Impact of Extracellular Matrix Components to Renal Cell Carcinoma Behavior

MMPs-related risk model identification and SAA1 promotes clear cell renal cell carcinoma migration via ERK-AP1-MMPs axis

Matrix Metalloproteinases (MMPs) have been demonstrated to be essential in facilitating the migration and metastasis of clear cell renal cell carcinoma (ccRCC). However, the ability of the MMP family to predict clinical outcomes and guide optimal therapeutic strategies for ccRCC patients remains incompletely understood. In this investigation, we initially conducted a thorough examination of the MMP family in pan-cancer. Notably, MMPs exhibited distinctive significance in ccRCC. Following this, we undertook an extensive analysis to evaluate the clinical value of MMPs and potential mechanisms by which MMPs contribute to the progression of ccRCC. A novel stratification method and prognostic model were developed based on MMPs in order to enhance the accuracy of prognosis prediction for ccRCC patients and facilitate personalized treatment. By conducting multi-omics analysis and transcriptional regulation analysis, it was hypothesized that SAA1 plays a crucial role in promoting ccRCC migration through MMPs. Subsequently, in vitro experiments confirmed that SAA1 regulates ccRCC cell migration via the ERK-AP1-MMPs axis. In conclusion, our study has explored the potential value of the MMP family as prognostic markers for ccRCC and as guides for medication regimens. Additionally, we have identified SAA1 as a crucial factor in the migration of ccRCC.

Integrating tumor and healthy epithelium in a micro-physiology multi-compartment approach to study renal cell carcinoma pathophysiology

The advent of micro-physiological systems (MPS) in biomedical research has enabled the introduction of more complex and relevant physiological into in vitro models. The recreation of complex morphological features in three-dimensional environments can recapitulate otherwise absent dynamic interactions in conventional models. In this study we developed an advanced in vitro Renal Cell Carcinoma (RCC) that mimics the interplay between healthy and malignant renal tissue. Based on the TissUse Humimic platform our model combines healthy renal proximal tubule epithelial cells (RPTEC) and RCC. Co-culturing reconstructed RPTEC tubules with RCC spheroids in a closed micro-perfused circuit resulted in significant phenotypical changes to the tubules. Expression of immune factors revealed that interleukin-8 (IL-8) and tumor necrosis factor-alfa (TNF-α) were upregulated in the non-malignant cells while neutrophil gelatinase-associated lipocalin (NGAL) was downregulated in both RCC and RPTEC. Metabolic analysis showed that RCC prompted a shift in the energy production of RPTEC tubules, inducing glycolysis, in a metabolic adaptation that likely supports RCC growth and immunogenicity. In contrast, RCC maintained stable metabolic activity, emphasizing their resilience to external factors. RNA-seq and biological process analysis of primary RTPTEC tubules demonstrated that the 3D tubular architecture and MPS conditions reverted cells to a predominant oxidative phosphorylate state, a departure from the glycolytic metabolism observed in 2D culture. This dynamic RCC co-culture model, approximates the physiology of healthy renal tubules to that of RCC, providing new insights into tumor-host interactions. Our approach can show that an RCC-MPS can expand the complexity and scope of pathophysiology and biomarker studies in kidney cancer research.

FN1 and cancer-associated fibroblasts markers influence immune microenvironment in clear cell renal cell carcinoma

BACKGROUND

Altered tumor microenvironment (TME) is characterized in clear cell renal cell carcinoma (ccRCC) as a result of the heterogeneity observed in the TME. Modulations in TME have shown tumor metastasis promotion; hence, identifying TME-based biomarkers can be critical for theranostics application.

METHODS

Here, we performed an integrated systems biology approach utilizing differential gene expression, network metrics and clinical samples cohorts to prioritize the major deregulated genes and their associated pathways specific for metastasis.

RESULTS

The gene expression profiling of 140 ccRCC samples resulted in 3657 differentially expressed genes, from which a network of 1867 up-regulated genes were further computed using network metrics for screening hub-genes. The specific pathways of ccRCC entailed through functional enrichment analysis of the hub-gene clusters indicated the role of the identified hub-genes in the enriched pathways, further validating the functional significance of the hub-genes. The positive correlation of TME cells, namely cancer-associated fibroblasts (CAFs) and its biomarkers (FAP and S100A4) with FN1, signified the role of hub-gene signaling for promoting metastasis in ccRCC. Thereafter, comparative expression, differential methylation, genetic alteration and overall survival analysis were analyzed to validate the screened hub-genes.

CONCLUSIONS

The hub-genes were validated and prioritized by correlating with expression-based parameters, including histological grades, tumor, metastatic and pathological stages (based on median transcript per million; analysis of variance [ANOVA], P ≤ 0.05) from a clinically curated ccRCC dataset to further substantiate the translational benefits of the screened hub-genes as potential diagnostic biomarkers for ccRCC.

Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma

The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment.

Advanced in vitro models for renal cell carcinoma therapy design

Renal cell carcinoma (RCC) and its principal subtype, clear cell RCC, are the most diagnosed kidney cancer. Despite substantial improvement over the last decades, current pharmacological intervention still fails to achieve long-term therapeutic success. RCC is characterized by a high intra- and inter-tumoral heterogeneity and is heavily influenced by the crosstalk of the cells composing the tumor microenvironment, such as cancer-associated fibroblasts, endothelial cells and immune cells. Moreover, multiple physicochemical properties such as pH, interstitial pressure or oxygenation may also play an important role. These elements are often poorly recapitulated in in vitro models used for drug development. This inadequate recapitulation of the tumor is partially responsible for the current lack of an effective and curative treatment. Therefore, there are needs for more complex in vitro or ex vivo drug screening models. In this review, we discuss the current state-of-the-art of RCC models and suggest strategies for their further development.

Research Progress of Tumor Microenvironment Targeted Therapy for Clear Cell Renal Cell Carcinoma

Renal clear cell carcinoma (ccRCC) and the tumor microenvironment (TME) influence each other, leading to the tumor microenvironment that can guide the corresponding treatment. With the deepening of research, some treatment options have achieved good results, such as tyrosine kinase inhibitors, immune checkpoint inhibitors, and so on. As the link between TME and malignancy is constantly discovered, more targeted studies on different components of TME are increasing, and this targeted therapy is a new method for treating ccRCC, and also a current research hotspot. This review summarizes the characteristics of the ccRCC tumor microenvironment, the outcomes of different treatments, and some potential targets.

A 20-Gene Signature Predicting Survival in Patients with Clear Cell Renal Cell Carcinoma Based on Basement Membrane

Objectives

The most common subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC), has a high heterogeneity and aggressive nature. The basement membrane (BM) is known to play a vital role in tumor metastasis. BM-related genes remain untested in ccRCC, however, in terms of their prognostic significance.

Methods

BM-related genes were gleaned from the most recent cutting-edge research. The RNA-seq and clinical data of the ccRCC were obtained from TCGA and GEO databases, respectively. The multigene signature was constructed using the univariate Cox regression and the LASSO regression algorithm. Then, clinical features and prognostic signatures were combined to form a nomogram to predict individual survival probabilities. Using functional enrichment analysis and immune-correlation analysis, we investigated potential enrichment pathways and immunological characteristics associated with BM-related-gene signature.

Results

In this study, we built a model of 20 BM-related genes and classified them as high-risk or low-risk, with each having its anticipated risk profile. Patients in the high-risk group showed significantly reduced OS compared with patients in the low-risk group in the TCGA cohort, as was confirmed by the testing dataset. Functional analysis showed that the BM-based model was linked to cell-substrate adhesion and tumor-related signaling pathways. Comparative analysis of immune cell infiltration degrees and immune checkpoints reveals a central role for BM-related genes in controlling the interplay between the immune interaction and the tumor microenvironment of ccRCC.

Conclusions

We combined clinical characteristics known to predict the prognosis of ccRCC patients to create a gene signature associated with BM. Our findings may also be useful for forecasting how well immunotherapies would work against ccRCC. Targeting BM may be a therapeutic alternative for ccRCC, but the underlying mechanism still needs further exploration.

New insights into fibrotic signaling in renal cell carcinoma

Fibrotic signaling plays a pivotal role in the development and progression of solid cancers including renal cell carcinoma (RCC). Intratumoral fibrosis (ITF) and pseudo-capsule (PC) fibrosis are significantly correlated to the disease progression of renal cell carcinoma. Targeting classic fibrotic signaling processes such as TGF-β signaling and epithelial-to-mesenchymal transition (EMT) shows promising antitumor effects both preclinically and clinically. Therefore, a better understanding of the pathogenic mechanisms of fibrotic signaling in renal cell carcinoma at molecular resolution can facilitate the development of precision therapies against solid cancers. In this review, we systematically summarized the latest updates on fibrotic signaling, from clinical correlation and molecular mechanisms to its therapeutic strategies for renal cell carcinoma. Importantly, we examined the reported fibrotic signaling on the human renal cell carcinoma dataset at the transcriptome level with single-cell resolution to assess its translational potential in the clinic.

The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma

Simple Summary

The extracellular matrix (ECM) controls fundamental properties of tumors, including growth, blood vessel investment, and invasion. The ECM defines rigidity of tumor tissue and individual ECM proteins have distinct biological effects on tumor cells. This article reviews the composition and biological functions of the ECM of clear cell renal cell carcinoma (ccRCC). The most frequent initiating genetic mutation in ccRCC inactivates the VHL gene, which plays a direct role in organizing the ECM. This is predicted to result in local ECM modification, which promotes the growth of tumor cells and the invasion of blood vessels. Later in tumor growth, connective tissue cells are recruited, which are predicted to produce large amounts of ECM, affecting the growth and invasive behaviors of tumor cells. Strategies to therapeutically control the ECM are under active investigation and a better understanding of the ccRCC ECM will determine the applicability of ECM-modifying drugs to this type of cancer.

Abstract

The extracellular matrix (ECM) of tumors is a complex mix of components characteristic of the tissue of origin. In the majority of clear cell renal cell carcinomas (ccRCCs), the tumor suppressor VHL is inactivated. VHL controls matrix organization and its loss promotes a loosely organized and angiogenic matrix, predicted to be an early step in tumor formation. During tumor evolution, cancer-associated fibroblasts (CAFs) accumulate, and they are predicted to produce abundant ECM. The ccRCC ECM composition qualitatively resembles that of the healthy kidney cortex in which the tumor arises, but there are important differences. One is the quantitative difference between a healthy cortex ECM and a tumor ECM; a tumor ECM contains a higher proportion of interstitial matrix components and a lower proportion of basement membrane components. Another is the breakdown of tissue compartments in the tumor with mixing of ECM components that are physically separated in healthy kidney cortex. Numerous studies reviewed in this work reveal effects of specific ECM components on the growth and invasive behaviors of ccRCCs, and extrapolation from other work suggests an important role for ECM in controlling ccRCC tumor rigidity, which is predicted to be a key determinant of invasive behavior.

TGF‑β1 affects the renal cancer miRNome and regulates tumor cells proliferation

TGF-β1 is a pleiotropic cytokine that can either promote or inhibit cancer development and progression. It was previously found that TGF-β1 can regulate the expression of several microRNAs (miR or miRNA) involved in the progression of renal cell carcinoma (RCC). Therefore, the present study aimed to analyze the effects of TGF-β1 on the global RCC miRNome. It was found that TGF-β1 can regulate a complex network consisting of miRNAs and mRNAs involved in RCC transformation. In particular, TGF-β1 was revealed to regulate the proliferation of RCC cells while concomitantly modifying the expression of oncogenic regulators, including avian erythroblastosis virus E26 (V-Ets) oncogene homolog-1 (ETS1). In addition, TGF-β1 was demonstrated to regulate the expression of a number of miRNAs including miR-30c-5p, miR-155-5p, miR-181a-5p and miR-181b-5p. By contrast, TGF-β1 reciprocally modified the expression of genes encoding TGF-β1 receptors and SMADs, indicating a novel regulatory feedback mechanism mediated through the miRNAs. These data suggested that ETS1 served different roles in different subtypes of RCC tumors, specifically by functioning as an oncogene in clear cell RCC while as a tumor suppressor in papillary RCC.

Identification of adhesion-associated extracellular matrix component thrombospondin 3 as a prognostic signature for clear cell renal cell carcinoma

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is a highly aggressive disease, and approximately 30% of patients are diagnosed at the metastatic stage. Even with targeted therapies, the prognosis of advanced ccRCC is poor. The aim of this study was to investigate clinical prognosis signatures by analyzing the ccRCC datasets in The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the function of thrombospondin 3 (THBS3) in ccRCC.

MATERIALS AND METHODS

We analyzed the ccRCC datasets in TCGA and CPTAC to search for extracellular matrix (ECM)-related and adhesion-associated genes, and conducted overall survival, Cox, and receiver operating characteristic analyses. We also performed CCK8, colony formation, and transwell assays to compared the proliferation and migration ability of THBS3 knockout cells with those of cells without THBS3 knockout.

RESULTS

Comprehensive bioinformatics analysis revealed that THBS3 is a novel candidate oncogene that is overexpressed in ccRCC tumor tissue and that its elevated expression indicates poor prognosis. Our study also showed that knockdown of THBS3 inhibits proliferation, colony formation, and migration of ccRCC cells.

CONCLUSIONS

In summary, our data have revealed that THBS3 is upregulated in cancer tissues and could be used as a novel prognostic marker for ccRCC. Our findings thus offer theoretical support with bioinformatics analyses to the study of ECM and adhesion proteins in ccRCC, which may provide a new perspective for the clinical management of ccRCC.

Syndecan-4 in Tumor Cell Motility

Simple Summary

Cell migration is crucial fReaor metastasis formation and a hallmark of malignancy. The primary cause of high mortality among oncology patients is the ability of cancer cells to metastasize. To form metastasis, primary tumor cells must be intrinsically able to move. The transmembrane, heparan sulfate proteoglycan syndecan-4 (SDC4) exhibits multiple functions in signal transduction by regulating Rac1 GTPase activity and consequently actin remodeling, as well as regulating focal adhesion kinase, protein kinase C-alpha and the level of intracellular calcium. By affecting several signaling pathways and biological processes, SDC4 is involved in cell migration under physiological and pathological conditions as well. In this review, we discuss the SDC4-mediated cell migration focusing on the role of SDC4 in tumor cell movement.

Abstract

Syndecan-4 (SDC4) is a ubiquitously expressed, transmembrane proteoglycan bearing heparan sulfate chains. SDC4 is involved in numerous inside-out and outside-in signaling processes, such as binding and sequestration of growth factors and extracellular matrix components, regulation of the activity of the small GTPase Rac1, protein kinase C-alpha, the level of intracellular calcium, or the phosphorylation of focal adhesion kinase. The ability of this proteoglycan to link the extracellular matrix and actin cytoskeleton enables SDC4 to contribute to biological functions like cell adhesion and migration, cell proliferation, cytokinesis, cellular polarity, or mechanotransduction. The multiple roles of SDC4 in tumor pathogenesis and progression has already been demonstrated; therefore, the expression and signaling of SDC4 was investigated in several tumor types. SDC4 influences tumor progression by regulating cell proliferation as well as cell migration by affecting cell-matrix adhesion and several signaling pathways. Here, we summarize the general role of SDC4 in cell migration and tumor cell motility.

Development of a mechanically matched silk scaffolded 3D clear cell renal cell carcinoma model

Development of a 3D, biomaterials-based model for clear cell renal cell carcinoma (ccRCC) would be advantageous for understanding disease progression in vitro. This study demonstrated the development of lyophilized silk scaffolds that mechanically match the experimentally determined Young's modulus for ex vivo ccRCC samples and normal kidney tissue. Scaffolds fabricated from silk solutions ranging from 3 to 12% (w/v) were evaluated through mechanical testing. Following mechanical characterization of ccRCC samples, it was demonstrated that 6% silk scaffolds mechanically matched ccRCC samples. No impact of pathological grade and stage on the calculated ccRCC modulus was observed and all tumors evaluated mechanically matched the 6% silk scaffold formulation. Stratifying tissue specimens based upon histological observations (e.g. evidence of high levels of collagen deposition) resulted in no significant differences between groups. To investigate the impact of a mechanically matched culturing environment on in vitro ccRCC disease characteristics a model ccRCC cell line, 786-O, was utilized. Scaffolded 786-O cells demonstrated increased lipid droplet accumulation, a hallmark of ccRCC, compared to standard two-dimensional (2D) culture conditions. Additionally, scaffolded 786-O cells demonstrated increased expression of genes associated with ccRCC aggressiveness (ex. VEGFA, TNF, and IL-6) or immune markers under investigation as therapeutic targets (ex. PDL1, CTLA4). Comparison with 786-O cells grown on non-mechanically matched scaffolds demonstrated that these improved ccRCC characteristics were driven by scaffold modulus. Overall, our findings support the use of silk scaffolds in replicating physiologic tumor behavior for clear cell renal cell carcinoma and provide a platform for investigating disease progression.

Prognostic and therapeutic implications of extracellular matrix associated gene signature in renal clear cell carcinoma

Complex interactions in tumor microenvironment between ECM (extra-cellular matrix) and cancer cell plays a central role in the generation of tumor supportive microenvironment. In this study, the expression of ECM-related genes was explored for prognostic and immunological implication in clear cell renal clear cell carcinoma (ccRCC). Out of 964 ECM genes, higher expression (z-score > 2) of 35 genes showed significant association with overall survival (OS), progression-free survival (PFS) and disease-specific survival (DSS). On comparison to normal tissue, 12 genes (NUDT1, SIGLEC1, LRP1, LOXL2, SERPINE1, PLOD3, ZP3, RARRES2, TGM2, COL3A1, ANXA4, and POSTN) showed elevated expression in kidney tumor (n = 523) compared to normal (n = 100). Further, Cox proportional hazard model was utilized to develop 12 genes ECM signature that showed significant association with overall survival in TCGA dataset (HR = 2.45; 95% CI [1.78-3.38]; p < 0.01). This gene signature was further validated in 3 independent datasets from GEO database. Kaplan-Meier log-rank test significantly associated patients with elevated expression of this gene signature with a higher risk of mortality. Further, differential gene expression analysis using DESeq2 and principal component analysis (PCA) identified genes with the highest fold change forming distinct clusters between ECM-rich high-risk and ECM-poor low-risk patients. Geneset enrichment analysis (GSEA) identified significant perturbations in homeostatic kidney functions in the high-risk group. Further, higher infiltration of immunosuppressive T-reg and M2 macrophages was observed in high-risk group patients. The present study has identified a prognostic signature with associated tumor-promoting immune niche with clinical utility in ccRCC. Further exploration of ECM dynamics and validation of this gene signature can assist in design and application of novel therapeutic approaches.

Syndecan-4 as a Pathogenesis Factor and Therapeutic Target in Cancer

Cancer is an important cause of morbidity and mortality worldwide. Advances in research on the biology of cancer revealed alterations in several key pathways underlying tumorigenesis and provided molecular targets for developing new and improved existing therapies. Syndecan-4, a transmembrane heparan sulfate proteoglycan, is a central mediator of cell adhesion, migration and proliferation. Although several studies have demonstrated important roles of syndecan-4 in cell behavior and its interactions with growth factors, extracellular matrix (ECM) molecules and cytoskeletal signaling proteins, less is known about its role and expression in multiple cancer. The data summarized in this review demonstrate that high expression of syndecan-4 is an unfavorable biomarker for estrogen receptor-negative breast cancer, glioma, liver cancer, melanoma, osteosarcoma, papillary thyroid carcinoma and testicular, kidney and bladder cancer. In contrast, in neuroblastoma and colorectal cancer, syndecan-4 is downregulated. Interestingly, syndecan-4 expression is modulated by anticancer drugs. It is upregulated upon treatment with zoledronate and this effect reduces invasion of breast cancer cells. In our recent work, we demonstrated that the syndecan-4 level was reduced after trastuzumab treatment. Similarly, syndecan-4 levels are also reduced after panitumumab treatment. Together, the data found suggest that syndecan-4 level is crucial for understanding the changes involving in malignant transformation, and also demonstrate that syndecan-4 emerges as an important target for cancer therapy and diagnosis.

Exploration of an Integrative Prognostic Model of Radiogenomics Features With Underlying Gene Expression Patterns in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies in urinary system, and radiomics has been adopted in tumor staging and prognostic evaluation in renal carcinomas. This study aimed to integrate image features of contrast-enhanced CT and underlying genomics features to predict the overall survival (OS) of ccRCC patients.

Method

We extracted 107 radiomics features out of 205 patients with available CT images obtained from TCIA database and corresponding clinical and genetic information from TCGA database. LASSO-COX and SVM-RFE were employed independently as machine-learning algorithms to select prognosis-related imaging features (PRIF). Afterwards, we identified prognosis-related gene signature through WGCNA. The random forest (RF) algorithm was then applied to integrate PRIF and the genes into a combined imaging-genomics prognostic factors (IGPF) model. Furthermore, we constructed a nomogram incorporating IGPF and clinical predictors as the integrative prognostic model for ccRCC patients.

Results

A total of four PRIF and four genes were identified as IGPF and were represented by corresponding risk score in RF model. The integrative IGPF model presented a better prediction performance than the PRIF model alone (average AUCs for 1-, 3-, and 5-year were 0.814 vs. 0.837, 0.74 vs. 0.806, and 0.689 vs. 0.751 in test set). Clinical characteristics including gender, TNM stage and IGPF were independent risk factors. The nomogram integrating clinical predictors and IGPF provided the best net benefit among the three models.

Conclusion

In this study we established an integrative prognosis-related nomogram model incorporating imaging-genomic features and clinical indicators. The results indicated that IGPF may contribute to a comprehensive prognosis assessment for ccRCC patients.

Upregulation of KIF20A promotes tumor proliferation and invasion in renal clear cell carcinoma and is associated with adverse clinical outcome

Extensive research has revealed the pivotal role of kinesin family member 20A (KIF20A) in cancer. However, its latent involvement in renal clear cell carcinoma (ccRCC) still remains unclear. Thus, here we explored the role of KIF20A in ccRCC. For this, a series of software including R (v. 3.6.1), SPSS (v. 23), ImageJ and FlowJo were used for the analyses. Open-access data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases. Weighted Gene Co-expression Network Analysis (WGCNA) was used for module gene identification. In vitro results indicated that KIF20A expression is up-regulated in ccRCC tissue. KIF20A knockdown was able to inhibite cell proliferation and invasion of kidney A498 and Caki-1 cells. Meanwhile, KIF20A showed a strong association with immune infiltration. Particularly, KIF20A had a strong positive correlation with Th2 cells, Treg cells and Macrophages, but a negative correlation with Th17 cells, Mast cells and NK cells. These correlations may suggest the use of KIF20A as an underlying immunotherapy target in ccRCC. Our data indicated that KIF20A may promote cell invasion and proliferation in ccRCC, thus serving as an independent tumor marker and a putative therapeutic target.