Zonal regulation of collagen-type proteins and posttranslational modifications in prostatic benign and cancer tissues by imaging mass spectrometry

Single-cell analysis extracted CAFs-related genes to established online app to predict clinical outcome and radiotherapy prognosis of prostate cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a significant role in regulating the clinical outcome and radiotherapy prognosis of prostate cancer (PCa). The aim of this study is to identify CAFs-related genes (CAFsRGs) using single-cell analysis and evaluate their potential for predicting the prognosis and radiotherapy prognosis in PCa.

METHODS

We acquire transcriptome and single-cell RNA sequencing (scRNA-seq) results of PCa and normal adjacent tissues from The GEO and TCGA databases. The "MCPcounter" and "EPIC" R packages were used to assess the infiltration level of CAFs and examine their correlation with PCa prognosis. ScRNA-seq and differential gene expression analyses were used to extract CAFsRGs. We also applied COX and LASSO analysis to further construct a risk score (CAFsRS) to assess biochemical recurrence-free survival (BRFS) and radiotherapy prognosis of PCa. The predictive efficacy of CAFsRS was evaluated by ROC curves and subgroup analysis. Finally, we integrated the CAFsRS gene signature with relevant clinical features to develop a nomogram, enhancing the predictive accuracy.

RESULTS

The abundance of CAFs is associated with a poor prognosis of PCa patients. ScRNA-seq and differential gene expression analysis revealed 323 CAFsRGs. After COX and LASSO analysis, we obtained seven CAFsRGs with prognostic significance (PTGS2, FKBP10, ENG, CDH11, COL5A1, COL5A2, and SRD5A2). Additionally, we established a risk score model based on the training set (n = 257). The ROC curve was used to confirm the performance of CAFsRS (The AUC values for 1, 3 and 5-year survival were determined to be 0.732, 0.773, and 0.775, respectively.). The testing set (n = 129), GSE70770 set (n = 199) and GSE116918 set (n = 248) revealed that the model exhibited exceptional predictive performance. This was also confirmed by clinical subgroup analysis. The violin plot demonstrated a statistically significant disparity in the CAFs infiltrations between the high-risk and low-risk groups of CAFsRS. Further analysis confirmed that both CAFsRS and T stage were independent prognostic factors for PCa. The nomogram was then established and its excellent predictive performance was demonstrated through calibration and ROC curves. Finally, we developed an online prognostic prediction app ( https://sysu-symh-cafsnomogram.streamlit.app/ ) to facilitate the practical application of the nomogram.

CONCLUSIONS

The prognostic prediction risk score model we constructed could accurately predict BRFS and radiotherapy prognosis PCa, which can provide new ideas for clinicians to develop personalized PCa treatment and follow-up programs.

Investigating the Role of SNAI1 and ZEB1 Expression in Prostate Cancer Progression and Immune Modulation of the Tumor Microenvironment

Prostate cancer (PCa) is an immunologically cold tumor and the molecular processes that underlie this behavior are poorly understood. In this study, we investigated a primary cohort of intermediate-risk PCa (n = 51) using two NanoString profiling panels designed to study cancer progression and immune response. We identified differentially expressed genes (DEGs) and pathways associated with biochemical recurrence (BCR) and clinical risk. Confirmatory analysis was performed using the TCGA-PRAD cohort. Noteworthy DEGs included collagens such as COL1A1, COL1A2, and COL3A1. Changes in the distribution of collagens may influence the immune activity in the tumor microenvironment (TME). In addition, immune-related DEGs such as THY1, IRF5, and HLA-DRA were also identified. Enrichment analysis highlighted pathways such as those associated with angiogenesis, TGF-beta, UV response, and EMT. Among the 39 significant DEGs, 11 (28%) were identified as EMT target genes for ZEB1 using the Harmonizome database. Elevated ZEB1 expression correlated with reduced BCR risk. Immune landscape analysis revealed that ZEB1 was associated with increased immunosuppressive cell types in the TME, such as naïve B cells and M2 macrophages. Increased expression of both ZEB1 and SNAI1 was associated with elevated immune checkpoint expression. In the future, modulation of EMT could be beneficial for overcoming immunotherapy resistance in a cold tumor, such as PCa.

Molecular analysis of the extracellular microenvironment: from form to function

The extracellular matrix (ECM) proteome represents an important component of the tissue microenvironment that controls chemical flux and induces cell signaling through encoded structure. The analysis of the ECM represents an analytical challenge through high levels of post-translational modifications, protease-resistant structures, and crosslinked, insoluble proteins. This review provides a comprehensive overview of the analytical challenges involved in addressing the complexities of spatially profiling the extracellular matrix proteome. A synopsis of the process of synthesizing the ECM structure, detailing inherent chemical complexity, is included to present the scope of the analytical challenge. Current chromatographic and spatial techniques addressing these challenges are detailed. Capabilities for multimodal multiplexing with cellular populations are discussed with a perspective on developing a holistic view of disease processes that includes both the cellular and extracellular microenvironment.

Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging

The integration of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with single cell spatial omics methods allows for a comprehensive investigation of single cell spatial information and matrisomal N-glycan and extracellular matrix protein imaging. Here, the performance of the antibody-directed single cell workflows coupled with MALDI-MSI are evaluated. Miralys™ photocleavable mass-tagged antibody probes (MALDI-IHC, AmberGen, Inc.), GeoMx DSP® (NanoString, Inc.), and Imaging Mass Cytometry (IMC, Standard BioTools Inc.) were used in series with MALDI-MSI of N-glycans and extracellular matrix peptides on formalin-fixed paraffin-embedded tissues. Single cell omics protocols were performed before and after MALDI-MSI. The data suggests that for each modality combination, there is an optimal order for performing both techniques on the same tissue section. An overall conclusion is that MALDI-MSI studies may be completed on the same tissue section as used for antibody-directed single cell modalities. This work increases access to combined cellular and extracellular information within the tissue microenvironment to enhance research on the pathological origins of disease.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Reviewing the Regulators of COL1A1

The collagen family contains 28 proteins, predominantly expressed in the extracellular matrix (ECM) and characterized by a triple-helix structure. Collagens undergo several maturation steps, including post-translational modifications (PTMs) and cross-linking. These proteins are associated with multiple diseases, the most pronounced of which are fibrosis and bone diseases. This review focuses on the most abundant ECM protein highly implicated in disease, type I collagen (collagen I), in particular on its predominant chain collagen type I alpha 1 (COLα1 (I)). An overview of the regulators of COLα1 (I) and COLα1 (I) interactors is presented. Manuscripts were retrieved searching PubMed, using specific keywords related to COLα1 (I). COL1A1 regulators at the epigenetic, transcriptional, post-transcriptional and post-translational levels include DNA Methyl Transferases (DNMTs), Tumour Growth Factor β (TGFβ), Terminal Nucleotidyltransferase 5A (TENT5A) and Bone Morphogenic Protein 1 (BMP1), respectively. COLα1 (I) interacts with a variety of cell receptors including integrinβ, Endo180 and Discoidin Domain Receptors (DDRs). Collectively, even though multiple factors have been identified in association to COLα1 (I) function, the implicated pathways frequently remain unclear, underscoring the need for a more spherical analysis considering all molecular levels simultaneously.

Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

Perspectives on pediatric congenital aortic valve stenosis: Extracellular matrix proteins, post translational modifications, and proteomic strategies

In heart valve biology, organization of the extracellular matrix structure is directly correlated to valve function. This is especially true in cases of pediatric congenital aortic valve stenosis (pCAVS), in which extracellular matrix (ECM) dysregulation is a hallmark of the disease, eventually leading to left ventricular hypertrophy and heart failure. Therapeutic strategies are limited, especially in pediatric cases in which mechanical and tissue engineered valve replacements may not be a suitable option. By identifying mechanisms of translational and post-translational dysregulation of ECM in CAVS, potential drug targets can be identified, and better bioengineered solutions can be developed. In this review, we summarize current knowledge regarding ECM proteins and their post translational modifications (PTMs) during aortic valve development and disease and contributing factors to ECM dysregulation in CAVS. Additionally, we aim to draw parallels between other fibrotic disease and contributions to ECM post-translational modifications. Finally, we explore the current treatment options in pediatrics and identify how the field of proteomics has advanced in recent years, highlighting novel characterization methods of ECM and PTMs that may be used to identify potential therapeutic strategies relevant to pCAVS.

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

Angiogenesis plays the critical roles in promoting tumor progression, aggressiveness, and metastasis. Although few studies have revealed some angiogenesis-related genes (ARGs) could serve as prognosis-related biomarkers for the prostate cancer (PCa), the integrated role of ARGs has not been systematically studied. The RNA-sequencing data and clinical information of prostate adenocarcinoma (PRAD) were downloaded from The Cancer Genome Atlas (TCGA) as discovery dataset. Twenty-three ARGs in total were identified to be correlated with prognosis of PRAD by the univariate Cox regression analysis, and a 19-ARG signature was further developed with significant correlation with the disease-free survival (DFS) of PRAD by the least absolute shrinkage and selection operator (LASSO) Cox regression with tenfold cross-validation. The signature stratified PRAD patients into high- and low-ARGs signature score groups, and those with high ARGs signature score were associated with significantly poorer outcomes (median DFS: 62.71 months vs unreached, p < 0.0001). The predicting ability of ARGs signature was subsequently validated in two independent cohorts of GSE40272 & PRAD_MSKCC. Notably, the 19-ARG signature outperformed the typical clinical features or each involved ARG in predicting the DFS of PRAD. Furthermore, a prognostic nomogram was constructed with three independent prognostic factors, including the ARGs signature, T stage and Gleason score. The predicted results from the nomogram (C-index = 0.799, 95%CI = 0.744-0.854) matched well with the observed outcomes, which was verified by the calibration curves. The values of area under receiver operating characteristic curve (AUC) for DFS at 1-, 3-, 5-year for the nomogram were 0.82, 0.83, and 0.83, respectively, indicating the performance of nomogram model is of reasonably high accuracy and robustness. Moreover, functional enrichment analysis demonstrated the potential targets of E2F targets, G2M checkpoint pathways, and cell cycle pathways to suppress the PRAD progression. Of note, the high-risk PRAD patients were more sensitive to immune therapies, but Treg might hinder benefits from immunotherapies. Additionally, this established tool also could predict response to neoadjuvant androgen deprivation therapy (ADT) and some chemotherapy drugs, such as cisplatin, paclitaxel, and docetaxel, etc. The novel ARGs signature, with prognostic significance, can further promote the application of targeted therapies in different stratifications of PCa patients.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

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.

An optimized MALDI MSI protocol for spatial detection of tryptic peptides in fresh frozen prostate tissue

MALDI MS imaging (MSI) is a powerful analytical tool for spatial peptide detection in heterogeneous tissues. Proper sample preparation is crucial to achieve high quality, reproducible measurements. Here we developed an optimized protocol for spatially resolved proteolytic peptide detection with MALDI time‐of‐flight MSI of fresh frozen prostate tissue sections. The parameters tested included four different tissue washes, four methods of protein denaturation, four methods of trypsin digestion (different trypsin densities, sprayers, and incubation times), and five matrix deposition methods (different sprayers, settings, and matrix concentrations). Evaluation criteria were the number of detected and excluded peaks, percentage of high mass peaks, signal‐to‐noise ratio, spatial localization, and average intensities of identified peptides, all of which were integrated into a weighted quality evaluation scoring system. Based on these scores, the optimized protocol included an ice‐cold EtOH+H₂O wash, a 5 min heating step at 95°C, tryptic digestion incubated for 17h at 37°C and CHCA matrix deposited at a final amount of 1.8 μg/mm². Including a heat‐induced protein denaturation step after tissue wash is a new methodological approach that could be useful also for other tissue types. This optimized protocol for spatial peptide detection using MALDI MSI facilitates future biomarker discovery in prostate cancer and may be useful in studies of other tissue types.

Evaluation of Therapeutic Collagen-Based Biomaterials in the Infarcted Mouse Heart by Extracellular Matrix Targeted MALDI Imaging Mass Spectrometry

The goal of this study was to develop strategies to localize human collagen-based hydrogels within an infarcted mouse heart, as well as analyze its impact on endogenous extracellular matrix (ECM) remodeling. Collagen is a natural polymer that is abundantly used in bioengineered hydrogels because of its biocompatibility, cell permeability, and biodegradability. However, without the use of tagging techniques, collagen peptides derived from hydrogels can be difficult to differentiate from the endogenous ECM within tissues. Imaging mass spectrometry is a robust tool capable of visualizing synthetic and natural polymeric molecular structures yet is largely underutilized in the field of biomaterials outside of surface characterization. In this study, our group leveraged a recently developed matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technique to enzymatically target collagen and other ECM peptides within the tissue microenvironment that are both endogenous and hydrogel-derived. Using a multimodal approach of fluorescence microscopy and ECM-IMS techniques, we were able to visualize and relatively quantify significantly abundant collagen peptides in an infarcted mouse heart that were localized to regions of therapeutic hydrogel injection sites. On-tissue MALDI MS/MS was used to putatively identify sites of collagen peptide hydroxyproline site occupancy, a post-translational modification that is critical in collagen triple helical stability. Additionally, the technique could putatively identify over 35 endogenously expressed ECM peptides that were expressed in hydrogel-injected mouse hearts. Our findings show evidence for the use of MALDI-IMS in assessing the therapeutic application of collagen-based biomaterials.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

Defining the Tumor Microenvironment by Integration of Immunohistochemistry and Extracellular Matrix Targeted Imaging Mass Spectrometry

Breast stroma plays a significant role in breast cancer risk and progression yet remains poorly understood. In breast stroma, collagen is the most abundantly expressed protein and its increased deposition and alignment contributes to progression and poor prognosis. Collagen post-translation modifications such as hydroxylated-proline (HYP) control deposition and stromal organization. The clinical relevance of collagen HYP site modifications in cancer processes remains undefined due to technical issues accessing collagen from formalin-fixed, paraffin-embedded (FFPE) tissues. We previously developed a targeted approach for investigating collagen and other extracellular matrix proteins from FFPE tissue. Here, we hypothesized that immunohistochemistry staining for fibroblastic markers would not interfere with targeted detection of collagen stroma peptides and could reveal peptide regulation influenced by specific cell types. Our initial work demonstrated that stromal peptide peak intensities when using MALD-IMS following IHC staining (αSMA, FAP, P4HA3 and PTEN) were comparable to serial sections of nonstained tissue. Analysis of histology-directed IMS using PTEN on breast tissues and TMAs revealed heterogeneous PTEN staining patterns and suggestive roles in stromal protein regulation. This study sets the foundation for investigations of target cell types and their unique contribution to collagen regulation within extracellular matrix niches.

Gene Expression Analysis Provides New Insights into the Mechanism of Intramuscular Fat Formation in Japanese Black Cattle

Japanese Black cattle (Japanese Wagyu) have a unique phenotype in which ectopic intramuscular fat accumulates in skeletal muscle, producing finely marbled beef. However, the mechanism of intramuscular fat formation in Japanese Black cattle remains unclear. To investigate the key genes involved in intramuscular fat accumulation, we comprehensively analyzed mRNA levels in subcutaneous and intramuscular fat tissues using RNA sequence (RNA-seq) analysis, which detected 27,606 genes. We identified eight key genes, namely carboxypeptidase E, tenascin C, transgelin, collagen type IV alpha 5 (COL4A5), cysteine and glycine-rich protein 2, PDZ, and LIM domain 3, phosphatase 1 regulatory inhibitor subunit 14A, and regulator of calcineurin 2. These genes were highly and specifically expressed in intramuscular fat tissue. Immunohistochemical analysis revealed a collagen network, including COL4A5, in the basement membrane around the intramuscular fat tissue. Moreover, pathway analysis revealed that, in intramuscular fat tissue, differentially expressed genes are related to cell adhesion, proliferation, and cancer pathways. Furthermore, pathway analysis showed that the transforming growth factor-β (TGF-β) and small GTPases regulators RASGRP3, ARHGEF26, ARHGAP10, ARHGAP24, and DLC were upregulated in intramuscular fat. Our study suggests that these genes are involved in intramuscular fat formation in Japanese Black cattle.

Mass Spectrometry Imaging of Fibroblasts: Promise and Challenge

INTRODUCTION

Fibroblasts maintain tissue and organ homeostasis through output of extracellular matrix that affects nearby cell signaling within the stroma. Altered fibroblast signaling contributes to many disease states and extracellular matrix secreted by fibroblasts has been used to stratify patient by outcome, recurrence, and therapeutic resistance. Recent advances in imaging mass spectrometry allow access to single cell fibroblasts and their ECM niche within clinically relevant tissue samples.

AREAS COVERED

We review biological and technical challenges as well as new solutions to proteomic access of fibroblast expression within the complex tissue microenvironment. Review topics cover conventional proteomic methods for single fibroblast analysis and current approaches to accessing single fibroblast proteomes by imaging mass spectrometry approaches. Strategies to target and evaluate the single cell stroma proteome on the basis of cell signaling are presented.

EXPERT OPINION

The promise of defining proteomic signatures from fibroblasts and their extracellular matrix niches is the discovery of new disease markers and the ability to refine therapeutic treatments. Several imaging mass spectrometry approaches exist to define the fibroblast in the setting of pathological changes from clinically acquired samples. Continued technology advances are needed to access and understand the stromal proteome and apply testing to the clinic.

Collagen fiber regulation in human pediatric aortic valve development and disease

Congenital aortic valve stenosis (CAVS) affects up to 10% of the world population without medical therapies to treat the disease. New molecular targets are continually being sought that can halt CAVS progression. Collagen deregulation is a hallmark of CAVS yet remains mostly undefined. Here, histological studies were paired with high resolution accurate mass (HRAM) collagen-targeting proteomics to investigate collagen fiber production with collagen regulation associated with human AV development and pediatric end-stage CAVS (pCAVS). Histological studies identified collagen fiber realignment and unique regions of high-density collagen in pCAVS. Proteomic analysis reported specific collagen peptides are modified by hydroxylated prolines (HYP), a post-translational modification critical to stabilizing the collagen triple helix. Quantitative data analysis reported significant regulation of collagen HYP sites across patient categories. Non-collagen type ECM proteins identified (26 of the 44 total proteins) have direct interactions in collagen synthesis, regulation, or modification. Network analysis identified BAMBI (BMP and Activin Membrane Bound Inhibitor) as a potential upstream regulator of the collagen interactome. This is the first study to detail the collagen types and HYP modifications associated with human AV development and pCAVS. We anticipate that this study will inform new therapeutic avenues that inhibit valvular degradation in pCAVS and engineered options for valve replacement.

Angiogenesis related gene expression significantly associated with the prognostic role of an urothelial bladder carcinoma

Background

Bladder urothelial carcinoma (BLCA) is still one of the most malignant diseases and has a dismal outcome. Angiogenesis has confirmed its critical role in the development of malignant neoplasms. In this study, we uncovered the prognostic implications of the angiogenesis-related gene panel in urothelial tumors.

Methods

The RNA-seq data and clinical records of 402 patients with BLCA were collected from the TCGA database. The panel, including 145 genes involved in angiogenesis, was retrieved from the Uniprot database and the published work. The patients with similar expressed profiles were clustered, and the differences in gene expression were compared. The correlation of gene expression and BLCA outcomes or clinical features were analyzed.

Results

There were two clusters of BLCA patients identified on the expressed basis of angiogenesis-related genes. A significant difference was detected in the tumor stages between the two clusters (P<0.001) and a striking advantaged prognosis shown in cluster_1 (86.83 vs. 27.06 months, P=0.001). According to statistics, 115 genes showed a discrepancy in expression between the two clusters, and 16 genes positively correlated to tumor stage progression. Separately analyzed the correlation of those stage-related genes and overall survivals (OS) revealed that high expression of 8 genes, including ECM1 (HR =1.72, P<0.001), FN1 (HR =1.564, P=0.004), FGF1 (HR =1.519, P=0.005), FAP (HR =1.449, P=0.020), JAM3 (HR =1.396, P=0.026), THBS1 (HR =1.402, P=0.028), MFGE8 (HR =1.394, P=0.028) and COL8A2 (HR =1.388, P=0.035), were showed worse prognosis of BLCA, respectively.

Conclusions

This study showed an integrated profile of angiogenesis-related genes and identified the different BLCA subgroups with favorable prognosis and poor prognosis depended on the expression pattern of angiogenesis-related genes. Furthermore, this work revealed the single gene expressions of ECM1, FN1, FGF1, FAP, JAM3, THBS1, MFGE8 and COL8A2 involved in angiogenesis associated the prognosis remarkably.