Upregulation of COL6A1 is predictive of poor prognosis in clear cell renal cell carcinoma patients

Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization

Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T₁ relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.

High expression of COL6A1 predicts poor prognosis and response to immunotherapy in bladder cancer

Extracellular matrix (ECM), as an important framework for tumor microenvironment, plays important roles in many critical processes, including tumor growth, invasion, immune suppression, and drug resistance. However, few biomarkers of ECM-related genes (ERGs) have been developed for prognosis prediction and clinical treatment of bladder cancer (BC) patients. Bioinformatics analysis and LC-MS/MS analysis were used to screen differentially expressed ERGs in BC. Multivariate Cox regression analysis and Lasso regression analysis were used to construct and validate an ERGs-based prognostic prediction model for BC. Immunohistochemistry was used to detect the protein expression of hub gene-COL6A1 in BC patients. Using bioinformatics analysis from The Cancer Genome Atlas (TCGA) database and proteomic analysis from our BC cohort, we constructed and validated an effective prognostic prediction model for BC patients based on four differentially expressed ERGs (MAP1B, FBN1, COL6A1, and MFAP5). Moreover, we identified human collagen VI-COL6A1 was a hub gene in this prognostic prediction model and found that COL6A1 was closely related to malignancy progression, prognosis, and response to PD-1 inhibitor immunotherapy in BC. Our findings highlight the satisfactory predictive value of ECM-related prognostic models in BC and suggested that COL6A1 may be a potential biomarker in predicting malignant progression, prognosis, and efficacy of immunotherapy in BC.

A novel focal adhesion-related risk model predicts prognosis of bladder cancer —— a bioinformatic study based on TCGA and GEO database

Background

Bladder cancer (BLCA) is the ninth most common cancer globally, as well as the fourth most common cancer in men, with an incidence of 7%. However, few effective prognostic biomarkers or models of BLCA are available at present.

Methods

The prognostic genes of BLCA were screened from one cohort of The Cancer Genome Atlas (TCGA) database through univariate Cox regression analysis and functionally annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The intersecting genes of the BLCA gene set and focal adhesion-related gene were obtained and subjected to the least absolute shrinkage and selection operator regression (LASSO) to construct a prognostic model. Gene set enrichment analysis (GSEA) of high- and low-risk patients was performed to explore further the biological process related to focal adhesion genes. Univariate and multivariate Cox analysis, receiver operating characteristic (ROC) curve analysis, and Kaplan–Meier survival analysis (KM) were used to evaluate the prognostic model. DNA methylation analysis was presented to explore the relationship between prognosis and gene methylation. Furthermore, immune cell infiltration was assessed by CIBERSORT, ESTIMATE, and TIMER. The model was verified in an external GSE32894 cohort of the Gene Expression Omnibus (GEO) database, and the Prognoscan database presented further validation of genes. The HPA database validated the related protein level, and functional experiments verified significant risk factors in the model.

Results

VCL, COL6A1, RAC3, PDGFD, JUN, LAMA2, and ITGB6 were used to construct a prognostic model in the TCGA-BLCA cohort and validated in the GSE32894 cohort. The 7-gene model successfully stratified the patients into both cohorts’ high- and low-risk groups. The higher risk score was associated with a worse prognosis.

Conclusions

The 7-gene prognostic model can classify BLCA patients into high- and low-risk groups based on the risk score and predict the overall survival, which may aid clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10264-5.

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.

P4HA1 Regulates CD31 via COL6A1 in the Transition of Glioblastoma Stem-Like Cells to Tumor Endothelioid Cells

Glioblastoma multiforme (GBM) is a common intracranial malignancy characterized by abundant and aberrant vasculature. The efficiency of existing antivascular treatments remains unsatisfactory. The transition of glioblastoma stem-like cells (GSCs) into tumor endothelioid cells (ECs) has been thought to cause glioma neovascularization and anti-angiogenesis tolerance, but the mechanisms regulating glioma transdifferentiation remains unclear. Our previous study found that P4HA1 regulates GSCs vascular mimicry in a hypoxic microenvironment, but the detailed molecular mechanism has not been determined. In this study, candidate protein COL6A1 was screened by mass spectrometry. In vitro experiments show that P4HA1 regulates the expression of CD31 via COL6A1, with the levels of expression of P4HA1, COL6A1 and the vascular endothelial molecular markers CD31 showing positive correlations in vivo assay. Altering the expression of P4HA1 in GSCs altered the expression of COL6A1 and CD31, thereby inducing glioma angiogenesis. In conclusion, this study revealed that the P4HA1/COL6A1 axis modulates the transdifferentiation process of GSCs into ECs. Interrupting this signaling axis can inhibit glioma angiogenesis, suggesting that this axis may be a novel target for antivascular therapy in patients with glioma.

The role of network-forming collagens in cancer progression

Collagens are the main components of extracellular matrix in the tumor microenvironment. Both fibrillar and nonfibrillar collagens are involved in tumor progression. The nonfibrillar network-forming collagens such as type IV and type VIII collagens are frequently overexpressed in various types of human cancers, which promotes tumor cell proliferation, adhesion, invasion, metastasis and angiogenesis. Studies on the roles of these collagens have shed light on the mechanisms underpinning the effects of this protein family. Future research has to explicit the role of network-forming collagens with respect to cancer progression and treatment. Herein, we review the regulation of network-forming collagens expression in cancer; the roles of network-forming collagens in tumor invasion, metastasis and angiogenesis; and the clinical significance of network-forming collagens expression in cancer patients. This article is protected by copyright. All rights reserved.

Key genes associated with prognosis and metastasis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a tumor that frequently shows the hematogenous pathway and tends to be resistant to radiotherapy and chemotherapy. However, the exact mechanism of ccRCC metastasis remains unknown.

METHODS

Differentially expressed genes (DEGs) of three gene expression profiles (GSE85258, GSE105288 and GSE22541) downloaded from the Gene Expression Omnibus (GEO) database were analyzed by GEO2R analysis, and co-expressed DEGs among the datasets were identified using a Venn drawing tool. The co-expressed DEGs were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and hub genes were determined based on the protein-protein interaction network established by STRING. After survival analysis performed on UALCAN website, possible key genes were selected and verified in ccRCC cell lines and ccRCC tissues (n = 44). Statistical analysis was conducted using GraphPad Prism (Version 8.1.1).

RESULTS

A total of 104 co-expressed DEGs were identified in the three datasets. Pathway analysis revealed that these genes were enriched in the extracellular matrix (ECM)-receptor interaction, protein digestion and absorption and focal adhesion. Survival analysis on 17 hub genes revealed that four key genes with a significant impact on survival: procollagen C-endopeptidase enhancer (PCOLCE), prolyl 4-hydroxylase subunit beta (P4HB), collagen type VI alpha 2 (COL6A2) and collagen type VI alpha 3 (COL6A3). Patients with higher expression of these key genes had worse survival than those with lower expression. In vitro experiments revealed that the mRNA expression levels of PCOLCE, P4HB and COL6A2 were three times higher and that of COL6A3 mRNA was 16 times higher in the metastatic ccRCC cell line Caki-1 than the corresponding primary cell line Caki-2. Immunohistochemistry revealed higher expression of the proteins encoded by these four genes in metastatic ccRCC compared with tumors from the corresponding primary sites, with statistical significance.

CONCLUSION

PCOLCE, P4HB, COL6A2 and COL6A3 are upregulated in metastatic ccRCC and might be related to poor prognosis and distant metastases.

A Five Collagen-Related Gene Signature to Estimate the Prognosis and Immune Microenvironment in Clear Cell Renal Cell Cancer

Collagen is the main component of the extracellular matrix (ECM) and might play an important role in tumor microenvironments. However, the relationship between collagen and clear cell renal cell cancer (ccRCC) is still not fully clarified. Hence, we aimed to establish a collagen-related signature to predict the prognosis and estimate the tumor immune microenvironment in ccRCC patients. Patients with a high risk score were often correlated with unfavorable overall survival (OS) and an immunosuppressive microenvironment. In addition, the collagen-related genetic signature was highly correlated with clinical pathological features and can be considered as an independent prognostic factor in ccRCC patients. Moreover, GSEA results show that patients with a high risk grade tend to be associated with epithelial–mesenchymal junctions (EMT) and immune responses. In this study, we developed a collagen-related gene signature, which might possess the potential to predict the prognosis and immune microenvironment of ccRCC patients and function as an independent prognostic factor in ccRCC.

The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma Determines Cancer Associated Fibroblast Growth

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and is often caused by mutations in the oxygen-sensing machinery of kidney epithelial cells. Due to its pseudo-hypoxic state, ccRCC recruits extensive vasculature and other stromal components. Conventional cell culture methods provide poor representation of stromal cell types in primary cultures of ccRCC, and we hypothesized that mimicking the extracellular environment of the tumor would promote growth of both tumor and stromal cells. We employed proteomics to identify the components of ccRCC extracellular matrix (ECM) and found that in contrast to healthy kidney cortex, laminin, collagen IV, and entactin/nidogen are minor contributors. Instead, the ccRCC ECM is composed largely of collagen VI, fibronectin, and tenascin C. Analysis of single cell expression data indicates that cancer-associated fibroblasts are a major source of tumor ECM production. Tumor cells as well as stromal cells bind efficiently to a nine-component ECM blend characteristic of ccRCC. Primary patient-derived tumor cells bind the nine-component blend efficiently, allowing to us to establish mixed primary cultures of tumor cells and stromal cells. These miniature patient-specific replicas are conducive to microscopy and can be used to analyze interactions between cells in a model tumor microenvironment.

Identification of differentially expressed genes using microarray analysis and COL6A1 induction of bone metastasis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a major cause of cancer-associated mortality worldwide, and bone metastasis is the most prevalent event observed in patients with advanced NSCLC. However, the pathogenesis of bone metastases has not been fully elucidated. In the present study, differentially expressed genes (DEGs) were identified by gene expression microarray analysis of NSCLC tissue samples with or without bone metastases. Subsequently, collagen type 6A1 (COL6A1) was chosen as the target gene through Ingenuity Pathway Analysis and reverse transcription-quantitative (RT-q) PCR validation of the top eight DEGs. COL6A1 was overexpressed or knocked down, and the proliferation and invasion of NSCLC cells was assessed using Cell Counting Kit-8, colony formation and Transwell invasion assays. Additionally, the osteogenic capacity of HOB and hES-MP 002.5 cells was assessed using RT-qPCR, western blotting, Alizarin Red and alkaline phosphatase staining. A total of 364 DEGs were identified in NSCLC tissues with bone metastases compared with NSCLC tissues without bone metastases, including 140 upregulated and 224 downregulated genes. Gene Ontology analysis results demonstrated that the upregulated and downregulated genes were primarily enriched in 'cellular process', 'metabolic process' and 'biological regulation'. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the upregulated genes were primarily enriched in 'cysteine and methionine metabolism', 'oxidative phosphorylation' and 'ribosome', whereas the downregulated genes were primarily enriched in the 'transcriptional misregulation in cancer', 'ribosome' and 'mitophagy-animal' pathways. COL6A1 was highly expressed in NSCLC tissue samples with bone metastases. Functionally, COL6A1 overexpression induced the proliferation and invasion of HARA cells, and its knockdown inhibited the proliferation and invasion of HARA-B4 cells. Finally, it was demonstrated that HOB and hES-MP 002.5 cells exhibited osteogenic capacity, and overexpression of COL6A1 in HARA cells increased the adhesion of these cells to the osteoblasts, whereas knockdown of COL6A1 in HARA-B4 cells reduced their adhesive ability. In conclusion, COL6A1 may serve as a potential diagnostic marker and therapeutic target for bone metastasis in NSCLC.

Effect of Glucose Variability on Pancreatic Cancer Through Regulation of COL6A1

Background

Pancreatic cancer (PC), a devastating cancer worldwide, remains dismal prognosis due to its clinical elusiveness, especially in relation to diabetes mellitus (DM). The study aims to investigate the effect of glucose variability on COL6A1 in PC cancer cells and the prognostic potential of COL6A1 for PC patient associated with DM.

Methods

After PC cancer cell lines of AsPC-1 and BxPC-3 were treated with hyperglycemia and hypoglycemia, Giemsa staining and Transwell chamber were performed to assay plate clone formation, migration and invasion. Expressions of COL6A1 of PC cancer cell lines under different extracellular glucose levels were detected by qRT-PCR and Western blotting. The level of COL6A1 expression in PC patients with/without DM was further observed with immunohistochemistry. The prognostic impact of COL6A1 on PC patients with DM was assessed by Kaplan–Meier survival curve analysis.

Results

Hyperglycemia promoted proliferation, migration and invasion of PC cancer cells compared with hypoglycemia. Glucose variability could regulate expression of COL6A1 in PC cancer cells, both Col6a1 mRNA and COL6A1 protein upregulated in cancer cells cultured with hyperglycemic than that with hypoglycemic. The level of COL6A1 expression was higher in PC patients with DM than that without DM. Besides, COL6A1 was significantly associated with the clinical prognosis of PC patients with DM, higher COL6A1 leading to lower overall survival (OS).

Conclusion

Glucose variability had effect on PC cancer cells through regulation of COL6A1. Accordingly, COL6A1 was associated with poorer prognosis in PC patients with DM.

H3K27 acetylation activated-COL6A1 promotes osteosarcoma lung metastasis by repressing STAT1 and activating pulmonary cancer-associated fibroblasts

Background: Collagen type VI alpha 1 (COL6A1) has been found to be dysregulated in several human malignancies. However, the role of COL6A1 in osteosarcoma (OS) progression remains largely unclear. Here, we aimed to explore the clinical significance and biological involvement of COL6A1 in the OS cell migration and invasion. Material and Methods: We used immunohistochemistry, qRT-PCR and western blot to detect the expression of COL6A1 in 181 OS patient samples. Chromatin immunoprecipitation (ChIP) and PCR were carried out to verify the regulatory interaction of p300, c-Jun and COL6A1 promoter. The invasion and migration function of COL6A1 in OS was detected in vitro and in vivo. RNA sequence was performed to detect the downstream pathway of COL6A1, and then co-immunoprecipitation (co-IP), ubiquitination assays and rescue experiments were performed to determine the regulatory effect of COL6A1 and signal transducers and activators of transcription (STAT1). Exosomes derived from OS cell lines were assessed for the ability to promote cancer progression by co-cultured assay and exosomes tracing. Results: COL6A1 was commonly upregulated in OS tissues, especially in lung metastasis tissues, which was associated with a poor prognosis. c-Jun bound p300 increased the enrichment of H3K27ac at the promoter region of the COL6A1 gene, which resulted in the upregulation of COL6A1 in OS. Overexpression of COL6A1 promoted OS cell migration and invasion via interacting with SOCS5 to suppress STAT1 expression and activation in an ubiquitination and proteasomal degradation manner. Most interestingly, we found that exosomal COL6A1 derived from OS cells convert normal fibroblasts to cancer-associated fibroblasts (CAFs) by secreting pro-inflammatory cytokines, including IL-6 and IL-8. The activated CAFs could promote OS cell invasion and migration by mediating TGF-β/COL6A1 signaling pathway. Conclusion: Our data demonstrated that upregulation of COL6A1 activated by H3K27 acetylation promoted the cell migration and invasion by suppressing STAT1 pathway in OS cells. Moreover, COL6A1 can be packaged into OS cell-derived exosomes and activate CAFs to promote OS metastasis.

The role of COL6A1and PD-1 expressions in renal cell carcinoma

OBJECTIVE

The COL6A1 is a gene encoding the alpha 1 polypeptide subunit of collagen 6 (COL6A1), an extracellular matrix protein subunit. Programmed cell death receptor-1 (PD-1) and its ligand, programmed cell death receptor ligand-1 (PD-L1) have been shown to have a prognostic significance in clear cell renal cell carcinomas (RCCs). In this study, we evaluated the expressions of COL6A1 and PD-1 in four different RCC subtypes.

MATERIALS AND METHODS

A total of 161 radical nephrectomy and nephron-sparing surgery cases with RCCs from five different health care centers were included in this study. Clinical data of the cases were taken from electronic records of the institutions. The pathological data were collected by an expert uropathologist and re-evaluated with slides obtained from paraffin blocks of the cases. The correlation of COL6A1 and PD-1 expression with sex, age, tumor type, lymphovascular invasion (LVI), World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade, and tumor stage (pT) was analyzed with the Pearson chi-squared test.

RESULTS

Patients with sarcomatoid RCC and clear cell RCC had significantly higher COL6A1 scores and intensities than in other types of RCC (p=0.004 and p=0.002, respectively). WHO/ISUP grade and, COL6A1 and PD-1 staining scores also showed positive correlation (r=0.230, p=0.004 and r=0.277, p=0.001, respectively for COL6A1 and r=0.191, p=0.018 and r=0.166, p=0.041, respectively for PD-1). The staining scores and intensities of COL6A1 and PD-1 were not different between the patients with positive and negative LVI (p>0.05).

CONCLUSION

In high-grade RCCs, we found the relationship between immunohistochemical staining scores of COL6A1 and PD-1 proteins and clinical, demographic, and histopathological parameters. Our results proved that COL6A1 and PD-1 are really promising proteins as prognostic parameters and for targeted immunotherapy.

The clinical significance of collagen family gene expression in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a subtype of esophageal cancer with high incidence and mortality. Due to the poor 5-year survival rates of patients with ESCC, exploring novel diagnostic markers for early ESCC is emergent. Collagen, the abundant constituent of extracellular matrix, plays a critical role in tumor growth and epithelial-mesenchymal transition. However, the clinical significance of collagen genes in ESCC has been rarely studied. In this work, we systematically analyzed the gene expression of whole collagen family in ESCC, aiming to search for ideal biomarkers.

Methods

Clinical data and gene expression profiles of ESCC patients were collected from The Cancer Genome Atlas and the gene expression omnibus databases. Bioinformatics methods, including differential expression analysis, survival analysis, gene sets enrichment analysis (GSEA) and co-expression network analysis, were performed to investigate the correlation between the expression patterns of 44 collagen family genes and the development of ESCC.

Results

A total of 22 genes of collagen family were identified as differentially expressed genes in both the two datasets. Among them, COL1A1, COL10A1 and COL11A1 were particularly up-regulated in ESCC tissues compared to normal controls, while COL4A4, COL6A5 and COL14A1 were notably down-regulated. Besides, patients with low COL6A5 expression or high COL18A1 expression showed poor survival. In addition, a 7-gene prediction model was established based on collagen gene expression to predict patient survival, which had better predictive accuracy than the tumor-node-metastasis staging based model. Finally, GSEA results suggested that collagen genes might be tightly associated with PI3K/Akt/mTOR pathway, p53 pathway, apoptosis, cell cycle, etc.

Conclusion

Several collagen genes could be potential diagnostic and prognostic biomarkers for ESCC. Moreover, a novel 7-gene prediction model is probably useful for predicting survival outcomes of ESCC patients. These findings may facilitate early detection of ESCC and help improves prognosis of the patients.

COL6A1 knockdown suppresses cell proliferation and migration in human aortic vascular smooth muscle cells

Vascular smooth muscle cell (VSMC) migration is an important pathophysiological signature of neointimal hyperplasia. The aim of the present study was to investigate the effects of collagen type VI α1 chain (COL6A1) on VSMC migration. COL6A1 expression was silenced in platelet-derived growth factor (PDGF-BB)-stimulated VSMCs. Cell counting kit-8, wound healing and Transwell assays were used to measure cell viability, migration and invasion, respectively. Reverse transcription-quantitative PCR and western blot analysis were performed to analyze the expression of factors associated with metastasis. COL6A1 silencing attenuated PDGF-BB-induced increases in cell viability and invasive abilities of VSMCs, in addition to partially reversing the increased expression of fibronectin (FN), matrix metalloproteinase (MMP)-2 and MMP-9 induced by PDGF-BB stimulation. The silencing of COL6A also overturned PDGF-BB-induced reduction in tissue inhibitor of metalloproteinase 2 expression in VSMCs. PDGF-BB activated the AKT/mTOR pathway, which was also inhibited by COL6A1 knockdown. Taken together, these findings suggest that COL6A1 silencing inhibited VSMC viability and migration by inhibiting AKT/mTOR activation.

Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings

OBJECTIVES

To assess the potential of T1 mapping-based extracellular volume fraction (ECV) for the identification of higher grade clear cell renal cell carcinoma (cRCC), based on histopathology as the reference standard.

METHODS

For this single-center, institutional review board-approved prospective study, 27 patients (17 men, median age 62 ± 12.4 years) with pathologic diagnosis of cRCC (nucleolar International Society of Urological Pathology (ISUP) grading) received abdominal MRI scans at 1.5 T using a modified Look-Locker inversion recovery (MOLLI) sequence between January 2017 and June 2018. Quantitative T1 values were measured at different time points (pre- and postcontrast agent administration) and quantification of the ECV was performed on MRI and histological sections (H&E staining).

RESULTS

Reduction in T1 value after contrast agent administration and MR-derived ECV were reliable predictors for differentiating higher from lower grade cRCC. Postcontrast T1_diff values (T1_diff = T1 difference between the native and nephrogenic phase) and MR-derived ECV were significantly higher for higher grade cRCC (ISUP grades 3-4) compared with lower grade cRCC (ISUP grades 1-2) (p < 0.001). A cutoff value of 700 ms could distinguish higher grade from lower grade tumors with 100% (95% CI 0.69-1.00) sensitivity and 82% (95% CI 0.57-0.96) specificity. There was a positive and strong correlation between MR-derived ECV and histological ECV (p < 0.01, r = 0.88). Interobserver agreement for quantitative longitudinal relaxation times in the T1 maps was excellent.

CONCLUSIONS

T1 mapping with ECV measurement could represent a novel in vivo biomarker for the classification of cRCC regarding their nucleolar grade, providing incremental diagnostic value as a quantitative MR marker.

KEY POINTS

• Reduction in MRI T1 relaxation times after contrast agent administration and MR-derived extracellular volume fraction are useful parameters for grading of clear cell renal cell carcinoma (cRCC). • T1 differences between the native and the nephrogenic phase are higher for higher grade cRCC compared with lower grade cRCC and MRI-derived extracellular volume fraction (ECV) and histological ECV show a strong correlation. • T1 mapping with ECV measurement may be helpful for the noninvasive assessment of cRCC pathology, being a safe and feasible method, and it has potential to optimize individualized treatment options, e.g., in the decision of active surveillance.

Proteome profiling of clear cell renal cell carcinoma in von Hippel-Lindau patients highlights upregulation of Xaa-Pro aminopeptidase-1, an anti-proliferative and anti-migratory exoprotease

Patients of the von Hippel-Lindau (VHL) disease frequently develop clear cell renal cell carcinoma (ccRCC). Using archived, formalin-fixed, paraffin-embedded (FFPE) samples, we sought to determine global proteome alterations that distinguish ccRCC tissue from adjacent, non-malignant kidney tissue in VHL-patients. Our quantitative proteomic analysis clearly discriminated tumor and non-malignant tissue. Significantly dysregulated proteins were distinguished using the linear models for microarray data algorithm. In the ccRCC tissue, we noticed a predominant under-representation of proteins involved in the tricarboxylic acid cycle and an increase in proteins involved in glycolysis. This profile possibly represents a proteomic fingerprint of the "Warburg effect", which is a molecular hallmark of ccRCC. Furthermore, we observed an increase in proteins involved in extracellular matrix organization. We also noticed differential expression of many exoproteases in the ccRCC tissue. Of particular note were opposing alterations of Xaa-Pro Aminopeptidases-1 and -2 (XPNPEP-1 and -2): a strong decrease of XPNPEP-2 in ccRCC was accompanied by abundant presence of the related protease XPNPEP-1. In both cases, we corroborated the proteomic results by immunohistochemical analysis of ccRCC and adjacent, non-malignant kidney tissue of VHL patients. To functionally investigate the role of XPNPEP-1 in ccRCC, we performed small-hairpin RNA mediated XPNPEP-1 expression silencing in 786-O ccRCC cells harboring a mutated VHL gene. We found that XPNPEP-1 expression dampens cellular proliferation and migration. These results suggest that XPNPEP-1 is likely an anti-target in ccRCC. Methodologically, our work further validates the robustness of using FFPE material for quantitative proteomics.

Screening disrupted molecular functions and pathways associated with clear cell renal cell carcinoma using Gibbs sampling

OBJECTIVE

To explore the disturbed molecular functions and pathways in clear cell renal cell carcinoma (ccRCC) using Gibbs sampling.

METHODS

Gene expression data of ccRCC samples and adjacent non-tumor renal tissues were recruited from public available database. Then, molecular functions of expression changed genes in ccRCC were classed to Gene Ontology (GO) project, and these molecular functions were converted into Markov chains. Markov chain Monte Carlo (MCMC) algorithm was implemented to perform posterior inference and identify probability distributions of molecular functions in Gibbs sampling. Differentially expressed molecular functions were selected under posterior value more than 0.95, and genes with the appeared times in differentially expressed molecular functions ≥5 were defined as pivotal genes. Functional analysis was employed to explore the pathways of pivotal genes and their strongly co-regulated genes.

RESULTS

In this work, we obtained 396 molecular functions, and 13 of them were differentially expressed. Oxidoreductase activity showed the highest posterior value. Gene composition analysis identified 79 pivotal genes, and survival analysis indicated that these pivotal genes could be used as a strong independent predictor of poor prognosis in patients with ccRCC. Pathway analysis identified one pivotal pathway - oxidative phosphorylation.

CONCLUSIONS

We identified the differentially expressed molecular functions and pivotal pathway in ccRCC using Gibbs sampling. The results could be considered as potential signatures for early detection and therapy of ccRCC.

Expression of COL6A1 predicts prognosis in cervical cancer patients

COL6A1 has been shown to play an important role in tumor initiation and progression. The present study is to investigate the clinical significance of COL6A1 in cervical cancer. In this study, the COL6A1 expression levels in 10 paired cervical cancer tissues and the adjacent non-tumor tissues were examined by real-time PCR. The expression of COL6A1 protein was examined in 162 cervical cancer samples by immunohistochemistry, and the correlation of COL6A1 expression with clinicopathologic factors was analyzed. The overall and recurrent-free survival rates were estimated using Kaplan-Meier method and compared with the log-rank test. The prognostic analysis was carried out with multivariate Cox regressions model. The result showed that COL6A1 expression was up-regulated in cervical cancer tissues in compared with that in non-tumor tissues. High expression of COL6A1 was significantly correlated with FIGO stage (P<0.001), tumor size (P=0.025) and lymph node metastasis (P=0.028) of the disease. Moreover, survival analysis showed that high expression of COL6A1 was significantly associated with poorer overall (OS) and recurrent free (RFS) survival (p=0.004 and =0.001, respectively) of cervical cancer patients. Multivariate analysis suggested that COL6A1 expression was an independent prognostic marker of cervical cancer (P=0.029). Thus, COL6A1 may serve as an oncogene in the initiation and progression of cervical cancer, and as a predictor of poor prognosis in cervical cancer patients.

Twist1-induced activation of human fibroblasts promotes matrix stiffness by upregulating palladin and collagen α1(VI)

The transcription factor Twist1 is involved in the epithelial-mesenchymal transition and contributes to cancer metastasis through mostly unknown mechanisms. In colorectal cancer, Twist1 expression is mainly restricted to the tumor stroma. We found that human fibroblast cell lines stably transfected with Twist1 acquired characteristics of activated cancer-associated fibroblasts (CAFs), such as hyperproliferation, an increased ability to migrate and an alignment of the actin cytoskeleton. Further, Twist1-activated fibroblasts promoted increased matrix stiffness. Using quantitative proteomics, we identified palladin and collagen α1(VI) as two major mediators of the Twist1 effects in fibroblast cell lines. Co-immunoprecipitation studies indicated that palladin and Twist1 interact within the nucleus, suggesting that palladin could act as a transcription regulator. Palladin was found to be more relevant for the cellular biomechanical properties, orientation and polarity, and collagen α1(VI) for the migration and invasion capacity, of Twist1-activated fibroblasts. Both palladin and collagen α1(VI) were observed to be overexpressed in colorectal CAFs and to be associated with poor colorectal cancer patient survival and relapse prediction. Our results demonstrate that Twist1-expressing fibroblasts mimic the properties of CAFs present at the tumor invasive front, which likely explains the prometastatic activities of Twist1. Twist1 appears to require both palladin and collagen α1(VI) as downstream effectors for its prometastatic effects, which could be future therapeutic targets in cancer metastasis.