) rates of 90.8%, 80.1%, 68.2%, and 50.7% respectively, at 5 years. This trend was replicated in the Validation cohort. Notably, these genomically defined groups were independent of tumor mutational burden. Amongst patients eligible for adjuvant therapy, those with a VHL+0 tumor (29%) had a 5-year DFS rate of 79.3% and could, therefore, potentially be spared further treatment. Conversely, patients with VHL+2 and VHL+≥3 tumors (32%) had equivalent DFS rates of 45.6% and 35.3%, respectively, and should be prioritized for adjuvant therapy.

CONCLUSIONS

Genomic characterization of ccRCC identified biologically distinct groups of patients with divergent relapse rates. These groups account for the ∼80% of cases with VHL mutations and could be used to personalize adjuvant treatment discussions with patients as well as inform future adjuvant trial design.

Viewing RCC with a DNA Methylation Lens ENHANCES Understanding of ICI Resistance

Clear-cell renal cell carcinoma tumors with an enhancer demethylator phenotype (TED) harbor a worse prognosis and derive less clinical benefit from immunotherapy. The TED phenotype may help predict immunotherapy resistance. See related article by Lu et al., p. 1279.

Tumor and immune remodeling following radiotherapy in human renal cell carcinoma

BACKGROUND

Studies evaluating peripheral patient samples show radiation can modulate immune responses, yet the biological changes in human tumors particularly at the cellular level remain largely unknown. Here, we address how radiation treatment shapes the immune compartment and interactions with cancer cells within renal cell carcinoma (RCC) patient tumors.

METHODS

To identify how radiation shaped the immune compartment and potential immune interactions with tumor cells we evaluated RCC tumors from patients treated only with nephrectomy or with radiation followed by nephrectomy. Spectral flow cytometry using a 35-marker panel was performed on cell suspensions to evaluate protein expression within immune subsets. To reveal how radiation alters programming of immune populations and interactions with tumor cells, we examined transcriptional changes by single-cell RNA sequencing (scRNAseq).

RESULTS

Spectral flow cytometry analysis revealed increased levels of early-activated as well as effector programmed cell death protein-1 (PD-1)⁺ CD8 T-cell subsets within irradiated tumors. Following quality control, scRNAseq of tumor samples from nephrectomy-only or radiation followed by nephrectomy-treated patients generated an atlas containing 34,626 total cells. Transcriptional analysis revealed increased transition from stem-like T-cell populations to effector T cells in irradiated tumors. Interferon (IFN) pathways, that are central to radiation-induced immunogenicity, were enriched in irradiated lymphoid, myeloid, and cancer cell populations. Focused cancer cell analysis showed enhanced antigen presentation and increased predicted TRAIL-mediated and IFN-mediated interactions between tumor cells and the same effector T-cell subsets increased by radiation. TRAIL and IFN pathways enriched in irradiated tumors were associated with survival in patients treated with immunotherapy.

CONCLUSIONS

These findings identify the source of IFN enrichment within irradiated RCC and reveal heightened levels of PD-1⁺ CD8⁺ T-cell subsets and increased probability of interactions with tumor cells following standalone radiation treatment. This study provides a window into the irradiated tumor-immune microenvironment of patients and rationale for treatment combinations.

A novel immune-related model to predict prognosis and responsiveness to checkpoint and angiogenesis blockade therapy in advanced renal cancer

Background

Immune checkpoint blockade (ICB) and anti-angiogenic drug combination has prolonged the survival of patients with advanced renal cell carcinoma (RCC). However, not all patients receive clinical benefits from this intervention. In this study, we aimed to establish a promising immune-related prognostic model to stratify the patients responding to ICB and anti-angiogenic drug combination and facilitate the development of personalized therapies for patients with RCC.

Materials and methods

Based on clinical annotations and RNA-sequencing (RNA-seq) data of 407 patients with advanced RCC from the IMmotion151 cohort, nine immune-associated differentially expressed genes (DEGs) between responders and non-responders to atezolizumab (anti-programmed death-ligand 1 antibody) plus bevacizumab (anti-vascular endothelial growth factor antibody) treatment were identified via weighted gene co-expression network analysis. We also conducted single-sample gene set enrichment analysis to develop a novel immune-related risk score (IRS) model and further estimate the prognosis of patients with RCC by predicting their sensitivity to chemotherapy and responsiveness to immunotherapy. IRS model was further validated using the JAVELIN Renal 101 cohort, the E-MTAB-3218 cohort, the IMvigor210 and GSE78220 cohort. Predictive significance of the IRS model for advanced RCC was assessed using receiver operating characteristic curves.

Results

The IRS model was constructed using nine immune-associated DEGs: SPINK5, SEMA3E, ROBO2, BMP5, ORM1, CRP, CTSE, PMCH and CCL3L1. Advanced RCC patients with high IRS had a high risk of undesirable clinical outcomes (hazard ratio = 1.91; 95% confidence interval = 1.43–2.55; P &lt; 0.0001). Transcriptome analysis revealed that the IRS-low group exhibited significantly high expression levels of CD8+ T effectors, antigen-processing machinery, and immune checkpoints, whereas the epithelial–mesenchymal transition pathway was enriched in the IRS-high group. IRS model effectively differentiated the responders from non-responders to ICB combined with angiogenesis blockade therapy or immunotherapy alone, with area under the curve values of 0.822 in the IMmotion151 cohort, 0.751 in the JAVELIN Renal 101 cohort, and 0.776 in the E-MTAB-3218 cohort.

Conclusion

IRS model is a reliable and robust immune signature that can be used for patient selection to optimize the efficacy of ICB plus anti-angiogenic drug therapies in patients with advanced RCC.

Overexpression of TREM1 is Associated with the Immune-Suppressive Microenvironment and Unfavorable Prognosis in Pan-Cancer

Background

Triggering receptors expressed by myeloid cells-1 (TREM1) is a receptor belonging to the immunoglobulin superfamily and plays an important role in pro-inflammation in acute and chronic inflammatory disorders. However, the understanding of the immunomodulatory roles of TREM1 in the tumor microenvironment remains incomplete.

Methods

The expression patterns of TREM1 mRNA in tumors and adjacent normal tissues were compared by analyzing data obtained from the Genotype-Tissue Expression and The Cancer Genome Atlas datasets. Survival analysis was performed to determine the prognostic value of TREM1. Functional enrichment analysis was applied to decipher the discrepancy in biological processes between high- and low-TREM1 groups across various cancers. The correlation between TREM1 and immune cell infiltration determined by using multiple algorithms was evaluated with the Pearson method. Four independent immunotherapy cohorts were adopted to validate the role of TREM1 as a biomarker.

Results

TREM1 was elevated in most cancers as verified with clinical samples. Overexpression of TREM1 was linked with undesirable prognosis in patients. Further analysis revealed that TREM1 was positively correlated with immune response, pro-tumor pathways, and myeloid cell infiltration, while being negatively correlated with CD8⁺ T cell (including infiltration level and biological processes). Concordantly, tumors with high TREM1 levels were more resistant to immunotherapy. Through connective map analysis, therapeutically potential compounds like tozasertib and TPCA-1 were identified, which can be used synergistically with immunotherapy to improve the poor prognosis of patients with high TREM1 levels.

Conclusion

Through a systematic and comprehensive pan-cancer analysis, we demonstrated that overexpression of TREM1 in tumors correlated closely with unfavorable outcome, infiltration of immune-suppressive cells, and immune regulation, which highlights its potential use as a tumor prognostic biomarker and a novel target for immunotherapy.

The expanding role of BAP1 in clear cell renal cell carcinoma

Mutations drive renal cell carcinoma biology and tumor growth. The BRCA1-associated protein-1 (BAP1) gene is frequently mutated in clear cell renal cell carcinoma (ccRCC) and has emerged as a prognostic and putative predictive biomarker. In this review, we discuss the role of BAP1 as a signature event of a subtype of ccRCC marked by aggressiveness, inflammation, and possibly a heightened response to immunotherapy.

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.

Navigating and adapting care integrating immunotherapy, antiangiogenic therapy, and combinations in patients with advanced renal cell carcinoma

Advanced renal cell carcinoma is a biologically heterogeneous disease with multiple treatment options that largely involve immunotherapy and/or anti-angiogenic therapies. The choice of initial and subsequent therapy depends on both clinical and biological considerations. Here, we describe the application of recent data to clinical practice.

Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate-risk clear cell kidney cancer

BACKGROUND

Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear.

METHODS

Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA-seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease-free status was the primary endpoint assessed.

RESULTS

SSIGN and RS were calculated for 428 patients with non-metastatic ccRCC. SSIGN low-, intermediate-, and high-risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3-year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease-free status (sub-distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00-1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate-risk group (sHR 2.22 [95% CI 1.10-4.50], p = 0.03). SSIGN intermediate-risk patients with low and high RS had a 3-year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination.

CONCLUSIONS

Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate-risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.

Urine supernatant reveals a signature that predicts survival in clear-cell renal cell carcinoma

OBJECTIVE

To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), we then performed a targeted mRNA analysis of genes encoding the above proteins and defined their effects on overall survival (OS).

SUBJECTS/PATIENTS AND METHODS

Samples were collected prospectively from ccRCC patients. A multiplex proximity extension assay was used to measure the concentrations of 92 inflammation-related proteins in cell-free urine supernatants and plasma. Transcriptomic and clinical information from ccRCC patients was obtained from TCGA. Unsupervised clustering and differential protein expression analyses were performed on protein concentration data. Targeted mRNA analysis on genes encoding significant differentially expressed proteins was performed using TCGA. Backward stepwise regression analyses were used to build a nomogram. The performance of the nomogram and clinical benefit was assessed by discrimination and calibration, and a decision curve analysis, respectively.

RESULTS

Unsupervised clustering analysis revealed inflammatory signatures in the cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The decision curve analysis showed that our model was associated with a net benefit improvement compared to the treat-all/none strategies.

CONCLUSION

We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We showed that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumour stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.

Our Current Understanding of the Heterogeneity in Prostate Cancer and Renal Cell Carcinoma

Urological cancer is a collective term for cancers of the bladder, kidney, ureter, penis, prostate, and testicles. Last year, more than 444,000 people were diagnosed with urinary cancers in the United States. In this review, we talk about the complexity of prostate and kidney cancer.

A novel lipid metabolism gene signature for clear cell renal cell carcinoma using integrated bioinformatics analysis

Background: Clear cell renal cell carcinoma (ccRCC), which is the most prevalent type of renal cell carcinoma, has a high mortality rate. Lipid metabolism reprogramming is a hallmark of ccRCC progression, but its specific mechanism remains unclear. Here, the relationship between dysregulated lipid metabolism genes (LMGs) and ccRCC progression was investigated. Methods: The ccRCC transcriptome data and patients' clinical traits were obtained from several databases. A list of LMGs was selected, differentially expressed gene screening performed to detect differential LMGs, survival analysis performed, a prognostic model established, and immune landscape evaluated using the CIBERSORT algorithm. Gene Set Variation Analysis and Gene set enrichment analysis were conducted to explore the mechanism by which LMGs affect ccRCC progression. Single-cell RNA-sequencing data were obtained from relevant datasets. Immunohistochemistry and RT-PCR were used to validate the expression of prognostic LMGs. Results: Seventy-one differential LMGs were identified between ccRCC and control samples, and a novel risk score model established comprising 11 LMGs (ABCB4, DPEP1, IL4I1, ENO2, PLD4, CEL, HSD11B2, ACADSB, ELOVL2, LPA, and PIK3R6); this risk model could predict ccRCC survival. The high-risk group had worse prognoses and higher immune pathway activation and cancer development. Conclusion: Our results showed that this prognostic model can affect ccRCC progression.

Soluble CD163: a novel independent prognostic biomarker in patients with metastatic renal cell carcinoma

The hemoglobin-haptoglobin scavenger receptor CD163 is present in both a membrane-bound form on monocytes and macrophages (mCD163) and a shed soluble circulating form (sCD163). CD163 is a well-described marker of M2-like tumor-associated macrophages, but in patients with metastatic renal cell carcinoma (mRCC), monocyte mCD163 and serum sCD163 levels have not previously been investigated and associated with patient overall survival (OS). Here, we report mCD163 expression on peripheral blood monocytes, as well as sCD163 serum levels, in samples from 89 patients newly diagnosed with mRCC and 20 healthy controls. We found that in mRCC patients, compared to healthy controls, monocyte mCD163 levels were reduced (P < 0.001) whereas serum sCD163 levels were increased (P = 0.004). Moreover, an inverse correlation between mCD163 and sCD163 levels (P = 0.04) was shown. In survival analyses, intermediary levels of monocyte mCD163 were associated with longest OS, compared to both lower and higher mCD163 levels, which were both associated with worse outcomes (P < 0.01). Further, higher levels of sCD163 at diagnosis were associated with poor OS in both univariate (P < 0.001) and multivariate analysis (HR = 1.28; 95%CI 1.09-1.50, P = 0.002). Importantly, stratification by low vs. high sCD163 was able to separate patients with International Metastatic RCC Database Consortium (IMDC) intermediate risk (IMDC_INT) into two subgroups with different OS (P = 0.03): IMDC_INT-sCD163_LOW showed survival similar to IMDC_FAV patients, and IMDC_INT-sCD163_HIGH showed survival similar to IMDC_POOR patients. Thus, baseline sCD163 is a novel independent biomarker of OS in mRCC, and using sCD163 as an add-on biomarker may improve prognostic value for patients in the heterogenous IMDC intermediate group.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Unraveling the Synergy between Atezolizumab and Bevacizumab for the Treatment of Hepatocellular Carcinoma

Tyrosine kinase inhibitors (TKIs) with antiangiogenic properties, such as sorafenib, have been the standard choice to systemically treat hepatocellular carcinoma for over a decade. More recently, encouraging results were obtained using immune checkpoint inhibitors, although head-to-head comparisons with sorafenib in phase 3 trials could not demonstrate superiority in terms of overall survival. The IMbrave150 was a breakthrough study that resulted in atezolizumab/bevacizumab, a combination of an antiangiogenic and an immune checkpoint inhibitor, as a new standard of care for advanced HCC. This review discusses the mode of action, clinical efficacy, and biomarker research for both drug classes and for the combination therapy. Moreover, the synergy between atezolizumab and bevacizumab is highlighted, unraveling pathophysiological mechanisms underlying an enhanced anticancer immunity by changing the immunosuppressed to a more immunoreactive tumor microenvironment (TME). This is achieved by upregulation of antigen presentation, upregulation of T-cell proliferation, trafficking and infiltration, impairing recruitment, and proliferation of immunosuppressive cells in the TME. However, more insights are needed to identify biomarkers of response that may improve patient selection and outcome.

The chromosomal instability 25 gene signature is identified in clear cell renal cell carcinoma and serves as a predictor for survival and Sunitinib response

Background

Chromosomal instability (CIN) is a cancer hallmark and it is difficult to directly measure its phenotype, while a CIN25 gene signature was established to do so in several cancer types. However, it is currently unclear whether there exists this signature in clear cell renal cell carcinoma (ccRCC), and if so, which biological and clinical implications it has.

Methods

Transcriptomic profiling was performed on 10 ccRCC tumors and matched renal non-tumorous tissues (NTs) for CIN25 signature analyses. TCGA and E-MBAT1980 ccRCC cohorts were analyzed for the presence of CIN25 signature, CIN25 score-based ccRCC classification, and association with molecular alterations and overall or progression-free survival (OS or PFS). IMmotion150 and 151 cohorts of ccRCC patients treated with Sunitinib were analyzed for the CIN25 impact on Sunitinib response and survival.

Results

The transcriptomic analysis of 10 patient samples showed robustly upregulated expression of the CIN25 signature genes in ccRCC tumors, which were further confirmed in TCGA and E-MBAT1980 ccRCC cohorts. Based on their expression heterogeneity, ccRCC tumors were categorized into CIN25-C1 (low) and C2 (high) subtypes. The CIN25-C2 subtype was associated with significantly shorter patient OS and PFS, and characterized by increased telomerase activity, proliferation, stemness and EMT. The CIN25 signature reflects not only a CIN phenotype, but also levels of the whole genomic instability including mutation burden, microsatellite instability and homologous recombination deficiency (HRD). Importantly, the CIN25 score was significantly associated with Sunitinib response and survival. In IMmotion151 cohort, patients in the CIN25-C1 group exhibited 2-fold higher remission rate than those in the CIN25-C2 group (P = 0.0004) and median PFS in these two groups was 11.2 and 5.6 months, respectively (P = 7.78E-08). Similar results were obtained from the IMmotion150 cohort analysis. Higher EZH2 expression and poor angiogenesis, well characterized factors leading to Sunitinib resistance, were enriched in the CIN25-C2 tumors.

Conclusion

The CIN25 signature identified in ccRCC serves as a biomarker for CIN and other genome instability phenotypes and predicts patient outcomes and response to Sunitinib treatment. A PCR quantification is enough for the CIN25-based ccRCC classification, which holds great promises in clinical routine application.

Cobimetinib Alone and Plus Venetoclax With/Without Atezolizumab in Patients With Relapsed/Refractory Multiple Myeloma

INTRODUCTION

Mitogen-activated protein kinase pathway mutations are present in >50% of patients with relapsed/refractory (R/R) multiple myeloma (MM). MEK inhibitors show limited single-agent activity in R/R MM; combination with B-cell lymphoma-2 (BCL-2) and programmed death-ligand 1 inhibition may improve efficacy. This phase Ib/II trial (NCT03312530) evaluated safety and efficacy of cobimetinib (cobi) alone and in combination with venetoclax (ven) with/without atezolizumab (atezo) in patients with R/R MM.

PATIENTS AND METHODS

Forty-nine patients were randomized 1:2:2 to cobi 60 mg/day on days 1-21 (n = 6), cobi 40 mg/day on days 1-21 + ven 800 mg/day on days 1-28 with/without atezo 840 mg on days 1 and 15 of 28-day cycles (cobi-ven, n = 22; cobi-ven-atezo, n = 21). Safety run-in cohorts evaluated cobi-ven and cobi-ven-atezo dose levels.

RESULTS

Any-grade common adverse events (AEs) with cobi, cobi-ven, and cobi-ven-atezo, respectively, included diarrhea (33.3%, 81.8%, 90.5%) and nausea (16.7%, 50.0%, 66.7%); common grade ≥3 AEs included anemia (0%, 22.7%, 23.8%), neutropenia (0%, 13.6%, 38.1%), and thrombocytopenia (0%, 18.2%, 23.8%). The overall response rate for all-comers was 0% (cobi), 27.3% (cobi-ven), and 28.6% (cobi-ven-atezo), and 0%, 50.0%, and 100%, respectively, in patients with t(11;14)+. Biomarker analysis demonstrated non-t(11;14) patient selection with NRAS/KRAS/BRAF mutation or high BCL-2/BCL-2-L1 ratio (>52% of the study population) could enrich for responders to the cobi-ven combination.

CONCLUSIONS

Cobi-ven and cobi-ven-atezo demonstrated manageable safety with moderate activity in all-comers, and higher activity in patients with t(11;14)+ MM, supporting a biomarker-driven approach for ven in MM.

The 2022 Updated European Association of Urology Guidelines on the Use of Adjuvant Immune Checkpoint Inhibitor Therapy for Renal Cell Carcinoma

In KEYNOTE-564, adjuvant pembrolizumab, a PD-1 antibody, significantly improved disease-free survival (DFS) in localised clear-cell renal cell carcinoma (ccRCC) with a high risk of relapse. In 2021, the European Association of Urology RCC Guidelines Panel issued a weak recommendation for adjuvant pembrolizumab for high-risk ccRCC as defined by the trial until final overall survival data and results from other trials were available. Meanwhile, the primary DFS endpoints were not met for adjuvant atezolizumab (PD-L1 inhibitor; IMmotion010), adjuvant nivolumab plus ipilimumab (CheckMate 914), or perioperative nivolumab (PROSPER). Owing to heterogeneity, a meta-analysis is not recommended. Pembrolizumab remains the only immune checkpoint inhibitor currently recommended in this setting. Overall survival data are immature and biomarkers to predict outcome are lacking. Uncertainty exists and overtreatment is occurring. Treatment decisions should be made with caution and with the involvement of each patient. PATIENT SUMMARY: New results from three trials of immunotherapy after surgery for kidney cancer to reduce the risk of recurrence showed no improvement with these treatments. These results are in contrast to an earlier study that showed that the antibody pembrolizumab did extend the time before kidney cancer recurrence, even though it is not yet clear if overall survival is longer. Thus, we cautiously recommend pembrolizumab as additional treatment in high-risk kidney cancer after surgery, but patient preference should be carefully considered and the risk of overtreatment should be discussed.

Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

Radiomics and artificial intelligence (AI) may increase the differentiation of benign from malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma (RCC), differentiation of oncocytoma from RCC, differentiation of different subtypes of RCC, to predict Fuhrman grade, to predict gene mutation through molecular biomarkers and to predict treatment response in metastatic RCC undergoing immunotherapy. Neural networks analyze imaging data. Statistical, geometrical, textural features derived are giving quantitative data of contour, internal heterogeneity and gray zone features of lesions. A comprehensive literature review was performed, until July 2022. Studies investigating the diagnostic value of radiomics in differentiation of renal lesions, grade prediction, gene alterations, molecular biomarkers and ongoing clinical trials have been analyzed. The application of AI and radiomics could lead to improved sensitivity, specificity, accuracy in detecting and differentiating between renal lesions. Standardization of scanner protocols will improve preoperative differentiation between benign, low-risk cancers and clinically significant renal cancers and holds the premises to enhance the diagnostic ability of imaging tools to characterize renal lesions.

Semantic Computed Tomography Features for Predicting BRCA1-associated Protein 1 and/or Tumor Protein p53 Gene Mutation Status in Clear Cell Renal Cell Carcinoma

PURPOSE

The purpose of this study was to explore the semantic computed tomography (CT) features associated with BRCA1-associated protein 1 (BAP1) and/or tumor protein p53 (TP53) mutation in clear cell renal cell carcinoma (ccRCC).

METHODS AND MATERIALS

Clinical characteristics and gene mutation information of 336 ccRCC patients were retrieved from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma database (TCGA-KIRC). Kaplan-Meier analysis was performed to examine prognosis by gene mutation. The CT imaging data and gene mutation information of 156 ccRCC patients treated between January 2019 and January 2021 (the training cohort) were retrospectively analyzed. The CT imaging information and gene mutation data of 123 patients with ccRCC were downloaded from The Cancer Imaging Archive and The Cancer Genome Atlas database (the external validation cohort). Univariate Chi-square test and multivariate binary logistic regression analysis were performed to determine predictors of gene mutation; a nomogram was developed using these predictors. Receiver operating characteristic curve analysis and the Hosmer-Lemeshow test were performed to evaluate the performance of the nomogram.

RESULTS

Kaplan-Meier analysis showed that BAP1 and/or TP53 mutation was significantly correlated with worse survival outcome. Multivariate binary logistic regression analysis indicated ill-defined margin (P = .001), spiculated margin (P = .018), renal vein invasion (P = .002), and renal pelvis invasion (P = .001) were independent predictors of BAP1 and/or TP53 mutation. A nomogram containing these 4 semantic CT features was constructed; the area under the receiver operating characteristic curves was 0.872 (95% CI, 0.809-0.920). The Hosmer-Lemeshow test showed acceptable goodness-of-fit for the nomogram (X² = 1.194, P = .742). The nomogram was validated in the validation cohort; it showed good accuracy (area under the receiving operating characteristic curve = 0.819, 95% CI, 0.740-0.883) and was well calibrated (X² = 3.934, P = .559).

CONCLUSIONS

Semantic CT features are a potential and promising method for predicting BAP1 and/or TP53 mutation status in ccRCC patients.

Adjuvant Therapy in Renal Cell Carcinoma: Are we ready for prime time?

The standard of care for localized renal cell carcinoma (RCC) is radical or partial nephrectomy. Despite complete resection, a subset of patients will develop locoregional recurrence or metastatic disease. Adjuvant immunotherapy has been studied since the 1980 s as the primary method to mitigate tumor recurrence after definitive surgery. We herein discuss published and ongoing clinical trials investigating adjuvant therapy in localized or locoregional RCC.

BAP1 and PTEN mutations shape the immunological landscape of clear cell renal cell carcinoma and reveal the intertumoral heterogeneity of T cell suppression: a proof-of-concept study

Clear cell renal cell carcinoma (ccRCC) is an immunologically vulnerable tumor entity, and immune checkpoint inhibitors are now widely used to treat patients with advanced disease. Whether and to what extent immune responses in ccRCC are shaped by genetic alterations, however, is only beginning to emerge. In this proof-of-concept study, we performed a detailed correlative analysis of the mutational and immunological landscapes in a series of 23 consecutive kidney cancer patients. We discovered that a high infiltration with CD8 + T cells was not dependent on the number of driver mutations but rather on the presence of specific mutational events, namely pathogenic mutations in PTEN or BAP1. This observation encouraged us to compare mechanisms of T cell suppression in the context of four different genetic patterns, i.e., the presence of multiple drivers, a PTEN or BAP1 mutation, or the absence of detectable driver mutations. We found that ccRCCs harboring a PTEN or BAP1 mutation showed the lowest level of Granzyme B positive tumor-infiltrating lymphocytes (TILs). A multiplex immunofluorescence analysis revealed a significant number of CD8 + TILs in the vicinity of CD68 + macrophages/monocytes in the context of a BAP1 mutation but not in the context of a PTEN mutation. In line with this finding, direct interactions between CD8 + TILs and CD163 + M2-polarized macrophages were found in BAP1-mutated ccRCC but not in tumors with other mutational patterns. While an absence of driver mutations was associated with more CD8 + TILs in the vicinity of FOXP3 + Tregs and CD68 + monocytes/macrophages, the presence of multiple driver mutations was, to our surprise, not found to be strongly associated with immunosuppressive mechanisms. Our results highlight the role of genetic alterations in shaping the immunological landscape of ccRCC. We discovered a remarkable heterogeneity of mechanisms that can lead to T cell suppression, which supports the need for personalized immune oncological approaches.

Spatiotemporal evolution of the clear cell renal cell carcinoma microenvironment links intra-tumoral heterogeneity to immune escape

BACKGROUND

Intratumoral heterogeneity (ITH) is a hallmark of clear cell renal cell carcinoma (ccRCC) that reflects the trajectory of evolution and influences clinical prognosis. Here, we seek to elucidate how ITH and tumor evolution during immune checkpoint inhibitor (ICI) treatment can lead to therapy resistance.

METHODS

Here, we completed a single-arm pilot study to examine the safety and feasibility of neoadjuvant nivolumab in patients with localized RCC. Primary endpoints were safety and feasibility of neoadjuvant nivolumab. Then, we spatiotemporally profiled the genomic and immunophenotypic characteristics of 29 ccRCC patients, including pre- and post-therapy samples from 17 ICI-treated patients. Deep multi-regional whole-exome and transcriptome sequencing were performed on 29 patients at different time points before and after ICI therapy. T cell repertoire was also monitored from tissue and peripheral blood collected from a subset of patients to study T cell clonal expansion during ICI therapy.

RESULTS

Angiogenesis, lymphocytic infiltration, and myeloid infiltration varied significantly across regions of the same patient, potentially confounding their utility as biomarkers of ICI response. Elevated ITH associated with a constellation of both genomic features (HLA LOH, CDKN2A/B loss) and microenvironmental features, including elevated myeloid expression, reduced peripheral T cell receptor (TCR) diversity, and putative neoantigen depletion. Hypothesizing that ITH may itself play a role in shaping ICI response, we derived a transcriptomic signature associated with neoantigen depletion that strongly associated with response to ICI and targeted therapy treatment in several independent clinical trial cohorts.

CONCLUSIONS

These results argue that genetic and immune heterogeneity jointly co-evolve and influence response to ICI in ccRCC. Our findings have implications for future biomarker development for ICI response across ccRCC and other solid tumors and highlight important features of tumor evolution under ICI treatment.

TRIAL REGISTRATION

The study was registered on ClinicalTrial.gov (NCT02595918) on November 4, 2015.

Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer

Tumor behavior is intricately dependent on the oncogenic properties of cancer cells and their multi-cellular interactions. To understand these dependencies within the wider microenvironment, we studied over 270,000 single-cell transcriptomes and 100 microdissected whole exomes from 12 patients with kidney tumors, prior to validation using spatial transcriptomics. Tissues were sampled from multiple regions of the tumor core, the tumor-normal interface, normal surrounding tissues, and peripheral blood. We find that the tissue-type location of CD8+ T cell clonotypes largely defines their exhaustion state with intra-tumoral spatial heterogeneity that is not well explained by somatic heterogeneity. De novo mutation calling from single-cell RNA-sequencing data allows us to broadly infer the clonality of stromal cells and lineage-trace myeloid cell development. We report six conserved meta-programs that distinguish tumor cell function, and find an epithelial-mesenchymal transition meta-program highly enriched at the tumor-normal interface that co-localizes with IL1B-expressing macrophages, offering a potential therapeutic target.

The Continuing Question of Adjuvant Therapy in Clear Cell Renal Cell Carcinoma

Treatment advances in kidney cancer continually evolve. The focus of treatment options continues with oral vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors (TKIs) or intravenous immune checkpoint inhibitors (ICIs). Multiple trials exploring the role of adjuvant treatment after cytoreductive nephrectomy in high-risk clear cell renal cell carcinoma are currently ongoing. The discovery of biomarkers may help determine which patients benefit from these treatments, but these are not yet available outside clinical studies. Trials with combination therapies are also ongoing, especially using novel therapies with new mechanisms of action, and will hopefully provide more clues on proper patient and therapy selection in the adjuvant setting.

Long-term Clinical Outcomes of a Spanish Cohort of Metastatic Renal Cell Carcinoma Patients with a Complete Response to Sunitinib

INTRODUCTION

The long-term clinical outcomes of patients with metastatic renal cell carcinoma (mRCC) and a complete response (CR) to the tyrosine kinase inhibitor (TKI) sunitinib are poorly known. The characteristics of these patients could reveal previously undetected associations with clinical variables.

PATIENTS AND METHODS

This observational, retrospective study (ATILA) used data from a registry of patients with mRCC who had received first-line sunitinib and had achieved CR from 2007 to 2018 in Spain.

RESULTS

Sixty-two patients with CR were included; 48 patients (77.4%) received sunitinib in monotherapy and 14 (22.6%) combined with or followed by local treatment. Median age was 58.5 years (range, 32-81). Most patients (79.0%) had clear cell histology and had undergone previous nephrectomy (90.3%). The majority (70.2%) had an intermediate IMDC prognosis, 23% favorable and 7.0% poor. The median time on treatment with sunitinib was 28.2 months (IQR, 16.7-41.0) and the median time to CR was 10.9 months (IQR, 7.2-19.3). After a median follow-up of 8 years (range, 3-13 years), the median PFS was not reached. The overall median duration of complete response was 64.1 months (IQR, 32.2-99.4). The tolerance and safety profile of sunitinib was consistent with previous reports.

CONCLUSION

Durable CR to sunitinib was observed in patients regardless the prognosis group, metastasis site or histology type, with 75% of patients remaining in CR after 10 years.

CLINICALTRIALS

gov: NCT03916458.

Proteogenomic characterization of MiT family translocation renal cell carcinoma

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

Facts and Hopes for Immunotherapy in Renal Cell Carcinoma

Immunotherapy has made a significant impact in many tumors, including renal cell carcinoma (RCC). RCC has been known to be immunoresponsive since the cytokine era of IFNα and IL2, but only a small number of patients had durable clinical benefit. Since then, discoveries of key tumor drivers, as well as an understanding of the contribution of angiogenesis and the tumor microenvironment (TME), has led to advances in drug development, ultimately transforming patient outcomes. Combinations of anti-angiogenic agents with immune checkpoint inhibitors are now standard of care. Current challenges include patient selection for immunotherapy combinations, resistance acquisition, and optimally sequencing therapies. Further discoveries about RCC biology, the TME, and resistance mechanisms will likely pave the way for the next generation of therapies.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

Molecular mechanisms of resistance to tyrosine kinase inhibitor in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Loss of von Hippel-Lindau tumor suppressor gene is frequently observed in ccRCC and increases the expression of hypoxia-inducible factors and their targets, including epidermal growth factor, vascular endothelial growth factor, and platelet-derived growth factor. Tyrosine kinase inhibitors (TKIs) offer a survival benefit in metastatic renal cell carcinoma (mRCC). Recently, immune checkpoint inhibitors have been introduced in mRCC. Combination therapy with TKIs and immune checkpoint inhibitors significantly improved patient outcomes. Therefore, TKIs still play an essential role in mRCC treatment. However, the clinical utility of TKIs is compromised when primary and acquired resistance are encountered. The mechanism of resistance to TKI is not fully elucidated. Here, we comprehensively reviewed the molecular mechanisms of resistance to TKIs and a potential strategy to overcome this resistance. We outlined the involvement of angiogenesis, non-angiogenesis, epithelial-mesenchymal transition, activating bypass pathways, lysosomal sequestration, non-coding RNAs, epigenetic modifications and tumor microenvironment factors in the resistance to TKIs. Deep insight into the molecular mechanisms of resistance to TKIs will help to better understand the biology of RCC and can ultimately help in the development of more effective therapies.

A novel thinking: DDR axis refines the classification of ccRCC with distinctive prognosis, multi omics landscape and management strategy

Background

DNA damage response and repair (DDR) related signatures play an important role in maintaining genome stability and other biological processes. It also affects the occurrence, development, and treatment of cancer. However, in renal cell carcinoma (RCC), especially clear cell renal carcinoma (ccRCC), the potential association between DDR-related signatures and tumor heterogeneity and tumor microenvironment (TME) remains unclear.

Methods

Utilizing unsupervised clustering algorithm, we divided RCC into two subgroups, DCS1 and DCS2, according to the differences in DDR gene expression, and compared the characteristics of the two subgroups through multiple dimensions.

Results

Compared with DCS1, DCS2 patients have higher clinical stage/grade and worse prognosis, which may be related to active metabolic status and immunosuppression status. At the same time, the high mutation rate in DCS2 may also be an important reason for the prognosis. We also analyzed the sensitivity of the two subgroups to different therapeutic agents and established a subtypes' biomarkers-based prognostic system with good validation results to provide ideas for clinical diagnosis and treatment. Finally, we identified a pivotal role for DDX1 in the DDR gene set, which may serve as a future therapeutic target.

Conclusion

This study showed that DDR has an important impact on the development and treatment of RCC. DCS2 subtypes have a poor prognosis, and more personalized treatment and follow-up programs may be needed. The assessment of DDR gene mutations in patients may be helpful for clinical decision-making. DDX1 may be one of the effective targets for RCC treatment in the future.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Contemporary Drug Therapy for Renal Cell Carcinoma- Evidence Accumulation and Histological Implications in Treatment Strategy

Renal cell carcinoma (RCC) is a heterogeneous disease comprising a variety of histological subtypes. Approximately 70-80% of RCC cases are clear cell carcinoma (ccRCC), while the remaining subtypes constitute non-clear cell carcinoma (nccRCC). The medical treatment of RCC has greatly changed in recent years through advances in molecularly targeted therapies and immunotherapies. Most of the novel systemic therapies currently available have been approved based on ccRCC clinical trial data. nccRCC can be subdivided into more than 40 histological subtypes that have distinct clinical, histomorphological, immunohistochemical, and molecular features. These entities are listed as emerging in the 2022 World Health Organization classification. The diagnosis of nccRCC and treatments based on cancer histology and biology remain challenging due to the disease's rarity. We reviewed clinical trials focused on recent discoveries regarding clinicopathological features.

Longitudinal Molecular Profiling of Circulating Tumor Cells in Metastatic Renal Cell Carcinoma

PURPOSE

Liquid biopsies in metastatic renal cell carcinoma (mRCC) provide a unique approach to understand the molecular basis of treatment response and resistance. This is particularly important in the context of immunotherapies, which target key immune-tumor interactions. Unlike metastatic tissue biopsies, serial real-time profiling of mRCC is feasible with our noninvasive circulating tumor cell (CTC) approach.

METHODS

We collected 457 longitudinal liquid biopsies from 104 patients with mRCC enrolled in one of two studies, either a prospective cohort or a phase II multicenter adaptive immunotherapy trial. Using a novel CTC capture and automated microscopy platform, we profiled CTC enumeration and expression of HLA I and programmed cell death-ligand 1 (PD-L1). Given their diametric immunological roles, we focused on the HLA I to PD-L1 ratio (HP ratio).

RESULTS

Patients with radiographic responses showed significantly lower CTC abundances throughout treatment. Furthermore, patients whose CTC enumeration trajectory was in the highest quartile (> 0.12 CTCs/mL annually) had shorter overall survival (median 17.0 months v 21.1 months, P < .001). Throughout treatment, the HP ratio decreased in patients receiving immunotherapy but not in patients receiving tyrosine kinase inhibitors. Patients with an HP ratio trajectory in the highest quartile (≥ 0.0012 annually) displayed significantly shorter overall survival (median 18.4 months v 21.2 months, P = .003).

CONCLUSION

In the first large longitudinal CTC study in mRCC to date to our knowledge, we identified the prognostic importance of CTC enumeration and the change over time of both CTC enumeration and the HP ratio. These insights into changes in both tumor burden and the molecular profile of tumor cells in response to different treatments provide potential biomarkers to predict and monitor response to immunotherapy in mRCC.

Genomic Characteristics and Single-Cell Profiles After Immunotherapy in Fumarate Hydratase-Deficient Renal Cell Carcinoma

PURPOSE

Fumarate hydratase-deficient renal cell carcinoma (FHRCC) is highly malignant, but the urgent need for effective treatment remains unmet. We aimed to analyze the genomic characteristics and microenvironment of FHRCC and the cause of heterogeneous response to immune checkpoint inhibitor (ICI)-based treatment at single-cell level.

EXPERIMENTAL DESIGN

Whole-exome sequencing and IHC staining analyses were performed in 30 advanced FHRCC patients. Single-cell RNA sequencing following ICI-based treatment was conducted in 4 patients. The clinical characteristics, therapeutic effect, and follow-up data were analyzed.

RESULTS

The median tumor mutation burden was only 0.14 mutations per megabase. IHC staining showed an immune-active tumor microenvironment characterized by extensive CD8+ T-cell infiltration. ATM expression was inversely correlated with percentage of tumor-infiltrating CD8+ T cells. Trajectory analysis indicated gradually upregulated exhausted markers and an increased apoptotic trend of CD8+ T cells despite continuous exposure to ICI-based treatment. ICI-based treatment was associated with improved overall response rate (17.6% vs. 0%, P = 0.046) and disease control rate (DCR; 64.7% vs. 12.5%, P = 0.004) compared with tyrosine kinase inhibitor. Among patients with germline mutation, the ORR (16.7% vs. 0%, P = 0.086) and the DCR (66.7% vs. 14.3%, P = 0.011) were higher after ICI-based treatment.

CONCLUSIONS

Immune infiltration is frequent in FHRCC. ICI-based treatment is a promising regimen, and treatment response depends on the functional status of tumor-infiltrating lymphocytes. ICI-based treatment cannot reverse the exhaustion of CD8+ T cells in patients with progressive disease, highlighting the need for additional therapeutic strategies.

The convergence of tumor suppressors on the type I interferon pathway in clear cell renal cell carcinoma and its therapeutic implications

In clear cell renal cell carcinoma (ccRCC), the von Hippel-Lindau tumor suppressor gene/hypoxia inducible factor (VHL/HIF) axis lays the groundwork for tumorigenesis and is the target of many therapeutic agents. HIF activation alone, however, is largely insufficient for kidney tumor development, and secondary mutations in PBRM1, BAP1, SETD2, KDM5C, or other tumor suppressor genes are strong enablers of tumorigenesis. Interestingly, it has been discovered that VHL loss and subsequent HIF activation results in upregulation of a negative feedback loop mediated by ISGF3, a transcription factor activated by type I interferon (IFN). Secondary mutations in the aforementioned tumor suppressor genes all partially disable this negative feedback loop to facilitate tumor growth. The convergence of several cancer genes on this pathway suggests that it plays an important role in ccRCC development and maintenance. Tumors with secondary mutations that dampen the negative feedback loop may be exquisitely sensitive to its reactivation, and pharmacological activation of ISGF3 either alone or in combination with other therapies could be an effective method to treat patients with ccRCC. In this review, we examine the relevance of the type I IFN pathway to ccRCC, synthesize our current knowledge of the ccRCC tumor suppressors in its regulation, and explore how this may impact the future treatment of patients with ccRCC.

Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information

Since U.S. President Barack Obama announced the Precision Medicine Initiative in his New Year's State of the Union address in 2015, the establishment of a precision medicine system has been emphasized worldwide, particularly in the field of oncology. With the advent of next-generation sequencers specifically, genome analysis technology has made remarkable progress, and there are active efforts to apply genome information to diagnosis and treatment. Generally, in the process of feeding back the results of next-generation sequencing analysis to patients, a molecular tumor board (MTB), consisting of experts in clinical oncology, genetic medicine, etc., is established to discuss the results. On the other hand, an MTB currently involves a large amount of work, with humans searching through vast databases and literature, selecting the best drug candidates, and manually confirming the status of available clinical trials. In addition, as personalized medicine advances, the burden on MTB members is expected to increase in the future. Under these circumstances, introducing cutting-edge artificial intelligence (AI) technology and information and communication technology to MTBs while reducing the burden on MTB members and building a platform that enables more accurate and personalized medical care would be of great benefit to patients. In this review, we introduced the latest status of elemental technologies that have potential for AI utilization in MTB, and discussed issues that may arise in the future as we progress with AI implementation.

Trans-Arterial Chemoembolization Plus Systemic Treatments for Hepatocellular Carcinoma: An Update

Recent years have seen the advent of novel treatment options for hepatocellular carcinoma (HCC). Given a strong biological rationale supporting this strategy, multiple studies have explored the role of combination treatments including locoregional plus systemic therapies to produce a synergistic effect and enhance antitumor activity. Among locoregional therapies, several clinical trials assessing trans-arterial chemoembolization (TACE) have been recently presented and published. In the current paper, we discuss available evidence and current and future research on combined TACE and systemic treatments, including antiangiogenic agents, immune checkpoint inhibitors, and immune-based combinations for HCC patients.

Circadian lncRNA ADIRF-AS1 binds PBAF and regulates renal clear cell tumorigenesis

We identify ADIRF-AS1 circadian long non-coding RNA (lncRNA). Deletion of ADIRF-AS1 in U2OS cells alters rhythmicity of clock-controlled genes and expression of extracellular matrix genes. ADIRF-AS1 interacts with all components of the PBAF (PBRM1/BRG1) complex in U2OS cells. Because PBRM1 is a tumor suppressor mutated in over 40% of clear cell renal carcinoma (ccRCC) cases, we evaluate ADIRF-AS1 in ccRCC cells. Reducing ADIRF-AS1 expression in ccRCC cells decreases expression of some PBAF-suppressed genes. Expression of these genes is partially rescued by PBRM1 loss, consistent with ADIRF-AS1 acting in part to modulate PBAF. ADIRF-AS1 expression correlates with survival in human ccRCC, particularly in PBRM1 wild-type, but not mutant, tumors. Loss of ADIRF-AS1 eliminates in vivo tumorigenesis, partially rescued by concurrent loss of PBRM1 only when co-injected with Matrigel, suggesting a PBRM1-independent function of ADIRF-AS1. Our findings suggest that ADIRF-AS1 functions partly through PBAF to regulate specific genes as a BMAL1-CLOCK-regulated, oncogenic lncRNA.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor response in metastatic renal cell carcinoma

BACKGROUND

Immunotherapy combinations including ipilimumab and nivolumab are now the standard of care for untreated metastatic renal cell carcinoma (mRCC). Biomarkers of response are lacking to predict patients who will have a favorable or unfavorable response to immunotherapy. This study aimed to use the OmniSeq transcriptome-based platform to develop biomarkers of response to immunotherapy.

METHODS

Two cohorts of patients were retrospectively collected. These included an investigational cohort of patients with mRCC treated with immune checkpoint inhibitor therapy from five institutions, and a subsequent validation cohort of patients with mRCC treated with combination ipilimumab and nivolumab from two institutions (Duke Cancer Institute and Cleveland Clinic Taussig Cancer Center). Tissue-based RNA sequencing was performed using the OmniSeq Immune Report Card on banked specimens to identify gene signatures and immune checkpoints associated with differential clinical outcomes. A 5-gene expression panel was developed based on the investigational cohort and was subsequently evaluated in the validation cohort. Clinical outcomes including progression-free survival (PFS) and overall survival (OS) were extracted by retrospective chart review. Objective response rate (ORR) was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1.

RESULTS

The initial investigation cohort identified 86 patients with mRCC who received nivolumab (80%, 69/86), ipilimumab/nivolumab (14%, 12/86), or pembrolizumab (6%, 5/86). A gene expression score was created using the top five genes found in responders versus non-responders (FOXP3, CCR4, KLRK1, ITK, TIGIT). The ORR in patients with high gene expression (GE_high) on the 5-gene panel was 29% (14/48), compared with low gene expression (GE_low) 3% (1/38, χ² p=0.001). The validation cohort was comprised of 62 patients who received ipilimumab/nivolumab. There was no difference between GE_high and GE_low in terms of ORR (44% vs 38.5%), PFS (HR 1.5, 95% CI 0.58 to 3.89), or OS (HR 0.96, 95% CI 0.51 to 1.83). Similarly, no differences in ORR, PFS or OS were observed when patients were stratified by tumor mutational burden (high=top 20%), PD-L1 (programmed death-ligand 1) expression by immunohistochemistry or RNA expression, or CTLA-4 (cytotoxic T-lymphocytes-associated protein 4) RNA expression. The International Metastatic RCC Database Consortium (IMDC) risk score was prognostic for OS but not PFS.

CONCLUSION

A 5-gene panel that was associated with improved ORR in a predominantly nivolumab monotherapy population of patients with mRCC was not predictive for radiographic response, PFS, or OS among patients with mRCC treated with ipilimumab and nivolumab.

Treatment of Refractory Metastatic Renal Cell Carcinoma

First-line treatment for metastatic renal cell carcinoma (mRCC) rapidly shifted in recent years with the advent of combination therapies, including immune checkpoint inhibitor (ICI) doublets and combinations of an ICI with a vascular endothelial growth factor receptor (VEGFR) targeted tyrosine kinase inhibitor (TKI). Despite improvements in overall survival and many durable responses, there exists a significant number of patients who fail to respond to these agents, and many patients eventually progress. Given the rapid changes in the front-line setting, it is essential to understand treatment options in refractory mRCC. Here, we review the evidence behind current options for later-line therapies, often involving additional VEGFR-TKIs alone or in combination with mammalian target of rapamycin (mTOR) targeted agents, as well as situations where consideration of immunotherapy rechallenge may be appropriate. Additionally, we describe ongoing clinical trials examining concurrent ICI and TKI in the refractory setting, as well as those studying novel agents, such as targeted drug-antibody conjugates and hypoxia inducible factor 2α (HIF-2α) inhibitors. Finally, we review considerations for non-clear cell histologies in the refractory setting and mechanisms of resistance in mRCC.

Location matters: LAG3 levels are lower in renal cell carcinoma metastatic sites compared to primary tumors, and expression at metastatic sites only may have prognostic importance

While great strides have been made in the treatment of advanced renal cell carcinoma (RCC) with the emergence of immune checkpoint inhibitors (ICIs) and VEGFR-targeting drugs, sizable proportions of patients still do not respond to upfront therapy and long-term responses only occur in a minority of patients. There is therefore a great need for the development of better predictors of response and an increased understanding of mechanisms of resistance to these therapies. Alternative immune checkpoints outside the PD-1/PD-L1 axis, such as LAG3, have been implicated as one mechanism of resistance to ICIs. These checkpoints thus represent attractive therapeutic targets, and indeed the LAG3 inhibitor relatlimab was recently approved for the treatment of metastatic melanoma in combination with anti-PD-1 therapy. LAG3 inhibitors are being evaluated for RCC as well. In this context, a better understanding of LAG3 expression patterns in RCC and how they relate to clinicopathologic features of disease and response to immunotherapy may give insight into mechanisms of resistance to PD-1 inhibitors and aid in the identification of subgroups of patients more likely to benefit from certain drug regimens. In this study, we assessed LAG3 protein levels in leukocytes in normal kidney adjacent to RCC, primary RCC tumors, and matched metastatic tumors, including large numbers of brain metastases. We found that LAG3 protein levels are on average lower at metastatic sites compared to matched primary tumors, and that the difference was more pronounced in patients with high-risk clinical characteristics, including those with larger primary tumor size, grade 4 tumors, IMDC poor-risk disease, and initial presentation with brain metastases. We further saw that the prognostic value of LAG3 levels varies depending on the tissue site queried (i.e., primary tumor versus metastases), and that relatively higher LAG3 levels at metastatic sites may predict a better response to immunotherapy and longer overall survival after the development of metastatic disease. These findings may have important implications for the design of future studies involving LAG3 or other immunotherapies in RCC.

Molecular characterization of renal cell carcinoma tumors from a phase III anti-angiogenic adjuvant therapy trial

Multigene assays can provide insight into key biological processes and prognostic information to guide development and selection of adjuvant cancer therapy. We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and that other factors such as immune response and tumor environment may be of greater importance.

Based on the S-TRAC results, sunitinib is approved as adjuvant treatment for adult patients at high risk of recurrent RCC following nephrectomy. Here, the authors report the results of an integrated multi-omics tumor analysis of 171 patients from the trial and identify specific molecular subtypes as well as potential new targets.

A Targetable Myeloid Inflammatory State Governs Disease Recurrence in Clear-Cell Renal Cell Carcinoma

It is poorly understood how the tumor immune microenvironment influences disease recurrence in localized clear-cell renal cell carcinoma (ccRCC). Here we performed whole-transcriptomic profiling of 236 tumors from patients assigned to the placebo-only arm of a randomized, adjuvant clinical trial for high-risk localized ccRCC. Unbiased pathway analysis identified myeloid-derived IL6 as a key mediator. Furthermore, a novel myeloid gene signature strongly correlated with disease recurrence and overall survival on uni- and multivariate analyses and is linked to TP53 inactivation across multiple data sets. Strikingly, effector T-cell gene signatures, infiltration patterns, and exhaustion markers were not associated with disease recurrence. Targeting immunosuppressive myeloid inflammation with an adenosine A2A receptor antagonist in a novel, immunocompetent, Tp53-inactivated mouse model significantly reduced metastatic development. Our findings suggest that myeloid inflammation promotes disease recurrence in ccRCC and is targetable as well as provide a potential biomarker-based framework for the design of future immuno-oncology trials in ccRCC.

SIGNIFICANCE

Improved understanding of factors that influence metastatic development in localized ccRCC is greatly needed to aid accurate prediction of disease recurrence, clinical decision-making, and future adjuvant clinical trial design. Our analysis implicates intratumoral myeloid inflammation as a key driver of metastasis in patients and a novel immunocompetent mouse model. This article is highlighted in the In This Issue feature, p. 2221.

A Phase II study of neoadjuvant axitinib for reducing the extent of venous tumour thrombus in clear cell renal cell cancer with venous invasion (NAXIVA)

BACKGROUND

Surgery for renal cell carcinoma (RCC) with venous tumour thrombus (VTT) extension into the renal vein (RV) and/or inferior vena cava (IVC) has high peri-surgical morbidity/mortality. NAXIVA assessed the response of VTT to axitinib, a potent tyrosine kinase inhibitor.

METHODS

NAXIVA was a single-arm, multi-centre, Phase 2 study. In total, 20 patients with resectable clear cell RCC and VTT received upto 8 weeks of pre-surgical axitinib. The primary endpoint was percentage of evaluable patients with VTT improvement by Mayo level on MRI. Secondary endpoints were percentage change in surgical approach and VTT length, response rate (RECISTv1.1) and surgical morbidity.

RESULTS

In all, 35% (7/20) patients with VTT had a reduction in Mayo level with axitinib: 37.5% (6/16) with IVC VTT and 25% (1/4) with RV-only VTT. No patients had an increase in Mayo level. In total, 75% (15/20) of patients had a reduction in VTT length. Overall, 41.2% (7/17) of patients who underwent surgery had less invasive surgery than originally planned. Non-responders exhibited lower baseline microvessel density (CD31), higher Ki67 and exhausted or regulatory T-cell phenotype.

CONCLUSIONS

NAXIVA provides the first Level II evidence that axitinib downstages VTT in a significant proportion of patients leading to reduction in the extent of surgery.

CLINICAL TRIAL REGISTRATION

NCT03494816.

Loss of apelin blocks the emergence of sprouting angiogenesis in experimental tumors

Angiogenesis inhibitor drugs targeting vascular endothelial growth factor (VEGF) signaling to the endothelial cell (EC) are used to treat various cancer types. However, primary or secondary resistance to therapy is common. Clinical and pre-clinical studies suggest that alternative pro-angiogenic factors are upregulated after VEGF pathway inhibition. Therefore, identification of alternative pro-angiogenic pathway(s) is critical for the development of more effective anti-angiogenic therapy. Here we study the role of apelin as a pro-angiogenic G-protein-coupled receptor ligand in tumor growth and angiogenesis. We found that loss of apelin in mice delayed the primary tumor growth of Lewis lung carcinoma 1 and B16F10 melanoma when combined with the VEGF receptor tyrosine kinase inhibitor, sunitinib. Targeting apelin in combination with sunitinib markedly reduced the tumor vessel density, and decreased microvessel remodeling. Apelin loss reduced angiogenic sprouting and tip cell marker gene expression in comparison to the sunitinib-alone-treated mice. Single-cell RNA sequencing of tumor EC demonstrated that the loss of apelin prevented EC tip cell differentiation. Thus, apelin is a potent pro-angiogenic cue that supports initiation of tumor neovascularization. Together, our data suggest that targeting apelin may be useful as adjuvant therapy in combination with VEGF signaling inhibition to inhibit the growth of advanced tumors.