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

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.

Application of weighted gene co-expression network analysis to identify key modules and hub genes in oral squamous cell carcinoma tumorigenesis

Purpose

Oral squamous cell carcinoma (OSCC) is one of the most common malignant diseases worldwide, yet its molecular mechanisms are largely unknown. We aimed to construct gene co-expression networks to identify key modules and hub genes involved in the pathogenesis of OSCC.

Patients and methods

We used dataset GSE30784 to construct co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). Hub genes were screened and validated by other datasets.

Results

Turquoise and brown modules were found to be the most significantly related to tumorigenesis. Functional enrichment analysis showed that the turquoise module was associated with cell–cell adhesion, extracellular matrix and collagen catabolic process. A total of 10 hub genes (MMP1, TNFRSF12A, PLAU, FSCN1, PDPN, KRT78, EVPL, GGT6, SMIM5 and CYSRT1) were identified and validated at transcriptional and translational levels. Their genetic alteration and survival analysis were also revealed.

Conclusion

We identified two modules and 10 hub genes, which were associated with the tumorigenesis of OSCC. The two modules provided references that will advance the understanding of mechanisms of tumorigenesis in OSCC. Moreover, the hub genes may serve as biomarkers and therapeutic targets for precise diagnosis and treatment of OSCC in the future.

Establishment of a SVM classifier to predict recurrence of ovarian cancer

Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of interest and a support vector machine (SVM) classifier was subsequently established to predict the recurrence of OC. Three datasets (GSE17260, GSE44104 and GSE51088) investigating OC gene expression were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) in samples from patients with non-recurrent and recurrent OC were revealed via a homogeneity test and quality control analysis. A protein-protein interaction (PPI) network was subsequently established for the DEGs using data from Biological General Repository for Interaction Datasets, Human Protein Reference Database and Database of Interacting Proteins. Degrees of interaction and betweenness centrality (BC) scores were calculated for each node in the PPI network. The top 100 genes ranked by BC scores were selected to identify feature genes via recursive feature elimination using the GSE17260 dataset. Following this, a SVM classifier was constructed and further validated using the GSE44104 and GSE51088 datasets and independent gene expression data obtained from the Cancer Genome Atlas (TCGA). A total of 639 DEGs were identified from the three gene expression datasets, and a PPI network including 249 nodes and 354 edges was constructed. A SVM classifier consisting of 39 feature genes (including cullin 3, mouse double minute 2 homolog, aurora kinase A, WW domain containing oxidoreducatase, large tumor suppressor kinase 2, sirtuin 6, staphylococcal nuclease and tudor domain containing 1, leucine rich repeats and immunoglobulin like domains 1 and aurora kinase 1 interacting protein 1) was subsequently constructed. The prediction accuracies of the SVM classifier for GSE17260, GSE44104 and GSE51088 datasets as well as data downloaded from TCGA were revealed to be 92.7, 93.3, 96.6 and 90.4%, respectively. Furthermore, the results of the present study revealed that patients with predicted non-recurrent OC survived significantly longer compared with the patients with predicted recurrent OC (P=6.598×10⁻⁶). A SVM classifier consisting of 39 feature genes was established for predicting the recurrence and prognosis of OC. Therefore, the results of the present study suggested that the 39 feature genes may serve important roles in the development of OC and may represent therapeutic biomarkers of OC.

The inhibitory effects of COL1A2 on colorectal cancer cell proliferation, migration, and invasion

Purpose: Collagen type I alpha 2 chain (COL1A2) has been shown to participate in the development of various human malignancies. However, the role of COL1A2 in human colorectal cancer (CRC) remains unknown. This study investigated the expression pattern of COL1A2 in primary CRC tissues as well as the correlation of COL1A2 expression with clinicopathological features and prognosis of CRC. The function of COL1A2 in CRC cell proliferation, migration, and invasion as well as the possible mechanisms were also examined. Methods: Real-time PCR and immunohistochemical analysis were performed to determine the expression of COL1A2 in primary cancer tissues and adjacent normal tissues from CRC patients. A COL1A2-expressing lentiviral vector was transfected into CRC cells, and cell counting kit-8 and Transwell assays were used to explore the effects of COL1A2 on CRC cell proliferation, migration, and invasion. Microarray-based mRNA expression profile screening was performed to reveal the possible signaling pathways involved in COL1A2-regulated cell behaviors. Results: COL1A2 was significantly downregulated in primary CRC tissues. The mRNA levels of COL1A2 in CRC tissues were correlated with tumor differentiation, invasion, and lymph node metastasis. Overexpression of COL1A2 inhibited proliferation, migration, and invasion of CRC cell lines (SW480 and SW620). The microarray analysis showed that COL1A2 overexpression regulated numerous oncogenes and cancer-related signaling pathways. Among them, altered expression of ten representative cancer-related genes in these pathways were further confirmed by western blotting. Conclusions: Our study identified COL1A2 as a novel tumor suppressor in CRC and provided a potential therapeutic approach to treat CRC.

Aspirin is Involved in the Cell Cycle Arrest, Apoptosis, Cell Migration, and Invasion of Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. In China, its 5-year survival rate is roughly 50%, owing to acquired chemotherapeutic resistance and metastasis of the disease. Accumulating evidence demonstrates that aspirin (ASA) acts as a preventive or therapeutic agent in multiple cancers; however, anti-tumor activities induced by aspirin are unclear in OSCC. To investigate the possible role of aspirin in OSCC development, we first employed bioinformatics to analyze the anti-OSCC effects of aspirin. We performed a genetic oncology (GO) enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), and the protein⁻protein interaction (PPI) network analysis by Cytoscape for differentially expressed genes (DEGs). We also evaluated the potential effects of aspirin on cell proliferation, invasion, migration, and apoptosis in two well-characterized OSCC cell lines (TCA8113 and CAL27). The bioinformatic results revealed that aspirin could inhibit proliferation by blocking the cell cycle, and could reduce migration and invasion via the PI3K-Akt and focal adhesion pathways. We found that ASA could downregulate the OSCC cell proliferation colony formation, invasion, and migration, as well as upregulate apoptosis. Furthermore, we found that ASA suppressed the activation of the focal adhesion kinase (FAK) and the phosphorylation of Akt, NF-κB, and STAT3. Overall, our data suggested that ASA may be developed as a chemopreventive agent to effectively treat OSCC.

Transcriptomic Characterization of Endometrioid, Clear Cell, and High-Grade Serous Epithelial Ovarian Carcinoma

Background: Endometrioid carcinoma (EC) and clear cell carcinoma (CC) histotypes of epithelial ovarian cancer are understudied compared with the more common high-grade serous carcinomas (HGSC). We therefore sought to characterize EC and CC transcriptomes in relation to HGSC.Methods: Following bioinformatics processing and gene abundance normalization, differential expression analysis of RNA sequence data collected on fresh-frozen tumors was completed with nonparametric statistical analysis methods (55 ECs, 19 CCs, 112 HGSCs). Association of gene expression with progression-free survival (PFS) was completed with Cox proportional hazards models. Eight additional multi-histotype expression array datasets (N = 852 patients) were used for replication.Results: In the discovery set, tumors generally clustered together by histotype. Thirty-two protein-coding genes were differentially expressed across histotype (P < 1 × 10^-10) and showed similar associations in replication datasets, including MAP2K6, KIAA1324, CDH1, ENTPD5, LAMB1, and DRAM1 Nine genes associated with PFS (P < 0.0001) showed similar associations in replication datasets. In particular, we observed shorter PFS time for CC and EC patients with high gene expression for CCNB2, CORO2A, CSNK1G1, FRMD8, LIN54, LINC00664, PDK1, and PEX6, whereas, the converse was observed for HGSC patients.Conclusions: The results suggest important histotype differences that may aid in the development of treatment options, particularly those for patients with EC or CC.Impact: We present replicated findings on transcriptomic differences and how they relate to clinical outcome for two of the rarer ovarian cancer histotypes of EC and CC, along with comparison with the common histotype of HGSC. Cancer Epidemiol Biomarkers Prev; 27(9); 1101-9. ©2018 AACR.

Targeting FXYD2 by cardiac glycosides potently blocks tumor growth in ovarian clear cell carcinoma

Ovarian clear cell carcinoma (OCCC) is an aggressive neoplasm with a high recurrence rate that frequently develops resistance to platinum-based chemotherapy. There are few prognostic biomarkers or targeted therapies exist for patients with OCCC. Here, we identified that FXYD2, the modulating subunit of Na⁺/K⁺-ATPases, was highly and specifically expressed in clinical OCCC tissues. The expression levels of FXYD2 were significantly higher in advanced-stage of OCCC and positively correlated with patients' prognoses. Silencing of FXYD2 expression in OCCC cells inhibited Na⁺/K⁺-ATPase enzyme activity and suppressed tumor growth via induction of autophagy-mediated cell death. We found that high FXYD2 expression in OCCC was transcriptionally regulated by the transcriptional factor HNF1B. Furthermore, up-regulation of FXYD2 expression significantly increased the sensitivity of OCCC cells to cardiac glycosides, the Na⁺/K⁺-ATPase inhibitors. Two cardiac glycosides, digoxin and digitoxin, had a great therapeutic efficacy in OCCC cells in vitro and in vivo. Taken together, our results demonstrate that FXYD2 is functionally upregulated in OCCC and may serve as a promising prognostic biomarker and therapeutic target of cardiac glycosides in OCCC.

Inhibitor of apoptosis proteins (IAPs) mediate collagen type XI alpha 1-driven cisplatin resistance in ovarian cancer

Although, cisplatin resistance is a major challenge in the treatment of ovarian cancer, the precise mechanisms underlying cisplatin resistance are not fully understood. Collagen type XI alpha 1 (COL11A1), a gene encoding a minor fibrillar collagen of the extracellular matrix, is identified as one of the most upregulated genes in cisplatin-resistant ovarian cancer and recurrent ovarian cancer. However, the exact functions of COL11A1 in cisplatin resistance are unknown. Here we demonstrate that COL11A1 binds to integrin α1β1 and discoidin domain receptor 2 (DDR2) and activates downstream signaling pathways to inhibit cisplatin-induced apoptosis in ovarian cancer cells. Mechanistically, we show that COL11A1 activates Src-PI3K/Akt-NF-kB signaling to induce the expression of three inhibitor apoptosis proteins (IAPs), including XIAP, BIRC2, and BIRC3. Genetic and pharmacological inhibition of XIAP, BIRC2, and BIRC3 is sufficient to restore cisplatin-induced apoptosis in ovarian cancer cells in the presence of COL11A1 in ovarian cancer cells and xenograft mouse models, respectively. We also show that the components of COL11A1- integrin α1β1/DDR2- Src-PI3K/Akt-NF-kB-IAP signaling pathway serve as poor prognosis markers in ovarian cancer patients. Taken together, our results suggest novel mechanisms by which COL11A1 confers cisplatin resistance in ovarian cancer. Our study also uncovers IAPs as promising therapeutic targets to reduce cisplatin resistance in ovarian cancer, particularly in recurrent ovarian cancer expressing high levels of COL11A1.

An Immunophenotyping of Ovarian Cancer With Clinical and Immunological Significance

Immune checkpoint blockade (ICB), mainly anti-CTLA-4 and anti-PD-1/PD-L1 therapy, has showed promising clinical benefits in the treatment of some cancer types; however, its application in ovarian cancer is still in the primary stage. Immunophenotyping can help us understand the clinical characteristics and immune status of cancer, and thus benefit immunotherapy and personalized therapy. In this study, we clustered 907 ovarian cancer patients into three immune molecular subtypes (IMMSs) based on 48 genes. Expression data were downloaded from the Gene Expression Omnibus database. Unsupervised consensus clustering was used to identify IMMS. Clinical and immunological characteristics and gene expression patterns of different IMMS were compared, and associations between IMMS and tumor microenvironment immune types were explored. Three IMMSs with different clinical and immunological characteristics were identified, in which type I and II ovarian cancer patients were similar to each other. There were more serous and low-grade tumors in type I and II ovarian cancer. IMMS was associated with disease-free survival before and after adjusting for clinical characteristics and ICB-related genes. Among the differentially expressed genes identified in our study, about 90% (25/28) were highly expressed in type I and II ovarian cancer. Genes related to ICB (CTLA-4, PD-L1, and PD-L2) and cytotoxic lymphocytes (CD8A, GZMA, and PRF1) were all highly expressed in type I and II ovarian cancer. Patients with type I and II ovarian cancer may be more sensitive to anti-CTLA-4 therapy, anti-PD-1/PD-L1 therapy, and a combination of immunotherapies. In contrast, patients with type III ovarian cancer may be insensitive to these treatments and require new therapies.

A 65‑gene signature for prognostic prediction in colon adenocarcinoma

The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination efficacy of the system was validated in the GSE17538 dataset using Kaplan‑Meier survival analysis. A total of 636 and 1,892 DEGs between the colon cancer samples and normal samples were screened from the TCGA and GSE44861 dataset, respectively. There were 155 survival‑related genes selected. The co‑expression network of survival‑related genes included 138 genes, 534 lines (connections) and five functional clusters, including the signaling pathway, cellular response to cAMP, and immune system process functional clusters. The molecular function, cellular components and biological processes were the significantly enriched functions. The peroxisome proliferator‑activated receptor signaling pathway, Wnt signaling pathway, B cell receptor signaling pathway, and cytokine‑cytokine receptor interactions were the significant pathways. A prognostic prediction system based on a 65‑gene signature was established using this co‑expression network. Its discriminatory effect was validated in the TCGA dataset (P=3.56e‑12) and the GSE17538 dataset (P=1.67e‑6). The 65‑gene signature included kallikrein‑related peptidase 6 (KLK6), collagen type XI α1 (COL11A1), cartilage oligomeric matrix protein, wingless‑type MMTV integration site family member 2 (WNT2) and keratin 6B. In conclusion, a 65‑gene signature was screened in the present study, which showed a prognostic prediction effect in colon adenocarcinoma. KLK6, COL11A1, and WNT2 may be suitable prognostic predictors for colon adenocarcinoma.

High expression of COL10A1 is associated with poor prognosis in colorectal cancer

Background

High expression of collagen type X alpha 1 chain (COL10A1), a member of the collagen family, had been observed in various human cancers, but the detailed function and molecular mechanism of COL10A1 were largely unclear.

Aim

The aim of this study was to investigate the expression of COL10A1 in colorectal cancer (CRC) tissues and cells and to reveal its biological function and mechanism in CRC.

Materials and methods

Immunohistochemistry (IHC), real-time quantitative polymerase chain reaction (QPCR) and Western blot experiments were used to determine the clinical relevance between expression levels of COL10A1 and CRC.

Results

Compared with normal tissues, COL10A1 expression was significantly higher in CRC tissues. Biological functional experiments showed that overexpression of COL10A1 enhanced proliferation, migration, and invasion of CRC cells, and knockdown of COL10A1 inhibited tumorigenesis in vivo. Western blot assays showed that COL10A1 promoted the process of epithelial–mesenchymal transition (EMT). The overexpression of COL10A1 was associated with adverse prognosis in CRC by tissue microarray (TMA) analysis.

Conclusion

Our findings had provided evidences to support the fact that COL10A1 was abnormally up-expressed in CRC and involved in the progression of CRC and the process of EMT. Furthermore, we demonstrated that the high-level expression of COL10A1 was an independent risk factor of prognosis and overall survival in CRC patients. These suggested that COL10A1 might be a new potential target for cancer therapy in the future.

Vitamin D-Binding Protein Enhances Epithelial Ovarian Cancer Progression by Regulating the Insulin-like Growth Factor-1/Akt Pathway and Vitamin D Receptor Transcription

Purpose: Malignant ascites of epithelial ovarian cancer (EOC) helps identify prognostic biomarkers or mechanisms of tumor progression. Vitamin D-binding protein (DBP) was revealed to be upregulated in EOC ascites in our previous proteomic study. Here, we examined the role of DBP in EOC.Experimental Design: We analyzed ascites, serum, and tissue samples of patients with newly diagnosed EOC to determine the prognostic effects of DBP. We verified DBP function using orthotopic animal models and DBP regulation in ovarian cancer cell lines.Results: Elevated ascitic DBP was significantly associated with poor response to chemotherapy, short progression-free interval, increased cancer progression, and death. Ascitic DBP overexpression was an independent unfavorable biomarker for progression-free survival; DBP overexpression in cancerous tissue was significantly related to chemoresistance. In vivo and in vitro investigations demonstrated an important role for DBP in ovarian cancer progression. Orthotopic model mice inoculated with DBP knockdown ovarian cancer cells displayed a significant reduction in tumor formation, malignant cell number, ascitic DBP levels, invasiveness, and metastasis, and increased survival compared with controls. In presence of vitamin D receptor (VDR), DBP promoted cell aggression (invasion and doubling time) via activation of the insulin-like growth factor-1/insulin-like growth factor-binding protein-2/Akt axis, and induced suppression of vitamin D-responsive genes. A NF-κB p65-binding site in the VDR promoter was identified as a major determinant of DBP-dependent VDR promoter activation.Conclusions: This study highlights the importance of DBP in ovarian tumor progression and the potential application of DBP as a therapeutic target for EOC. Clin Cancer Res; 24(13); 3217-28. ©2018 AACR.

Multiple mutations of lung squamous cell carcinoma shared common mechanisms

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell lung cancers which is the cause of 80% of all lung cancer deaths. The genes that highly mutated in patients with LUSC and their roles played in the tumorigenesis remains unknown. Data of patients with Lung squamous cell carcinoma (LUSC) were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified between control and cancer samples. Patients and controls can be separated by mRNA expression level showing that the between-group variance and totally 1265 genes were differentially expressed between controls and patients. Top genes whose mutations highly occurred in patients with LUSC were identified, most of these genes were shown to be related with tumorigenesis in previous studies. All of the genes mostly mutated were independently correlated with expression levels of all genes. These mutations did not show the trend of co-occurrence. However, the influenced gene of these mutations had overlaps. After studying the intersection of these genes, a group of shared genes were identified. The shared pathways enriched which played critical role in LUSC were identified based on these shared genes. Different mutations had contribution to the progression of LUSC. Though these genes involved different specific mechanisms, most of them may share a common mechanism which is critical for LUSC. The results may suggest a neglected mechanism and also indicate a potential target for therapies.

A core matrisome gene signature predicts cancer outcome

BACKGROUND

Accumulating evidence implicates the tumour stroma as an important determinant of cancer progression but the protein constituents relevant for this effect are unknown. Here we utilised a bioinformatics approach to identify an extracellular matrix (ECM) gene signature overexpressed in multiple cancer types and strongly predictive of adverse outcome.

METHODS

Gene expression levels in cancers were determined using Oncomine. Geneset enrichment analysis was performed using the Broad Institute desktop application. Survival analysis was performed using KM plotter. Survival data were generated from publically available genesets.

RESULTS

We analysed ECM genes significantly upregulated across a large cohort of patients with ovarian, lung, gastric and colon cancers and defined a signature of nine commonly upregulated genes. Each of these nine genes was considerably overexpressed in all the cancers studied, and cumulatively, their expression was associated with poor prognosis across all data sets. Further, the gene signature expression was associated with enrichment of genes governing processes linked to poor prognosis, such as EMT, angiogenesis, hypoxia, and inflammation.

CONCLUSIONS

Here we identify a nine-gene ECM signature, which strongly predicts outcome across multiple cancer types and can be used for prognostication after validation in prospective cancer cohorts.

Cytoplasmic collagen XIαI as a prognostic biomarker in esophageal squamous cell carcinoma

Stromal/cytoplasmic collagen XIαI (COL11A1) has been highlighted in the process of neoplastic transformation, including epithelial mesenchymal transition (EMT), metastasis and invasiveness. In this study, we aim to illuminate the clinical significance and biological role of COL11A1 in esophageal squamous cell carcinoma (ESCC). Herein, we investigated COL11A1 expression in 16 pairs of ESCC and adjacent normal tissues by RT-PCR and western blotting analysis. Correlations of COL11A1 expression with clinicopathologic parameters and survival status were then determined by immunohistochemistry in 116 ESCC and 50 normal specimens. Furthermore, bioinformatics was used for mechanisms exploration. And in vitro knockdown experiments were also performed. We found that COL11A1 expression was significantly higher in ESCC than in paired normal tissues at both mRNA and protein level. Immunohistochemistry showed that COL11A1 was predominantly localized to the cytoplasm rather than tumor stroma, patients with high COL11A1 expression had a poorer overall survival (OS) rate than those with low COL11A1 expression. Besides, increased COL11A1 expression was dramatically correlated with advanced clinical stage, invasion depth and lymph node metastases and served as an independent prognostic marker for ESCC. Likewise, COL11A1 dependent nomogram predicted a more precise survival outcome than traditional staging system. Moreover, COL11A1 silencing resulted in impaired cell proliferation and EMT, and subdued EMT inhibited cells aggressiveness. These biological processes (BPs) might be modulated by COL11A1 via the intracellular AKT/ERK/c-Myc cascades.

Development and Characterization of an In Vitro Model for Radiation-Induced Fibrosis

Radiation-induced fibrosis (RIF) is a major side effect of radiotherapy in cancer patients with no effective therapeutic options. RIF involves excess deposition and aberrant remodeling of the extracellular matrix (ECM) leading to stiffness in tissues and organ failure. Development of preclinical models of RIF is crucial to elucidate the molecular mechanisms regulating fibrosis and to develop therapeutic approaches. In addition to radiation, the main molecular perpetrators of fibrotic reactions are cytokines, including transforming growth factor-β (TGF-β). We hypothesized that human oral fibroblasts would develop an in vitro fibrotic reaction in response to radiation and TGF-β. We demonstrate here that fibroblasts exposed to radiation followed by TGF-β exhibit a fibrotic phenotype with increased collagen deposition, cell proliferation, migration and invasion. In this in vitro model of RIF (RIF_iv), the early biological processes involved in fibrosis are demonstrated, along with increased levels of several molecules including collagen 1α1, collagen XIα1, integrin-α2 and cyclin D1 mRNA in irradiated cells. A clinically relevant antifibrotic agent, pentoxifylline, and a curcumin analogue both mitigated collagen deposition in irradiated fibroblast cultures. In summary, we have established an in vitro model for RIF that facilitates the elucidation of molecular mechanisms in radiation-induced fibrosis and the development of effective therapeutic approaches.

Genomic analysis of atypical fibroxanthoma

Atypical fibroxanthoma (AFX), is a rare type of skin cancer affecting older individuals with sun damaged skin. Since there is limited genomic information about AFX, our study seeks to improve the understanding of AFX through whole-exome and RNA sequencing of 8 matched tumor-normal samples. AFX is a highly mutated malignancy with recurrent mutations in a number of genes, including COL11A1, ERBB4, CSMD3, and FAT1. The majority of mutations identified were UV signature (C>T in dipyrimidines). We observed deletion of chromosomal segments on chr9p and chr13q, including tumor suppressor genes such as KANK1 and CDKN2A, but no gene fusions were found. Gene expression profiling revealed several biological pathways that are upregulated in AFX, including tumor associated macrophage response, GPCR signaling, and epithelial to mesenchymal transition (EMT). To further investigate the presence of EMT in AFX, we conducted a gene expression meta-analysis that incorporated RNA-seq data from dermal fibroblasts and keratinocytes. Ours is the first study to employ high throughput sequencing for molecular profiling of AFX. These data provide valuable insights to inform models of carcinogenesis and additional research towards tumor-directed therapy.

Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis

OBJECTIVE

Breast cancer is a severe risk to public health and has adequately convoluted pathogenesis. Therefore, the description of key molecular markers and pathways is of much importance for clarifying the molecular mechanism of breast cancer-associated fibroblasts initiation and progression. Breast cancer-associated fibroblasts gene expression dataset was downloaded from Gene Expression Omnibus database.

METHODS

A total of nine samples, including three normal fibroblasts, three granulin-stimulated fibroblasts and three cancer-associated fibroblasts samples, were used to identify differentially expressed genes (DEGs) between normal fibroblasts, granulin-stimulated fibroblasts and cancer-associated fibroblasts samples. The gene ontology (GO) and pathway enrichment analysis was performed, and protein-protein interaction (PPI) network of the DEGs was constructed by NetworkAnalyst software.

RESULTS

Totally, 190 DEGs were identified, including 66 up-regulated and 124 down-regulated genes. GO analysis results showed that up-regulated DEGs were significantly enriched in biological processes (BP), including cell-cell signalling and negative regulation of cell proliferation; molecular function (MF), including insulin-like growth factor II binding and insulin-like growth factor I binding; cellular component (CC), including insulin-like growth factor binding protein complex and integral component of plasma membrane; the down-regulated DEGs were significantly enriched in BP, including cell adhesion and extracellular matrix organization; MF, including N-acetylgalactosamine 4-sulfate 6-O-sulfotransferase activity and calcium ion binding; CC, including extracellular space and extracellular matrix. WIKIPATHWAYS analysis showed the up-regulated DEGs were enriched in myometrial relaxation and contraction pathways. WIKIPATHWAYS, REACTOME, PID_NCI and KEGG pathway analysis showed the down-regulated DEGs were enriched endochondral ossification, TGF beta signalling pathway, integrin cell surface interactions, beta1 integrin cell surface interactions, malaria and glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulphate. The top 5 up-regulated hub genes, CDKN2A, MME, PBX1, IGFBP3, and TFAP2C and top 5 down-regulated hub genes VCAM1, KRT18, TGM2, ACTA2, and STAMBP were identified from the PPI network, and subnetworks revealed these genes were involved in significant pathways, including myometrial relaxation and contraction pathways, integrin cell surface interactions, beta1 integrin cell surface interaction. Besides, the target hsa-mirs for DEGs were identified. hsa-mir-759, hsa-mir-4446-5p, hsa-mir-219a-1-3p and hsa-mir-26a-5p were important miRNAs in this study.

CONCLUSIONS

We pinpoint important key genes and pathways closely related with breast cancer-associated fibroblasts initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying breast cancer-associated fibroblasts occurrence and progression, holding promise for acting as molecular markers and probable therapeutic targets.

CR6-interacting factor 1 inhibits invasiveness by suppressing TGF-β-mediated epithelial-mesenchymal transition in hepatocellular carcinoma

CR6-interacting factor 1 (CRIF1) regulates cell cycle progression and the DNA damage response. Here, we show that CRIF1 expression is decreased in hepatocellular carcinoma (HCC) tissues and positively correlates with patients’ survival. In vitro, down-regulation of CRIF1 promotes HCC cell proliferation and invasiveness, while over-expression has the opposite effect. in vivo, CRIF1 knockdown enhances growth of HCC xenografts. Analysis of mRNA microarrays showed that CRIF1 knockdown activates genes involved in TGF-β RI/Smad2/3 signaling, leading to epithelial-mesenchymal transition (EMT) and increased matrix metalloproteinase-3 (MMP3) expression. However, cell invasion and EMT are abrogated in HCC cells treated with SB525334, a specific TGF-β RI inhibitor, which indicates the inhibitory effect of CRIF1 on HCC tumor growth is mediated by TGF-β signaling. These results demonstrate that CRIF1 benefits patient survival by inhibiting HCC cell invasiveness through suppression of TGF-β-mediated EMT and MMP3 expression. This suggests CRIF1 may serve as a novel target for inhibiting HCC metastasis.

Cancer associated fibroblasts (CAFs) are activated in cutaneous basal cell carcinoma and in the peritumoural skin

Background

Cutaneous basal cell carcinoma (BCC) is the commonest cancer worldwide. BCC is locally invasive and the surrounding stromal microenvironment is pivotal for tumourigenesis. Cancer associated fibroblasts (CAFs) in the microenvironment are essential for tumour growth in a variety of neoplasms but their role in BCC is poorly understood.

Methods

Material included facial BCC and control skin from the peritumoural area and from the buttocks. With next-generation sequencing (NGS) we compared mRNA expression between BCC and peritumoural skin. qRT-PCR, immunohistochemical and immunofluorescent staining were performed to validate the NGS results and to investigate CAF-related cyto-and chemokines.

Results

NGS revealed upregulation of 65 genes in BCC coding for extracellular matrix components pointing at CAF-related matrix remodeling. qRT-PCR showed increased mRNA expression of CAF markers FAP-α, PDGFR-β and prolyl-4-hydroxylase in BCC. Peritumoural skin (but not buttock skin) also exhibited high expression of PDGFR-β and prolyl-4-hydroxylase but not FAP-α. We found a similar pattern for the CAF-associated chemokines CCL17, CCL18, CCL22, CCL25, CXCL12 and IL6 with high expression in BCC and peritumoural skin but absence in buttock skin. Immunofluorescence revealed correlation between FAP-α and PDGFR-β and CXCL12 and CCL17.

Conclusion

Matrix remodeling is the most prominent molecular feature of BCC. CAFs are present within BCC stroma and associated with increased expression of chemokines involved in tumour progression and immunosuppression (CXCL12, CCL17). Fibroblasts from chronically sun-exposed skin near tumours show gene expression patterns resembling that of CAFs, indicating that stromal fibroblasts in cancer-free surgical BCC margins exhibit a tumour promoting phenotype.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12885-017-3663-0) contains supplementary material, which is available to authorized users.

Integrated Analysis Reveals Tubal- and Ovarian-Originated Serous Ovarian Cancer and Predicts Differential Therapeutic Responses

Purpose: The relative importance of fallopian tube (FT) compared with ovarian surface epithelium (OSE) in the genesis of serous type of ovarian cancer (SOC) is still unsettled. Here, we followed an integrated approach to study the tissue origin of SOC, as well as its association with clinical outcome and response to therapeutic drugs.Experimental Design: A collection of transcriptome data of 80 FTs, 89 OSEs, and 2,668 SOCs was systematically analyzed to determine the characteristic of FT-like and OSE-like tumors. A molecular signature was developed for identifying tissue origin of SOC and then was used to reevaluate the prognostic genes and therapeutic biomarkers of SOC of different tissue origins. IHC staining of tissue array and functional experiments on a panel of ovarian cancer cell lines were used to further validate the key findings.Results: The expression patterns of tissue-specific genes, prognostic genes, and molecular markers all support a dualistic tissue origin of SOC, from either FT or OSE. A molecular signature was established to identify the tissue identity of SOCs. Surprisingly, the signature showed a strong association with overall survival (OSE-like vs. FT-like, HR = 4.16; 95% CI, 2.67-6.48; P < 10^-9). The pharmacogenomic approach revealed AXL to be a therapeutic target of the aggressive OSE-derived SOC.Conclusions: SOC has two subtypes originated from either FT or OSE, which show different clinical and pathologic features. Clin Cancer Res; 23(23); 7400-11. ©2017 AACR.

Activation of TWIST1 by COL11A1 promotes chemoresistance and inhibits apoptosis in ovarian cancer cells by modulating NF-κB-mediated IKKβ expression

We have shown that collagen type XI alpha 1 (COL11A1) promotes ovarian cancer progression and is associated with chemoresistance to cisplatin and paclitaxel in ovarian cancer cells. Here, we demonstrate how COL11A1 regulates twist family basic helix-loop-helix transcription factor 1-related protein 1 (TWIST1) to induce chemoresistance and inhibit apoptosis in ovarian cancer cells. Small interfering RNA-mediated reduction in COL11A1 protein levels increased the chemosensitivity to cisplatin and paclitaxel via downregulated TWIST1 expression. TWIST1 messenger RNA levels positively associated with COL11A1 messenger RNA expression levels in ovarian tumors. High TWIST1 expression levels were significantly associated with a progression-free interval of ≤ 6 months (p = 0.001) and death (p = 0.040). In addition, patients with high TWIST1 mRNA levels had significantly shorter 5-year overall-survival (p = 0.004) and progression-free survival (p = 0.009) rates, compared to patients with low TWIST1 levels. Increased TWIST1 expression caused by COL11A1-induced transcription of the inhibitor of nuclear factor kappa B kinase subunit beta (IKKβ) gene occurred via increased SP1 phosphorylation and binding to the IKKβ promoter. COL11A1-mediated nuclear factor-kappa B activation, via transcriptional activation of IKKβ, promoted TWIST1, Mcl-1, and GAS6 expression, which were associated with chemoresistance and anti-apoptosis in ovarian cancer cells. We suggest that IKKβ and TWIST1 can potentially be targeted in patients with COL11A1-positive ovarian cancer.

Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data

Epithelial ovarian cancer (EOC) is a common cancer in women worldwide. The present study assessed effective biomarkers for the prognosis of EOC metastasis. The GSE30587 dataset, containing 9 EOC primary tumor samples and 9 matched omental metastasis samples, was analyzed. Following normalization, the differentially expressed genes (DEGs) between these samples were identified using the limma package for R. Subsequently, pathway enrichment analysis was performed using ClueGO, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database. The microRNA (mRNA/miR)-target network was established using the multiMiR package. A set of 272 DEGs was identified in metastatic EOC samples, including 189 upregulated and 83 downregulated genes. Collagen type I α 1 chain (COL1A1), COL1A2, collagen type XI α 1 chain (COL11A1) and thrombospondin (THBS)1 were enriched in the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), focal adhesion and extracellular matrix (ECM)-receptor interaction signaling pathways. THBS1 and tissue inhibitor of metalloproteinase (TIMP)3 were two dominant nodes in the PPI network and were key in the miRNA-target network, being targeted by hsa-miR-1. Multiple DEGs and miRNAs were identified as potential biomarkers for the prognosis of EOC metastasis in the present study, which likely affected metastasis by regulating the PI3K/Akt, ECM-receptor interaction and cell adhesion signaling pathways. In addition, THBS1 and TIMP3 were identified as potential targets of hsa-miR-1.

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Chemoresistance is a leading cause of morbidity and mortality in cancer and it continues to be a challenge in cancer treatment. Chemoresistance is influenced by genetic and epigenetic alterations which affect drug uptake, metabolism and export of drugs at the cellular levels. While most research has focused on tumor cell autonomous mechanisms of chemoresistance, the tumor microenvironment has emerged as a key player in the development of chemoresistance and in malignant progression, thereby influencing the development of novel therapies in clinical oncology. It is not surprising that the study of the tumor microenvironment is now considered to be as important as the study of tumor cells. Recent advances in technological and analytical methods, especially ‘omics’ technologies, has made it possible to identify specific targets in tumor cells and within the tumor microenvironment to eradicate cancer. Tumors need constant support from previously ‘unsupportive’ microenvironments. Novel therapeutic strategies that inhibit such microenvironmental support to tumor cells would reduce chemoresistance and tumor relapse. Such strategies can target stromal cells, proteins released by stromal cells and non-cellular components such as the extracellular matrix (ECM) within the tumor microenvironment. Novel in vitro tumor biology models that recapitulate the in vivo tumor microenvironment such as multicellular tumor spheroids, biomimetic scaffolds and tumor organoids are being developed and are increasing our understanding of cancer cell-microenvironment interactions. This review offers an analysis of recent developments on the role of the tumor microenvironment in the development of chemoresistance and the strategies to overcome microenvironment-mediated chemoresistance. We propose a systematic analysis of the relationship between tumor cells and their respective tumor microenvironments and our data show that, to survive, cancer cells interact closely with tumor microenvironment components such as mesenchymal stem cells and the extracellular matrix.

Upregulation of distinct collagen transcripts in post-surgery scar tissue: a study of conjunctival fibrosis

Excessive accumulation of collagen is often used to assess the development of fibrosis. This study aims to identify collagen genes that define fibrosis in the conjunctiva following glaucoma filtration surgery (GFS). Using the mouse model of GFS, we have identified collagen transcripts that were upregulated in the fibrotic phase of wound healing via RNA-seq. The collagen transcripts that were increased the most were encoded by Col8a1, Col11a1 and Col8a2. Further analysis of the Col8a1, Col11a1 and Col8a2 transcripts revealed their increase by 67-, 54- and 18-fold, respectively, in the fibrotic phase, compared with 12-fold for Col1a1, the most commonly evaluated collagen gene for fibrosis. However, only type I collagen was significantly upregulated at the protein level in the fibrotic phase. Type VIII and type I collagens colocalized in fibrous structures and in ACTA2-positive pericytes, and appeared to compensate for each other in expression levels. Type XI collagen showed low colocalization with both type VIII and type I collagens but can be found in association with macrophages. Furthermore, we show that both mouse and human conjunctival fibroblasts expressed elevated levels of the most highly expressed collagen genes in response to TGFβ2 treatment. Importantly, conjunctival tissues from individuals whose GF surgeries have failed due to scarring showed 3.60- and 2.78-fold increases in type VIII and I collagen transcripts, respectively, compared with those from individuals with no prior surgeries. These data demonstrate that distinct collagen transcripts are expressed at high levels in the conjunctiva after surgery and their unique expression profiles may imply differential influences on the fibrotic outcome.

Summary: As well as providing an objective quantitative measure, distinct collagen genes may further aid in the characterization and definition of the development of fibrosis.

COL11A1 is overexpressed in gastric cancer tissues and regulates proliferation, migration and invasion of HGC-27 gastric cancer cells in vitro

The role of COL11A1 in carcinogenesis is increasingly recognized. However, the biological role and potential mechanisms of COL11A1 in gastric cancer have not been elucidated. In the present study, the COL11A1 mRNA expression in 57 patients with gastric cancer was measured by reverse transcription quantitative PCR (RT-qPCR), and the biological effects of COL11A1 suppression were determined using MTS, monolayer colony formation, flow cytometry and Transwell assays. In addition, the potential molecular mechanisms of COL11A1 in gastric cancer were analyzed by western blotting and cDNA microarray analysis. Compared with matched adjacent non-tumor tissue, COL11A1 mRNA was significantly overexpressed in tumor tissue and was positively related to age, tumor invasion depth, tumor size and lymph node positivity. Moreover, in vitro experiments demonstrated that COL11A1 suppression by short hairpin RNA (shRNA) significantly inhibited the proliferation, migration and invasion of HGC-27 cells and that COL11A1 suppression promoted cell apoptosis, induced G1-phase cell cycle arrest and led to a significant downregulation of cyclin D1 and upregulation of p21 and cleaved caspase-3. In addition, the cDNA microarray analysis of HGC-27 cells with and without COL11A1 suppression indicated that COL11A1 may regulate multiple genes responsible for cell growth and/or invasion, including downregulation of CDK6, TIAM1, ITGB8 and WNT5A and upregulation of RGS2 and NEFL following suppression of COL11A1 expression in HGC-27 cells, validated with RT-qPCR assays. Taken together, our findings demonstrate that COL11A1 might be an oncogene in GC and is a promising therapeutic target in cancer treatment.

Identification of COL1A1 and COL1A2 as candidate prognostic factors in gastric cancer

Background

The role of type I collagen, composed of collagen type I alpha 1 (COL1A1) and collagen type I alpha 2 (COL1A2), has been studied in several cancers. However, the expression of COL1A1 and COL1A2 in malignant, premalignant, and normal gastric tissues and their clinical significances in gastric cancer have not been elucidated.

Methods

Real-time quantitative PCR was performed in 55 malignant, 27 premalignant, and 19 normal tissues to measure COL1A1 and COL1A2 messenger RNA (mRNA) expression, and the correlations between COL1A1 and COL1A2 expression and clinicopathological parameters and patients’ survival rate were analyzed.

Results

We found that COL1A1 mRNA expression was significantly upregulated in premalignant and malignant tissues than in normal tissues, whereas COL1A2 mRNA expression was significantly higher in malignant tissues than in premalignant and normal tissues. Moreover, COL1A1 expression was unrelated to clinicopathological parameters, while COL1A2 expression was positively related to tumor size and depth of invasion. Besides, higher COL1A1 and COL1A2 expression levels were related to lower overall survival.

Conclusions

We find that COL1A1 might have its potential as a monitoring factor to screen early gastric cancer, and COL1A1 and COL1A2 might predict poor clinical outcomes in gastric cancer patients.

A COL11A1-correlated pan-cancer gene signature of activated fibroblasts for the prioritization of therapeutic targets

Although cancer-associated fibroblasts (CAFs) are viewed as a promising therapeutic target, the design of rational therapy has been hampered by two key obstacles. First, attempts to ablate CAFs have resulted in significant toxicity because currently used biomarkers cannot effectively distinguish activated CAFs from non-cancer associated fibroblasts and mesenchymal progenitor cells. Second, it is unclear whether CAFs in different organs have different molecular and functional properties that necessitate organ-specific therapeutic designs. Our analyses uncovered COL11A1 as a highly specific biomarker of activated CAFs. Using COL11A1 as a 'seed', we identified co-expressed genes in 13 types of primary carcinoma in The Cancer Genome Atlas. We demonstrated that a molecular signature of activated CAFs is conserved in epithelial cancers regardless of organ site and transforming events within cancer cells, suggesting that targeting fibroblast activation should be effective in multiple cancers. We prioritized several potential pan-cancer therapeutic targets that are likely to have high specificity for activated CAFs and minimal toxicity in normal tissues.

Intraoperative Diagnosis Support Tool for Serous Ovarian Tumors Based on Microarray Data Using Multicategory Machine Learning

OBJECTIVES

Serous borderline ovarian tumors (SBOTs) are a subtype of serous ovarian carcinoma with atypical proliferation. Frozen-section diagnosis has been used as an intraoperative diagnosis tool in supporting the fertility-sparing surgery by diagnosing SBOTs with accuracy of 48% to 79%. Using DNA microarray technology, we designed multicategory classification models to support frozen-section diagnosis within 30 minutes.

MATERIALS AND METHODS

We systematically evaluated 6 machine learning algorithms and 3 feature selection methods using 5-fold cross-validation and a grid search on microarray data obtained from the National Center for Biotechnology Information. To validate the models and selected biomarkers, expression profiles were analyzed in tissue samples obtained from the Yonsei University College of Medicine.

RESULTS

The best accuracy of the optimal machine learning model was 97.3%. In addition, 5 features, including the expression of the putative biomarkers SNTN and AOX1, were selected to differentiate between normal, SBOT, and serous ovarian carcinoma groups. Different expression levels of SNTN and AOX1 were validated by real-time quantitative reverse-transcription polymerase chain reaction, Western blotting, and immunohistochemistry. A multinomial logistic regression model using SNTN and AOX1 alone was used to construct a simple-to-use equation that gave a diagnostic test accuracy of 91.9%.

CONCLUSIONS

We identified 2 biomarkers, SNTN and AOX1, that are likely involved in the pathogenesis and progression of ovarian tumors. An accurate diagnosis of ovarian tumor subclasses by application of the equation in conjunction with expression analysis of SNTN and AOX1 would offer a new accurate diagnosis tool in conjunction with frozen-section diagnosis within 30 minutes.

Extracellular RNA in aging

Since the discovery of extracellular RNA (exRNA) in circulation and other bodily fluids, there has been considerable effort to catalog and assess whether exRNAs can be used as markers for health and disease. A variety of exRNA species have been identified including messenger RNA and noncoding RNA such as microRNA (miRNA), small nucleolar RNA, transfer RNA, and long noncoding RNA. Age-related changes in exRNA abundance have been observed, and it is likely that some of these transcripts play a role in aging. In this review, we summarize the current state of exRNA profiling in various body fluids and discuss age-related changes in exRNA abundance that have been identified in humans and other model organisms. miRNAs, in particular, are a major focus of current research and we will highlight and discuss the potential role that specific miRNAs might play in age-related phenotypes and disease. We will also review challenges facing this emerging field and various strategies that can be used for the validation and future use of exRNAs as markers of aging and age-related disease. WIREs RNA 2017, 8:e1385. doi: 10.1002/wrna.1385 For further resources related to this article, please visit the WIREs website.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data

BACKGROUND

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues.

RESULTS

To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies.

CONCLUSIONS

The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

COL11A1 confers chemoresistance on ovarian cancer cells through the activation of Akt/c/EBPβ pathway and PDK1 stabilization

Chemoresistance to anticancer drugs substantially reduces survival in epithelial ovarian carcinoma (EOC). Here, microarray analysis showed that collagen type XI alpha 1 (COL11A1) is a chemotherapy response-associated gene. Chemoresistant cells expressed higher COL11A1 and c/EBPβ than chemosensitive cells. COL11A1 or c/EBPβ downregulation suppressed chemoresistance, whereas COL11A1 overexpression attenuated sensitivity to cisplatin and paclitaxel.The c/EBPβ binding site in the COL11A1 promoter was identified as the major determinant of cisplatin- and paclitaxel-induced COL11A1 expression. Immunoprecipitation and immunofluorescence showed that in resistant cells, Akt and PDK1 were highly expressed and that anticancer drugs enhanced binding activity between COL11A1 and PDK1 binding and attenuated PDK1 ubiquitination and degradation. Conversely, chemosensitive cells showed decreased activity of COL11A1 binding to PDK1 and increased PDK1 ubiquitination, which were reversed by COL11A1 overexpression. Analysis of 104 EOC patients showed that high COL11A1 mRNA levels are significantly associated with poor chemoresponse and clinical outcome.

COL11A1 is overexpressed in recurrent non-small cell lung cancer and promotes cell proliferation, migration, invasion and drug resistance

Collagen type XI α1 (COL11A1), a minor fibrillar collagen, has been demonstrated to be involved in cell proliferation, migration and the tumorigenesis of many human malignancies. Previous studies have shown that COL11A1 may be a valuable diagnostic marker for non-small cell lung carcinoma (NSCLC). However, its biological function in NSCLC progression remains largely unclear. In the present study, we investigated the expression levels of COL11A1 in different human NSCLC samples, and found that COL11A1 was overexpressed in NSCLC with lymph node metastasis and in recurrent NSCLC tissues. We also revealed that COL11A1 promoted the cell proliferation, migration and invasion of NSCLC cell lines in vitro. Furthermore, our results highlighted the importance of COL11A1 in chemoresistance to cisplatin. Mechanistically, we found that the effects of the overexpression of COL11A1 in NSCLC cells were mediated by Smad signaling. Collectively, our findings suggest that COL11A1 may sever as a biomarker for metastatic NSCLC, and can be used to predict recurrence after surgical resection. Therapeutic approaches targeting COL11A1 may facilitate the optimization of cisplatin treatment of NSCLC by overcoming chemoresistance.

Overexpression of α1 chain of type XI collagen (COL11A1) aids in the diagnosis of invasive carcinoma in endoscopically removed malignant colorectal polyps

INTRODUCTION

The histologic distinction between benign misplaced adenomatous mucosa and invasive adenocarcinoma in colorectal polyps can be challenging. The α1 chain of type XI collagen (COL11A1) has been shown to be overexpressed in cancer-associated stromal fibroblasts. The aim of this study was to investigate the operating characteristics of COL11A1 immunostaining in benign and malignant colorectal polyps as a potential diagnostic aid.

MATERIALS AND METHODS

Sixty-six endoscopically-removed paraffin-embedded colorectal polyps were stained with anti-COL11A1 antibody. They comprised 50 malignant polyps (MPs) with invasive adenocarcinoma (including 5 with concurrent benign misplaced adenomatous mucosa) and 16 adenomas, 11 with and 5 without benign misplaced adenomatous mucosa.

RESULTS

COL11A1 was expressed either diffusely or focally in cancer-associated desmoplastic fibroblasts in 72.0% (36/50) of MPs. The rates of COL11A1 expression and the immunohistochemical staining patterns of the COL11A1 were positively correlated with the depth of cancer invasion in MPs. COL11A1 was expressed in all 9 (100%) MPs with a mucinous component and in 16/18 (88.9%) MPs associated with significant electrocautery effects. COL11A1 was not expressed adjacent to conventional adenomas or in the stroma adjacent to misplaced adenomatous mucosa.

CONCLUSIONS

COL11A1 antibody can assist in distinguishing the cancer-associated desmoplastic stroma from that associated with misplaced adenomatous mucosa. It is particularly helpful when electrocautery artifacts or mucin pools interfere with the diagnosis of invasive carcinoma. However, COL11A1 has limited value in diagnosing superfically invasive carcinomas with very little desmoplastic stroma due to its low positive rate and focal expression in some cases.

EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes

MOTIVATION

A major goal of biomedical research is to identify molecular features associated with a biological or clinical class of interest. Differential expression analysis has long been used for this purpose; however, conventional methods perform poorly when applied to data with high within class heterogeneity.

RESULTS

To address this challenge, we developed EMDomics, a new method that uses the Earth mover's distance to measure the overall difference between the distributions of a gene's expression in two classes of samples and uses permutations to obtain q-values for each gene. We applied EMDomics to the challenging problem of identifying genes associated with drug resistance in ovarian cancer. We also used simulated data to evaluate the performance of EMDomics, in terms of sensitivity and specificity for identifying differentially expressed gene in classes with high within class heterogeneity. In both the simulated and real biological data, EMDomics outperformed competing approaches for the identification of differentially expressed genes, and EMDomics was significantly more powerful than conventional methods for the identification of drug resistance-associated gene sets. EMDomics represents a new approach for the identification of genes differentially expressed between heterogeneous classes and has utility in a wide range of complex biomedical conditions in which sample classes show within class heterogeneity.

AVAILABILITY AND IMPLEMENTATION

The R package is available at http://www.bioconductor.org/packages/release/bioc/html/EMDomics.html.

The Extracellular Matrix in Epithelial Ovarian Cancer - A Piece of a Puzzle

Epithelial ovarian cancer is the fifth leading cause of cancer-related deaths in women and the most lethal gynecological malignancy. Extracellular matrix (ECM) is an integral component of both the normal and tumor microenvironment. ECM composition varies between tissues and is crucial for maintaining normal function and homeostasis. Dysregulation and aberrant deposition or loss of ECM components is implicated in ovarian cancer progression. The mechanisms by which tumor cells induce ECM remodeling to promote a malignant phenotype are yet to be elucidated. A thorough understanding of the role of the ECM in ovarian cancer is needed for the development of effective biomarkers and new therapies.

Prognostic significance of Traf2- and Nck- interacting kinase (TNIK) in colorectal cancer

BACKGROUND

The potential of expression profiling using microarray analysis as a tool to predict the prognosis for different types of cancer has been realized. This study aimed to identify a novel biomarker for colorectal cancer (CRC).

METHODS

The expression profiles of cancer cells in 152 patients with stage I-III CRC were examined using microarray analysis. High expression in CRC cells, especially in patients with distant recurrences, was a prerequisite to select candidate genes. Thus, we identified seventeen candidate genes, and selected Traf2- and Nck-interacting kinase (TNIK), which was known to be associated with progression in CRC through Wnt signaling pathways. We analyzed the protein expression of TNIK using immunohistochemistry (IHC) and investigated the relationship between protein expression and patient characteristics in 220 stage I-III CRC patients.

RESULTS

Relapse-free survival was significantly worse in the TNIK high expression group than in the TNIK low expression group in stage II (p = 0.028) and stage III (p = 0.006) patients. In multivariate analysis, high TNIK expression was identified as a significant independent risk factor of distant recurrence in stage III patients.

CONCLUSION

This study is the first to demonstrate the prognostic significance of intratumoral TNIK protein expression in clinical tissue samples of CRC, in that high expression of TNIK protein in primary tumors was associated with distant recurrence in stage II and III CRC patients. This TNIK IHC study might contribute to practical decision-making in the treatment of these patients.

Transcriptomic characterization of fibrolamellar hepatocellular carcinoma

Fibrolamellar hepatocellular carcinoma (FLHCC) tumors all carry a deletion of ∼ 400 kb in chromosome 19, resulting in a fusion of the genes for the heat shock protein, DNAJ (Hsp40) homolog, subfamily B, member 1, DNAJB1, and the catalytic subunit of protein kinase A, PRKACA. The resulting chimeric transcript produces a fusion protein that retains kinase activity. No other recurrent genomic alterations have been identified. Here we characterize the molecular pathogenesis of FLHCC with transcriptome sequencing (RNA sequencing). Differential expression (tumor vs. adjacent normal tissue) was detected for more than 3,500 genes (log2 fold change ≥ 1, false discovery rate ≤ 0.01), many of which were distinct from those found in hepatocellular carcinoma. Expression of several known oncogenes, such as ErbB2 and Aurora Kinase A, was increased in tumor samples. These and other dysregulated genes may serve as potential targets for therapeutic intervention.

Development of novel real-time PCR methodology for quantification of COL11A1 mRNA variants and evaluation in breast cancer tissue specimens

Background

Collagen XI is a key structural component of the extracellular matrix and consists of three alpha chains. One of these chains, the α1 (XI), is encoded by the COL11A1 gene and is transcribed to four different variants at least (A, B, C and E) that differ in the propensity to N-terminal domain proteolysis and potentially in the way the extracellular matrix is arranged. This could affect the ability of tumor cells to invade the remodeled stroma and metastasize. No study in the literature has so far investigated the expression of these four variants in breast cancer nor does a method for their accurate quantitative detection exist.

Methods

We developed a conventional PCR for the general detection of the general COL11A1 transcript and real-time qPCR methodologies with dual hybridization probes in the LightCycler platform for the quantitative determination of the variants. Data from 90 breast cancer tissues with known histopathological features were collected.

Results

The general COL11A1 transcript was detected in all samples. The developed methodologies for each variant were rapid as well as reproducible, sensitive and specific. Variant A was detected in 30 samples (33 %) and variant E in 62 samples (69 %). Variants B and C were not detected at all. A statistically significant correlation was observed between the presence of variant E and lymph nodes involvement (p = 0.037) and metastasis (p = 0.041).

Conclusions

With the newly developed tools, the possibility of inclusion of COL11A1 variants as prognostic biomarkers in emerging multiparameter technologies examining tissue RNA expression should be further explored.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1725-8) contains supplementary material, which is available to authorized users.

Expression profile of COL2A1 and the pseudogene SLC6A10P predicts tumor recurrence in high-grade serous ovarian cancer

Tumor recurrence, following initial response to adjuvant chemotherapy, is a major problem in women with high-grade serous ovarian cancer (HGSOC). Microarray analysis of primary tumors has identified genes that may be useful in risk stratification/overall survival, but are of limited value in predicting the >70% rate for tumor recurrence. In this study, we performed RNA-Seq analysis of primary and recurrent HGSOC to first identify unique differentially expressed genes. From this dataset, we selected 21 archetypical coding genes and one noncoding RNA, based on statistically significant differences in their expression profile between tumors, for validation by qPCR in a larger cohort of 110 ovarian tumors (71 primary and 39 recurrent) and for testing association of specific genes with time-to-recurrence (TTR). Kaplan-Meier tests revealed that high expression of collagen type II, alpha 1 (COL2A1) was associated with delayed TTR (HR = 0.47, 95% CI: 0.27-0.82, p = 0.008), whereas low expression of the pseudogene, solute carrier family 6 member 10 (SLC6A10P), was associated with longer TTR (HR = 0.53, 95% CI: 0.30-0.93, p = 0.027). Notably, TTR was significantly delayed for tumors that simultaneously highly expressed COL2A1 and lowly expressed SLC6A10P (HR = 0.21, 95% CI: 0.082-0.54, p = 0.0011), an estimated median of 95 months as compared to an estimated median of 16 months for subjects expressing other levels of COL2A1 and SLC6A10P. Thus, evaluating expression levels of COL2A1 and SLC6A10P at primary surgery could be beneficial for clinically managing recurrence of HGSOC.

Cigarette smoke modulates PC3 prostate cancer cell migration by altering adhesion molecules and the extracellular matrix

Prostate cancer (PCa) is the second leading cause of cancer-related mortality among American males. Studies suggest that cigarette smoking is associated with the progression of PCa; however, the molecular mechanisms underlying this process have not been extensively investigated. PCa progression is characterized by increased cell migration and alterations in extracellular matrix (ECM)- and cell adhesion molecule (CAM)-related gene expression. In the present study, the influence of cigarette smoke medium (SM) on cell migration and on the expression of ECM- and CAM-related genes in PC3 prostate adenocarcinoma cells was investigated. According to a wound-healing assay, SM treatment promoted PC3 cell migration. RNA expression levels from SM-treated and control cells were analyzed using a polymerase chain reaction (PCR) array. Of 84 genes analyzed, 27.38% (23/84) exhibited a ≥2-fold change in threshold cycle in PC3 cells following 0.5% SM treatment. Functional gene grouping analysis demonstrated that SM treatment modulated the RNA transcription of approximately 18.4% of CAMs and 33.93% of ECM-related genes. Quantitative PCR analysis showed that SM treatment led to a significant decrease in transcription levels of the following genes: Collagen 5 α-1(V), connective tissue growth factor, integrin β-2, kallmann syndrome 1, laminin α 3, matrix metallopeptidase 7 (MMP7), MMP13, secreted protein acidic cysteine-rich, thrombospondin-2 and versican; and that SM significantly increased the transcription levels of MMP2 and MMP12. Furthermore, MMP2 knockdown significantly reduced the migration of SM-treated PC3 cells. The present study provides novel insights into the association of cigarette smoking with PCa progression, via the alteration of ECM/CAM interactions.

A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics.

Identification of Commonly Dysregulated Genes in Non-small-cell Lung Cancer by Integrated Analysis of Microarray Data and qRT-PCR Validation

BACKGROUND

Non-small-cell lung cancer (NSCLC), the most common lung cancer, leads to the largest number of cancer-related deaths worldwide. There are many studies to identify the differentially expressed genes (DEGs) between NSCLC and normal control (NC) tissues by means of microarray technology. Because of the inconsistency of the microarray data sets, we performed an integrated analysis to identify DEGs and analyzed their biological function.

METHODS AND RESULTS

We combined 15 microarray data sets and identified 1063 DEGs between NSCLC and NC tissues; in addition, we found that the DEGs were enriched in regulation of cell proliferation process and focal adhesion signaling pathway. The protein-protein interaction network analysis for the top 20 significantly DEGs revealed that CAV1, COL1A1, and ADRB2 were the significant hub proteins. Finally, we employed qRT-PCR to validate the meta-analysis approach by determining the expression of the top 10 most significantly DEGs and found that the expression of these genes were significantly different between tumor and NC tissues, in accordance with the results of meta-analysis.

CONCLUSION

qRT-PCR results indicated that the meta-analysis approach in our study was acceptable. Our data suggested that some of the DEGs, including MMP12, COL11A1, THBS2, FAP, and CAV1, may participate in the pathology of NSCLC and could be applied as potential markers or therapeutic targets for NSCLC.

COL11A1/(pro)collagen 11A1 expression is a remarkable biomarker of human invasive carcinoma-associated stromal cells and carcinoma progression

The COL11A1 human gene codes for the α1 chain of procollagen 11A1 and mature collagen 11A1, an extracellular minor fibrillar collagen. Under regular conditions, this gene and its derived products are mainly expressed by chondrocytes and mesenchymal stem cells as well as osteoblasts. Normal epithelial cells and quiescent fibroblasts from diverse locations do not express them. Mesenchyme-derived tumors and related conditions, such as scleroderma and keloids, are positive for COL11A1/(pro)collagen 11A1 expression, as well as high-grade human gliomas/glioblastomas. This expression is almost absent in benign pathological processes such as breast hyperplasia, sclerosing adenosis, idiopathic pulmonary fibrosis, cirrhosis, pancreatitis, diverticulitis, and inflammatory bowel disease. By contrast, COL11A1/(pro)collagen 11A1 is highly expressed by activated stromal cells of the desmoplastic reaction of different human invasive carcinomas, and this expression is correlated with carcinoma aggressiveness and progression, and lymph node metastasis. COL11A1 upregulation has been shown to be associated to TGF-β1, Wnt, and Hh signaling pathways, which are especially active in cancer-associated stromal cells. At the front of invasive carcinomas, neoplastic epithelial cells, putatively undergoing epithelial-to-mesenchymal transition, and carcinoma-derived cells with highly metastatic capabilities, can express COL11A1. Thus, in established metastases, the expression of COL11A1/(pro)collagen 11A1 could rely on both the metastatic epithelial cells and/or the accompanying activated stromal cells. COL11A1/(pro)collagen 11A1 expression is a remarkable biomarker of human carcinoma-associated stromal cells and carcinoma progression.

Oncostatin M binds to extracellular matrix in a bioactive conformation: implications for inflammation and metastasis

Oncostatin M (OSM) is an interleukin-6-like inflammatory cytokine reported to play a role in a number of pathological processes including cancer. Full-length OSM is expressed as a 26 kDa protein that can be proteolytically processed into 24 kDa and 22 kDa forms via removal of C-terminal peptides. In this study, we examined both the ability of OSM to bind to the extracellular matrix (ECM) and the activity of immobilized OSM on human breast carcinoma cells. OSM was observed to bind to ECM proteins collagen types I and XI, laminin, and fibronectin in a pH-dependent fashion, suggesting a role for electrostatic bonds that involves charged amino acids of both the ECM and OSM. The C-terminal extensions of 24 kDa and 26 kDa OSM, which contains six and thirteen basic amino acids, respectively, enhanced electrostatic binding to ECM at pH 6.5-7.5 when compared to 22 kDa OSM. The highest levels of OSM binding to ECM, though, were observed at acidic pH 5.5, where all forms of OSM bound to ECM proteins to a similar extent. This indicates additional electrostatic binding properties independent of the OSM C-terminal extensions. The reducing agent dithiothreitol also inhibited the binding of OSM to ECM suggesting a role for disulfide bonds in OSM immobilization. OSM immobilized to ECM was protected from cleavage by tumor-associated proteases and maintained activity following incubation at acidic pH for extended periods of time. Importantly, immobilized OSM remained biologically active and was able to induce and sustain the phosphorylation of STAT3 in T47D and ZR-75-1 human breast cancer cells over prolonged periods, as well as increase levels of STAT1 and STAT3 protein expression. Immobilized OSM also induced epithelial-mesenchymal transition-associated morphological changes in T47D cells. Taken together, these data indicate that OSM binds to ECM in a bioactive state that may have important implications for the development of chronic inflammation and tumor metastasis.

Tumor matrix protein collagen XIα1 in cancer

The extracellular matrix is increasingly recognized as an essential player in cancer development and progression. Collagens are one of the most important components of the extracellular matrix, and have themselves been implicated in many aspects of neoplastic transformation. Collagen XI is a minor collagen whose main physiologic function is to regulate the diameter of major collagen fibrils. The α1 chain of collagen XI (colXIα1) has known pathogenic roles in several musculoskeletal disorders. Recent research has highlighted the importance of colXIα1 in many types of cancer, including its roles in metastasis, angiogenesis, and drug resistance, as well as its potential utility in screening tests and as a therapeutic target. High levels of colXIα1 overexpression have been reported in multiple expression profile studies examining differences between cancerous and normal tissue, and between beginning and advanced stage cancer. Its expression has been linked to poor progression-free and overall survival. The consistency of these data across cancer types is particularly striking, including colorectal, ovarian, breast, head and neck, lung, and brain cancers. This review discusses the role of collagen XIα1 in cancer and its potential as a target for cancer therapy.

Validation of COL11A1/procollagen 11A1 expression in TGF-β1-activated immortalised human mesenchymal cells and in stromal cells of human colon adenocarcinoma

Background

The human COL11A1 gene has been shown to be up-regulated in stromal cells of colorectal tumours, but, so far, the immunodetection of procollagen 11A1, the primary protein product of COL11A1, has not been studied in detail in human colon adenocarcinomas. Some cancer-associated stromal cells seem to be derived from bone marrow mesenchymal cells; the expression of the COL11A1 gene and the parallel immunodetection of procollagen 11A1 have not been evaluated in these latter cells, either.

Methods

We used quantitative RT-PCR and/or immunocytochemistry to study the expression of DES/desmin, VIM/vimentin, ACTA2/αSMA (alpha smooth muscle actin) and COL11A1/procollagen 11A1 in HCT 116 human colorectal adenocarcinoma cells, in immortalised human bone marrow mesenchymal cells and in human colon adenocarcinoma-derived cultured stromal cells. The immunodetection of procollagen 11A1 was performed with the new recently described DMTX1/1E8.33 mouse monoclonal antibody. Human colon adenocarcinomas and non-malignant colon tissues were evaluated by immunohistochemistry as well. Statistical associations were sought between anti-procollagen 11A1 immunoscoring and patient clinicopathological features.

Results

Procollagen 11A1 was immunodetected in human bone marrow mesenchymal cells and in human colon adenocarcinoma-associated spindle-shaped stromal cells but not in colon epithelial or stromal cells of the normal colon. This immunodetection paralleled, in both kinds of cells, that of the other mesenchymal-related biomarkers studied: vimentin and alpha smooth muscle actin, but not desmin. Thus, procollagen 11A1⁺ adenocarcinoma-associated stromal cells are similar to “activated myofibroblasts”. In the series of human colon adenocarcinomas here studied, a high procollagen 11A1 expression was associated with nodal involvement (p = 0.05), the development of distant metastases (p = 0.017), and advanced Dukes stages (p = 0.047).

Conclusion

The immunodetection of procollagen 11A1 in cancer-associated stromal cells could be a useful biomarker for human colon adenocarcinoma characterisation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2407-14-867) contains supplementary material, which is available to authorized users.