COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer

Circ-0005105 activates COL11A1 by targeting miR-20a-3p to promote pancreatic ductal adenocarcinoma progression

Growing evidence indicates that circular RNAs (circRNAs) are closely involved in tumorigenesis, but the association between circRNAs and pancreatic ductal adenocarcinoma (PDAC) is far from clear. Here, we focused on the functional investigation of circ-0005105, a newly identified circRNA, in PDAC progression. In the present study, we assessed circ-0005105 expression in PDAC tissues and cell lines with quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The biological functions of circ-0005105 in cellular proliferation and invasion were identified through gain- and loss-of-function experiments in vitro and in vivo. The interaction between circ-0005105 and the microRNA (miR)-20a-3p-COL11A1 (collagen type XI alpha 1) axis was examined using luciferase reporter and RNA immunoprecipitation assays. We found that circ-0005105 expression was upregulated in both PDAC tissues and cell lines. Higher circ-0005105 expression correlated positively with the malignant clinical phenotype and poor prognosis of patients with PDAC. Gain- and loss-of-function analysis showed that circ-0005105 facilitated both in vitro and in vivo cellular proliferation and invasion. Mechanistically, circ-000510 served as a competing endogenous RNA (ceRNA) of miR-20a-3p and indirectly modulated COL11A1 expression, leading to activation of epithelial-mesenchymal transition (EMT). Rescue experiments suggested that the oncogenic activity of circ-0005105 was dependent on the modulation of the miR-20a-3p-COL11A1 axis. More importantly, COL11A1 overexpression was significantly associated with poor prognosis in PDAC, and silencing COL11A1 reduced PDAC cell tumorigenicity and metastasis. Taken together, our findings confirm for the first time that circ-0005105 has critical functions by regulating the miR-20a-3p-COL11A1 axis. In the clinic, circ-0005105 can act as a potential prognostic marker and therapeutic target in PDAC.

Comprehensive Analysis and Identification of an Immune-Related Gene Signature with Prognostic Value for Prostate Cancer

Background

The tumor microenvironment (TME) has recently been proven to play a crucial role in the development and prognosis of tumors. However, the current knowledge on the potential of the TME in prostate cancer (PCa) remains scarce.

Purpose

This study aims to elucidate the value of TME-related genes for PCa prognosis by integrative bioinformatics analysis.

Materials and Methods

We downloaded the immune and stromal scores of PCa samples via the ESTIMATE and correlated these scores to clinicopathological characteristics and recurrence-free survival (RFS) of patients. Based on these scores, the TME-related differentially expressed genes were identified for functional enrichment analysis. Cox regression analyses were performed to identify prognostic genes and establish a predictive risk model. Moreover, gene set enrichment analysis (GSEA) was performed to evaluate the relationship between risk score and immune pathway.

Results

The stromal and immune scores were associated with clinicopathological characteristics and RFS in PCa patients. In total, 238 intersecting differentially expressed genes were identified. Functional enrichment analysis further revealed that these genes dramatically participated in the immune-related pathways. The immune-related risk model was built with C-type lectin domain containing 7A (CLEC7A) and collagen type XI alpha 1 chain (COL11A1) using Cox regression analyses. Kaplan–Meier survival analysis showed that the expression levels of CLEC7A and COL11A1 were significantly associated with the RFS. Further, the RFS time in high-risk group was significantly shorter than that in low-risk group. The areas under the curve for the risk model in predicting 3- and 5-year RFS rates were 0.694 and 0.731, respectively. GSEA suggested that immunosuppression existed in high-risk PCa patients.

Conclusion

CLEC7A and COL11A1 were selected to build a predictive risk model, which may help clinicians to assess the prognosis of PCa patients and select appropriate targets for immunotherapy.

Cancer immunotherapy by NC410, a LAIR-2 Fc protein blocking human LAIR-collagen interaction

Collagens are a primary component of the extracellular matrix and are functional ligands for the inhibitory immune receptor leukocyte-associated immunoglobulin-like receptor (LAIR)-1. LAIR-2 is a secreted protein that can act as a decoy receptor by binding collagen with higher affinity than LAIR-1. We propose that collagens promote immune evasion by interacting with LAIR-1 expressed on immune cells, and that LAIR-2 releases LAIR-1-mediated immune suppression. Analysis of public human datasets shows that collagens, LAIR-1 and LAIR-2 have unique and overlapping associations with survival in certain tumors. We designed a dimeric LAIR-2 with a functional IgG1 Fc tail, NC410, and showed that NC410 increases human T cell expansion and effector function in vivo in a mouse xenogeneic-graft versus-host disease model. In humanized mouse tumor models, NC410 reduces tumor growth that is dependent on T cells. Immunohistochemical analysis of human tumors shows that NC410 binds to collagen-rich areas where LAIR-1⁺ immune cells are localized. Our findings show that NC410 might be a novel strategy for cancer immunotherapy for immune-excluded tumors.

COL11A1 activates cancer-associated fibroblasts by modulating TGF-β3 through the NF-κB/IGFBP2 axis in ovarian cancer cells

Ovarian cancer has a unique tumor microenvironment (TME) that enables cancer-associated fibroblasts (CAFs) to interact with cellular and matrix constituents and influence tumor development and migration into the peritoneal cavity. Collagen type XI alpha 1 (COL11A1) is overexpressed in CAFs; therefore this study examines its role during CAF activation in epithelial ovarian cancer (EOC). Coculturing human ovarian fibroblasts (HOFs) with high COL11A1-expressing EOC cells or exposure to the conditioned medium of these cells prompted the expression of COL11A1 and CAF phenotypes. Conversely, coculturing HOFs with low COL11A1-expressing EOC cells or COL11A1-knockdown abrogated COL11A1 overexpression and secretion, in addition to CAF activation. Increased p-SP1 expression attributed to COL11A1-mediated extracellular signal-regulated kinase activation (ERK) induced p65 translocation into the nucleus and augmented its binding to the insulin-like growth factor binding protein 2 (IGFBP2) promoter, ultimately inducing TGF-β3 activation. The CAF-cancer cell crosstalk triggered interleukin-6 release, which in turn promoted EOC cell proliferation and invasiveness. These in vitro results were confirmed by in vivo findings in a mouse model, showing that COL11A1 overexpression in EOC cells promoted tumor formation and CAF activation, which was inhibited by TGF-β3 antibody. Human tumors with high TGF-β3 levels showed elevated expression of COL11A1 and IGFBP2, which was associated with poor survival. Our findings suggest the possibility that anti-TGF-β3 treatment strategy may be effective in targeting CAFs in COL11A1-positive ovarian tumors.

Activation of COL11A1 by PRRX1 promotes tumor progression and radioresistance in ovarian cancer

PURPOSE

Although radiotherapy is a common treatment option for all kinds of cancer patients, including ovarian cancer, a major obstacle limiting its application in the development of resistance. Therefore, it is urgently needed to clarify the mechanism of radiosensitivity modulation.

MATERIALS AND METHODS

We obtained open datasets and analyzed the expression of collagen type XI alpha 1 (COL11A1) in ovarian cancer patients with different stages. Meanwhile, the correlation of COL11A1 and survival outcomes is determined by Kaplan-Meier analysis. The role of COL11A1 in cell proliferation was observed in an in vitro knockdown system. SKOV3 radioresistant cells were established to determine the role of COL11A1 on radioresistant in ovarian cancer.

RESULTS AND DISCUSSION

COL11A1 were highly enriched in late-stage ovarian cancer tumor tissues and negatively correlated with survival outcomes in ovarian cancer. The functional analysis found that COL11A1 promoted ovarian cancer cell proliferation in vitro. Importantly, COL11A1 decreased radiosensitivity in ovarian cancer by AKT activation. Paired related homeobox 1 (PRRX1) acted as an upstream transcription factor to regulate COL11A1 expression in ovarian cancer. Increased COL11A1 expression is related to low survival outcomes and radiosensitivity in ovarian cancer.

CONCLUSIONS

Targeting COL11A1 is a promising strategy for improving radiotherapy efficiency.

Identification of crucial noncoding RNAs and mRNAs in hypertrophic scars via RNA sequencing

Hypertrophic scarring (HS) is a dermal fibroproliferative disorder characterized by excessive deposition of collagen and other extracellular matrix components. The aim of this study is to explore crucial long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with HS and provide a better understanding of the molecular mechanism of HS. To investigate the lncRNA, circRNA and mRNA expression profiles, we performed RNA sequencing of human HS and normal skin tissues. After the identification of differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs) and circRNAs (DEcircRNAs), we performed functional enrichment of DEmRNAs. Further on, we constructed DElncRNA/DEcircRNA–DEmRNA coexpression networks and competing endogenous RNA regulatory networks, and performed functional analyses of the DEmRNAs in the constructed networks. In total, 487 DEmRNAs, 92 DElncRNAs and 17 DEcircRNAs were identified. DEmRNAs were significantly enriched in processes such as collagen fibril organization, extracellular matrix–receptor interaction and the phosphatidylinositol 3‐kinase (PI3K)–Akt signaling pathway. In addition, we detected 580 DElncRNA–DEmRNA and 505 DEcircRNA–DEmRNA coexpression pairs. The competing endogenous RNA network contained 18 circRNA–microRNA (miRNA) pairs, 18 lncRNA–miRNA pairs and 409 miRNA–mRNA pairs, including 10 circRNAs, 5 lncRNAs, 15 miRNAs and 160 mRNAs. We concluded that MIR503HG/hsa‐miR‐204‐3p/ACAN, MIR503HG/hsa‐miR‐431‐5p/TNFRSF9, MEG3/hsa‐miR‐6884‐5p/ADAMTS14, AC000035.1‐ADAMTS14 and hsa_circ_0069865‐COMP/ADAM12 interaction pairs may play a central role in HS.

MiR-144-3p inhibits the proliferation, migration and invasion of lung adenocargen cancer cells by targeting COL11A1

This study aimed to investigate the regulatory relationship between miR-144-3p and COL11A1, and to explore its effect on the proliferation, migration and invasion of lung adenocarcinoma (LUAD) cells. A series of methods and experiments were applied. miR-144-3p was downregulated in LUAD tissue and cells, whereas COL11A1 was highly expressed. Overexpressing miR-144-3p inhibited the proliferation, migration and invasion of LUAD cells, which could be reversed by overexpression of COL11A1. Overexpressing miR-144-3p inhibits the proliferation, migration and invasion of LUAD cells by silencing COL11A1.

Identification of disease-promoting stromal components by comparative proteomic and transcriptomic profiling of canine mammary tumors using laser-capture microdissected FFPE tissue

Cancer-associated stroma (CAS) profoundly influences progression of tumors including mammary carcinoma (mCA). Canine simple mCA represent relevant models of human mCA, notably also with respect to CAS. While transcriptomic changes in CAS of mCA are well described, it remains unclear to what extent these translate to the protein level. Therefore, we sought to gain insight into the proteomic changes in CAS and compare them with transcriptomic changes in the same tissue. To this end, we analyzed CAS and matched normal stroma using laser-capture microdissection (LCM) and LC-MS/MS in a cohort of 14 formalin-fixed paraffin embedded (FFPE) canine mCAs that we had previously characterized using LCM-RNAseq. Our results reveal clear differences in protein abundance between CAS and normal stroma, which are characterized by changes in the extracellular matrix, the cytoskeleton, and cytokines such as TNF. The proteomics- and RNAseq-based analyses of LCM-FFPE show a substantial degree of correlation, especially for the most deregulated targets and a comparable activation of pathways. Finally, we validate transcriptomic upregulation of LTBP2, IGFBP2, COL6A5, POSTN, FN1, COL4A1, COL12A1, PLOD2, COL4A2, and IGFBP7 in CAS on the protein level and demonstrate their adverse prognostic value for human breast cancer. Given the relevance of canine mCA as a model for the human disease, our analysis substantiates these targets as disease-promoting stromal components with implications for breast cancer in both species.

Cancer-associated fibroblast migration in non-small cell lung cancers is modulated by increased integrin α11 expression

Cancer‐associated fibroblasts (CAFs) regulate cancer progression through the modulation of extracellular matrix (ECM) and cancer cell adhesion. While undergoing a series of phenotypic changes, CAFs control cancer–stroma interactions through integrin receptor signaling. Here, we isolated CAFs from patients with non‐small‐cell lung cancer (NSCLC) and examined their gene expression profiles. We identified collagen type XI α1 (COL11A1), integrin α11 (ITGA11), and the ITGA11 major ligand collagen type I α1 (COL1A1) among the 390 genes that were significantly enriched in NSCLC‐associated CAFs. Increased ITGA11 expression in cancer stroma was correlated with a poor clinical outcome in patients with NSCLC. Increased expression of fibronectin and collagen type I induced ITGA11 expression in CAFs. The cellular migration of CAFs toward collagen type I and fibronectin was promoted via ERK1/2 signaling, independently of the fibronectin receptor integrin α5β1. Additionally, ERK1/2 signaling induced ITGA11 and COL11A1 expression in cancer stroma. We, therefore, propose that targeting ITGA11 and COL11A1 expressing CAFs to block cancer–stroma interactions may serve as a novel, promising anti‐tumor strategy.

Collagen Type I α-1 Promotes Malignant Glioma Cell Proliferation and Is Associated with Glioma Prognosis

Collagen type I α-1 chain (COL1A1) is closely involved in the advancement of various tumors, yet the role of COL1A1 in the progression of glioma is not clear. Herein, we evaluated the effect of COL1A1 on glioma cell proliferation. The effect of COL1A1 on glioma cell proliferation was assessed through overexpression or knockdown of COL1A1. The CCK-8 and colony formation assays, as well as immunohistochemistry (IHC) were used to detect COL1A1 expression in different glioma grades. U-87MG as well as U-251MG cells were stably-inserted with lentivirus containing COL1A1 through transfection, we additionally used qRT-PCR as well as Western blot assay to validate their overexpression efficiencies. COL1A1 mRNA and protein levels were upregulated in the high-grade glioma (HGG) compared to the low-grade glioma (LGG). COL1A1 IHC score was remarkably higher in HGG than LGG. The staining index (SI) further showed that COL1A1 protein levels were higher in HGG than LGG. The Kaplan–Meier analysis showed that elevated COL1A1 mRNA levels were obviously correlated with lower overall survival (OS) and disease-free survival (DFS) for brain glioma patients. COL1A1 mRNA and protein levels were markedly upregulated in human glioma cell lines when compared with brain astrocyte cell lines. The high expression level of COL1A1 facilitated glioma cell proliferation. COL1A1 knockdown remarkably inhibited glioma cell proliferation. Thus, this research shows that COL1A1 promotes glioma cell proliferation and is closely related to glioma prognosis.

Collagen Type XI Alpha 1 (COL11A1): A Novel Biomarker and a Key Player in Cancer

Collagen type XI alpha 1 (COL11A1), one of the three alpha chains of type XI collagen, is crucial for bone development and collagen fiber assembly. Interestingly, COL11A1 expression is increased in several cancers and high levels of COL11A1 are often associated with poor survival, chemoresistance, and recurrence. This review will discuss the recent discoveries in the biological functions of COL11A1 in cancer. COL11A1 is predominantly expressed and secreted by a subset of cancer-associated fibroblasts, modulating tumor-stroma interaction and mechanical properties of extracellular matrix. COL11A1 also promotes cancer cell migration, metastasis, and therapy resistance by activating pro-survival pathways and modulating tumor metabolic phenotype. Several inhibitors that are currently being tested in clinical trials for cancer or used in clinic for other diseases, can be potentially used to target COL11A1 signaling. Collectively, this review underscores the role of COL11A1 as a promising biomarker and a key player in cancer.

Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis

Background

Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. We aimed to identify differentially expressed genes (DEGs) and their potential mechanisms associated with the prognosis of GC patients.

Material/Methods

This study was based on gene profiling information for 37 paired samples of GC and adjacent normal tissues from the GSE118916, GSE79973, and GSE19826 datasets in the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the biological role of the DEGs. The protein–protein interaction (PPI) network was constructed by Cytoscape, and the Kaplan-Meier plotter was used for prognostic analysis.

Results

We identified 119 DEGs, including 21 upregulated and 98 downregulated genes, in GC. The 21 upregulated genes were mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and transforming growth factor-β signaling, while the 98 downregulated genes were significantly associated with gastric acid secretion, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. Thirty hub DEGs were obtained for further analysis. Twenty-five of the 30 hub DEGs were significantly associated with the prognosis of GC, and 21 of the 25 hub DEGs showed consistent expression trends within the 3 profile datasets. KEGG reanalysis of these 21 hub DEGs showed that COL1A1, COL1A2, COL2A1, COL11A1, THBS2, and SPP1 were mainly enriched in the extracellular matrix-receptor interaction pathways.

Conclusions

We identified 6 genes that were significantly related to the prognosis of GC patients. These genes and pathways could serve as potential prognostic markers and be used to develop treatments for GC patients.

Quercetin attenuates metastatic ability of human metastatic ovarian cancer cells via modulating multiple signaling molecules involved in cell survival, proliferation, migration and adhesion

Ovarian cancer is the most deadly gynaecology related cancer due to its high metastasizing ability. Quercetin is the most abundant flavonoids received increased interest due to its anti-cancer properties. Although the anticancer property of quercetin is very well known, its anti-metastatic effect on metastatic ovarian cancer cells and their underlying molecular mechanism remains to be elucidated. Quercetin treatment at 50 μM and 75 μM concentration inhibit human metastatic ovarian cancer PA-1 cell survival and proliferation via inactivating PI3k/Akt, Ras/Raf pathways and EGFR expression. It also alters the expression of N-cadherin in PA-1 cells. Quercetin also decreases the secretion of gelatinase enzyme, proteolytic activity of MMP-2/-9, and both MMPs gene expression in metastatic ovarian cancer PA-1 cells. In addition to this quercetin inhibits the migration of PA-1 cells. Treatment of quercetin with PA-1 cells also downregulates the tight junctional molecules such as Claudin-4 and Claudin-11 while upregulates the expression of occludin. It is further validated by cell adhesion assay in which quercetin reduces the adhesion of PA-1 ovarian cancer cells. Results suggest that quercetin inhibits cell survival, proliferation, migration, and adhesion which plays crucial role in ovarian cancer metastasis. Hence, it could be a valuable therapeutic drug for the treatment and prevention of metastatic ovarian cancer.

Exploring the Differential Expression and Prognostic Significance of the COL11A1 Gene in Human Colorectal Carcinoma: An Integrated Bioinformatics Approach

Colorectal cancer is one of the most common cancers of humans and the second highest in cancer-related death. Genes used as prognostic biomarkers play an imperative role in cancer detection and may direct the development of appropriate therapeutic strategies. Collagen type XI alpha 1 (COL11A1) is a minor fibrillary collagen that has an essential role in the regulation of cell division, differentiation, proliferation, migration, growth, and apoptosis of intestinal and colon cells. The present study seeks to evaluate the significance of the COL11A1 gene in the progression of colorectal cancer in humans across the various parameters using advanced bioinformatics approaches. The application of various databases and servers like ONCOMINE, UALCAN, and GEPIA were accessed for analyzing the differential expression of the COLL11A1 gene and its relative influence over the survival of the transformed subjects. In addition, oncogenomics of COL11A1 gene, mutations associated with this gene and interacting partners of the gene in the context of oncogenesis were studied using COSMIC, cBioPortal, GeneMANIA, and NetworkAnalyst. Our experimental data indicate that the COL11A1 gene is overexpressed in the transformed tissues across the various clinicopathological parameters reduces the probability of survival in both overall and disease-specific survival cases. Mutational studies imply that it can induce perturbations in various signaling pathways viz. RTK-RAS-PI3K, Wnt, TGF-β, and TP53 pathways influencing cancer development. Also, a positive association and correlation amongst the THBS2, COL10A1, COL5A2, and COL1A2 genes were observed, which most likely to contribute to the upregulation of carcinogenesis. Conclusively, this comprehensive study indicates the COL11A1 gene to be a significant contributor in the etiology of colorectal cancer, henceforth this gene can be considered as a prognostic biomarker for the conception of diagnostic and therapeutic strategies against colorectal cancer in the near future.

Mutant collagen COL11A1 enhances cancerous invasion

Collagens are the most abundant proteins in the body and comprise the basement membranes and stroma through which cancerous invasion occurs; however, a pro-neoplastic function for mutant collagens is undefined. Here we identify COL11A1 mutations in 66 of 100 cutaneous squamous cell carcinomas (cSCCs), the second most common U.S. cancer, concentrated in a triple helical region known to produce trans-dominant collagens. Analysis of COL11A1 and other collagen genes found that they are mutated across common epithelial malignancies. Knockout of mutant COL11A1 impairs cSCC tumorigenesis in vivo. Compared to otherwise genetically identical COL11A1 wild-type tissue, gene-edited mutant COL11A1 skin is characterized by induction of β1 integrin targets and accelerated neoplastic invasion. In mosaic tissue, mutant COL11A1 cells enhanced invasion by neighboring wild-type cells. These results suggest that specific collagens are commonly mutated in cancer and that mutant collagens may accelerate this process.

The COL11A1/Akt/CREB signaling axis enables mitochondrial-mediated apoptotic evasion to promote chemoresistance in pancreatic cancer cells through modulating BAX/BCL-2 function

Collagen XI, a member of the collagen family, is present in the extracellular matrix (ECM), and high collagen XI/αI (COL11A1) expression in tumor tissue is reportedly correlated with the clinicopathological parameters of pancreatic ductal adenocarcinoma (PDAC). However, the function of COL11A1 in the development of pancreatic cancer cells remains unclear. In the current study, we assessed mRNA expression of COL11A1 and its receptors and created a testing-model of both a COL11A1-overexpressing tumor microenvironment and/or altered-COL11A1 expression in pancreatic cancer cell lines. Next, we investigated the mechanism by which COL11A1 affects growth, gemcitabine (GEM) resistance and apoptosis in pancreatic cancer cells. We demonstrated that COL11A1 phosphorylated Akt^Ser473, promoting proliferation of cancer cells and inhibiting their apoptosis. Additionally, our data showed that COL11A1/Akt/CREB altered the balance between BCL-2 and BAX and mediated their mitochondrial translocation in pancreatic cancer cells. The COL11A1/Akt axis induced disruption of mitochondrial transmembrane function, enabling mitochondria-mediated apoptotic evasion to promote chemoresistance. We also explored the regulatory effect of COL11A1/Akt on molecular signaling in the mitochondria-mediated apoptotic program. COL11A1/Akt disturbed the BCL-2/BAX balance, inhibiting cytochrome c (Cyt-C) release and binding of Apaf-1/procaspase-9/Cyt-C, which suppressed the apoptotic program and induced GEM resistance in pancreatic cancer cells. In conclusion, COL11A1 modulates apoptotic inhibition and chemoresistance in pancreatic cancer cells by activating the Akt/CREB/BCL-2/BAX signaling pathway. COL11A1 may represent a distinct prognostic indicator and may be an attractive therapeutic target for PDAC.

High expression of collagen 1A2 promotes the proliferation and metastasis of esophageal cancer cells

Background

To undertake a bioinformatics analysis to identify abnormally expressed genes [also referred to as differentially expressed genes (DEGs)] and their functions in esophageal carcinoma (ESCA).

Methods

DEGs (i.e., GSE100942, GSE17351, GSE26886, and GSE77861) were obtained from a gene expression omnibus database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using online tools from the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was then constructed based on the Search Tool for the Retrieval of Interacting Genes website. Cytoscape software was used to identify the top 20 DEGs located in the central region of the network. For the overall survival analysis, a Kaplan-Meier analysis was conducted of the Gene Expression Profiling Interactive Analysis website, and collagen (COL) 1A2 was selected to detect the molecular mechanism of COL1A2-small interfering ribonucleic acid (siRNA) in the following ESCA cell lines: Eca109 and TE-1. Next, the expression of COL1A2-messanger ribonucleic acid was determined using real-time quantitative polymerase chain reaction. The expression of COL1A2 was also verified by Western blot. Cell proliferation was measured by colony-forming and MTT assays, and migration and invasion by the transwell assay.

Results

Based on the GEO database and screening out the hub gene, we identified that COL1A2 was abnormally expressed in ESCA. With a series of in vitro experiments, the expression of COL1A2 was defined as higher in Eca109 and TE-1.

Conclusions

COL1A2 was highly expressed in ESCA tissue samples. Additionally, the proliferation and metastasis of Eca109 and TE-1 cell lines were significantly attenuated by siRNA-COL1A2-mediated small interference. Notably, the expression level of COL1A2 was obviously related to the Akt and epithelial-mesenchymal transition (EMT) pathways.

Bizarre giant cells in human angiosarcoma exhibit chemoresistance and contribute to poor survival outcomes

Giant cells (GC) are a poorly understood subset of tumor cells that have been increasingly recognized as a potential contributor to tumor heterogeneity and treatment resistance. We aimed to characterize the biological and clinical significance of GC in angiosarcoma, an aggressive rare cancer of endothelial origin. Archival angiosarcoma samples were examined for the presence of GC and compared with clinicopathological as well as NanoString gene expression data. GC were examined in angiosarcoma cell lines MOLAS and ISOHAS using conventional and electron microscopy, single cell whole genome profiling, and other assays. In the cell lines, GC represented a rare population of mitotically active, non–senescent CD31⁺ cells, and shared similar genomic profiles with regular‐sized cells, consistent with a malignant endothelial phenotype. GC remained viable and persisted in culture following exposure to paclitaxel and doxorubicin. In patient samples, GC were present in 24 of 58 (41.4%) cases. GC was correlated with poorer responses to chemotherapy (25.0% vs 73.3%, P = 0.0213) and independently contributed to worse overall survival outcomes (hazard ratio 2.20, 95% confidence interval 1.17‐4.15, P = 0.0142). NanoString profiling revealed overexpression of genes, including COL11A1, STC1, and ERO1A, accompanied by upregulation of immune‐related metabolic stress and metastasis/matrix remodeling pathways in GC‐containing tumors. In conclusion, GC may contribute to chemoresistance and poor prognosis in angiosarcoma.

COL11A1 Was Involved in Cell Proliferation, Apoptosis and Migration in Non-Small Cell Lung Cancer Cells

BACKGROUND

Type XI collagen (COL11A1) was reported to associate with malignancy in several cancer types, whereas its role in lung cancer is not fully understood. Therefore, the present study aimed to explore the expression level and biological role of COL11A1 in lung cancer cells.

METHODS

Gene Expression Omnibus (GEO) database containing 6 lung cancer tissues and normal lung tissues was used to identify potential aberrantly expressed genes. The expression of COL11A1, apoptosis related genes, cell cycle related genes and migration associated genes at the protein level were evaluated by western blot and at the mRNA level was determined by real-time PCR in lung cancer cell lines. Furthermore, the expression of COL11A1 was silenced by siRNA, and cell viability was detected by Cell counting kit-8 (CCK-8) assay. Moreover, cell apoptosis and cell cycle were determined by flow cytometry. In addition, transwell and wound-healing assay were applied to determine cell migration ability.

RESULTS

GEO analysis suggests that COL11A1 was highly expressed in patients with lung cancer, which was consistent with the results in lung cancer cell lines. COL11A1 knockdown in lung cancer cells significantly lowered the colony formation ability, augmented cell apoptosis rate and elevated the expression of cleaved caspase-3, cleaved caspase-9, Bax, P21 and the expression of Bcl-2, CyclinD1, CDK2 and CDK-4 was significantly downregulated (all p < 0.05). Moreover, post-COL11A1 knockdown, the cell wound-healing and migration ability was significantly impaired, which also supported by the upregulation of E-Cadherin and downregulation of N-Cadherin, Vimentin and Snail (all p < 0.05). Furthermore, we also found that COL11A1 knockdown decreased the expression of p-AKT, p-PI3K and p-ERK.

CONCLUSION

The present study revealed that COL11A1 may contribute to the malignancy and involve in the pathogenesis of lung cancer.

Uveal Melanoma-Derived Extracellular Vesicles Display Transforming Potential and Carry Protein Cargo Involved in Metastatic Niche Preparation

Extracellular vesicles (EVs) carry molecules derived from donor cells and are able to alter the properties of recipient cells. They are important players during the genesis and progression of tumors. Uveal melanoma (UM) is the most common primary intraocular tumor in adults and is associated with a high rate of metastasis, primarily to the liver. However, the mechanisms underlying this process are poorly understood. In the present study, we analyzed the oncogenic potential of UM-derived EVs and their protein signature. We isolated and characterized EVs from five UM cell lines and from normal choroidal melanocytes (NCMs). BRCA1-deficient fibroblasts (Fibro-BKO) were exposed to the EVs and analyzed for their growth in vitro and their reprograming potential in vivo following inoculation into NOD-SCID mice. Mass spectrometry of proteins from UM-EVs and NCM-EVs was performed to determine a protein signature that could elucidate potential key players in UM progression. In-depth analyses showed the presence of exosomal markers, and proteins involved in cell-cell and focal adhesion, endocytosis, and PI3K-Akt signaling pathway. Notably, we observed high expression levels of HSP90, HSP70 and integrin V in UM-EVs. Our data bring new evidence on the involvement of UM-EVs in cancer progression and metastasis.

lncRNA small nucleolar RNA host gene 12 promotes renal cell carcinoma progression by modulating the miR‑200c‑5p/collagen type XI α1 chain pathway

Renal cell carcinoma (RCC) is a primary malignant kidney cancer subtype. It has been suggested that long non-coding RNAs (lncRNAs) serve important roles in the progression of kidney cancer. In fact, the lncRNA small nucleolar RNA host gene 12 (SNHG12) was discovered to be overexpressed in various types of cancer. However, to the best of our knowledge, the role of SNHG12 in RCC remains unclear. The present study aimed to investigate the function of SNHG12 and its underlying molecular mechanism of action in RCC. In patient samples and datasets from The Cancer Genome Atlas. Reverse transcription-quantitative PCR, demonstrated that SNHG12 expression levels were upregulated in RCC tumor tissues, but not in normal kidney tissues. SNHG12 upregulation was also observed in RCC cell lines. Kaplan-Meier survival analysis indicated a poor prognosis for those patients with RCC who had upregulated SNHG12 expression levels. Following lentivirus transduction, SNHG12 was successfully knocked down (validated by western blot analysis) and cell migration and invasion assays were performed. SNHG12 knockdown markedly inhibited cell viability and invasion, while increasing apoptosis in both A498 and 786O cell lines. The results of the luciferase reporter assay suggested that SNHG12 exerted its role by sponging microRNA (miR)-200c-5p, which led to the upregulation of its target gene, collagen type XI α1 chain (COL11A1). This was further validated, as miR-200c-5p inhibition reduced the effects of SNHG12 downregulation on cell viability and apoptosis, without affecting SNHG12 expression levels. Furthermore, the findings indicated that SNHG12 may partially exert its role through COL11A1, which was also upregulated in RCC. In conclusion, the results of the present study suggested that the SNHG12/miR-200c-5p/COL11A1 axis may be crucial for RCC progression, which provided an insight into potential therapeutic strategies for RCC treatment.

Expression Profiling of Extracellular Matrix Genes Reveals Global and Entity-Specific Characteristics in Adenoid Cystic, Mucoepidermoid and Salivary Duct Carcinomas

Simple Summary

The extracellular matrix (ECM), an important factor in tumour metastasis and therapy resistance, has not been studied in salivary gland carcinomas (SGC), so far. In this retrospective study, we profiled the RNA expression of 28 ECM-related genes in 11 adenoid cystic (AdCy), 14 mucoepidermoid (MuEp) and 9 salivary duct carcinomas (SaDu). Also, we validated our results in a multimodal approach. MuEp and SaDu shared a common gene signature involving an overexpression of COL11A1. In contrast, nonhierarchical clustering revealed a more specific gene expression pattern for AdCy, characterized by overexpression of COL27A1. In situ studies at RNA level indicated that in AdCy, ECM production results from tumour cells and not from cancer-associated fibroblasts as is the case in MuEp and SaDu. For the first time, we characterized the ECM composition in SGC and identified several differentially expressed genes, which are potential therapeutic targets.

Abstract

The composition of the extracellular matrix (ECM) plays a pivotal role in tumour initiation, metastasis and therapy resistance. Until now, the ECM composition of salivary gland carcinomas (SGC) has not been studied. We quantitatively analysed the mRNA of 28 ECM-related genes of 34 adenoid cystic (AdCy; n = 11), mucoepidermoid (MuEp; n = 14) and salivary duct carcinomas (SaDu; n = 9). An incremental overexpression of six collagens (including COL11A1) and four glycoproteins from MuEp and SaDu suggested a common ECM alteration. Conversely, AdCy and MuEp displayed a distinct overexpression of COL27A1 and LAMB3, respectively. Nonhierarchical clustering and principal component analysis revealed a more specific pattern for AdCy with low expression of the common gene signature. In situ studies at the RNA and protein level confirmed these results and indicated that, in contrast to MuEp and SaDu, ECM production in AdCy results from tumour cells and not from cancer-associated fibroblasts (CAFs). Our findings reveal different modes of ECM production leading to common and distinct RNA signatures in SGC. Of note, an overexpression of COL27A1, as in AdCy, has not been linked to any other neoplasm so far. Here, we contribute to the dissection of the ECM composition in SGC and identified a panel of deferentially expressed genes, which could be putative targets for SGC therapy and overcoming therapeutic resistance.

Deep learning-based ovarian cancer subtypes identification using multi-omics data

Background

Identifying molecular subtypes of ovarian cancer is important. Compared to identify subtypes using single omics data, the multi-omics data analysis can utilize more information. Autoencoder has been widely used to construct lower dimensional representation for multi-omics feature integration. However, learning in the deep architectures in Autoencoder is difficult for achieving satisfied generalization performance. To solve this problem, we proposed a novel deep learning-based framework to robustly identify ovarian cancer subtypes by using denoising Autoencoder.

Results

In proposed method, the composite features of multi-omics data in the Cancer Genome Atlas were produced by denoising Autoencoder, and then the generated low-dimensional features were input into k-means for clustering. At last based on the clustering results, we built the light-weighted classification model with L1-penalized logistic regression method. Furthermore, we applied the differential expression analysis and WGCNA analysis to select target genes related to molecular subtypes. We identified 34 biomarkers and 19 KEGG pathways associated with ovarian cancer.

Conclusions

The independent test results in three GEO datasets proved the robustness of our model. The literature reviewing show 19 (56%) biomarkers and 8(42.1%) KEGG pathways identified based on the classification subtypes have been proved to be associated with ovarian cancer. The outcomes indicate that our proposed method is feasible and can provide reliable results.

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.

Head and Neck Cancer Metastasis and the Effect of the Local Soluble Factors, from the Microenvironment, on Signalling Pathways: Is It All about the Akt?

The signalling pathways involved in metastasis of oral adenoid cancer cells (TYS) in response to cancer-associated fibroblasts (COM D24) and normal oral mucosal fibroblasts (MM1) was examined. Metastatic cell behaviour was observed by cell-scatter, 3-D-collagen gel migration, and 3-D-spheroid invasion assays. Akt (v-Akt murine thymoma viral oncogene), MAPK(Mitogen activated protein kinase), EGFR (Epidermal growth factor receptor), TGFβRI (Transforming growth factor beta receptor 1), and CXCR4 (C-X-C chemokine receptor 4) inhibitors were used to identify the signalling pathways involved. Signalling pathway protein expression and activation were assessed by SDS-PAGE and Western blotting. COM-CM (conditioned medium from COM D24 cells) and MM1-CM (conditioned medium from MM1 cells) stimulated cancer cell scattering, which was blocked only by the Akt inhibitor. COM-CM-induced scattered cancer cells showed higher levels of Akt phosphorylation than the negative control and MM1-CM. Migration and invasion of TYS cells into collagen gels from the spheroids was stimulated by CM from both fibroblast cell lines, compared to the negative control. COM cells stimulated TYS invasion into the collagen more than MM1 and the control. Akt and EGFR inhibitors effectively blocked CM and COM cell-induced invasion. Akt-silenced cancer cells were not stimulated to migrate and invade by fibroblast-CM and did not survive the addition of an EGFR inhibitor. This suggests that CAFs stimulate head and neck cancer cell migration and invasion in an Akt- dependent manner. Akt may represent a potential target for inhibitor design to treat metastatic head and neck cancer.

Fibroblast Growth Factor-14 Acts as Tumor Suppressor in Lung Adenocarcinomas

Investigation of the molecular dynamics in lung cancer is crucial for the development of new treatment strategies. Fibroblast growth factor (FGF) 14 belongs to the FGF family, which might play a crucial role in cancer progression. We analyzed lung adenocarcinoma (LUAC) patients samples and found that FGF14 was downregulated, correlating with reduced survival and oncogenic mutation status. FGF14 overexpression in lung cancer cell lines resulted in decreased proliferation, colony formation, and migration, as well as increased expression of epithelial markers and a decreased expression of mesenchymal markers, indicating a mesenchymal to epithelial transition in vitro. We verified these findings using small interfering RNA against FGF14 and further confirmed the suppressive effect of FGF14 in a NOD.Cg-Prkdc^scid Il2rg^tm1Wjl/SzJ immunodeficient xenograft tumor model. Moreover, FGF14 overexpressing tumor cell RNA sequencing data suggests that genes affected by FGF14 were related to the extracellular matrix, playing a role in proliferation and migration. Notably, newly identified FGF14 target genes, adenosine deaminase RNA specific B1 (ADARB1), collagen and calcium-binding epidermal growth factor domain-containing protein 1 (CCBE1), α1 chain of collagen XI (COL11A1), and mucin 16 (MUC16) expression was negatively correlated with overall survival when FGF14 was downregulated in LUAC. These findings led us to suggest that FGF14 regulates proliferation and migration in LUAC.

Inhibition of collagen XI alpha 1-induced fatty acid oxidation triggers apoptotic cell death in cisplatin-resistant ovarian cancer

Collagen type XI alpha 1 (COL11A1) is a novel biomarker associated with cisplatin resistance in ovarian cancer. However, the mechanisms underlying how COL11A1 confers cisplatin resistance in ovarian cancer are poorly understood. We identified that fatty acid β-oxidation (FAO) is upregulated by COL11A1 in ovarian cancer cells and that COL11A1-driven cisplatin resistance can be abrogated by inhibition of FAO. Furthermore, our results demonstrate that COL11A1 also enhances the expression of proteins involved in fatty acid synthesis. Interestingly, COL11A1-induced upregulation of fatty acid synthesis and FAO is modulated by the same signaling molecules. We identified that binding of COL11A1 to its receptors, α1β1 integrin and discoidin domain receptor 2 (DDR2), activates Src-Akt-AMPK signaling to increase the expression of both fatty acid synthesis and oxidation enzymes, although DDR2 seems to be the predominant receptor. Inhibition of fatty acid synthesis downregulates FAO despite the presence of COL11A1, suggesting that fatty acid synthesis might be a driver of FAO in ovarian cancer cells. Taken together, our results suggest that COL11A1 upregulates fatty acid metabolism in ovarian cancer cells in a DDR2-Src-Akt-AMPK dependent manner. Therefore, we propose that blocking FAO might serve as a promising therapeutic target to treat ovarian cancer, particularly cisplatin-resistant recurrent ovarian cancers which typically express high levels of COL11A1.

Comparing PI3K/Akt Inhibitors Used in Ovarian Cancer Treatment

Epithelial ovarian carcinoma (EOC) is the most lethal gynecological malignancy. Herein, we sought to determine the efficacy of phosphoinositide 3-kinase (PI3K)/Akt inhibition using three AZD compounds in a NOD-SCID xenograft mouse model and Akt regulation in a panel of eight ovarian cancer cell lines. Elevated Akt phosphorylation on Ser473 but not on Thr308 in cancerous tissues correlated with short progression-free survival (PFS), overall survival (OS), and death. AZD8835 and AZD8186 inhibited Akt phosphorylation while AZD5363 augmented its phosphorylation on Ser473. To add, all compounds inhibited the Akt downstream effectors 4E-BP1 and p70S6 kinase. AZD8835 and AZD5363 sensitized chemoresistant ovarian cancer cells to cisplatin and paclitaxel treatment. Only AZD5363 could inhibit COL11A1 mRNA and promoter activity, which are important factors in Akt regulation and chemoresistance in ovarian cancer. By using a mouse xenograft model, AZD8835 and AZD5363, but not AZD8186, caused a significant reduction in tumor formation. AZD compounds did not change the mRNA expression of BRCA1/BRCA in ovarian cancer cells, but AZD8835 inhibited BRCA1/BRCA2 mRNA expression and p-ERK protein expression in OVCAR-8 cells with the KRAS mutation. This study highlights the importance of PI3K/Akt in ovarian tumor progression and chemoresistance and the potential application of AZD compounds, especially AZD8835 and AZD5363, as therapeutic agents for the treatment of ovarian cancer.

Alteration and prognostic values of collagen gene expression in patients with gastric cancer under different treatments

Collagen (COL) genes participate in tumor extracellular matrix (ECM)-receptor interactions and focal adhesion pathways, which play a crucial role in tumor invasion and metastasis. The prognostic value of COL genes has been shown for several malignancies. In the present study, we analyzed multiple microarray datasets using the Oncomine database to identify alterations of COL genes in gastric cancer (GC). Gene expression levels were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) in GC tissues and matched adjacent tissues. The prognostic value of differentially expressed COL genes in GC was evaluated by Kaplan-Meier survival analysis based on the complete mRNA transcriptomics data from The Cancer Genome Atlas (TCGA). We found that seven COL genes (COL1A2, COL4A1, COL4A2, COL6A1, COL6A2, COL6A3, and COL11A1) were elevated in GC. Among them, stepwise multivariate Cox regression was applied, and it was determined that COL4A1 and COL4A2 were signature and independent prognostic biomarkers in GC patients with obviously different overall survival (OS). High expression of COL4A1, COL4A2, COL6A1, COL6A2, and COL6A3 was correlated with poorer prognosis of GC patients treated by surgery only, while higher expression of COL4A1 and COL11A1 correlated with poorer survival of patients treated by 5-fluorouracil-based adjuvant therapy. Our results indicate that overexpression of COL genes might be utilized as novel prognostic markers for GC and assist with therapy selection.

Marine Collagen Substrates for 2D and 3D Ovarian Cancer Cell Systems

A fundamental structural component of extracellular matrix in all connective and interstitial tissue, collagen is the most abundant protein in the human body. To date, mammalian collagens sources represent the golden standard for multiple biomedical applications, while marine-derived collagens have largely been used in industry (food, pharmaceutical, and cosmetic), with little use in research and clinical applications. Herein we demonstrate the effective use Rhizostoma pulmo jellyfish collagen, a source of biocompatible, sustainable collagen for 2D and 3D cell culture, addressing the global drive for technological developments that result in the replacement of animals and their derived products in research. Jellyfish collagen harbors similar structural features mammalian collagen type I, despite differing slightly in amino acid content. Jellyfish collagen supports ovarian cancer (OvCa) cell line proliferation, cellular morphology and expression of epithelial to mesenchymal transition markers, supporting the use of R. pulmo as a non-mammalian collagen cell culture substrate. Furthermore, R. pulmo collagen is effective in 3D device fabrication such as sponges where it mimics tissue architecture complexity. OvCa cells migrated and differentiated within the R. pulmo collagen 3D scaffolds confirming its suitability for advanced cell culturing applications, providing an excellent alternative to mammalian collagen sources for the culture of human cells.

Immunohistochemical analysis of the expression of cancer-associated fibroblast markers in esophageal cancer with and without neoadjuvant therapy

Esophageal carcinoma (EC) is one of the most aggressive human malignancies with high rates of resistance to conventional anticancer treatment. Cancer-associated fibroblasts (CAFs) are an important part of the tumor microenvironment and associated with tumor progression. COL11A1, SPARC, and CD90 have been identified as rather specific CAF markers, with COL11A1 expression particularly shown to influence response to chemotherapy. We investigated the impact of CAFs in esophageal cancer with a special focus on response to neoadjuvant treatment (nTX). Two collections of esophageal carcinomas were investigated: 164 cases treated with primary resection and 256 cases receiving nTX before resection. The expression of CAF markers was determined using next-generation tissue microarray (ngTMA®) technology and immunohistochemistry. The presence of COL11A1 and SPARC in fibroblasts within both primary resected cases and nTX-treated cases was associated with unfavorable clinicopathological variables such as higher (y)pT category and lymphatic invasion (p<0.001 each). The presence of COL11A1-positive CAFs was associated with worse overall survival in primary resected cases (HR: 2.162, p = 0.004, CI 95% 1.275-3.686). While in tumors showing regression after nTX, COL11A1-positive CAFs were detected less frequently, SPARC-positive CAFs were enriched after nTX, in both responding and non-responding patients (p < 0.001). Our results support the concept of CAFs as an important factor of tumor promotion and maintenance in EC. The population of CAFs increases with tumor progression and decreases, partly depending on the subtype, after regression following nTX. CAFs may serve as potential target for future therapeutic approaches for these highly aggressive tumors.

Increased expression of TET3 predicts unfavorable prognosis in patients with ovarian cancer-a bioinformatics integrative analysis

Ovarian carcinoma is a lethal gynecological malignancy. Women with ovarian cancer (OC) are highly recurrent and typically diagnosed at late stage. Ten-eleven translocation protein 3 (TET3) belongs to the family of ten-eleven translocations (TETs) which induce DNA demethylation and gene regulation in epigenetic level by converting 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC). Previous studies indicated that TET3 is overexpressed in ovarian cancer tissues. However, the clinic-pathological functions and prognostic values of TET3 remain unclear. Here we performed an integrative study to identify the role of TET3 by bioinformatics analysis. The TET3 expression in ovarian cancer was assessed with Oncomine database, and validated with TCGA and GTEx database. The correlation of TET3 gene alteration and clinic-pathological functions was addressed by integrative analysis of GEO datasets. Then we showed mainly TET3 gain and diploid but less deletion in ovarian cancer by copy number alteration (CNA) or mutation analysis with cBioPortal. Furthermore, by using Kaplan-Meier plotter (K-M plotter), we evaluated that high TET3 level was associated with poor survival in ovarian cancer patients, which was validated with analysis by PrognoScan database and gene differential analyses with TCGA and GTEx. This is the first study demonstrated that elevated expression of TET3 is associated with poor clinic-pathological functions, poor prognosis, wherein TET3, which presents epigenetic changes or methylation changes, might be served as a diagnostic marker or therapeutic target for ovarian cancer.

Transcriptome Profiling Reveals Matrisome Alteration as a Key Feature of Ovarian Cancer Progression

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy. There is a lack of comprehensive investigation of disease initiation and progression, including gene expression changes during early metastatic colonization.

METHODS

RNA-sequencing (RNA-seq) was done with matched primary tumors and fallopian tubes (n = 8 pairs) as well as matched metastatic and primary tumors (n = 11 pairs) from ovarian cancer patients. Since these are end point analyses, it was combined with RNA-seq using high-grade serous ovarian cancer cells seeded on an organotypic three-dimensional (3D) culture model of the omentum, mimicking early metastasis. This comprehensive approach revealed key changes in gene expression occurring in ovarian cancer initiation and metastasis, including early metastatic colonization.

RESULTS

2987 genes were significantly deregulated in primary tumors compared to fallopian tubes, 845 genes were differentially expressed in metastasis compared to primary tumors and 304 genes were common to both. An assessment of patient metastasis and 3D omental culture model of early metastatic colonization revealed 144 common genes that were altered during early colonization and remain deregulated even in the fully developed metastasis. Deregulation of the matrisome was a key process in early and late metastasis.

CONCLUSION

These findings will help in understanding the key pathways involved in ovarian cancer progression and eventually targeting those pathways for therapeutic interventions.

Collagen (XI) alpha-1 chain is an independent prognostic factor in breast ductal carcinoma in situ

Collagen11A1 (COL11A1) is a fibrillary type collagen constituting a minor component of the extracellular matrix and plays role in tissue tensile strength. Overexpression of COL11A1 expression is associated with aggressive behavior and poor outcome in several human malignancies. In this study, we evaluated the association between COL11A1 expression and clinicopathological parameters of the breast ductal carcinoma in situ (DCIS) and its prognostic value. COL11A1 protein expression was assessed immunohistochemically in a large well-characterized cohort of DCIS including pure (n = 776) and DCIS associated with invasive carcinoma (DCIS-mixed, n = 239). COL11A1 expression was assessed in tumor cells and surrounding stromal cells, and correlated with clinicopathological parameters, immunoprofile and disease outcome. In pure DCIS, high COL11A1 expression was observed in tumor cells and surrounding stromal cells in 25 and 13% of cases, respectively. Higher COL11A1 expression within the stromal cells was associated with hormone receptor negative, HER2 enriched and triple negative molecular subtypes and showed a positive linear correlation with proliferation index, dense tumor infiltrating lymphocytes and hypoxia-inducible factor 1 alpha. COL11A1 expression in tumor and stromal cells was significantly higher in DCIS associated with invasive carcinoma than in pure DCIS, and within the DCIS-mixed cohort, the invasive component showed higher COL11A1 expression than the DCIS component (all, p < 0.0001). Overexpression of stromal COL11A1 was an independent predictor of shorter local recurrence-free interval for all recurrences (HR = 13.2, 95% CI = 6.9-25.4, p < 0.0001) and for invasive recurrences (HR = 11.2, 95% CI = 4.9-25.8, p < 0.0001). When incorporated with other risk factors, stromal COL11A1 provided better patient risk stratification. DCIS with higher stromal COL11A1 expression showed poor outcome even with adjuvant radiotherapy management. In conclusion, overexpression of stromal COL11A1 is associated with invasive recurrence in DCIS and is a potential marker to predict the response to radiotherapy.

The role of collagen in cancer: from bench to bedside

Collagen is the major component of the tumor microenvironment and participates in cancer fibrosis. Collagen biosynthesis can be regulated by cancer cells through mutated genes, transcription factors, signaling pathways and receptors; furthermore, collagen can influence tumor cell behavior through integrins, discoidin domain receptors, tyrosine kinase receptors, and some signaling pathways. Exosomes and microRNAs are closely associated with collagen in cancer. Hypoxia, which is common in collagen-rich conditions, intensifies cancer progression, and other substances in the extracellular matrix, such as fibronectin, hyaluronic acid, laminin, and matrix metalloproteinases, interact with collagen to influence cancer cell activity. Macrophages, lymphocytes, and fibroblasts play a role with collagen in cancer immunity and progression. Microscopic changes in collagen content within cancer cells and matrix cells and in other molecules ultimately contribute to the mutual feedback loop that influences prognosis, recurrence, and resistance in cancer. Nanoparticles, nanoplatforms, and nanoenzymes exhibit the expected gratifying properties. The pathophysiological functions of collagen in diverse cancers illustrate the dual roles of collagen and provide promising therapeutic options that can be readily translated from bench to bedside. The emerging understanding of the structural properties and functions of collagen in cancer will guide the development of new strategies for anticancer therapy.

Microarray‑based analysis of COL11A1 and TWIST1 as important differentially‑expressed pathogenic genes between left and right‑sided colon cancer

Colonic cancer has become a main reason of mortality associated with cancer; however, left and right-sided colonic cancer have diverse outcomes in terms of epidemiological, histological, clinical parameters and prognosis. We aimed to examine the discrepancies between these two types of colon cancers to identify potential therapeutic targets. In the present study, three gene expression profiles (GSE44076, GSE31595, GSE26906) from Gene Expression Omnibus (GEO) database were downloaded and further analyzed. A PPI (protein-protein interaction) network of the differentially-expressed genes (DEGs) of GSE44076 between tumor and normal was established with the Search Tool for the Retrieval of Interacting Genes database. Then, the DEGs of these two colon cancers (left, right) samples were identified. Subsequently, the intersection of DEGs of left and right-sided colon cancer samples obtained from three databases, and DEGs of tumor and normal samples were analyzed. Collagen type XI α1 chain (COL11A1), Twist family bHLH transcription factor 1 (TWIST1), insulin-like 5 and chromogranin A were upregulated proteins, while 3β-hydroxysteroid dehydrogenase was downregulated protein in right colon cancer than in left-sided tumor samples. Through further experimental verification, we revealed that COL11A1 and TWIST1 were significantly upregulated at the mRNA and protein levels within right-sided colon cancer compared with in left-sided colon cancer samples (P<0.05), consistent with bioinformatical analysis. Furthermore, a positive correlation between COL11A1 and TWIST1 protein expression was observed (P<0.0276). Collectively, our data showed that COL11A1 and TWIST1 may be potential prognostic indicators and molecular targets for the treatment of right-sided colon cancer.

Study of Gene Expression Profiles of Breast Cancers in Indian Women

Breast cancer is the most common cancer among women globally. In India, the incidence of breast cancer has increased significantly during the last two decades with a higher proportion of the disease at a young age compared to the west. To understand the molecular processes underlying breast cancer in Indian women, we analysed gene expression profiles of 29 tumours and 9 controls using microarray. In the present study, we obtained 2413 differentially expressed genes, consisting of overexpressed genes such as COL10A1, COL11A1, MMP1, MMP13, MMP11, GJB2, and CST1 and underexpressed genes such as PLIN1, FABP4, LIPE, AQP7, LEP, ADH1A, ADH1B, and CIDEC. The deregulated pathways include cell cycle, focal adhesion and metastasis, DNA replication, PPAR signaling, and lipid metabolism. Using PAM50 classifier, we demonstrated the existence of molecular subtypes in Indian women. In addition, qPCR validation of expression of metalloproteinase genes, MMP1, MMP3, MMP11, MMP13, MMP14, ADAMTS1, and ADAMTS5 showed concordance with that of the microarray data; wherein we found a significant association of ADAMTS5 down-regulation with older age (≥55 years) of patients. Together, this study reports gene expression profiles of breast tumours from the Indian subcontinent, throwing light on the pathways and genes associated with the breast tumourigenesis in Indian women.

Chemotherapy Resistance in Advanced Ovarian Cancer Patients

Ovarian cancer is the seventh most common gynaecologic malignancy seen in women. Majority of the patients with ovarian cancer are diagnosed at the advanced stage making prognosis poor. The standard management of advanced ovarian cancer includes tumour debulking surgery followed by chemotherapy. Various types of chemotherapeutic regimens have been used to treat advanced ovarian cancer, but the most promising and the currently used standard first-line treatment is carboplatin and paclitaxel. Despite improved clinical response and survival to this combination of chemotherapy, numerous patients either undergo relapse or succumb to the disease as a result of chemotherapy resistance. To understand this phenomenon at a cellular level, various macromolecules such as DNA, messenger RNA and proteins have been developed as biomarkers for chemotherapy response. This review comprehensively summarizes the problem that pertains to chemotherapy resistance in advanced ovarian cancer and provides a good overview of the various biomarkers that have been developed in this field.

Molecular profiling of mucinous epithelial ovarian cancer by weighted gene co-expression network analysis

PURPOSE

In order to identify the molecular characteristics and improve the efficacy of early diagnosis of mucinous epithelial ovarian cancer (mEOC), here, the transcriptome profiling by weighted gene co-expression network analysis (WGCNA) has been proposed as an effective method.

METHODS

The gene expression dataset GSE26193 was reanalyzed with a systematical approach, WGCNA. mEOC-related gene co-expression modules were detected and the functional enrichments of these modules were performed at GO and KEGG terms. Ten hub genes in the mEOC-related modules were validated using two independent datasets GSE44104 and GSE30274.

RESULTS

11 co-expressed gene modules were identified by WGCNA based on 4917 genes and 99 epithelial ovarian cancer samples. The turquoise module was found to be significantly associated with the subtype of mEOC. KEGG pathway enrichment analysis showed genes in the turquoise module significantly enriched in metabolism of xenobiotics by cytochrome P450 and steroid hormone biosynthesis. Ten hub genes (LIPH, BCAS1, FUT3, ZG16B, PTPRH, SLC4A4, MUC13, TFF1, HNF4G and TFF2) in the turquoise module were validated to be highly expressed in mEOC using two independent gene expression datasets GSE44104 and GSE30274.

CONCLUSION

Our work proposed an applicable framework of molecular characteristics for patients with mEOC, which may help us to obtain a precise and comprehensive understanding on the molecular complexities of mEOC. The hub genes identified in our study, as potential specific biomarkers of mEOC, may be applied in the early diagnosis of mEOC in the future.

Clinical significance of LOXL4 expression and features of LOXL4-associated protein-protein interaction network in esophageal squamous cell carcinoma

Lysyl oxidase-like 4 (LOXL4), a member of the LOX family proteins, catalyzes oxidative deamination of lysine residues in collagen and elastin, which are responsible for maintaining extracellular matrix homeostasis. In this study, the mRNA expression of LOXL4 in seven esophageal squamous cell carcinoma (ESCC) cell lines and 15 ESCC pairs of clinical samples were examined. Furthermore, LOXL4 protein levels in the ESCC cell lines were determined using western blotting. With the use of immunofluorescence, LOXL4 was observed to be localized primarily in the cytoplasm, but was also present in the nucleus. In addition, the results indicated that the upregulated expression of LOXL4 was associated with poor survival in patients with ESCC even following curative resection (P = 0.010). Similar Kaplan-Meier estimator curves for proteins that interact with LOXL4, SUV39H1 (P = 0.014) and COL2A1 (P = 0.011), were plotted. The analyses based on the protein-protein interaction network depicted the expression of LOXL4 and its associated proteins as well as their functions, suggesting that LOXL4 and its associated proteins may serve a significant role in the development and progression of ESCC. In conclusion, the results of the present study suggest that LOXL4 is a potential biomarker for patients with ESCC, as well as SUV39H1 and COL2A1, and high expression levels of these genes are associated with poor prognosis in patients with ESCC.

Identification of Important Invasion-Related Genes in Non-functional Pituitary Adenomas

Non-functioning pituitary adenomas (NFPAs) are locally invasive with high morbidity. The objective of this study was to diagnose important genes and pathways related to the invasiveness of NFPAs and gain more insights into the underlying molecular mechanisms of NFPAs. The gene expression profiles of GSE51618 were downloaded from the Gene Expression Omnibus database with 4 non-invasive NFPA samples, 3 invasive NFPA samples, and 3 normal pituitary gland samples. Differentially expressed genes (DEGs) are screened between invasive NFPA samples and normal pituitary gland samples, followed by pathway and ontology (GO) enrichment analyses. Subsequently, a protein-protein interaction (PPI) network was constructed and analyzed for these DEGs, and module analysis was performed. In addition, a target gene-miRNA network and target gene-TF (transcription factor) network were analyzed for these DEGs. A total of 879 DEGs were obtained. Among them, 439 genes were upregulated and 440 genes were downregulated. Pathway enrichment analysis indicated that the upregulated genes were significantly enriched in cysteine biosynthesis/homocysteine degradation (trans-sulfuration) and PI3K-Akt signaling pathway, while the downregulated genes were mainly associated with docosahexaenoate biosynthesis III (mammals) and chemokine signaling pathway. GO enrichment analysis indicated that the upregulated genes were significantly enriched in animal organ morphogenesis, extracellular matrix, and hormone activity, while the downregulated genes were mainly associated with leukocyte chemotaxis, dendrites, and RAGE receptor binding. Subsequently, ESR1, SOX2, TTN, GFAP, WIF1, TTR, XIST, SPAG5, PPBP, AR, IL1R2, and HIST1H1C were diagnosed as the top hub genes in the upregulated and downregulated PPI networks and modules. In addition, HS3ST1, GPC4, CCND2, and SCD were diagnosed as the top hub genes in the upregulated and downregulated target gene-miRNA networks, while CISH, ISLR, UBE2E3, and CCNG2 were diagnosed as the top hub genes in the upregulated and downregulated target gene-TF networks. The new important DEGs and pathways diagnosed in this study may serve key roles in the invasiveness of NFPAs and indicate more molecular targets for the treatment of NFPAs.

Akt inhibitor SC66 promotes cell sensitivity to cisplatin in chemoresistant ovarian cancer cells through inhibition of COL11A1 expression

We studied Akt inhibition using SC66 in a NOD-SCID xenograft mouse model and a panel of eight ovarian cancer cell lines. Elevated phospho-Akt levels in cancerous tissue were associated with short progression-free survival and overall survival. Cell sensitivity to SC66 was inversely correlated with phospho-Akt and COL11A1 expression levels, as well as resistance to cisplatin or paclitaxel. SC66 inhibited phosphorylation of Akt and its downstream effectors 4EBP1 and p70S6 kinase. SC66 also attenuated expression of TWIST1 and Mcl-1, factors important in cell invasiveness and anti-apoptosis, respectively. SC66-sensitized chemoresistant cells to cisplatin and paclitaxel treatment, and promoted apoptosis. In addition, SC66 inhibited COL11A1 expression via decreased binding of CCAAT/enhancer-binding protein beta (c/EBPβ), reducing chemoresistance and decreasing binding of nuclear transcription factor Y (NF-YA) to COL11A1. A mouse xenograft experiment demonstrated that SC66 treatment caused a reduction in tumor formation and enhanced the therapeutic efficacy of cisplatin. This study demonstrates the role of Akt in ovarian tumor progression and chemoresistance, and supports the application of SC66 as a therapy for ovarian cancer.

Functional and transcriptomic characterization of carboplatin-resistant A2780 ovarian cancer cell line

Background

Ovarian cancer is a significant cancer-related cause of death in women worldwide. The most used chemotherapeutic regimen is based on carboplatin (CBDCA). However, CBDCA resistance is the main obstacle to a better prognosis. An in vitro drug-resistant cell model would help in the understanding of molecular mechanisms underlying this drug-resistance phenomenon. The aim of this study was to characterize cellular and molecular changes of induced CBDCA-resistant ovarian cancer cell line A2780.

Methods

The cell selection strategy used in this study was a dose-per-pulse method using a concentration of 100 μM for 2 h. Once 20 cycles of exposure to the drug were completed, the cell cultures showed a resistant phenotype. Then, the ovarian cancer cell line A2780 was grown with 100 μM of CBDCA (CBDCA-resistant cells) or without CBDCA (parental cells). After, a drug sensitivity assay, morphological analyses, cell death assays and a RNA-seq analysis were performed in CBDCA-resistant A2780 cells.

Results

Microscopy on both parental and CBDCA-resistant A2780 cells showed similar characteristics in morphology and F-actin distribution within cells. In cell-death assays, parental A2780 cells showed a significant increase in phosphatidylserine translocation and caspase-3/7 cleavage compared to CBDCA-resistant A2780 cells (P < 0.05 and P < 0.005, respectively). Cell viability in parental A2780 cells was significantly decreased compared to CBDCA-resistant A2780 cells (P < 0.0005). The RNA-seq analysis showed 156 differentially expressed genes (DEGs) associated mainly to molecular functions.

Conclusion

CBDCA-resistant A2780 ovarian cancer cells is a reliable model of CBDCA resistance that shows several DEGs involved in molecular functions such as transmembrane activity, protein binding to cell surface receptor and catalytic activity. Also, we found that the Wnt/β-catenin and integrin signaling pathway are the main metabolic pathway dysregulated in CBDCA-resistant A2780 cells.

Electronic supplementary material

The online version of this article (10.1186/s40659-019-0220-0) contains supplementary material, which is available to authorized users.

Collagens and Cancer associated fibroblasts in the reactive stroma and its relation to Cancer biology

The extracellular matrix (ECM) plays an important role in cancer progression. It can be divided into the basement membrane (BM) that supports epithelial/endothelial cell behavior and the interstitial matrix (IM) that supports the underlying stromal compartment. The major components of the ECM are the collagens. While breaching of the BM and turnover of e.g. type IV collagen, is a well described part of tumorigenesis, less is known regarding the impact on tumorigenesis from the collagens residing in the stroma. Here we give an introduction and overview to the link between tumorigenesis and stromal collagens, with focus on the fibrillar collagens type I, II, III, V, XI, XXIV and XXVII as well as type VI collagen. Moreover, we discuss the impact of the cells responsible for this altered stromal collagen remodeling, the cancer associated fibroblasts (CAFs), and how these cells are key players in orchestrating the tumor microenvironment composition and tissue microarchitecture, hence also driving tumorigenesis and affecting response to treatment. Lastly, we discuss how specific collagen-derived biomarkers reflecting the turnover of stromal collagens and CAF activity may be used as tools to non-invasively interrogate stromal reactivity in the tumor microenvironment and predict response to treatment.

Gene expression profiling of spontaneously occurring canine mammary tumours: Insight into gene networks and pathways linked to cancer pathogenesis

Spontaneously occurring canine mammary tumours (CMTs) are the most common neoplasms of unspayed female dogs leading to thrice higher mortality rates than human breast cancer. These are also attractive models for human breast cancer studies owing to clinical and molecular similarities. Thus, they are important candidates for biomarker studies and understanding cancer pathobiology. The study was designed to explore underlying molecular networks and pathways in CMTs for deciphering new prognostic factors and therapeutic targets. To gain an insight into various pathways and networks associated with the development and pathogenesis of CMTs, comparative cDNA microarray expression profiling was performed using CMT tissues and healthy mammary gland tissues. Upon analysis, 1700 and 1287 differentially expressed genes (DEGs, P ≤ 0.05) were identified in malignant and benign tissues, respectively. DEGs identified from microarray analysis were further annotated using the Ingenuity Systems Pathway Analysis (IPA) tool for detection of deregulated canonical pathways, upstream regulators, and networks associated with malignant, as well as, benign disease. Top scoring key networks in benign and malignant mammary tumours were having central nodes of VEGF and BUB1B, respectively. Cyclins & cell cycle regulation and TREM1 signalling were amongst the top activated canonical pathways in CMTs. Other cancer related significant pathways like apoptosis signalling, dendritic cell maturation, DNA recombination and repair, Wnt/β-catenin signalling, etc. were also found to be altered. Furthermore, seven proteins (ANXA2, APOCII, CDK6, GATC, GDI2, GNAQ and MYH9) highly up-regulated in malignant tissues were identified by two-dimensional gel electrophoresis (2DE) and MALDI-TOF PMF studies which were in concordance with microarray data. Thus, the study has uncovered ample number of candidate genes associated with CMTs which need to be further validated as therapeutic targets and prognostic markers.

Integrated transcriptome interactome study of oncogenes and tumor suppressor genes in breast cancer

Breast cancer is the leading cause for mortality among women worldwide. Dysregulation of oncogenes and tumor suppressor genes is the major reason for the cause of cancer. Understanding these genes will provide clues and insights about their regulatory mechanism and their interplay in cancer. In the present study, an attempt is made to compare the functional characteristics and interactions of oncogenes and tumor suppressor genes to understand their biological role. 431 breast cancer samples from seven publicly available microarray datasets were collected and analysed using GEO2R tool. The identified 416 differentially expressed genes were classified into five gene sets as oncogenes (OG), tumor suppressor genes (TSG), druggable genes, essential genes and other genes. The gene sets were subjected to various analysis such as enrichment analysis (viz., GO, Pathways, Diseases and Drugs), network analysis, calculation of mutation frequencies and Guanine-Cytosine (GC) content. From the results, it was observed that the OG were having high GC content as well as high interactions than TSG. Moreover, the OG are found to have frequent mutations than TSG. The enrichment analysis results suggest that the oncogenes are involved in positive regulation of cellular protein metabolic process, macromolecule biosynthetic process and majorly in cell cycle and focal adhesion pathway in cancer. It was also found that these oncogenes are involved in other diseases such as skin diseases and viral infections. Collagenase, paclitaxel and docetaxel are some of the drugs found to be enriched for oncogenes.

Adaptively capturing the heterogeneity of expression for cancer biomarker identification

Background

Identifying cancer biomarkers from transcriptomics data is of importance to cancer research. However, transcriptomics data are often complex and heterogeneous, which complicates the identification of cancer biomarkers in practice. Currently, the heterogeneity still remains a challenge for detecting subtle but consistent changes of gene expression in cancer cells.

Results

In this paper, we propose to adaptively capture the heterogeneity of expression across samples in a gene regulation space instead of in a gene expression space. Specifically, we transform gene expression profiles into gene regulation profiles and mathematically formulate gene regulation probabilities (GRPs)-based statistics for characterizing differential expression of genes between tumor and normal tissues. Finally, an unbiased estimator (aGRP) of GRPs is devised that can interrogate and adaptively capture the heterogeneity of gene expression. We also derived an asymptotical significance analysis procedure for the new statistic. Since no parameter needs to be preset, aGRP is easy and friendly to use for researchers without computer programming background. We evaluated the proposed method on both simulated data and real-world data and compared with previous methods. Experimental results demonstrated the superior performance of the proposed method in exploring the heterogeneity of expression for capturing subtle but consistent alterations of gene expression in cancer.

Conclusions

Expression heterogeneity largely influences the performance of cancer biomarker identification from transcriptomics data. Models are needed that efficiently deal with the expression heterogeneity. The proposed method can be a standalone tool due to its capacity of adaptively capturing the sample heterogeneity and the simplicity in use.

Software availability

The source code of aGRP can be downloaded from https://github.com/hqwang126/aGRP.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2437-2) contains supplementary material, which is available to authorized users.

Identification of COL1A1 as an invasion‑related gene in malignant astrocytoma

Malignant astrocytoma (MA) is the most common and severe type of brain tumor. A greater understanding of the underlying mechanisms responsible for the development of MA would be beneficial for the development of targeted molecular therapies. In the present study, the upregulated differentially expressed genes (DEGs) in MA were obtained from the Gene Expression Omnibus database using R/Bioconductor software. DEGs in different World Health Organization classifications were compared using the Venny tool and 15 genes, including collagen type I α1 chain (COL1A1) and laminin subunit γ1 (LAMC1), were revealed to be involved in the malignant progression of MA. In addition, the upregulated DEGs in MA were evaluated using functional annotations of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes with the Database for Annotation, Visualization, and Integrated Discovery tool. The results indicated that invasion-associated enrichment was observed in 'extracellular matrix' (ECM), 'cell adhesion' and 'phosphoinositide 3-kinase-protein kinase B signaling pathway'. Subsequently, the analysis of the protein-protein interactions was performed using STRING and Cytoscape software, which revealed that the ECM component was the invasion-associated module and its corresponding genes included COL1A1, LAMC1 and fibronectin 1. Finally, survival Kaplan-Meier estimate was conducted using cBioportal online, which demonstrated that COL1A1 expression affected the survival of and recurrence in patients with MA. Moreover, the results of in vitro Transwell assay and western blot analysis revealed that the depleted levels of COL1A1 also decreased the expression of several proteins associated with cell invasion, including phosphorylated-signal transducer and activator of transcription 3, matrix metalloproteinase (MMP)-2, MMP-9 and nuclear factor-κB. On the whole, the present study identified the invasion-related target genes and the associated potential pathways in MA. The results indicated that COL1A1 may be a candidate biomarker for the prognosis and treatment of MA.