Overexpression of COL3A1 confers a poor prognosis in human bladder cancer identified by co-expression analysis

Unveiling Collagen's Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications

Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I-XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment.

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

A glimpse into let-7e roles in human disorders; friend or foe?

MicroRNAs (miRNAs) have been linked to abnormal expression and regulation in a number of diseases, including cancer. Recent studies have concentrated on miRNA Let-7e's significance in precision medicine for cancer screening and diagnosis as well as its prognostic and therapeutic potential. Differential let-7e levels in bodily fluids have the possibility to enable early detection of cancer utilizing less-invasive techniques, reducing biopsy-related risks. Although Let-7e miRNAs have been described as tumor suppressors, it is crucial to note that there exists proof to support their oncogenic activity in vitro and in in vivo. Let-7e's significance in chemo- and radiation treatment decisions has also been demonstrated. Let-7e can also prevent the synthesis of proinflammatory cytokines in a number of degenerative disorders, including musculoskeletal and neurological conditions. For the first time, an overview of the significance of let-7e in the prevention, detection, and therapy of cancer and other conditions has been given in the current review. Additionally, we focused on the specific molecular processes that underlie the actions of let-7e, more particularly, on malignant cells.

Col3a1 delivered via extracellular vesicles of Sertoli cells is essential for mice Sertoli cell proliferation

It is generally believed that Sertoli cells can proliferate only before sexual maturity. In this study, we found that extracellular vesicles of Sertoli cells derived from prepubertal mice (SEVs) have the ability to promote the proliferation of Sertoli cell population. In addition, via proteomic analysis, we compared the functional components of extracellular vesicles derived from Sertoli cells of mice at 12-14 days and 8 weeks. The functional profiling of SEVs suggested important developmental roles, and this was confirmed by analysis comparing the transcriptomic changes in Sertoli cells treated with DMSO and GW4869. The following analysis pointed to Col3a1 as a key factor in SEVs, which was further validated using primary Sertoli cells and TM4 cell line. The present study suggests a possible role for Col3a1 in promoting the proliferation of cultured Sertoli cells and provides a new perspective on the function of extracellular vesicles in Sertoli cell development.

Biological and therapeutic implications of RKIP in Gastrointestinal Stromal Tumor (GIST): an integrated transcriptomic and proteomic analysis

BACKGROUND

Gastrointestinal stromal tumors (GIST) represent a significant clinical challenge due to their metastatic potential and limited treatment options. Raf kinase inhibitor protein (RKIP), a suppressor of the MAPK signaling pathway, is downregulated in various cancers and acts as a metastasis suppressor. Our previous studies demonstrated low RKIP expression in GIST and its association with poor outcomes. This study aimed to expand on the previous findings and investigate the biological and therapeutic implications of RKIP loss on GIST.

METHODS

To validate the RKIP prognostic significance, its expression was evaluated by immunohistochemistry in 142 bona fide GIST cases. The functional role of RKIP was evaluated in vitro, using the GIST-T1 cell line, which was knocked out for RKIP. The biological and therapeutic implications of RKIP were evaluated by invasion, migration, apoptosis, and 2D / 3D viability assays. Additionally, the transcriptome and proteome of RKIP knockout cells were determined by NanoString and mass spectrometry, respectively.

RESULTS

Immunohistochemical analysis revealed the absence of RKIP in 25.3% of GIST cases, correlating with a tendency toward poor prognosis. Functional assays demonstrated that RKIP knockout increased GIST cells' invasion and migration potential by nearly 60%. Moreover, we found that RKIP knockout cells exhibited reduced responsiveness to Imatinib treatment and higher cellular viability in 2D and 3D in vitro models, as assessed by apoptosis-related protein expression. Through comprehensive genetic and proteomic profiling of RKIP knockout cells, we identified several putative RKIP-regulated proteins in GIST, such as COL3A1.

CONCLUSIONS

Using a multidimensional integrative analysis, we identified, for the first time in GIST, molecules and pathways modulated by RKIP that may potentially drive metastasis and, consequently, poor prognosis in this disease.

LGALS1 regulates cell adhesion to promote the progression of ovarian cancer

The present study aimed to explore the significance and molecular mechanisms of galectin-1 (LGALS1) in ovarian cancer (OC). Using the Gene Expression Omnibus database and The Cancer Genome Atlas database, the results of the present study demonstrated that LGALS1 mRNA expression was markedly increased in OC and associated with advanced tumor, lymphatic metastasis and residual lesions. In Kaplan-Meier analysis, patients who expressed LGALS1 highly had a poor prognosis. Furthermore, using The Cancer Genome Atlas database, differentially expressed genes that are potentially regulated by LGALS1 in OC were determined. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to build a biological network of upregulated differentially expressed genes. The results of the enrichment analysis revealed that the upregulated differentially expressed genes were primarily associated with 'ECM-receptor interaction', 'cell-matrix adhesion' and 'focal adhesion', which are closely associated with the metastasis of cancer cells. Subsequently, cell adhesion was selected for further analysis. The results demonstrated that LGALS1 was co-expressed with the candidate genes. Subsequently, the elevated expression levels of candidate genes were verified in OC tissues, and survival analysis indicated that high expression of candidate genes was associated with shortened overall survival of patients with OC. In the present study, OC samples were also collected to verify the high protein expression levels of LGALS1 and fibronectin 1. The results of the present study highlighted that LGALS1 may regulate cell adhesion and participate in the development of OC. Therefore, LGALS1 exhibits potential as a therapeutic target in OC.

Emerging role of mRNA methylation in regulating the hallmarks of cancer

The dynamic chemical modifications of DNA, RNA, and proteins can transform normal cells into malignant ones. While the DNA and protein modifications in cancer have been described extensively in the literature, there are fewer reports about the role of RNA modifications in cancer. There are over 100 forms of RNA modifications and one of these, mRNA methylation, plays a critical role in the malignant properties of the cells. mRNA methylation is a reversible modification responsible for regulating protein expression at the post-transcriptional level. Despite being discovered in the 1970s, a complete understanding of the different proteins involved and the mechanism behind mRNA methylation remains largely unknown. However, these mRNA methylations have been shown to foster cancer hallmarks via specific cellular targets inside the cell. In this review, we provide a brief overview of mRNA methylation and its emerging role in regulating the various hallmarks of cancer.

Identification of gene profiles related to the development of oral cancer using a deep learning technique

BACKGROUND

Oral cancer (OC) is a debilitating disease that can affect the quality of life of these patients adversely. Oral premalignant lesion patients have a high risk of developing OC. Therefore, identifying robust survival subgroups among them may significantly improve patient therapy and care. This study aimed to identify prognostic biomarkers that predict the time-to-development of OC and survival stratification for patients using state-of-the-art machine learning and deep learning.

METHODS

Gene expression profiles (29,096 probes) related to 86 patients from the GSE26549 dataset from the GEO repository were used. An autoencoder deep learning neural network model was used to extract features. We also used a univariate Cox regression model to select significant features obtained from the deep learning method (P < 0.05). High-risk and low-risk groups were then identified using a hierarchical clustering technique based on 100 encoded features (the number of units of the encoding layer, i.e., bottleneck of the network) from autoencoder and selected by Cox proportional hazards model and a supervised random forest (RF) classifier was used to identify gene profiles related to subtypes of OC from the original 29,096 probes.

RESULTS

Among 100 encoded features extracted by autoencoder, seventy features were significantly related to time-to-OC-development, based on the univariate Cox model, which was used as the inputs for the clustering of patients. Two survival risk groups were identified (P value of log-rank test = 0.003) and were used as the labels for supervised classification. The overall accuracy of the RF classifier was 0.916 over the test set, yielded 21 top genes (FUT8-DDR2-ATM-CD247-ETS1-ZEB2-COL5A2-GMAP7-CDH1-COL11A2-COL3A1-AHR-COL2A1-CHORDC1-PTP4A3-COL1A2-CCR2-PDGFRB-COL1A1-FERMT2-PIK3CB) associated with time to developing OC, selected among the original 29,096 probes.

CONCLUSIONS

Using deep learning, our study identified prominent transcriptional biomarkers in determining high-risk patients for developing oral cancer, which may be prognostic as significant targets for OC therapy. The identified genes may serve as potential targets for oral cancer chemoprevention. Additional validation of these biomarkers in experimental prospective and retrospective studies will launch them in OC clinics.

COL3A1: Potential prognostic predictor for head and neck cancer based on immune-microenvironment alternative splicing

We aimed to identify a novel prognostic biomarker for head and neck squamous cell carcinoma (HNSCC) based on tumor immunology-related alternative splicing (AS). Data for 502 HNSCC and 44 normal samples were obtained from the TCGA database and used to establish an AS-related risk model through univariate, least absolute shrinkage, and selection operator Cox regression analyses. Fresh HNSCC and normal oral tissues were surgically obtained from 44 HNSCC patients. Western blotting and quantitative reverse transcription-PCR were used to assess gene expression levels. Kaplan-Meier was performed to evaluate patients' overall survival (OS) rate. The CIBERSORT algorithm, single-sample gene set enrichment analysis, and immune checkpoint analyses were performed to compare immune activities between subgroups. The risk model was established using 10 pivotal AS events first. Collagen Type III Alpha 1 Chain (COL3A1) were screened based on |log2FC| ≥ 1 and FDR < 0.05 criteria. COL3A1 expression levels in HNSCC tissues were elevated relative to normal tissues (p < 0.001). Moreover, COL3A1 was a reliable biomarker for HNSCC patients' prognostic prediction in both cohorts (p < 0.001, p = 0.0085, respectively). COL3A1 protein (p = 0.0054) and mRNA (p < 0.0001) levels were correlated with HNSCC differentiation. Furthermore, the T stage was correlated with COL3A1 expression (p = 0.043), and COL3A1 expression was an independent prognostic predictor for HNSCC patients (p = 0.006). Compared with the risk model, COL3A1 was better at evaluating immune cell infiltrations, immune activities, and immune checkpoint gene expressions of HNSCC lesions.

Bioinformatics Identification of Therapeutic Gene Targets for Gastric Cancer

INTRODUCTION

The global prevalence of gastric cancer (GC) is increasing, and novel chemotherapeutic targets are needed.

METHODS

We searched for potential biomarkers for GC in three microarray data sets within the Gene Expression Omnibus (GEO) database. FunRich (v3.1.3) was used to perform Gene Ontology (GO) analyses and STRUN and Cytoscape (v3.6.0) were employed to construct a protein-protein interaction (PPI) network. To explore hub gene expression and survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier (KM) plotter. Drugs that were closely related to key genes were screened by the Gene Set Cancer Analysis (GSCA), and relevant correlations were verified experimentally. We validated that the sensitivity of a GC cell line to these drugs was correlated with fibrillin 1 (FBN1) mRNA expression levels.

RESULTS

We identified 83 upregulated and 133 downregulated differentially expressed genes (DEGs) and these were enriched with regards to their cellular component (extracellular and exosomes), molecular function (extracellular matrix structural constituent and catalytic activity), and biological process (cell growth and/or maintenance and metabolism). The biological pathways most prominently involved were epithelial-to-mesenchymal transition (EMT) and β3 integrin cell surface interactions. For the PPI network, we selected 10 hub genes, and 70% of these were significantly connected to poor overall survival (OS) in patients with GC. We found a significant link between the expression of FBN1 and two small molecule drugs (PAC-1 and PHA-793887).

CONCLUSIONS

Overall, we suggest that these hub genes can be used as biomarkers and novel targets for GC. FBN1 may be associated with drug resistance in gastric cancer.

Silencing of COL3A1 represses proliferation, migration, invasion, and immune escape of triple negative breast cancer cells via down-regulating PD-L1 expression

This study is designed to illuminate the specific role and underlying mechanism of collagen type III alpha 1 chain (COL3A1) in triple negative breast cancer (TNBC). Quantitative real-time polymerase chain reaction was applied to examine mRNA expression of COL3A1. Western blot analysis was employed to determine protein levels of COL3A1, programmed death ligand 1 (PD-L1), Bcl-2, and cleaved caspase-3. Immunohistochemistry staining was utilized for assessing protein expression of Ki67 and COL3A1 in tissues. The proliferous capacity of cells was assessed through CCK-8 assay and 5-Ethynyl-2'-deoxyuridine assay. Cell apoptosis and the percentage of CD8+ T cells were measured using flow cytometry. Migration and invasion of TNBC cells were examined via transwell assay. Lactate dehydrogenase (LDH) release was measured via a LDH assay kit. For establishing a xenograft tumor model, MDA-MB-231 cells were injected into the flank of mice through subcutaneous injection. COL3A1 expression was raised in TNBC tissues and cells, and it was inversely associated with overall survival data of TNBC patients. COL3A1 downregulation repressed proliferation, invasion, migration, and immune escape of TNBC cells along with tumor growth of xenograft mice. In TNBC cells and tumor tissues of mice, protein expression of PD-L1 was reduced by COL3A1 knockdown. COL3A1 knockdown-mediated inhibitory effects on cell proliferation, migration, invasion, and immune escape were reversed by PD-L1 upregulation in vitro. Silencing of COL3A1 exerted an antitumor role in TNBC, implying its potential as a therapeutic target for TNBC.

Vascular Ehlers-Danlos Syndrome: Pathological Variants, Recent Discoveries, and Theoretical Approaches

Vascular Ehlers-Danlos syndrome (vEDS) is a rare autosomal dominant genetic disorder. It is the most fatal among all types of EDS. In addition to typical EDS characteristics, vEDS patients are at risk of blood vessel rupture due to possession of pathogenic variants of the COL3A1 gene, which encodes type III collagen. Type III collagen is a major component of humans' vascular walls. The management of this disease is possible; however, there is no cure as of present. Recently, discoveries with potential impact on the management of vEDS have been elucidated. Mice with vEDS traits treated with a beta-blocker celiprolol showed significant improvements in their thoracic aorta biomechanical strength. Moreover, it has been demonstrated that the specifically designed small interference RNAs (siRNA) can effectively silence the pathogenic variant allele. To enhance the normal allele expression, an intracellularly expressed lysyl oxidase is shown to regulate the transcription rate of the COL3A1 promoter. Similarly, an embryonic homeobox transcription factor Nanog upregulates the wild-type COL3A1 expression through activation of the transforming growth factor-beta pathway, which increases type III collagen synthesis. Despite numerous advancements, more studies are to be performed to incorporate these discoveries into clinical settings, and eventually, more personalized treatments can be created.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

CDH1 overexpression predicts bladder cancer from early stage and inversely correlates with immune infiltration

Background

Bladder cancer (BC) seriously endangers public health, but effective biomarkers for BC diagnosis, particularly in the early stage, are still lacking. Identification of reliable biomarkers associated with early-stage BC is of great importance to early treatment and an improved outcome.

Methods

Differentially expressed genes (DEGs) were identified using four publicly available early-stage BC gene-expression profiles. Protein–protein interaction (PPI) and survival analysis for hub genes was evaluated. The correlation between methylation of genes and prognosis was evaluated using the MethSurv database. Co-expressed genes were explored using Cancer Cell Line Encyclopedia database and the corresponding expression were assessed in vitro. The competing endogenous RNA network and the immune cell infiltration in BC were generated using data of The Cancer Genome Atlas.

Results

Ten hub genes of the 213 integrated DEGs were identified, including CDH1, IGFBP3, PPARG, SDC1, EPCAM, ACTA2, COL3A1, TPM1, ACTC1, and ACTN1. CDH1 appeared to increase from tumor initiation stage and negatively correlated with methylation. Six methylated sites in CDH1 indicated a good prognosis and one site indicated an aberrant prognosis. High CDH1 expression was negatively correlated with infiltrations by most immune cells, such as plasmacytoid dendritic cells (pDCs), regulatory T cells, macrophages, neutrophils, DCs, and natural killer cells. CDH1 was highly positively correlated with EPCAM and appeared to be directly regulated by miR-383.

Conclusions

The identified oncogenic alterations provide theoretical support for the development of novel biomarkers to advance early-stage BC diagnosis and personalized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01103-7.

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

Simple Summary

Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology.

Abstract

Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.

Lysosomal-associated membrane protein family member 5 promotes the metastatic potential of gastric cancer cells

BACKGROUND

Metastatic gastric cancer (GC) has a poor prognosis, and elucidating the molecular mechanisms involved in metastasis may lead to the development of novel therapeutic modalities.

METHODS

Transcriptome analysis of surgically resected metastatic tissue from GC patients and noncancerous tissue was performed to identify novel metastasis-related genes. Analyses of in vitro cell function, apoptosis, the cell cycle and cancer stemness were performed using GC cell lines with a stable knockout of a candidate gene. In vivo percutaneous, peritoneal dissemination and liver metastasis xenograft models were also generated. PCR array and proteome analyses were performed. Expression of the candidate gene was analyzed in GC tissues from 300 patients.

RESULTS

Lysosomal Associated Membrane Protein Family Member 5 (LAMP5) was upregulated in the metastatic tissues. LAMP5 knockout significantly suppressed proliferation, invasion, and migration of GC cells and increased apoptosis, cell cycle arrest and cancer stemness. LAMP5 knockout virtually suppressed tumor growth in in vivo percutaneous, peritoneal dissemination and liver metastasis models. EMT- and autophagy-related genes were associated with LAMP5. High LAMP5 mRNA levels were significantly associated with a worse prognosis.

CONCLUSION

LAMP5 plays a vital role in metastasis formation and may be a promising novel target of drug development for metastatic GC in the future.

Investigation of the effects of overexpression of jumping translocation breakpoint (JTB) protein in MCF7 cells for potential use as a biomarker in breast cancer

Jumping translocation breakpoint (JTB) gene acts as a tumor suppressor or an oncogene in different malignancies, including breast cancer (BC), where it was reported as overexpressed. However, the molecular functions, biological processes and underlying mechanisms through which JTB protein causes increased cell growth, proliferation and invasion is still not fully deciphered. Our goal is to identify the functions of JTB protein by cellular proteomics approaches. MCF7 breast cancer cells were transfected with sense orientation of hJTB cDNA in HA, His and FLAG tagged CMV expression vector to overexpress hJTB and the expression levels were confirmed by Western blotting (WB). Proteins extracted from transfected cells were separated by SDS-PAGE and the in-gel digested peptides were analyzed by nano-liquid chromatography tandem mass spectrometry (nanoLC-MS/MS). By comparing the proteome of cells with upregulated conditions of JTB vs control and identifying the protein dysregulation patterns, we aim to understand the function of this protein and its contribution to tumorigenesis. Gene Set Enrichment Analysis (GSEA) algorithm was performed to investigate the biological processes and pathways that are associated with the JTB protein upregulation. The results demonstrated four significantly enriched gene sets from the following significantly upregulated pathways: mitotic spindle assembly, estrogen response late, epithelial-to-mesenchymal transition (EMT) and estrogen response early. JTB protein itself is involved in mitotic spindle pathway by its role in cell division/cytokinesis, and within estrogen response early and late pathways, contributing to discrimination between luminal and mesenchymal breast cancer. Thus, the overexpressed JTB condition was significantly associated with an increased expression of ACTNs, FLNA, FLNB, EZR, MYOF, COL3A1, COL11A1, HSPA1A, HSP90A, WDR, EPPK1, FASN and FOXA1 proteins related to deregulation of cytoskeletal organization and biogenesis, mitotic spindle organization, ECM remodeling, cellular response to estrogen, proliferation, migration, metastasis, increased lipid biogenesis, endocrine therapy resistance, antiapoptosis and discrimination between different breast cancer subtypes. Other upregulated proteins for overexpressed JTB condition are involved in multiple cellular functions and pathways that become dysregulated, such as tumor microenvironment (TME) acidification, the transmembrane transport pathways, glycolytic flux, iron metabolism and oxidative stress, metabolic reprogramming, nucleocytosolic mRNA transport, transcriptional activation, chromatin remodeling, modulation of cell death pathways, stress responsive pathways, and cancer drug resistance. The downregulated proteins for overexpressed JTB condition are involved in adaptive communication between external and internal environment of cells and maintenance between pro-apoptotic and anti-apoptotic signaling pathways, vesicle trafficking and secretion, DNA lesions repair and suppression of genes involved in tumor progression, proteostasis, redox state regulation, biosynthesis of macromolecules, lipolytic pathway, carbohydrate metabolism, dysregulation of ubiquitin-mediated degradation system, cancer cell immune escape, cell-to-cell and cell-to-ECM interactions, and cytoskeletal behaviour. There were no significantly enriched downregulated pathways.

Bioinformatics Analysis and Identification of Potential Genes Associated with Pathogenesis and Prognosis of Gastric Cancer

OBJECTIVE

Gastric cancer (GC) is a deadly cancer and a challenging public health problem globally. This study aimed to analyze potential genes associated with pathogenesis and prognosis of gastric cancer.

METHODS

This work selected the overlapping differentially expressed genes (DEGs) in GC from four datasets, the GSE29272, GSE29998, GSE54129 and GSE118916 Gene Expression Omnibus databases. These DEGs were used to carry out comprehensive bioinformatic analysis to analyze the related functions and pathways enriched, the relative expression levels and immune infiltrates, the prognostic characteristics and the interaction network.

RESULTS

In total, 55 DEGs increased while 98 decreased in their expression levels. For those DEGs with increased expression, they were mostly concentrated on "focal adhesion" and "ECM-receptor interaction", whereas DEGs with decreased expression were mostly associated with "gastric acid secretion" and "drug metabolism cytochrome P450". MCODE and ClueGO results were then integrated to screen 10 hub genes, which were FN1, COL1A1, COL3A1, BGN, TIMP1, COL1A2, LUM, VCAN, COL5A2 and SPP1. Survival analysis revealed that higher expression of the ten hub genes significantly predicted lower overall survival of GC patients. TIMP1 was most significantly related to neutrophils, CD8⁺ T cells, as well as dendritic cells, while LUM was most significantly related to macrophages.

CONCLUSION

Immunohistochemistry results and functional testing showed that the expression of COL5A2 was elevated in GC and that it might be a key gene in GC tumorigenesis.

P3H4 and PLOD1 expression associates with poor prognosis in bladder cancer

PURPOSE

The prolyl 3-hydroxylase family member 4 gene (P3H4) is involved in the development of human cancers. The association of P3H4 with bladder cancer (BC) prognosis is unclear. This study aimed to analyze the association of P3H4 with BC prognosis.

METHODS

RNA-Seq data were downloaded from The Cancer Genome Atlas project and BC microarray datasets (GSE13507, GSE31684, and GSE32548) were downloaded from the Gene Expression Omnibus database. We analyzed the differences in P3H4 expression levels between BC tumors and non-tumor tissues and between samples with different clinical information. The association of P3H4 and P3H4-related genes with BC prognosis and the possibility of using P3H4 expression as a prognostic biomarker in BC patients were also analyzed. RevMan was used to perform the meta-analysis.

RESULTS

P3H4 was upregulated in BC tissues compared with the adjacent non-tumor tissues (p = 4.06e-08). Univariate Cox regression analysis and meta-analysis showed that high P3H4 expression level contributed to a poor BC prognosis (Hazard ratio, HR = 1.348, 95% CI 1.140-1.594, p = 4.89e-04; meta-analysis: HR = 1.45, 95% CI 1.10-1.91; p = 9.00e-03). Among the genes related to P3H4, the PLOD1 gene was closely associated with P3H4 expression (r = 0.620, p = 2.49e-44). Also, a meta-analysis showed that PLOD1 expression was associated with a poor prognosis in BC patients (HR = 1.77, 95% CI 1.31-2.38; p = 2.00e-04).

CONCLUSIONS

The P3H4 and PLOD1 genes might be used as reliable prognostic biomarkers for BC.

Prognostic signatures associated with high infiltration of Tregs in bone metastatic prostate cancer

Metastatic cancer especially bone metastasis (BM) is the lethal end-stage of castration-resistant prostate cancer (CRPC). To understand the possible molecular mechanisms underlying the development of the distant metastasis is of potential clinical value. We sought to identify differentially expressed genes between patient-matched primary and bone metastatic CRPC tumors. Functional enrichment, protein-protein interaction networks, and survival analysis of DEGs were performed. DEGs with a prognostic value considered as candidate genes were evaluated, followed by genetic analysis of tumor infiltrating immune cells based on Wilcoxon test and immunofluorescence identification. Expression profiles analysis showed that 381 overlapping genes were screened as differentially expressed genes (DEGs), of which 16 DEGs were randomly selected to be validated and revealed that most of these genes showed a transcriptional profile similar to that seen in the datasets (Pearson’s r = 0.76). Six core genes were found to be involved in regulation of extracellular matrix receptor interaction and chemotactic activity, and four of them were significantly correlated with the survival of PCa patients with bone metastases. Immune infiltration analysis showed that the expressions levels of COL3A1, RAC1, FN1, and SDC2 in CD4+T cells were significantly higher than those in tumor cells, especially regulatory T cell infiltration was significantly increased in BM tumors. We analyzed gene expression signatures specifically associated with the development of bone metastases of CRPC patients. Characterization of genes associated with BM of mCRPC is critical for identification of predictive biomarkers and potential therapeutic targets.

Cadmium cytotoxicity and possible mechanisms in human trophoblast HTR-8/SVneo cells

The accumulation of cadmium (Cd) in the human body through food chain can lead to adverse pregnancy outcomes. In this study, Cd cytotoxicity and its mechanisms in HTR-8/SVneo cells were investigated. Cd disrupted the cellular submicrostructure and inhibited the cell viability in a time- and dose-dependent manner. The levels of reactive oxygen species, malondialdehyde content, and the activities of glutathione peroxidase (GSH-Px) and total superoxode dismutase (T-SOD) were concentration-dependently increased by Cd. In addition, Cd dose-dependently inducedcell apoptosis and decreased cell migration and invasion capacities. Finally, Cd significantly upregulated all the genes related to oxidative stress (SOD1, ROS1, and HSPA6), inflammatory response, cell cycle, apoptosis, and migration and invasion. This study will provide insights into the prevention and treatment of pregnancy-related diseases caused by Cd intoxication.

miR-29a-3p-dependent COL3A1 and COL5A1 expression reduction assists sulforaphane to inhibit gastric cancer progression

The antitumor properties of cruciferous vegetables are mainly due to their high content of isothiocyanates, and sulforaphane (SFA) is the most well-known compound. The aim of this study was to determine the mechanism of SFA inhibiting gastric cancer (GC) progression. After verifying SFA suppressing GC growth in vivo, we utilized the GSE79973 and GSE118916 datasets to identify the GC development signatures that overlap with the RNA-seq analysis in SFA-treated AGS cells. GSEA of the RNA-seq data indicated that SFA regulation of GC progression was related to extracellular matrix and collagens; thus, we identified COL3A1 and COL5A1 as the targets of SFA, which functioned as oncogenes. We found positive correlations between COL3A1 and COL5A1 expression in GC cells, and confirmed that miR-29a-3p is the common regulator of their expression. RNA immunoprecipitation assays based on Ago2, Dicer, and exportin-5 showed that SFA could promote mature miR-29a-3p generation. We also proved that SFA inactivated the Wnt/β-catenin pathway in GC cells in a miR-29a-3p-dependent manner. Overall, SFA boosts miR-29a-3p maturation to downregulate COL3A1 and COL5A1 and inactivate the Wnt/ β -catenin pathway to suppress GC progression.

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.

Cancer stem cell marker DCLK1 reprograms small extracellular vesicles toward migratory phenotype in gastric cancer cells

Doublecortin-like kinase 1 (DCLK1) is a putative cancer stem cell marker, a promising diagnostic and prognostic maker for malignant tumors and a proposed driver gene for gastric cancer (GC). DCLK1 overexpression in a majority of solid cancers correlates with lymph node metastases, advanced disease and overall poor-prognosis. In cancer cells, DCLK1 expression has been shown to promote epithelial-to-mesenchymal transition (EMT), driving disruption of cell-cell adhesion, cell migration and invasion. Here, we report that DCLK1 influences small extracellular vesicle (sEV/exosome) biogenesis in a kinase-dependent manner. sEVs isolated from DCLK1 overexpressing human GC cell line MKN1 (MKN1^OE -sEVs), promote the migration of parental (non-transfected) MKN1 cells (MKN1^PAR ). Quantitative proteome analysis of MKN1^OE -sEVs revealed enrichment in migratory and adhesion regulators (STRAP, CORO1B, BCAM, COL3A, CCN1) in comparison to MKN1^PAR -sEVs. Moreover, using DCLK1-IN-1, a specific small molecule inhibitor of DCLK1, we reversed the increase in sEV size and concentration in contrast to other EV subtypes, as well as kinase-dependent cargo selection of proteins involved in EV biogenesis (KTN1, CHMP1A, MYO1G) and migration and adhesion processes (STRAP, CCN1). Our findings highlight a specific role of DCLK1-kinase dependent cargo selection for sEVs and shed new light on its role as a regulator of signaling in gastric tumorigenesis.

Clear Cell Renal Carcinoma: MicroRNAs With Efficacy in Preclinical In Vivo Models

In order to identify new targets and treatment modalities for clear cell renal carcinoma, we surveyed the literature with respect to microRNAs involved in this disease. In this review, we have focused on up- and down-regulated miRs which mediate efficacy in preclinical clear-cell renal carcinoma-related in vivo models. We have identified 10 up-regulated and 33 down-regulated micro-RNAs according to this criterion. As proof-of-concept, micro-RNAs interfering with VEGF (miR-205p) and mTOR (mir-99a) pathways, which are modulated by approved drugs for this disease, have been identified. miRs targeting hypoxia induced factor-2α (HIF-2α) (miR-145), E3 ubiquitinylases speckle-type POZ protein (SPOP) (miR 520/372/373) and casitas B-lineage lymphoma (CBL) (miR-200a-3p), interfere with druggable targets. Further identified miRs interfere with cell-cycle dependent kinases, such as CDK2 (miR-200c), CDK4, 6 (miR-1) and CDK4, 9 (206c). Transmembrane receptor Ral interacting protein of 76 kD (RLIP76), targeted by mir-137, has emerged as another important target for ccRCC. Additional miRs and their targets merrying further preclinical validation are discussed.

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.

The prognostic value of cytokeratin and extracellular collagen expression in urinary bladder cancer

BACKGROUND

Expression levels of collagens have been implicated in the progression of various cancers and interact with cytokeratins, but are not well studied in bladder cancer (BC). Therefore, we analyzed the gene and protein expression levels of collagen 1A1 (Col1a1/COL1A1), collagen 3A1 (col3a1/COL3A1), collagen 5A2 (col5a2/COL5A2), cytokeratin 14 (krt14/CK14), and cytokeratin 17 (krt17/CK17) in urothelial BC samples of different stages.

METHODS

In total, 102 fresh frozen and 190 formalin fixed and paraffin embedded (FFPE) samples were tested using immunohistochemistry and RT-qPCR. Expression levels were correlated to clinicopathological and follow-up data.

RESULTS

Col1a1, col3a1, col5a2 and krt14 mRNA levels were significantly overexpressed in high-grade and muscle-invasive BC (MIBC) compared to low-grade and non-muscle invasive BC (NMIBC) cases. Disease-specific survival (DSS) was shorter in patients with high expression levels of col1a1 (p = 0.004), col3a1 (p = 0.004), and col5a2 (p = 0.028). CK14 (p = 0.020), COL3A1 (p = 0.006) and Col5A2 (p = 0.006) protein expression levels were significantly higher and protein expression levels of CK17 (p = 0.05) significantly lower in MIBC compared to NMIBC. Furthermore, CK14 (p = 0.002) and COL5A2 (p = 0.006) protein expressions were significantly higher in high-grade compared to low-grade BC. DSS was shorter in patients with high expression levels of COL5A2 (p = 0.033) and CK14 (p = 0.042).

CONCLUSION

Expression changes of collagens and cytokeratins are univariable prognostic markers in BC.

Targeting the tumor microenvironment in cholangiocarcinoma: implications for therapy

Introduction: Cholangiocarcinoma (CCA) is a rare, deadly cancer that is characterized by an abundant desmoplastic stroma. Late diagnoses and limited available effective treatments are major problems with this malignancy. Targeting of the tumor microenvironment (TME) has emerged as a potential therapeutic strategy.Areas covered: In this review, we describe the role of the various compartments of the TME in CCA and focus on the preclinical rationale for the development of innovative therapies. Relevant literature was identified by a PubMed search covering the last decade (2010-2020).Expert opinion: Low efficacy of surgery and cytotoxic chemotherapy emphasizes the need for new therapeutic strategies and companion biomarkers. Single-cell RNA sequencing of the stroma is yielding a critical functional characterization of TME in CCA and is paving the way for immunotherapies and cancer-associated fibroblast and extracellular matrix-oriented treatments. We believe that the development of treatments targeting the components of the TME will produce the best results if in combination with cytotoxic chemotherapy. Biomarkers should be developed to define the patient population of interest for each combination strategy.

Prognostic Impact of let-7e MicroRNA and Its Target Genes in Localized High-Risk Intestinal GIST: A Spanish Group for Research on Sarcoma (GEIS) Study

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level, and they have been described as being associated with tumor prognosis. Here, miRNA profiling was planned to explore new molecular prognostic biomarkers in localized intestinal high-risk GIST. Paraffin tumor blocks of 14 and 86 patients were used in the discovery and expansion sets, respectively. GeneChip miRNA v3.0 was employed to identify the miRNAs differentially expressed between relapsed and non-relapsed patient samples, which were validated in the expansion set, by qRT-PCR. RT2 Profiler PCR Array was used for the screening of let-7e targets. Expression levels were correlated with relapse-free survival and overall survival. In the discovery set, 39 miRNAs were significantly deregulated, let-7e and miR-550 being the most underexpressed and overexpressed miRNAs in the relapsed group, respectively. In the expansion set, the underexpression of let-7e or the overexpression of 4 of its target genes (ACVR1B, CASP3, COL3A1, and COL5A2) were statistically associated with worse relapse-free survival. The expression of let-7e and 4 of its target genes are potential prognostic biomarkers in high-risk localized intestinal GIST. The expression of these genes is a potential molecular tool useful for a more accurate prognosis in this subset of GIST patients.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.

Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes

As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficult to cure. However, the advent of precision medicine provides an opportunity to improve the treatment of lung cancer. Subtyping lung cancer plays an important role in performing a specific treatment. Here, we developed a framework that combines k-means clustering, t-test, sensitivity analysis, self-organizing map (SOM) neural network, and hierarchical clustering methods to classify LUAD into four subtypes. We determined that 24 differentially expressed genes could be used as therapeutic targets, and five genes (i.e., RTKN2, ADAM6, SPINK1, COL3A1, and COL1A2) could be potential novel markers for LUAD. Multivariate analysis showed that the four subtypes could serve as prognostic subtypes. Representative genes of each subtype were also identified, which could be potentially targetable markers for the different subtypes. The function and pathway enrichment analyses of these representative genes showed that the four subtypes have different pathological mechanisms. Mutations associated with the subtypes, e.g., epidermal growth factor receptor (EGFR) mutations in subtype 4 and tumor protein p53 (TP53) mutations in subtypes 1 and 2, could serve as potential markers for drug development. The four subtypes provide a foundation for subtype-specific therapy of LUAD.

Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

Background

Gastric cancer is one of the most common malignant cancers worldwide. Despite substantial developments in therapeutic strategies, the five-year survival rate remains low. Therefore, novel biomarkers and therapeutic targets involved in the progression of gastric tumors need to be identified.

Methods

We obtained the mRNA microarray datasets GSE65801, GSE54129 and GSE79973 from the Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to analyze DEG pathways and functions, and the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape to obtain the protein-protein interaction (PPI) network. Next, we validated the hub gene expression levels using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA), and conducted stage expression and survival analysis.

Results

From the three microarray datasets, we identified nine major hub genes: COL1A1, COL1A2, COL3A1, COL5A2, COL4A1, FN1, COL5A1, COL4A2, and COL6A3.

Conclusion

Our study identified COL1A1 and COL1A2 as potential gastric cancer prognostic biomarkers.

A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

BACKGROUND

Prostate cancer (PCa) is the second leading cause of cancer death in men in 2018. Thus, the evaluation of prognosis is crucial for clinical treatment decision of human PCa patients. We aim to establishing an effective and reliable model to predict the outcome of PCa patients.

METHODS

We first identified differentially expressed genes between prostate cancer and normal prostate in TCGA-PRAD and then performed WGCNA to initially identify the candidate Gleason score related genes. Then, the candidate genes were applied to construct a LASSO Cox regression analysis model. Numerous independent validation cohorts, time-dependent receiver operating characteristic (ROC), univariate cox regression analysis, nomogram were used to test the effectiveness, accuracy and clinical utility of the prognostic model. Furthermore, functional analysis and immune cells infiltration were performed.

RESULTS

Gleason score-related differentially expressed candidates were identified and used to build up the outcome model in TCGA-PRAD cohort and was validated in MSKCC cohort. We found the 3-gene outcome model (CDC45, ESPL1 and RAD54L) had good performance in predicting recurrence free survival, metastasis free survival and overall survival of PCa patients. Time-dependent ROC and nomogram indicated an ideal predictive accuracy and clinical utility of the outcome model. Moreover, outcome model was enriched in 28 pathways by GSVA and GSEA. In addition, the risk score was positively correlated with memory B cells, native CD4 T cells, activated CD4 memory T cells and eosinophil, and negatively correlated with plasma cells, resting CD4 memory T cells, resting mast cells and neutrophil.

CONCLUSIONS

In summary, our outcome model proves to be an effective prognostic model for predicting the risk of prognosis in PCa.

Functional and genomic characterization of three novel cell lines derived from a metastatic gallbladder cancer tumor

Background

Gallbladder cancer (GBC) is the most common tumor of the biliary tract. The incidence of GBC shows a large geographic variability, being particularly frequent in Native American populations. In Chile, GBC represents the second cause of cancer-related death among women. We describe here the establishment of three novel cell lines derived from the ascitic fluid of a Chilean GBC patient, who presented 46% European, 36% Mapuche, 12% Aymara and 6% African ancestry.

Results

After immunocytochemical staining of the primary cell culture, we isolated and comprehensively characterized three independent clones (PUC-GBC1, PUC-GBC2 and PUC-GBC3) by short tandem repeat DNA profiling and RNA sequencing as well as karyotype, doubling time, chemosensitivity, in vitro migration capability and in vivo tumorigenicity assay. Primary culture cells showed high expression of CK7, CK19, CA 19-9, MUC1 and MUC16, and negative expression of mesothelial markers. The three isolated clones displayed an epithelial phenotype and an abnormal structure and number of chromosomes. RNA sequencing confirmed the increased expression of cytokeratin and mucin genes, and also of TP53 and ERBB2 with some differences among the three cells lines, and revealed a novel exonic mutation in NF1. The PUC-GBC3 clone was the most aggressive according to histopathological features and the tumorigenic capacity in NSG mice.

Conclusions

The first cell lines established from a Chilean GBC patient represent a new model for studying GBC in patients of Native American descent.

Potential Salivary mRNA Biomarkers for Early Detection of Oral Cancer

We evaluated potential biomarkers in human whole saliva for the early diagnosis of oral squamous cell carcinoma (OSCC). We selected 30 candidate genes with relevance to cancer from recent reports in PubMed. Saliva samples were obtained from 34 non-tumor control and 33 OSCC patients. Real-time PCR was performed, and mRNA levels were compared. Normalized mRNA levels of six genes (NGFI-A binding protein 2 (NAB2), cytochrome P450, family 27, subfamily A, polypeptide 1 (CYP27A1), nuclear pore complex interacting protein family, member B4 (NPIPB4), monoamine oxidase B (MAOB), sialic acid acetyltransferase (SIAE), and collagen, type III, alpha 1 (COL3A1)) were significantly lower in saliva of OSCC patients. Receiver operating characteristics (ROC) analysis was used to individually evaluate the predictive power of the potential biomarkers for OSCC diagnosis. The area under the curve (AUC) values were evaluated for the OSCC vs. non-tumor groups via univariate ROC analyses, as well as multivariate ROC analyses of combinations of multiple potential biomarkers. The combination of CYP27A1 + SIAE showed a favorable AUC value of 0.84. When we divided saliva samples into two groups according to age using a 60-year cut-off, with OSCC patients and controls evaluated together, the AUC of MAOB-NAB2 was more predictive of OSCC in the under-60 group (AUC, 0.91; sensitivity, 0.92; and specificity, 0.86) than any other gene combination. These results are expected to aid the early diagnosis of OSCC, especially in patients under 60 years of age. While more studies with larger numbers of patients are necessary, our result suggest that salivary mRNA would be a potent biomarker for early OSCC diagnosis.

Integrated Analysis Revealed Prognostic Factors for Prostate Cancer Patients

BACKGROUND Prostate cancer (PCa) is one of the major causes of cancer-induced death among males. Here, we applied integrated bioinformatics analysis to identify key prognostic factors for PCa patients. MATERIAL AND METHODS The gene expression data were obtained from the UCSC Xena website. We calculated the differentially expressed genes between PCa tissues and normal controls. Pathway enrichment analyses found cell cycle-related pathways might play crucial roles during PCa tumorigenesis. The genes were assigned into 22 modules established via weighted gene co-expression network analysis (WGCNA). RESULTS The results indicated that the purple and red modules were obviously linked to the Gleason score, pathological N, pathological T, recurrence, and recurrence-free survival (RFS). In addition, Kaplan-Meier curve analysis found 8 modules were markedly correlated with RFS, serving as prognostic markers for PCa patients. Then, the hub genes in the most 2 critical modules (purple and red) were visualized by Cytoscape software. Pathway enrichment analyses confirmed the above findings that cell cycle-related pathways might play vital roles during PCa initiation and progression. Lastly, we randomly chose the PILRß (also termed PILRB) in the red module for clinical validation. The immunohistochemistry (IHC) results showed that PILRß was significantly increased in the high-risk PCa population compared with low-/middle-risk patients. CONCLUSIONS We used integrated bioinformatics approaches to identify hub genes that can serve as prognosis markers and potential treatment targets for PCa patients.

Identification of potential core genes in metastatic renal cell carcinoma using bioinformatics analysis

Most cases of mRCC without an early finding are not candidates for curative therapies, which may be one of the reasons for the poor patient prognosis. Therefore, candidate markers to diagnose the disease and treatment with high efficiency are urgently demanded. Three datasets of mRNA microarray have been assessed to discover DEGs between tissues from metastatic RCC and RCC. 111 DEGs in total were identified according to the expression profile result of genes in the database of GEO. Enrichment analyses for GO and KEGG have been conducted to reveal the interacting activities in the DEGs. A network of PPI has been established to reveal the interconnection among the DEGs, and we selected 10 hub genes. Subsequently, the disease-free survival rate and total survival rate analysis for the hub genes have been carried out with the method of Kaplan-Meier curve. RCC patients with CDH11, COL3A1, COL5A1, COL5A2, COL6A3 and COL11A1 alteration showed worse overall survival. Nonetheless, RCC patients with CDH11, COL3A1, COL5A1, COL5A2 and COL11A1 alteration showed worse disease-free survival. In the Jones Renal dataset, mRNA levels of 10 hub genes were associated with metastasis, and the gene expression level in patients with mRCC was higher than that in patients without metastasis. COL5A1, COL6A3 and COL11A1 expression levels were remarkably related to RCC patient survival rate using UALCAN. COL5A1, COL6A3 and COL11A1 were positively correlated with each other in RCC. These genes have been recognized as genes with clinical relevance, revealing that they might have important roles in carcinogenesis or development of mRCC.

Matrisome analysis of intrahepatic cholangiocarcinoma unveils a peculiar cancer-associated extracellular matrix structure

Background

Intrahepatic cholangiocarcinoma (iCCA) is a malignancy that arises from the intrahepatic biliary tree, showing high mortality rates due to its late clinical presentation and limited treatment options. iCCA is characterized by a dense, reactive desmoplastic stroma marked by a dramatic accumulation of extracellular matrix (ECM). Although recent results strongly suggest a relationship between increasing desmoplastic stroma and the enhanced malignant behaviour of iCCA, the importance of ECM proteins in the pathogenesis of iCCA still have to be addressed.

Methods

iCCA ECM fibrillar structural organization was characterized by histological analysis. ECM proteome profiles from decellularized iCCA and surrounding noncancerous tissues were analysed by nLC coupled to MALDI-TOF/TOF analysis.

Results

iCCA tissues displayed high levels of collagen fibers and low abundance of reticular and elastic fibers, suggesting stiffness and loss of polarity. The ECM proteome profiles of iCCA samples, when compared to those obtained from the surrounding noncancerous tissues showed a dismantling of the basement membrane, a reduced angiogenesis and a downregulation of oncosuppressive activity. In particular, we focused on the effects of the overexpression of collagen type III alpha 1 chain (COL3A1) in iCCA, thus providing evidences that COL3A1 promotes iCCA cells migration and is a component of tumor-associated aligned collagen.

Conclusions

Overall, this study contributes to the understanding of molecular basis underlying desmoplasia in iCCA and indicates the type III collagen as a promising therapeutic target.

Novel Biomarkers Associated With Progression and Prognosis of Bladder Cancer Identified by Co-expression Analysis

Our study's goal was to screen novel biomarkers that could accurately predict the progression and prognosis of bladder cancer (BC). Firstly, we used the Gene Expression Omnibus (GEO) dataset GSE37815 to screen differentially expressed genes (DEGs). Secondly, we used the DEGs to construct a co-expression network by weighted gene co-expression network analysis (WGCNA) in GSE71576. We then screened the brown module, which was significantly correlated with the histologic grade (r = 0.85, p = 1e-12) of BC. We conducted functional annotation on all genes of the brown module and found that the genes of the brown module were mainly significantly enriched in "cell cycle" correlation pathways. Next, we screened out two real hub genes (ANLN, HMMR) by combining WGCNA, protein-protein interaction (PPI) network and survival analysis. Finally, we combined the GEO datasets (GSE13507, GSE37815, GSE31684, GSE71576). Oncomine, Human Protein Atlas (HPA), and The Cancer Genome Atlas (TCGA) dataset to confirm the predict value of the real hub genes for BC progression and prognosis. A gene-set enrichment analysis (GSEA) revealed that the real hub genes were mainly enriched in "bladder cancer" and "cell cycle" pathways. A survival analysis showed that they were of great significance in predicting the prognosis of BC. In summary, our study screened and confirmed that two biomarkers could accurately predict the progression and prognosis of BC, which is of great significance for both stratification therapy and the mechanism study of BC.

Construction of a circular RNA-microRNA-messengerRNA regulatory network in stomach adenocarcinoma

OBJECTIVES

Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in cancer cells. However, the roles of competitive endogenous RNA (ceRNA) networks consisting of differentially expressed circRNAs (DECs), miRNAs, and messenger RNAs (mRNAs) in stomach adenocarcinoma (STAD) remain unclear. This study was performed to explore novel regulatory networks in STAD.

METHODS

The circRNA expression profiles, as well as miRNA and mRNA sequence data of STAD, were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), respectively. Candidates were identified to construct a network through a comprehensive bioinformatics strategy. The expression of hub-genes identified by protein-protein interactions (PPI) was validated by quantitative reverse transcription (RT) polymerase chain reaction.

RESULTS

A total of 51 DECs were identified in the GSE83521 and GSE89143 datasets of GEO. A total of 11 448 differentially expressed mRNAs (DEMs) and 458 differentially expressed miRNAs (DEMIs) were obtained by RNA sequencing of TCGA-STAD. Prediction by using five online databases (Cancer-Specific CircRNA, CircInteractome, miRTarBase, miRDB, and TargetScan) resulted in the selection of 6 DECs, 6 DEMIs, and 36 DEMs to establish a circRNA-miRNA-mRNA regulatory network based on the interactions of circRNA-miRNA and miRNA-mRNA. Through PPI analysis, four hub-genes (COL10A1, COL5A2, COL4A1, and COL3A1) were discovered. Moreover, overexpressions of COL10A1, COL5A1, and COL4A1 were associated with a poor overall survival rate of patients with STAD. On the basis of TNM staging, we found that the expressions of COL10A1, COL5A2, and COL3A1 in T2, T3, and T4 was significantly higher than in T1. Hub-genes expressions were validated in STAD tissues and cell lines.

CONCLUSIONS

Our study provides a novel perspective on the regulatory mechanism of STAD involving ceRNAs including DECs, DEMIs, and DEMs.

PPWD1 is associated with the occurrence of postmenopausal osteoporosis as determined by weighted gene co‑expression network analysis

Postmenopausal osteoporosis (PMO) is the most common type of primary osteoporosis (OP), a systemic skeletal disease. Although many factors have been revealed to contribute to the occurrence of PMO, specific biomarkers for the early diagnosis and therapy of PMO are not available. In the present study, a weighted gene co-expression network analysis (WGCNA) was performed to screen gene modules associated with menopausal status. The turquoise module was verified as the clinically significant module, and 12 genes (NUP133, PSMD12, PPWD1, RBM8A, CRNKL1, PPP2R5C, RBM22, PIK3CB, SKIV2L2, PAPOLA, SRSF1 and COPS2) were identified as ‘real’ hub genes in both the protein-protein interaction (PPI) network and co-expression network. Furthermore, gene expression analysis by microarray in blood monocytes from pre- and post-menopausal women revealed an increase in the expression of these hub genes in postmenopausal women. However, only the expression of peptidylprolyl isomerase domain and WD repeat containing 1 (PPWD1) was correlated with bone mineral density (BMD) in postmenopausal women. In the validation set, a similar expression pattern of PPWD1 was revealed. Functional enrichment analysis revealed that the fatty acid metabolism pathway was significantly abundant in the samples that exhibited a higher expression of PPWD1. Collectively, PPWD1 is indicated as a potential diagnostic biomarker for the occurrence of PMO.

Identification of biomarkers associated with progression and prognosis in bladder cancer via co-expression analysis

BACKGROUND

Bladder cancer is one of the most common genitourinary malignancies, with a high rate of recurrence and progression. The prognosis for patients with bladder cancer, especially muscle-invasive bladder cancer, remains poor despite systemic therapy.

OBJECTIVE

To explore the underlying disease mechanisms and identify more effective biomarkers for bladder cancer.

METHODS

Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were applied to identify hub genes correlated with the bladder cancer progression. Survival analyses were then conducted to identify potential biomarkers correlated with the prognosis of bladder cancer. Finally, validation and analysis of these potential biomarkers were conducted by a series of bioinformatics analyses.

RESULTS

Based on the results of weighted gene co-expression network analysis and protein-protein interaction network analysis, ten hub genes closely correlated with bladder cancer progression were identified in the relevant module. Survival analyses of these genes indicated that elevated expressions of six potential biomarkers (COL3A1, FN1, COL5A1, FBN1, COL6A1 and THBS2) were significantly associated with a worse overall survival. Furthermore, these 6 potential biomarkers were validated in association with the progression of bladder cancer. Bladder cancer samples with higher expression of these genes were most significantly enriched in gene set associated with ECM-receptor interaction.

CONCLUSIONS

This study identified several biomarkers associated with bladder cancer progression and prognosis. As novel findings, these may have important clinical implications for diagnosis, treatment and prognosis prediction.

A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival

Background

Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA.

Methods

Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA.

Results

WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models.

Conclusion

The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA.

miR-30b-5p acts as a tumor suppressor microRNA in esophageal squamous cell carcinoma

Background

To study miR-30b-5p expression in esophageal squamous cell carcinoma (ESCC) by comparisons between tumor tissues and matched adjacent non-cancerous tissues to elucidate the correlation between miR-30b-5p expression and ESCC clinical parameters, and to explore the signaling pathways associated with miR-30b-5p and key target genes.

Methods

Clinical data, cancer tissues, and adjacent non-cancerous tissues of 32 patients diagnosed with ESCC were collected from Taizhou Hospital of Zhejiang Province. The expression levels of miR-30b-5p were determined by real-time polymerase chain reaction (RT-PCR). mRNA data for ESCC tissues and normal tissues, and clinical materials of patients with ESCC were obtained from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA). Associations between miR-30b-5p expression and clinical features of patients with ESCC and overall survival were explored. A bioinformatics analysis was performed to determine the pathways and key miR-30b-5p targets associated with ESCC. Additionally, a cytological experiment was performed to evaluate the biological functions of miR-30b-5p. Finally, correlations between miR-30b-5p and key targets involved in PI3K/Akt signaling pathways were validated by western blotting.

Results

The expression level of miR-30b-5p in the 32 ESCC tissues was significantly lower than that in adjacent normal tissues (P<0.01) and was significantly disparate in the T stage, with higher expression in T1 than in T2 (P<0.05). Among the patients with higher expression levels of miR-30b-5p in ESCC tissues than in adjacent normal tissues, patients with higher expression of miR-30b-5p had a better prognosis (P<0.05). An analysis of gene chip data from the GEO database showed similar results. A gene enrichment analysis indicated a series of pathways that may be associated with the downregulation of miR-30b-5p, including focal adhesion, ECM-receptor interaction, and PI3K/Akt signaling pathways. Seven key target genes (PDGFRB, VIM, ITGA5, ACTN1, THBS2, SERPINE1, and RUNX2) were identified; these were found to be upregulated in ESCC tissues and were negatively correlated with miR-30b-5p. Functional experiments showed that miR-30b-5p attenuated migration (P<0.01) and invasion (P<0.05) in the Eca109 cell line. Moreover, the levels of ITGA5, PDGFRB, p-PI3K, and p-AKT, which are involved in the PI3K/Akt signaling pathway, were decreased in the miR-30b-5p-overexpressing Eca109 cell line.

Conclusions

Upregulated miR-30b-5p may inhibit migration and invasion in ESCC by targeting ITGA5, PDGFRB, and signaling pathways, such as PI3K/Akt, involved in ESCC regulation. Our results indicate that miR-30b-5p plays an important role in the occurrence and progression of ESCC and is a potential therapeutic target.

Cancer-associated methylated lncRNAs in patients with bladder cancer

Epigenetic modifications via DNA methylation and long non-coding RNAs (lncRNAs) have been identified in bladder cancer (BC). However, DNA methylation of lncRNAs involved in BC has not been elucidated. Here, DNA immunoprecipitation-sequencing (MeDIP-seq) and RNA-sequencing (RNA-seq) were carried out using eight paired tumor and adjacent normal tissue samples from patients with BC. Differences in methylation patterns between tumors and controls were compared and the percentage of differentially methylated genes, including lncRNA genes, was calculated. RNA-seq data were subjected to gene ontology (GO), Kyoto encyclopedia of genes, and genomes (KEGG) analysis. The association between DNA methylation modification and lncRNA expression was determined by pairwise analysis of MeDIP-seq and RNA-seq data. The most enriched motifs in the promoter region, as well as the methylated density in the 3 kb region surrounding super-enhancers of lncRNA genes, were analyzed. A peak of 5mC methylation in the region 2 kb upstream of the transcription start site (TSS), with the lowest point in the TSS region, was observed. In total, 436 and 239 genes were identified to be hyper and hypomethylated, respectively, in BC tissue around the TSS region. RNA-seq revealed differentially expressed lncRNAs between tumor and normal tissues, many of which were cancer-associated lncRNAs based on GO and KEGG pathway analysis. Combined MeDIP-seq and RNA-seq analysis revealed that expression of 26 lncRNAs were candidates of 5mC controlled genes. The possible link between 5mC modification and differential lncRNAs may relate to enrichment of 5mC reads in the region surrounding super-enhancers of lncRNA. Survival analysis indicated that the methylated lncRNA, LINC00574, was associated with shorter overall survival time in patients with BC (HR = 1.7, p-value = 0.035). Taken together, these findings indicate that lncRNAs genes are under control of DNA methylation. Methylated lncRNA genes, which are transcripted to LINC00574, may serve as biomarkers for BC prognosis.

Cytological effects of honokiol treatment and its potential mechanism of action in non-small cell lung cancer

PURPOSE

In this study, we aimed to explore key micro(mi)RNAs and their potential regulatory mechanisms induced by honokiol treatment in non-small cell lung cancer (NSCLC) cells.

METHODS

NSCLC A549 cells were treated with 0 (control) or 45 μM honokiol. Cell proliferation and migration were determined using CCK-8 and transwell assay, respectively, and apoptosis was determined using flow cytometry. RNA-sequencing was performed to detect the transcript expression levels. The differentially expressed miRNAs (DE-miRNAs) between the honokiol group and the control group were screened and analyzed for their functions and pathways. Then, protein-protein interaction (PPI) networks and miRNA-mRNA regulatory networks were constructed. In addition, survival analysis based on the key miRNAs was performed. Finally, the expression of the key miRNAs and their target genes were determined, and their effects on drug sensitivity were validated using their inhibitors.

RESULTS

Cell proliferation and migration were inhibited (P < 0.01), and the apoptosis rate was increased (P < 0.01) after honokiol treatment compared to that in the control group. A total of 26 upregulated and 20 downregulated DE-miRNAs were screened. DE-miRNAs were enriched in 10 pathways and 48 biological processes, such as the PI3K/AKT signaling pathway (involving miR-148a-3p). The miRNA-mRNA regulatory networks involved eight upregulated (including miR-148a-3p and let-7c-5p) and seven downregulated miRNAs (including miR-7-5p) and 190 target mRNAs. Survival analysis revealed that let-7c-5p, miR-148a-3p, and miR-148a-5p levels correlated with NSCLC prognosis. The expression of let-7c-5p, miR-148a-3p, and miR-148a-5p was significantly increased and negatively correlated with the expression of their target genes. The cytological effects of honokiol on A549 cells was partly reversed by treatment with the inhibitors of Let-7c-5p and miR-148a-3p.

CONCLUSION

Let-7c-5p, miR-148a-3p, miR-148a-5p, and miR-7-5p are favorable indicators of NSCLC patients treated with honokiol.

Type III collagen (COL3A1): Gene and protein structure, tissue distribution, and associated diseases

Collagen alpha-1(III) chain, also known as the alpha 1 chain of type III collagen, is a protein that in humans is encoded by the COL3A1 gene. Three alpha 1 chains are required to form the type III collagen molecule which has a long triple-helical domain. Type III collagen, an extracellular matrix protein, is synthesized by cells as a pre-procollagen. It is found as a major structural component in hollow organs such as large blood vessels, uterus and bowel. Other functions of type III collagen include interaction with platelets in the blood clotting cascade and it is also an important signaling molecule in wound healing. Mutations in the COL3A1 gene cause the vascular type of Ehlers-Danlos syndrome (vEDS; OMIM 130050). It is the most serious form of EDS, since patients often die suddenly due to a rupture of large arteries. Inactivation of the murine Col3a1 gene leads to a shorter life span in homozygous mutant mice. The mice die prematurely from a rupture of major arteries mimicking the human vEDS phenotype. The biochemical and cellular effects of COL3A1 mutations have been studied extensively. Most of the glycine mutations lead to the synthesis of type III collagen with reduced thermal stability, which is more susceptible for proteinases. Intracellular accumulation of this normally secreted protein is also found. Ultrastructural analyses have demonstrated dilated rough endoplasmic reticulum and changes in the diameter of collagen fibers. Other clinical conditions associated with type III collagen are several types of fibroses in which increased amounts of type III collagen accumulate in the target organs.