Subgroup-Independent Mapping of Renal Cell Carcinoma-Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries

Decoding the Intricate Landscape of Pancreatic Cancer: Insights into Tumor Biology, Microenvironment, and Therapeutic Interventions

Pancreatic ductal adenocarcinoma (PDAC) presents significant oncological challenges due to its aggressive nature and poor prognosis. The tumor microenvironment (TME) plays a critical role in progression and treatment resistance. Non-neoplastic cells, such as cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), contribute to tumor growth, angiogenesis, and immune evasion. Although immune cells infiltrate TME, tumor cells evade immune responses by secreting chemokines and expressing immune checkpoint inhibitors (ICIs). Vascular components, like endothelial cells and pericytes, stimulate angiogenesis to support tumor growth, while adipocytes secrete factors that promote cell growth, invasion, and treatment resistance. Additionally, perineural invasion, a characteristic feature of PDAC, contributes to local recurrence and poor prognosis. Moreover, key signaling pathways including Kirsten rat sarcoma viral oncogene (KRAS), transforming growth factor beta (TGF-β), Notch, hypoxia-inducible factor (HIF), and Wnt/β-catenin drive tumor progression and resistance. Targeting the TME is crucial for developing effective therapies, including strategies like inhibiting CAFs, modulating immune response, disrupting angiogenesis, and blocking neural cell interactions. A recent multi-omic approach has identified signature genes associated with anoikis resistance, which could serve as prognostic biomarkers and targets for personalized therapy.

Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma

The integration of artificial intelligence (AI) with histopathology images and gene expression patterns has led to the emergence of the dynamic fields of pathomics and genomics. These fields have revolutionized renal cell carcinoma (RCC) diagnosis and subtyping and improved survival prediction models. Machine learning has identified unique gene patterns across RCC subtypes and grades, providing insights into RCC origins and potential treatments, as targeted therapies. The combination of pathomics and genomics using AI opens new avenues in RCC research, promising future breakthroughs and innovations that patients and physicians can anticipate.

Efficacy of Immune Checkpoint Inhibitors vs. Tyrosine Kinase Inhibitors/Everolimus in Adjuvant Renal Cell Carcinoma: Indirect Comparison of Disease-Free Survival

BACKGROUND

The proven efficacy of mTOR inhibitors (mTORIs), tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitors (ICIs) in metastatic renal cell carcinoma (RCC) suggests that these agents should be investigated as adjuvant therapy with the aim of eliminating undetectable microscopic residual disease after curative resection. The aim of our study was to compare the efficacy of these treatments using an innovative method of reconstructing individual patient data.

METHODS

Nine phase III trials describing adjuvant RCC treatments were selected. The IPDfromKM method was used to reconstruct individual patient data from Kaplan-Meier (KM) curves. The combination treatments were compared with the control arm (placebo) for disease-free survival (DFS). Multi-treatment KM curves were used to summarize the results. Standard statistical tests were performed. These included hazard ratio and likelihood ratio tests for heterogeneity.

RESULTS

In the overall population, the study showed that two ICIs (nivolumab plus ipilimumab and pembrolizumab) and one TKI (sunitinib) were superior to the placebo, whereas both TKIs and mTORIs were inferior. As we assessed DFS as the primary endpoint for the adjuvant comparison, the overall survival benefit remains unknown.

CONCLUSIONS

This novel approach to investigating survival has allowed us to conduct all indirect head-to-head comparisons between these agents in a context where no "real" comparative trials have been conducted.

Metformin Regulates the miR-205/VEGFA Axis in Renal Cell Carcinoma Cells: Exploring a Clinical Synergism with Tyrosine Kinase Inhibitors

INTRODUCTION

Metformin (MF) intake could be associated with a favorable outcome in sunitinib (SUT)- and axitinib (AX)-treated clear cell renal cell carcinoma (ccRCC) patients. Functionally, MF induces miR-205, a microRNA serving as a tumor suppressor in several cancers.

METHODS

Real-time quantitative PCR, viability assays, and Western blotting analyzed MF and SUT/AX effects in RCC4 and 786-O cells. A tetracycline-inducible overexpression model was used to study the role of miR-205 and its known target gene, VEGFA. We analyzed miR-205 and VEGFA within a public and an in-house ccRCC cohort. Human umbilical vein endothelial cell (HUVEC) sprouting assays examined miR-205 effects on angiogenesis initiation. To determine the influence of the von Hippel-Lindau tumor suppressor (VHL), we examined VHLwt reexpressing RCC4 and 786-O cells.

RESULTS

Viability assays confirmed a sensitizing effect of MF toward SUT/AX in RCC4 and 786-O cells. Overexpression of miR-205 diminished VEGFA expression - as did treatment with MF. Tumor tissue displayed a downregulation of miR-205 and an upregulation of VEGFA. Accordingly, miR-205 caused less and shorter vessel sprouts in HUVEC assays. Finally, VHLwt-expressing RCC4 and 786-O cells displayed higher miR-205 and lower VEGFA levels.

CONCLUSION

Our results support the protective role of MF in ccRCC and offer functional insights into the clinical synergism with tyrosine kinase inhibitors.

Deciphering the implications of mitophagy-related signatures in clinical outcomes and microenvironment heterogeneity of clear cell renal cell carcinoma

BACKGROUND

The role of mitophagy in various cancer-associated biological processes is well recognized. Nonetheless, the comprehensive implications of mitophagy in clear cell renal cell carcinoma (ccRCC) necessitate further exploration.

METHODS

Based on the transcriptomic data encompassing 25 mitophagy-related genes (MRGs), we identified the distinct mitophage patterns in 763 ccRCC samples. Subsequently, a mitophage-related predictive signature with machine learning algorithms was constructed, designated as RiskScore, to quantify the individual mitophagy status in ccRCC patients. Employing multispectral immunofluorescence (mIF) and immunohistochemistry (IHC) staining, we detected the effect of PTEN-induced putative kinase 1 (PINK1) in the prognosis and immune microenvironment of ccRCC.

RESULTS

Our analysis initially encompassed a comprehensive assessment of the expression profiling, genomic variations, and interactions among the 25 MRGs in ccRCC. Subsequently, the consensus clustering algorithm was applied to stratify ccRCC patients into three clusters with distinct prognostic outcomes, tumor microenvironment (TME) characteristics, and underlying biological pathways. We screened eight pivotal genes (CLIC4, PTPRB, SLC16A12, ENPP5, FLRT3, HRH2, PDK4, and SCD5) to construct a mitophagy-related predictive signature, which showed excellent prognostic value for ccRCC patients. Moreover, patient subgroups divided by the RiskScore showed contrasting expression levels of immune checkpoints (ICPs), abundance of immune cells, and immunotherapy response. Additionally, a nomogram was established with robust predictive power integrating the RiskScore and clinical features. Notably, we observed that PINK1 expression markedly correlated with favorable treatment response and advanced maturation stages of tertiary lymphoid structures, which potentially shed light on enhancing anti-tumor immunity of ccRCC.

CONCLUSION

Collectively, this study initially developed a signature associated with mitophagy, which demonstrated an excellent ability to predict the clinical prognosis, TME characterization, and responsiveness to targeted therapy and immunotherapy for ccRCC patients. Of particular note is the pivotal role of PINK1 in mediating the treatment response and immune microenvironment for ccRCC patients.

Mitochondrially targeted tamoxifen as anticancer therapy: case series of patients with renal cell carcinoma treated in a phase I/Ib clinical trial

Mitochondrially targeted anticancer drugs (mitocans) that disrupt the energy-producing systems of cancer are emerging as new potential therapeutics. Mitochondrially targeted tamoxifen (MitoTam), an inhibitor of mitochondrial respiration respiratory complex I, is a first-in-class mitocan that was tested in the phase I/Ib MitoTam-01 trial of patients with metastatic cancer. MitoTam exhibited a manageable safety profile and efficacy; among 37% (14/38) of responders, the efficacy was greatest in patients with metastatic renal cell carcinoma (RCC) with a clinical benefit rate of 83% (5/6) of patients. This can be explained by the preferential accumulation of MitoTam in the kidney tissue in preclinical studies. Here we report the mechanism of action and safety profile of MitoTam in a case series of RCC patients. All six patients were males with a median age of 69 years, who had previously received at least three lines of palliative systemic therapy and suffered progressive disease before starting MitoTam. We recorded stable disease in four, partial response in one, and progressive disease (PD) in one patient. The histological subtype matched clear cell RCC (ccRCC) in the five responders and claro-cellular carcinoma with sarcomatoid features in the non-responder. The number of circulating tumor cells (CTCs) was evaluated longitudinally to monitor disease dynamics. Beside the decreased number of CTCs after MitoTam administration, we observed a significant decrease of the mitochondrial network mass in enriched CTCs. Two patients had long-term clinical responses to MitoTam, of 50 and 36 weeks. Both patients discontinued treatment due to adverse events, not PD. Two patients who completed the trial in November 2019 and May 2020 are still alive without subsequent anticancer therapy. The toxicity of MitoTam increased with the dosage but was manageable. The efficacy of MitoTam in pretreated ccRCC patients is linked to the novel mechanism of action of this first-in-class mitochondrially targeted drug.

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

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

Therapeutic targeting of P2X4 receptor and mitochondrial metabolism in clear cell renal carcinoma models

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. Large-scale metabolomic data have associated metabolic alterations with the pathogenesis and progression of renal carcinoma and have correlated mitochondrial activity with poor survival in a subset of patients. The aim of this study was to determine whether targeting mitochondria-lysosome interaction could be a novel therapeutic approach using patient-derived organoids as avatar for drug response.

METHODS

RNAseq data analysis and immunohistochemistry were used to show overexpression of Purinergic receptor 4 (P2XR4) in clear cell carcinomas. Seahorse experiments, immunofluorescence and fluorescence cell sorting were used to demonstrate that P2XR4 regulates mitochondrial activity and the balance of radical oxygen species. Pharmacological inhibitors and genetic silencing promoted lysosomal damage, calcium overload in mitochondria and cell death via both necrosis and apoptosis. Finally, we established patient-derived organoids and murine xenograft models to investigate the antitumor effect of P2XR4 inhibition using imaging drug screening, viability assay and immunohistochemistry.

RESULTS

Our data suggest that oxo-phosphorylation is the main source of tumor-derived ATP in a subset of ccRCC cells expressing P2XR4, which exerts a critical impact on tumor energy metabolism and mitochondrial activity. Prolonged mitochondrial failure induced by pharmacological inhibition or P2XR4 silencing was associated with increased oxygen radical species, changes in mitochondrial permeability (i.e., opening of the transition pore complex, dissipation of membrane potential, and calcium overload). Interestingly, higher mitochondrial activity in patient derived organoids was associated with greater sensitivity to P2XR4 inhibition and tumor reduction in a xenograft model.

CONCLUSION

Overall, our results suggest that the perturbed balance between lysosomal integrity and mitochondrial activity induced by P2XR4 inhibition may represent a new therapeutic strategy for a subset of patients with renal carcinoma and that individualized organoids may be help to predict drug efficacy.

Critical Evaluation of a microRNA-Based Risk Classifier Predicting Cancer-Specific Survival in Renal Cell Carcinoma with Tumor Thrombus of the Inferior Vena Cava

(1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCCIVC) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier—containing miR-21-5p, miR-126-3p and miR-221-3p expression—which significantly predicted the cancer-specific survival (CSS) of ccRCCIVC patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCCIVC, we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan–Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan–Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCCIVC according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCCIVC cohort.

Predicting Microenvironment in CXCR4- and FAP-Positive Solid Tumors-A Pan-Cancer Machine Learning Workflow for Theranostic Target Structures

(1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database-representing n = 9242 specimens from 29 tumor entities. CXCR4- and FAP-positive samples were assessed via StringDB cluster analysis, EnrichR, Metascape, and Gene Set Enrichment Analysis (GSEA). Findings were validated via correlation analyses in n = 1541 tumor samples. TIMER2.0 analyzed the association of CXCR4 / FAP expression and infiltration levels of immune-related cells. (3) Results: We identified entity-independent CXCR4 and FAP gene signatures representative for the majority of solid cancers. While CXCR4 positivity marked an immune-related microenvironment, FAP overexpression highlighted an angiogenesis-associated niche. TIMER2.0 analysis confirmed characteristic infiltration levels of CD8+ cells for CXCR4-positive tumors and endothelial cells for FAP-positive tumors. (4) Conclusions: CXCR4- and FAP-directed PET imaging could provide a non-invasive decision aid for entity-agnostic treatment of microenvironment in solid malignancies. Moreover, this machine learning workflow can easily be transferred towards other theranostic targets.

Visualizing the Interactions Shaping the Imaging of the Microenvironment in Human Cancers

The Visium Spatial Gene Expression Solution (Visium 10×) allows for the mRNA analysis using high throughput sequencing and maps a transcriptional expression pattern in tissue sections using high-resolution microscope imaging in ex-vivo human and mice samples. The workflow surveys spatial global gene expression in tissue sections, exploiting the whole transcriptome profiling and defining the set of transcripts via targeted gene panels. An automated cell type annotation allows a comparison with control tissue samples. This technique delineates cancerous or diseased tissue boundaries and details gene expression gradients in the tissue surrounding the tumor or pathologic nests. Remarkably, the Visium 10× allows for whole transcriptome and targeted analysis without the loss of spatial information. This approach provides gene expression data within the context of tissue architecture, tissue microenvironments, and cell groups. It can be used in association with therapy, anti-angiogenic therapy, and immunotherapy to improve treatment response.

Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors-Dependencies and Novel Pitfalls

Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.

Phytochemicals for the Prevention and Treatment of Renal Cell Carcinoma: Preclinical and Clinical Evidence and Molecular Mechanisms

Renal cell carcinoma (RCC) is associated with about 90% of renal malignancies, and its incidence is increasing globally. Plant-derived compounds have gained significant attention in the scientific community for their preventative and therapeutic effects on cancer. To evaluate the anticancer potential of phytocompounds for RCC, we compiled a comprehensive and systematic review of the available literature. Our work was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. The literature search was performed using scholarly databases such as PubMed, Scopus, and ScienceDirect and keywords such as renal cell carcinoma, phytochemicals, cancer, tumor, proliferation, apoptosis, prevention, treatment, in vitro, in vivo, and clinical studies. Based on in vitro results, various phytochemicals, such as phenolics, terpenoids, alkaloids, and sulfur-containing compounds, suppressed cell viability, proliferation and growth, showed cytotoxic activity, inhibited invasion and migration, and enhanced the efficacy of chemotherapeutic drugs in RCC. In various animal tumor models, phytochemicals suppressed renal tumor growth, reduced tumor size, and hindered angiogenesis and metastasis. The relevant antineoplastic mechanisms involved upregulation of caspases, reduction in cyclin activity, induction of cell cycle arrest and apoptosis via modulation of a plethora of cell signaling pathways. Clinical studies demonstrated a reduced risk for the development of kidney cancer and enhancement of the efficacy of chemotherapeutic drugs. Both preclinical and clinical studies displayed significant promise of utilizing phytochemicals for the prevention and treatment of RCC. Further research, confirming the mechanisms and regulatory pathways, along with randomized controlled trials, are needed to establish the use of phytochemicals in clinical practice.

Targeting circDGKD Intercepts TKI's Effects on Up-Regulation of Estrogen Receptor β and Vasculogenic Mimicry in Renal Cell Carcinoma

Vasculogenic mimicry (VM) has been reported as an alternative channel to increase tumor nutrient supplies and accelerate tumor progression, and is associated with poor survival prognosis in multiple cancers, including renal cell carcinoma (RCC). The currently used anti-angiogenic treatment for metastatic RCC, sunitinib, a tyrosine kinase inhibitor (TKI), has been reported to induce VM formation. Previously we identified that the estrogen receptor β (ERβ) functions as an oncogenic factor to promote RCC progression, supported by the analytic results from The Cancer Genome Atlas (TCGA) database. We have also found evidence that sunitinib induces RCC VM formation by up-regulating ERβ expression. In this study, we further demonstrated that treatment with sunitinib, as well as axitinib, another TKI, could induce ERβ expression in RCC cell lines. Clinical clear cell RCC (ccRCC) patients with higher ERβ expression are more likely to be found VE-cadherin positive and VM positive. Mechanism dissection showed that TKI- induced ERβ transcriptionally up-regulates the circular RNA of DGKD (circDGKD, hsa_circ_0058763), which enhances VE-cadherin expression by sponging the microRNA miR-125-5p family. Targeting circDGKD intercepts sunitinib-pretreatment-induced RCC VM formation, reduces metastases and improves survival in an experimental orthotopic animal model. Targeting ERβ/circDGKD signals may improve the TKI efficacy and provide novel combination therapies for metastatic RCC.

Systematic Analysis of the Expression and Prognosis of Fcγ Receptors in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) remains a common malignancy in the urinary system. Although dramatic progress was made in multimodal therapies, the improvement of its prognosis continues to be unsatisfactory. The antibody-binding crystallizable fragment (Fc) γ receptors (FcγRs) are expressed on the surface of leukocytes, to mediate antibody-induced cell-mediated anti-tumor responses when tumor-reactive antibodies are present. FcγRs have been studied extensively in immune cells, but rarely in cancer cells.

Methods

ONCOMINE, UALCAN, GEPIA, TIMER, TISIDB, Kaplan–Meier Plotter, SurvivalMeth, and STRING databases were utilized in this study.

Results

Transcriptional levels of FcγRs were upregulated in patients with ccRCC. There was a noticeable correlation between the over expressions of FCGR1A/B/C, FCGR2A, and clinical cancer stages/tumor grade in ccRCC patients. Besides, higher transcription levels of FcγRs were found to be associated with poor overall survival (OS) in ccRCC patients. Further, high DNA methylation levels of FcγRs were also observed in ccRCC patients, and higher DNA methylation levels of FcγRs were associated with shorter OS. Moreover, we also found that the expression of FcγRs was significantly correlated with immune infiltrates, namely, immune cells (NK, macrophages, Treg, cells) and immunoinhibitor (IL-10, TGFB1, and CTLA-4).

Conclusions

Our study demonstrated that high DNA methylation levels of FcγRs lead to their low mRNA, protein levels, and poor prognosis in ccRCC patients, which may provide new insights into the choice of immunotherapy targets and prognostic biomarkers.

Angiogenesis as Therapeutic Target in Metastatic Prostate Cancer - Narrowing the Gap Between Bench and Bedside

Angiogenesis in metastatic castration-resistant prostate cancer (mCRPC) has been extensively investigated as a promising druggable biological process. Nonetheless, targeting angiogenesis has failed to impact overall survival (OS) in patients with mCRPC despite promising preclinical and early clinical data. This discrepancy prompted a literature review highlighting the tumor heterogeneity and biological context of Prostate Cancer (PCa). Narrowing the gap between the bench and bedside appears critical for developing novel therapeutic strategies. Searching clinicaltrials.gov for studies examining angiogenesis inhibition in patients with PCa resulted in n=20 trials with specific angiogenesis inhibitors currently recruiting (as of September 2021). Moreover, several other compounds with known anti-angiogenic properties - such as Metformin or Curcumin - are currently investigated. In general, angiogenesis-targeting strategies in PCa include biomarker-guided treatment stratification - as well as combinatorial approaches. Beyond established angiogenesis inhibitors, PCa therapies aiming at PSMA (Prostate Specific Membrane Antigen) hold the promise to have a substantial anti-angiogenic effect - due to PSMA´s abundant expression in tumor vasculature.

Identification of TRPM2 as a Marker Associated With Prognosis and Immune Infiltration in Kidney Renal Clear Cell Carcinoma

TRPM2 (transient receptor potential melastatin-2), a Ca²⁺ permeable, non-selective cation channel, is highly expressed in cancers and regulates tumor cell migration, invasion, and proliferation. However, no study has yet demonstrated the association of TRPM2 with the prognosis of cancer patients or tumor immune infiltration, and the possibility and the clinical basis of TRPM2 as a prognostic marker in cancers are yet unknown. In the current study, we first explored the correlation between the mRNA level of TRPM2 and the prognosis of patients with different cancers across public databases. Subsequently, the Tumor Immune Estimation Resource (TIMER) platform and the TISIDB website were used to assess the correlation between TRPM2 and tumor immune cell infiltration level. We found that 1) the level of TRPM2 was significantly elevated in most tumor tissues relative to normal tissues; 2) TRPM2 upregulation was significantly associated with adverse clinical characteristics and poor survival of kidney renal clear cell carcinoma (KIRC) patients; 3) the level of TRPM2 was positively related to immune cell infiltration. Moreover, TRPM2 was closely correlated to the gene markers of diverse immune cells; 4) a high TRPM2 expression predicted worse prognosis in KIRC based on different enriched immune cell cohorts; and 5) TRPM2 was mainly implemented in the T-cell activation process indicated by Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. In conclusion, TRPM2 can serve as a marker to predict the prognosis and immune infiltration in KIRC through the regulation of T-cell activation. The current data may provide additional information for further studies surrounding the function of TRPM2 in KIRC.

A Novel Prognostic Predictor of Immune Microenvironment and Therapeutic Response in Kidney Renal Clear Cell Carcinoma based on Necroptosis-related Gene Signature

Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis. Conclusion: The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC.

Determination of Exosome Mitochondrial DNA as a Biomarker of Renal Cancer Aggressiveness

Simple Summary

Components of liquid biopsy are potential non-invasive biomarkers for monitoring renal cell carcinoma (RCC) status. The aim of our study was to examine mitochondrial genes (such as HV1 and CYB) included in exosomal fractions as promising and innovative biomarkers in RCC. We found that phase C containing different types of vesicles and phase F rich in exosomes with a high mitochondrial DNA (mtDNA) content could be considered as powerful biomarkers for susceptibility to RCC. Interestingly, mtDNA was a good genetic marker when aggressiveness was evaluated.

Abstract

Here, the role of non-invasive biomarkers in liquid biopsy was evaluated, mainly in exosomes and mitochondrial DNA (mtDNA) as promising, novel, and stable biomarkers for renal cell carcinoma (RCC). A total of 140 fractions (named from B to F) obtained by ultracentrifugations of whole blood samples from 28 individuals (13 patients and 15 controls) were included. Nanoparticle Tracking Analysis (NTA) was conducted to characterized exosomal fraction. Subsequently, an analysis of digital PCR (dPCR) using the QuantStudio™ 3D Digital PCR platform was performed and the quantification of mtDNA copy number by QuantStudioTM 12K Flex Real-Time PCR System (qPCR) was developed. Moreover, Next Generation Sequencing (NGS) analyses were included using MiSeq system (Illumina, San Diego, CA, USA). An F fraction, which contains all exosome data and all mitochondrial markers, was identified in dPCR and qPCR with statistically significant power (adjusted p values ≤ 0.03) when comparing cases and controls. Moreover, present analysis in mtDNA showed a relevant significance in RCC aggressiveness. To sum up, this is the first time a relation between exosomal mtDNA markers and clinical management of RCC is analyzed. We suggest a promising strategy for future liquid biopsy RCC analysis, although more analysis should be performed prior to application in routine clinical practice.

Prognostic and Clinicopathological Significance of the Systemic Immune-Inflammation Index in Patients With Renal Cell Carcinoma: A Meta-Analysis

Background

The systemic immune-inflammation index (SII) is a hematological parameter based on neutrophil, platelet, and lymphocyte counts. Studies that have investigated the prognostic value of SII in patients with renal cell carcinoma (RCC) have reported controversial results. In this study, we systematically investigated the prognostic value of SII in patients with RCC.

Methods

We systematically searched English articles in the PubMed, Embase, Web of Science, and Cochrane Library databases up to October 2021. Hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were used to obtain pooled results.

Results

The meta-analysis included 10 studies that enrolled 3,180 patients. A high SII was associated with poor overall survival (HR 1.75, 95% CI 1.33–2.30, p<0.001) in patients with RCC. However, a high SII was not shown to be a significant prognostic factor for progression-free survival/disease-free survival (HR 1.22, 95% CI 0.84–1.76, p=0.293) or poor cancer-specific survival (HR 1.46, 95% CI 0.68–3.12, p=0.332) in patients with RCC. A high SII was correlated with male sex (OR 1.51, 95% CI 1.11–2.04, p=0.008), Fuhrman grade G3–G4 (OR 1.80, 95% CI 1.08–3.00, p=0.024), and poor risk based on the International Metastatic Renal Cell Carcinoma Database Consortium criteria (OR 19.12, 95% CI 9.13–40.06, p<0.001).

Conclusion

A high SII was independently associated with poor survival outcomes in patients with RCC. Additionally, an elevated SII indicated more aggressive disease. The SII may serve as a useful cost-effective prognostic indicator in patients with RCC.

Identification of CCL4 as an Immune-Related Prognostic Biomarker Associated With Tumor Proliferation and the Tumor Microenvironment in Clear Cell Renal Cell Carcinoma

The last decade has witnessed revolutionary advances taken in immunotherapy for various malignant tumors. However, immune-related molecules and their characteristics in the prediction of clinical outcomes and immunotherapy response in clear cell renal cell carcinoma (ccRCC) remain largely unclear. C-C Motif Chemokine Ligand 4 (CCL4) was extracted from the intersection analysis of common differentially expressed genes (DEGs) of four microarray datasets from the Gene Expression Omnibus database and immune-related gene lists in the ImmPort database using Cytoscape plug-ins and univariate Cox regression analysis. Subsequential analysis revealed that CCL4 was highly expressed in ccRCC patients, and positively correlated with multiple clinicopathological characteristics, such as grade, stage and metastasis, while negatively with overall survival (OS). We performed gene set enrichment analysis (GSEA) and gene set variant analysis (GSVA) with gene sets coexpressed with CCL4, and observed that gene sets positively related to CCL4 were enriched in tumor proliferation and immune-related pathways while metabolic activities in the negatively one. To further explore the correlation between CCL4 and immune-related biological process, the CIBERSORT algorithm, ESTIMATE method, and tumor mutational burden (TMB) score were employed to evaluate the tumor microenvironment (TME) characteristics of each sample and confirmed that high CCL4 expression might give rise to high immune cell infiltration. Moreover, correlation analysis revealed that CCL4 was positively correlated with common immune checkpoint genes, such as programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3). Overall, this study demonstrated that CCL4 might serve as a potential immune-related prognostic biomarker to predict clinical outcomes and immunotherapy response in ccRCC. Moreover, CCL4 might contribute to TME modulation, indicating the mechanism CCL4 involved in tumor proliferation and metastasis, which could provide novel therapeutic perceptions for ccRCC patients.

A Mitochondrial Dysfunction and Oxidative Stress Pathway-Based Prognostic Signature for Clear Cell Renal Cell Carcinoma

Mitochondria not only are the main source of ATP synthesis but also regulate cellular redox balance and calcium homeostasis. Its dysfunction can lead to a variety of diseases and promote cancer and metastasis. In this study, we aimed to explore the molecular characteristics and prognostic significance of mitochondrial genes (MTGs) related to oxidative stress in clear cell renal cell carcinoma (ccRCC). A total of 75 differentially expressed MTGs were analyzed from The Cancer Genome Atlas (TCGA) database, including 46 upregulated and 29 downregulated MTGs. Further analysis screened 6 prognostic-related MTGs (ACAD11, ACADSB, BID, PYCR1, SLC25A27, and STAR) and was used to develop a signature. Kaplan-Meier survival and receiver operating characteristic (ROC) curve analyses showed that the signature could accurately distinguish patients with poor prognosis and had good individual risk stratification and prognostic potential. Stratified analysis based on different clinical variables indicated that the signature could be used to evaluate tumor progression in ccRCC. Moreover, we found that there were significant differences in immune cell infiltration between the low- and high-risk groups based on the signature and that ccRCC patients in the low-risk group responded better to immunotherapy than those in the high-risk group (46.59% vs 35.34%, P = 0.008). We also found that the expression levels of these prognostic MTGs were significantly associated with drug sensitivity in multiple ccRCC cell lines. Our study for the first time elucidates the biological function and prognostic significance of mitochondrial molecules associated with oxidative stress and provides a new protocol for evaluating treatment strategies targeting mitochondria in ccRCC patients.

Malignancy and NF-κB signalling strengthen coordination between expression of mitochondrial and nuclear-encoded oxidative phosphorylation genes

BACKGROUND

Mitochondria are ancient endosymbiotic organelles crucial to eukaryotic growth and metabolism. The mammalian mitochondrial genome encodes for 13 mitochondrial proteins, and the remaining mitochondrial proteins are encoded by the nuclear genome. Little is known about how coordination between the expression of the two sets of genes is achieved.

RESULTS

Correlation analysis of RNA-seq expression data from large publicly available datasets is a common method to leverage genetic diversity to infer gene co-expression modules. Here we use this method to investigate nuclear-mitochondrial gene expression coordination. We identify a pitfall in correlation analysis that results from the large variation in the proportion of transcripts from the mitochondrial genome in RNA-seq data. Commonly used normalisation techniques based on total read counts, such as FPKM or TPM, produce artefactual negative correlations between mitochondrial- and nuclear-encoded transcripts. This also results in artefactual correlations between pairs of nuclear-encoded genes, with important consequences for inferring co-expression modules beyond mitochondria. We show that these effects can be overcome by normalizing using the median-ratio normalisation (MRN) or trimmed mean of M values (TMM) methods. Using these normalisations, we find only weak and inconsistent correlations between mitochondrial and nuclear-encoded mitochondrial genes in the majority of healthy human tissues from the GTEx database.

CONCLUSIONS

We show that a subset of healthy tissues with high expression of NF-κB show significant coordination, suggesting a role for NF-κB in ensuring balanced expression between mitochondrial and nuclear genes. Contrastingly, most cancer types show robust coordination of nuclear and mitochondrial OXPHOS gene expression, identifying this as a feature of gene regulation in cancer.

LINC01232 serves as a novel biomarker and promotes tumour progression by sponging miR-204-5p and upregulating RAB22A in clear cell renal cell carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) are involved in the progression of various cancers, including clear cell renal cell carcinoma (ccRCC). This study aimed to investigate the expression and prognostic value of long intergenic non-protein coding RNA (LINC) 01232 in ccRCC and preliminary explore the molecular mechanism underlying the role of LINC01232 in ccRCC progression.

METHODS

Tumour tissues and adjacent normal tissues of 122 patients with ccRCC were collected in this study. The levels of LINC01232, microRNA (miR)-204-5p and RAB22A were measured by quantitative real-time PCR. The proliferation, migration and invasion of ccRCC cells were detected by cell counting kit-8 assay and Transwell assay, respectively. The interaction among LINC01232, miR-204-5p and RAB22A was confirmed by bioinformatics analysis, dual-luciferase reporter assay and Pearson correlation analysis. The association of LINC01232 and miR-204-5p with ccRCC patient survival was verified by the Kaplan-Meier method and log-rank test. The prognostic value of LINC01232 in ccRCC was confirmed by Cox regression analysis.

RESULTS

LINC01232 expression was increased in ccRCC tumour tissues and ccRCC cells and independently predicted the prognosis of ccRCC patients. In addition, LINC01232 silencing inhibited ccRCC cell proliferation, migration and invasion. Moreover, LINC01232 served as a sponge for miR-204-5p, and miR-204-5p reduction reversed the inhibitory effect of LINC01232 silencing on ccRCC cell function. Furthermore, LINC01232 could sponge miR-204-5p, causing the elevation of RAB22A in ccRCC, thereby promoting ccRCC cell function.

CONCLUSION

LINC01232 may be an independent prognostic biomarker in ccRCC and plays an oncogenic role in ccRCC progression by sponging miR-204-5p and upregulating RAB22A.

Deregulation of N6-Methyladenosine RNA Modification and Its Erasers FTO/ALKBH5 among the Main Renal Cell Tumor Subtypes

(1) Background: Methylation of N6-adenosine (m6A) is the most abundant messenger RNA (mRNA) modification in eukaryotes. We assessed the expression profiles of m6A regulatory proteins in renal cell carcinoma (RCC) and their clinical relevance, namely, as potential biomarkers. (2) Methods: In silico analysis of The Cancer Genome Atlas (TCGA) dataset was use for evaluating the expression of the m6A regulatory proteins among RCC subtypes and select the most promising candidates for further validation. ALKBH5 and FTO transcript and protein expression were evaluated in a series of primary RCC (n = 120) and 40 oncocytomas selected at IPO Porto. (3) Results: In silico analysis of TCGA dataset disclosed altered expression of the major m6A demethylases among RCC subtypes, particularly FTO and ALKBH5. Furthermore, decreased FTO mRNA levels associated with poor prognosis in ccRCC and pRCC. In IPO Porto's cohort, FTO and ALKBH5 transcript levels discriminated ccRCC from oncocytomas. Furthermore, FTO and ALKBH5 immunoexpression differed among RCC subtypes, with higher expression levels found in ccRCC comparatively to the other RCC subtypes and oncocytomas. (4) Conclusion: We conclude that altered expression of m6A RNA demethylases is common in RCC and seems to be subtype specific. Specifically, FTO and ALKBH5 might constitute new candidate biomarkers for RCC patient management, aiding in differential diagnosis of renal masses and prognostication.

Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning

Simple Summary

Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated.

Abstract

Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.

Identification and Validation of PIK3CA as a Marker Associated with Prognosis and Immune Infiltration in Renal Clear Cell Carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is the most prevalent renal malignancy. The therapeutic strategies for advanced KIRC are very few, with only sunitinib being widely approved. Mutations in the PIK3CA gene can affect tumor cell proliferation, metastasis, and patients' survival.

Methods

Bioinformatics analysis was performed to explore the expression and clinical significance of PIK3CA in KIRC. Moreover, qRT-PCR was conducted to verify the result.

Results

Subgroup analyses of KIRC tissue based on gender, tumor grade, and cancer stage indicated downregulation of PIK3CA mRNA expression. The KIRC patients with high PIK3CA expression indicated a better overall survival, progression-free survival, and disease-free survival. A predictive nomogram was constructed and demonstrated that the calibration plots for the 3-year and 5-year OS rates were predicted relatively well compared with an ideal model in the TCGA KIRC cohort. The validation study revealed that downregulation of PIK3CA in KIRC tissues and low PIK3CA expression had a poor overall survival with an AUC of 0.775 in the ROC curve. Moreover, Cox regression analysis revealed that PIK3CA expression and clinical stage were independent factors affecting the prognosis of KIRC patients. PIK3CA expression was found to be significantly associated with the abundance of immune cells and immune biomarker sets. PIK3CA and associated genes were found to be mainly associated with immune response and the JAK-STAT signaling pathway.

Conclusion

We identified PIK3CA as a potential biomarker for prognosis correlated with immune infiltrates in KIRC. Further studies should focus on the functions of PIK3CA in KIRC carcinogenesis.

The Anti-VEGF(R) Drug Discovery Legacy: Improving Attrition Rates by Breaking the Vicious Cycle of Angiogenesis in Cancer

Resistance to anti-vascular endothelial growth factor (VEGF) molecules causes lack of response and disease recurrence. Acquired resistance develops as a result of genetic/epigenetic changes conferring to the cancer cells a drug resistant phenotype. In addition to tumor cells, tumor endothelial cells also undergo epigenetic modifications involved in resistance to anti-angiogenic therapies. The association of multiple anti-angiogenic molecules or a combination of anti-angiogenic drugs with other treatment regimens have been indicated as alternative therapeutic strategies to overcome resistance to anti-angiogenic therapies. Alternative mechanisms of tumor vasculature, including intussusceptive microvascular growth (IMG), vasculogenic mimicry, and vascular co-option, are involved in resistance to anti-angiogenic therapies. The crosstalk between angiogenesis and immune cells explains the efficacy of combining anti-angiogenic drugs with immune check-point inhibitors. Collectively, in order to increase clinical benefits and overcome resistance to anti-angiogenesis therapies, pan-omics profiling is key.