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Lay abstract The heterogeneity of colorectal cancer is largely based on their primary tumor locations. For example, patients with left-sided colon cancer generally have better prognoses and different treatment strategies in comparison with patients with right-sided colon cancer. Research is required to uncover the mechanisms underlying these differences. The authors showed that the addition of methyl groups (DNA methylation) to DNA encoding SPARCL1 (a protein involved in cell adhesion) could inhibit regular colorectal cell motility. Furthermore, SPARCL1 protein expression was higher and positively correlated with better prognosis specifically in patients with left-sided colon cancer. The present study provides an evidential basis for the different molecular biological features between left- and right-sided colon cancer. SPARCL1 is a promising candidate for predicting colon cancer prognosis and potential therapeutic intervention. Further in-depth study of SPARCL1 would be of great value for clinical application.

Background The understanding of vascular plasticity is key to defining the role of blood vessels in physiologic and pathogenic processes. In the present study, the impact of the vascular quiescence marker SPARCL1 on angiogenesis, capillary morphogenesis, and vessel integrity was evaluated. Methods Angiogenesis was studied using the metatarsal test, an ex vivo model of sprouting angiogenesis. In addition, acute and chronic dextran sodium sulfate colitis models with SPARCL1 knockout mice were applied. Results This approach indicated that SPARCL1 inhibits angiogenesis and supports vessel morphogenesis and integrity. Evidence was provided that SPARCL1-mediated stabilization of vessel integrity counteracts vessel permeability and inflammation in acute and chronic dextran sodium sulfate colitis models. Structure-function analyses of purified SPARCL1 identified the acidic domain of the protein necessary for its anti-angiogenic activity. Conclusions Our findings inaugurate SPARCL1 as a blood vessel–derived anti-angiogenic molecule required for vessel morphogenesis and integrity. SPARCL1 opens new perspectives as a vascular marker of susceptibility to colitis and as a therapeutic molecule to support blood vessel stability in this disease.

Astrocyte-secreted Hevin induces synapse formation by bridging the trans-synaptic organizers, neuroligins and neurexins. In this issue of Structure, Fan et al. (2021) elucidate the structural basis of Hevin's interaction with these molecules and reveal the competitive interplay between Hevin, SPARC, and MDGAs.

Nonalcoholic fatty liver disease (NAFLD) represents a spectrum of chronic liver disease ranging from simple steatosis (NAFL) to nonalcoholic steatohepatitis (NASH). However, the molecular mechanisms of NASH progression remain incompletely understood. White adipose tissue (WAT) has emerged as an important endocrine organ and contributes not only to the initial stage of NAFLD, but also to its severity. In the current study, through transcriptomic analysis we identified increased expression of Sparcl1, a secreted glycoprotein, in the WAT from NASH mice. Plasma Sparcl1 levels were similarly elevated and positively correlated with hepatic pathological features in NASH patients. Functional studies showed that both chronic injection of recombinant Sparcl1 protein and overexpression of Sparcl1 exaggerated hepatic inflammation and liver injury in mice. In contrast, genetic ablation of Sparcl1, knockdown of Sparcl1 in WAT, and treatment with a Sparcl1-neutralizing antibody dramatically alleviated diet-induced NASH pathogenesis. Mechanistically, Sparcl1 promoted the expression of C-C motif chemokine ligand 2 (CCL2) in hepatocytes through binding to Toll-like receptor 4 (TLR4) and activation of the NF-κB/p65 signaling pathway. Genetically or pharmacologically blocking the CCL2/CCR2 pathway attenuated the hepatic inflammatory response evoked by Sparcl1. Thus, our results demonstrated an important role for Sparcl1 in NASH progression, suggesting a potential target for therapeutic intervention.

Aging drives a progressive decline in cognition and decreases synapse numbers and synaptic function in the brain, thereby increasing the risk for neurodegenerative disease. Pioneering studies showed that introduction of blood from young mice into aged mice reversed age-associated cognitive impairments and increased synaptic connectivity in brain, suggesting that young blood contains specific factors that remediate age-associated decreases in brain function. However, whether such factors in blood from young animals act directly on neurons to enhance synaptic connectivity, or whether they act by an indirect mechanism remains unknown. Moreover, which factors in young blood mediate cognitive improvements in old mice is incompletely understood. Here, we show that serum extracted from the blood of young but not old mice, when applied to neurons transdifferentiated from human embryonic stem cells, directly increased dendritic arborization, augmented synapse numbers, doubled dendritic spine-like structures, and elevated synaptic N-methyl-d-aspartate (NMDA) receptors, thereby increasing synaptic connectivity. Mass spectrometry revealed that thrombospondin-4 (THBS4) and SPARC-like protein 1 (SPARCL1) were enriched in serum from young mice. Strikingly, recombinant THBS4 and SPARCL1 both increased dendritic arborization and doubled synapse numbers in cultured neurons. In addition, SPARCL1 but not THBS4 tripled NMDA receptor-mediated synaptic responses. Thus, at least two proteins enriched in young blood, THBS4 and SPARCL1, directly act on neurons as synaptogenic factors. These proteins may represent rejuvenation factors that enhance synaptic connectivity by increasing dendritic arborization, synapse formation, and synaptic transmission.

This study aimed to probe carcinogenic genes and pathways associated with Wilms' tumor (WT) onset and malignancy progression. After screening, three datasets acquired from the Gene Expression Omnibus database were analyzed. Differentially expressed genes (DEGs) were identified and GO functional enrichment, KEGG pathway enrichment and protein-protein interaction (PPI) were analyzed. The DEGs with top fold change values or top protein interaction scores were used to analyze overall survival based on the TARGET WT dataset. Together, 866 up-regulated genes in GDS1791, 585 up-regulated genes in GDS2010, and 277 down-regulated genes in GDS4802 were found, from which 46 key DEGs were selected for further analysis. In the PPI network, hub positions included COL5A1, COL4A1, ARPP21, SPARCL1, CD86, LY96 and PPP1R12B. The top DEGs (ARPP21, SYNPO, PRRC2B, PPP1R12B, EFCAB2 and LY96) were selected for survival analysis, and they consistently showed a significantly positive correlation with poor survival. Together, five key carcinogenic genes (SYNPO, PRRC2B, PPP1R12B, EFCAB2 and LY96) were highly associated with WT onset and patient survival. These risk genes, interaction networks and enrichments should improve our understanding of the complex molecular mechanisms in WT development and help clinical applications.

BackgroundColorectal cancer (CRC), one of the most common malignant tumors worldwide, has a high mortality rate, especially for patients with CRC liver metastasis (CLM). However, CLM pathogenesis remains unclear.MethodsWe integrated multiple cohort datasets and databases to clarify and verify potential key candidate biomarkers and signal transduction pathways in CLM. GEO2R, DAVID 6.8, ImageGP, STRING, UALCAN, ONCOMINE, THE HUMAN PROTEIN ATLAS, GEPIA 2.0, cBioPortal, TIMER 2.0, DRUGSURV, CRN, GSEA 4.0.3, FUNRICH 3.1.3 and R 4.0.3 were utilized in this study.ResultsSixty-three pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened from three gene expression profiles (GSE6988, GSE14297 and GSE81558). Thirty-one up-regulated genes and four down-regulated genes were identified from these three gene expression profiles and verified by another gene expression profiles (GSE 49355) and TCGA database. Two pathways (IGFBP-IGF signaling pathway and complement-coagulation cascade), eighteen key differentially expressed genes (DEGs), six hub genes (SPARCL1, CDH2, CP, HP, TF and SERPINA5) and two biomarkers (CDH2 and SPARCL1) with significantly prognostic values were screened by multi-omics data analysis and verified by Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) cohort.ConclusionsIn this study, we identified a robust set of potential candidate biomarkers in CLM, which would provide potential value for early diagnosis and prognosis, and would promote molecular targeting therapy for CRC and CLM.

Background This study hoped to explore the potential biomarkers and associated metabolites during osteosarcoma (OS) progression based on bioinformatics integrated analysis. Methods Gene expression profiles of GSE28424, including 19 human OS cell lines (OS group) and 4 human normal long bone tissue samples (control group), were downloaded. The differentially expressed genes (DEGs) in OS vs. control were investigated. The enrichment investigation was performed based on DEGs, followed by protein–protein interaction network analysis. Then, the feature genes associated with OS were explored, followed by survival analysis to reveal prognostic genes. The qRT-PCR assay was performed to test the expression of these genes. Finally, the OS-associated metabolites and disease-metabolic network were further investigated. Results Totally, 357 DEGs were revealed between the OS vs. control groups. These DEGs, such as CXCL12, were mainly involved in functions like leukocyte migration. Then, totally, 38 feature genes were explored, of which 8 genes showed significant associations with the survival of patients. High expression of CXCL12, CEBPA, SPARCL1, CAT, TUBA1A, and ALDH1A1 was associated with longer survival time, while high expression of CFLAR and STC2 was associated with poor survival. Finally, a disease-metabolic network was constructed with 25 nodes including two disease-associated metabolites cyclophosphamide and bisphenol A (BPA). BPA showed interactions with multiple prognosis-related genes, such as CXCL12 and STC2. Conclusion We identified 8 prognosis-related genes in OS. CXCL12 might participate in OS progression via leukocyte migration function. BPA might be an important metabolite interacting with multiple prognosis-related genes.

Purpose Exploring the molecular mechanisms of lung adenocarcinoma (LUAD) is beneficial for developing new therapeutic strategies and predicting prognosis. This study was performed to select core genes related to LUAD and to analyze their prognostic value. Methods Microarray datasets from the GEO (GSE75037) and TCGA-LUAD datasets were analyzed to identify differentially coexpressed genes in LUAD using weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. Functional enrichment analysis was conducted, and a protein–protein interaction (PPI) network was established. Subsequently, hub genes were identified using the CytoHubba plug-in. Overall survival (OS) analyses of hub genes were performed. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (THPA) databases were used to validate our findings. Gene set enrichment analysis (GSEA) of survival-related hub genes were conducted. Immunohistochemistry (IHC) was carried out to validate our findings. Results We identified 486 differentially coexpressed genes. Functional enrichment analysis suggested these genes were primarily enriched in the regulation of epithelial cell proliferation, collagen-containing extracellular matrix, transforming growth factor beta binding, and signaling pathways regulating the pluripotency of stem cells. Ten hub genes were detected using the maximal clique centrality (MCC) algorithm, and four genes were closely associated with OS. The CPTAC and THPA databases revealed that CHRDL1 and SPARCL1 were downregulated at the mRNA and protein expression levels in LUAD, whereas SPP1 was upregulated. GSEA demonstrated that DNA-dependent DNA replication and catalytic activity acting on RNA were correlated with CHRDL1 and SPARCL1 expression, respectively. The IHC results suggested that CHRDL1 and SPARCL1 were significantly downregulated in LUAD. Conclusions Our study revealed that survival-related hub genes closely correlated with the initiation and progression of LUAD. Furthermore, CHRDL1 and SPARCL1 are potential therapeutic and prognostic indicators of LUAD.

Diffuse intrinsic pontine glioma (DIPG) is a highly aggressive brain tumor with rare survival beyond two years. This poor prognosis is largely due to the tumor’s highly infiltrative and invasive nature. Previous reports demonstrate upregulation of the transcription factor ID1 with H3K27M and ACVR1 mutations, but this has not been confirmed in human tumors or therapeutically targeted. We developed an in utero electroporation (IUE) murine H3K27M-driven tumor model, which demonstrates increased ID1 expression in H3K27M- and ACVR1-mutated tumor cells. In human tumors, elevated ID1 expression is associated with H3K27M/ACVR1-mutation, brainstem location, and reduced survival. The ID1 promoter demonstrates a similar active epigenetic state in H3K27M tumor cells and murine prenatal hindbrain cells. In the developing human brain, ID1 is expressed highest in oligo/astrocyte-precursor cells (OAPCs). These ID1+/SPARCL1+ cells share a transcriptional program with astrocyte-like (AC-like) DIPG cells, and demonstrate upregulation of gene sets involved with regulation of cell migration. Both genetic and pharmacologic [cannabidiol (CBD)] suppression of ID1 results in decreased DIPG cell invasion/migration in vitro and invasion/tumor growth in multiple in vivo models. CBD reduces proliferation through reactive oxygen species (ROS) production at low micromolar concentrations, which we found to be achievable in the murine brainstem. Further, pediatric high-grade glioma patients treated off-trial with CBD (n=15) demonstrate tumor ID1 reduction and improved overall survival compared to historical controls. Our study identifies that ID1 is upregulated in DIPG through reactivation of a developmental OAPC transcriptional state, and ID1-driven invasiveness of DIPG is therapeutically targetable with CBD.One Sentence SummaryThe transcription factor ID1 is upregulated in a subset of DIPG tumor cells, and ID1-driven invasiveness is therapeutically targetable with CBD.

International audience; Hevin is a matricellular glycoprotein that plays important roles in neural developmental processes such as neuronal migration, synaptogenesis and synaptic plasticity. In contrast to other matricellular proteins whose expression decreases when development is complete, hevin remains highly expressed, suggesting its involvement in adult brain function. In vitro studies have shown that hevin can have different post-translational modifications. However, the glycosylation pattern of hevin in the human brain remains unknown, as well as its relative distribution and localization. The present study provides the first thorough characterization of hevin protein expression by Western blot in postmortem adult human brain. Our results demonstrated two major specific immunoreactive bands for hevin: an intense band migrating around 130 kDa, and a band migrating around 100 kDa. Biochemical assays revealed that both hevin bands have a different glycosylation pattern. Subcellular fractionation showed greater expression in membrane-enriched fraction than in cytosolic preparation, and a higher expression in prefrontal cortex (PFC) compared to hippocampus (HIP), caudate nucleus (CAU) and cerebellum (CB). We confirmed that a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) and matrixmetalloproteinase 3 (MMP-3) proteases digestion led to an intense double band with similar molecular weight to that described as SPARC-like fragment (SLF). Finally, hevin immunoreactivity was also detected in human astrocytoma, meningioma, cerebrospinal fluid and serum samples, but was absent from any blood cell type.

Background Liver cancer is the sixth most commonly diagnosed cancer and the fourth most common cause of cancer death. The purpose of this work is to find new diagnostic biomarkers or prognostic biomarkers and explore the biological functions related to the prognosis of liver cancer. Methods GSE25097 datasets were firstly obtained and compared with TCGA LICA datasets and an analysis of the overlapping differentially expressed genes (DEGs) was conducted. Cytoscape was used to screen out the Hub Genes among the DEGs. ROC curve analysis was used to screen the Hub Genes to determine the genes that could be used as diagnostic biomarkers. Kaplan-Meier analysis and Cox proportional hazards model screened genes associated with prognosis biomarkers, and further Gene Set Enrichment Analysis was performed on the prognosis genes to explore the mechanism affecting the survival and prognosis of liver cancer patients. Results 790 DEGs and 2162 DEGs were obtained respectively from the GSE25097 and TCGA LIHC data sets, and 102 Common DEGs were identified by overlapping the two DEGs. Further screening identified 22 Hub Genes from 102 Common DEGs. ROC and survival curves were used to analyze these 22 Hub Genes and it was found that there were 16 genes with a value of AUC > 90%. Among these, the expression levels of ESR1,SPP1 and FOSB genes were closely related to the survival time of liver cancer patients. Three common pathways of ESR1, FOBS and SPP1 genes were identified along with seven common pathways of ESR1 and SPP1 genes and four common pathways of ESR1 and FOSB genes. Conclusions SPP1, AURKA, NUSAP1, TOP2A, UBE2C, AFP, GMNN, PTTG1, RRM2, SPARCL1, CXCL12, FOS, DCN, SOCS3, FOSB and PCK1 can be used as diagnostic biomarkers for liver cancer, among which FOBS and SPP1 genes can also be used as prognostic biomarkers. Activation of the cell cycle-related pathway, pancreas beta cells pathway, and the estrogen signaling pathway, while on the other hand inhibition of the hallmark heme metabolism pathway, hallmark coagulation pathway, and the fat metabolism pathway may promote prognosis in liver cancer patients.

Highlights • Integrative single-cell transcriptome analysis reveals the accumulation of fibroblasts in liver cancer tissues. • SPARCL1 expression distinguishes two subpopulations of the liver cancer-distinct fibroblasts. • SPARCL1 positive fibroblasts are related to favorable prognosis of liver cancer patients., Single-cell transcriptome analysis has provided detailed insights into the ecosystem of liver cancer. However, the changes of the cellular and molecular components of liver tumors in comparison with normal livers have not been described at single-cell level. Here, we performed an integrative single-cell analysis of both normal livers and liver cancers. Principal component analysis was firstly performed to delineate the cell lineages in liver tissues. Differential gene expression within major cell types were then analyzed between tumor and normal samples, thus resolved the cell type-specific molecular alterations in liver cancer development. Moreover, a comparison between liver cancer derived versus normal liver derived cell components revealed that two subpopulations of fibroblasts were exclusively expanded in liver cancer tissues. By further defining subpopulation-specific gene signatures, characterizing their spatial distribution in tumor tissues and investigating their clinical significance, we found that the SPARCL1 positive fibroblasts, representing a group of tumor vessel associated fibroblasts, were related to reduced vascular invasion and prolonged survival of liver cancer patients. Through establishing an in-vitro endothelial-to-mesenchymal transition model, we verified the conversion of the fetal liver sinusoidal endothelial cells into the fibroblast-like cells, demonstrating a possible endothelial cell origination of the SPARCL1 positive fibroblasts. Our study provides new insights into the cell atlas alteration, especially the expanded fibroblasts in liver cancers.

Background and Objectives Endocrine therapy is one of the most effective anti-cancer treatments for HR-positive breast cancers. However, in a significant proportion of patients the disease will relapse irrespective of the treatment modality (SERM, SERD, AI). Despite the progress made with multigene signatures for molecular classification of luminal breast cancers, predicting sensitivity towards endocrine modalities remains challenging. With the help of invasive ductal luminal breast cancers (IDLBC) from the METABRIC study we have developed an integrated clinical-pathologic and genomic classification method, identifying three distinct groups (IDLBC1, -2 and -3) [1, 2]. The 3 groups differ by DNA damage load, predominant lesion type, characteristic lesion patterns and oncogenic driver mechanisms [1, 3]. Here we present characteristic gene expression profiles of IDLBCs and discuss their biologic and clinical implications. Methods Gene expression profiles based on cDNA microarray data of 1.104 IDLBCs on the METABRIC study were examined (EGAS00000000083) [3]. To identify differentially expressed genes across IDLBC1-3 groups (52%, 23%, 25%), we compiled a gene list (N=2034) from 34 gene signatures reported to be predictive of ER, PR, GATA3, FOXA1 and/or AR signalling. A multiclass significance analysis of microarrays with 100 iterations and a false discovery rate of 0.05 was used to extract differentially expressed genes. Results Of 2034 steroid receptor signalling associated genes 36 exhibited differential expression in the IDLBC1/2 and -3 groups. The IDLBC1/2 specific set included 2 ER-associated genes (WLS, SPARCL1), 1 FOXA1-associated gene (NTN4) and 2 PR-associated genes (ZBTB16, CRY2). The IDLBC3 overexpressed set included 31 genes, amongst them regulators of mitotic fidelity, as well as effectors of centromere and kinetochore functioning. Eight of these genes have been reported as ER-associated (POLR2H, ECE2, SCL7A5, KIF11, FAM83D, GPSM2, MASTL, POLE2). Additional IDLBC3 hallmarks included high proliferation activity, defect apoptosis, epithelial-mesenchymal-transformation (EMT), BRCA-ness, multiple-drug resistance (MDR) and early relapse. The estimated relapse-free-survival rate at 5 years in the IDLBC3 group was 77% [95%CI 72; 82], significantly lower than in IDLBC1/2 tumours (91% [95%CI 89; 93]) and comparable to triple negative IDLBCs on the METABRIC study (70% [95%CI: 65; 76]). Conclusions We have shown that our integrated classification method has the potential to segregate early relapsing luminal breast cancers (IDLBC3) from tumours with favourable prognosis (IDLBC1/2). The data presented here and in the abstract by Demanse et al [4] provide also an intuitive hypothesis why IDLBC3 tumours are sensitive towards Letrozole but not Tamoxifen. Prospective clinical studies will be required to validate this hypothesis and to demonstrate the value of the IDLBC classification approach. References 1. Demanse, manuscript in preparation (2018) 2. Pereira, Nat Commun (2016) 3. Curtis, Nat (2012) 4. Demanse, SABCS, abstract submitted (2018) 5. Loi SABCS, Oral Presentation (2016) 6. Luen, JAMA Oncology (2018) Citation Format: Hackl W, Pinet D, Demanse D. A novel integrated, clinical-pathologic and genomic classification method segregates early from late relapsing invasive ductal luminal breast cancers (IDLBC) of the METABRIC study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-08-06.

Background/Aims: Secreted protein acidic and rich in cysteines-like 1 (SPARCL1) is abnormally expressed in gastrointestinal (GI) malignancies. However, the correlation between SPARCL1 expression and the prognosis of patients remains unknown. Therefore, we performed a meta-analysis to investigate the potential value of SPARCL1 as a prognostic predictive marker for GI malignancies. Methods: The PubMed, Embase, EBSCO, CNKI, and Wanfang databases were systematically searched for studies examining SPARCL1 and clinicopathological features, including the prognoses of patients. Hazard ratios (HRs) and odds ratios (ORs) from individual studies were calculated and pooled using a random-effects or fix-effects model. Heterogeneity and publication bias analyses were performed. Results: Data from 8 studies, including a total of 2,356 patients, were summarized. The expression of SPARCL1 suggested a better prognosis (HR=0.57, 95% CI: 0.445-0.698, P=0.000) and was associated with clinicopathological features of GI malignancies, including distant metastasis (OR=0.44, 95% CI: 0.23-0.85, P=0.014), lymph node metastasis (OR=0.56, 95% CI: 0.39–0.81, P=0.002) and tumor differentiation (OR=2.21, 95% CI: 1.82–2.69, P=0.000). Subgroup analyses based on cancer type revealed that the expression of SPARCL1 had no effect on lymph node metastasis in colorectal cancer, and it did not influence tumor differentiation in gastric cancer. Egger’s test showed no evidence of publication bias (all P>0.05). Conclusion: SPARCL1 could be a novel prognostic predictive factor for GI malignancies. The expression of SPARCL1 could influence the clinicopathological features of GI malignancies. Further large-scale studies are essential to confirm SPARCL1’s prognostic predictive value, and more fundamental experimental studies are needed to illustrate the mechanisms.

Metastasis significantly reduces the survival rate of osteosarcoma (OS) patients. Therefore, identification of novel targets remains extremely important to prevent metastasis and treat OS. In this report, we show that SPARCL1 is downregulated in OS by epigenetic methylation of promoter DNA. In vitro and in vivo experiments revealed that SPARCL1 inhibits OS metastasis. We further demonstrated that SPARCL1-activated WNT/β-catenin signaling by physical interaction with various frizzled receptors and lipoprotein receptor-related protein 5/6, leading to WNT-receptor complex stabilization. Activation of WNT/β-catenin signaling contributes to the SPARCL1-mediated inhibitory effects on OS metastasis. Furthermore, we uncovered a paracrine effect of SPARCL1 on macrophage recruitment through activated WNT/β-catenin signaling-mediated secretion of chemokine ligand5 from OS cells. These findings suggest that the targeting of SPARCL1 as a new anti-metastatic strategy for OS patients.

Background The aim of this study is to identify the potential pathogenic and metastasis-related differentially expressed genes (DEGs) in osteosarcoma through bioinformatic analysis of Gene Expression Omnibus (GEO) database. Results Gene expression profiles of GSE14359, GSE16088, and GSE33383, in total 112 osteosarcoma tissue samples and 7 osteoblasts, were analyzed. Seventy-four normal-primary DEGs (NPDEGs) and 764 primary-metastatic DEGs (PMDEGs) were screened. VAMP8, A2M, HLA-DRA, SPARCL1, HLA-DQA1, APOC1 and AQP1 were identified continuously upregulating during the oncogenesis and metastasis of osteosarcoma. The enriched functions and pathways of NPDEGs include procession and presentation of antigens, activation of MHC class II receptors and phagocytosis. The enriched functions and pathways of PMDEGs include mitotic nuclear division, cell adhesion molecules (CAMs) and focal adhesion. With protein-protein interaction (PPI) network analyzed by Molecular Complex Detection (MCODE) plug-in of Cytoscape software, one hub NPDEG (HLA-DRA) and 7 hub PMDEGs (CDK1, CDK20, CCNB1, MTIF2, MRPS7, VEGFA and EGF) were eventually selected, and the most significant pathways in NPDEGs module and PMDEGs module were enriched in the procession and presentation of exogenous peptide antigen via MHC class II and the nuclear division, respectively. Conclusions By integrated bioinformatic analysis, numerous DEGs related to osteosarcoma were screened, and the hub DEGs identified in this study are possibly part of the potential biomarkers for osteosarcoma. However, further experimental studies are still necessary to elucidate the biological function and mechanism of these genes.

The last decade has been characterized by a deluge of published scientific literature as well as data generation by biological experiments. The major impediment for the research community to unlock the knowledge contained in literature and further drive biomedical research is the inability to process huge data resources in a faster and efficient manner. Efforts are ongoing to develop knowledge management systems with automated text mining methods at the heart of such systems but the results have been tempered by varying factors such as ease of use, efficiency, reliability, and applicability across different scenarios. Despite the shortcomings, the research community has been able to leverage automatic literature processing to close the information gap between the reporting of facts in literature and the use of validated data in research, and in particular in the area of drug discovery. Within the scope of this thesis, I have brought together state of the art solutions in two different areas of automated text mining: machine learning-based methods and lexicon-based methods in a manner to leverage the advantages of both the approaches while trying to minimize the problems faced when they are used in isolation. The work has been used for the identification of protein interactions to validate the biological mechanisms explaining the repair processes in a myocardial infarction condition. In recent times a less-investigated protein SPARCL1, has come up as a prognostic marker in various types of cancer and wound healing/repair mechanisms in different tissues including in injured cardiomyocytes but the mechanism of action of the protein remains unclear. The presented research work used established data resources for the mining of Medline abstracts and full-text literature. This thesis used features for the relation extraction using the GENIA Corpus, used geniatagger as the machine learning-based text mining component in conjunction with a lexicon of gene and protein names of over 8 million instances derived from HGNC and UniProt. The hybrid NER solution has been evaluated against the BioCreative 2 corpus, leading to 68.7% precision and 64% recall, which is both equivalent (or even superior) to other reported solutions, that use heterogeneous data sources for text mining and include a gene normalisation step. The relation extraction has been evaluated against the IntAct corpus and lead to recall and precision of 3.7% and 28.6%, respectively, which again is equivalent to state of the art solutions. The findings from the automatic text processing have been evaluated against the other available (interactive, non-automatic) data sources for relevant protein relations to identify that the interaction between Decorin and SPARCL1 is a very promising candidate for the regulation of the inflammatory processes in relation to myocardial infarction, and has not been considered as a key candidate in the literature so far. The interaction between Decorin and SPARCL1 has been validated experimentally and provides compelling evidence to be considered as the key factor for mediating repair of cardiomyocytes after myocardial infarction, offering opportunities to develop new therapies. Overall the thesis demonstrates the full workflow for hypothesis generation from the scientific literature up to its validation through experimental results and thus extends the work by Swanson and Smallheiser, where merely the association of not directly related concepts has been proven by finding similarities between sets of documents. The experimental validation aims to provide a high degree of confidence in the deployed workflow and open up avenues for newer therapies in other conditions too.

Glioblastoma (GBM) is the most malignant brain tumor of adults and is characterized by extensive cell dissemination within the brain parenchyma and enhanced angiogenesis. Effective preclinical modeling of these key features suffers from several shortcomings. Aim of this study was to determine whether modulating the expression of extracellular matrix (ECM) modifiers in proneural (PN) and mesenchymal (MES) cancer stem cells (CSCs) and in conventional glioma cell lines (GCLs) might improve tumor invasion and vascularization. To this end, we selected secreted, acidic and rich in cysteine-like 1 (SPARCL1) as a potential mediator of ECM remodeling in GBM. SPARCL1 transcript and protein expression was assessed in PN and MES CSCs as well as GCLs, in their xenografts and in patient-derived specimens by qPCR, WB and IHC. SPARCL1 expression was then enforced in both CSCs and GCLs by lentiviral-based transduction. The effect of SPARCL1 gain-of-function on microvascular proliferation, microglia activation and advanced imaging features was tested in intracranial xenografts by IHC and MRI and validated by chorioallantoic membrane (CAM) assays. SPARCL1 expression significantly enhanced the infiltrative and neoangiogenic features of PN and MES CSC/GCL-induced tumors, with the concomitant activation of inflammatory responses associated with the tumor microenvironment, thus resulting in experimental GBMs that reproduced both the parenchymal infiltration and the increased microvascular density, typical of GBM. Overall, these results indicate that SPARCL1 overexpression might be instrumental for the generation of CSC-derived preclinical models of GBM in which the main pathognomonic hallmarks of GBMs are retrievable, making them suitable for effective preclinical testing of therapeutics.

Aim: This study assessed the utility of SPARC-like protein 1 (SPARCL1) as a biomarker of maladaptive right ventricular (RV) function in patients with pulmonary hypertension (PH). Methods: In this prospective study, we examined SPARCL1 levels in 105 patients with adaptive (n = 34) and maladaptive RV (n = 32) pressure overload caused by PH, dilated cardiomyopathy (DCM, n = 18) with LVEF < 35% and preserved RV function and controls without LV or RV abnormalities (n = 21). Results: The median SPARCL1 concentration in patients with maladaptive RV function was higher than in those with adaptive RV function (p p p p p Conclusion: SPARCL1 shows potential as novel biomarker of RV pathological remodelling and is associated with RV maladaptation and ventriculoarterial uncoupling in PH.

Our understanding of cancer has evolved mainly from results of studies utilizing experimental models. Simplification inherent to in vitro cell culture models enabled potential ways of cell behaviour in response to various external stimuli to be described, but it has led also to disappointments in clinical trials, presumably due to the lack of crucial tissue components, including extracellular matrix (ECM). ECM and its role in healthy and diseased tissues are being explored extensively and significance of ECM for cell behaviour has been evidenced experimentally. Part of the information gathered in such research that is relevant for natural conditions of a human body can be identified by carefully designed analyses of human tissue samples. This review summarizes published information on clinical significance of ECM in cancer and examines whether effects of ECM on cell behaviour evidenced in vitro, could be supported by clinically based data acquired from analysis of tissue samples. Based on current approaches of clinical immunohistochemical analyses, impact of ECM components on tumour cell behaviour is vague. Except of traditionally considered limitations, other reasons may include lack of stratification of analyzed cases based on clinicopathologic parameters, inclusion of patients treated postoperatively by different treatments or neglecting complexity of interactions among tumour constituents. Nevertheless, reliable immunohistochemical studies represent a source of crucial information for design of tumour models comprising ECM corresponding to real clinical situation. Knowledge gathered from such immunohistochemical studies combined with achievements in tissue engineering hold promise for reversal of the unfavourable trends in the current translational oncologic research.

Secreted protein acidic and rich in cysteines-like protein 1 (SPARCL1) has been implicated in tumor initiation, formation, and progression of various cancers, yet its role in hilar cholangiocarcinoma remains largely uncharacterized. In the present study, tissue microarrays containing resected hilar cholangiocarcinoma specimens from 92 patients were used to evaluate the expression of SPARCL1 protein by immunohistochemistry (IHC). In vitro assays were used to determine the effect of SPARCL1 overexpression on cell growth and migration. Loss of SPARCL1 expression was observed in 46 (50.0 %) of the 92 primary tumors. SPARCL1 expression is inversely associated with poorly or undifferentiation specimens (P = 0.030) in addition to lymph node metastasis (P = 0.047). Survival analysis demonstrated that SPARCL1 is an independent factor in predicting the outcome of patients with hilar cholangiocarcinoma. SPARCL1 overexpression suppressed tumor cell migration in vitro by inhibiting MMP-9, MMP-2, Vimentin, and Fibronectin expression, whereas did not inhibit cell proliferation in vitro. Our results suggest that loss of SPARCL1 is involved in the tumorigenesis of hilar cholangiocarcinoma and may serve as a novel molecular biomarker for patients' outcome.

Summary Objective To assess the impact of osteoarthritis (OA) on the meniscus by comparing transcripts and biological processes in the meniscus between patients with and without OA. Design RNA microarrays were used to identify transcripts differentially expressed (DE) in meniscus obtained from 12 OA and 12 non-OA patients. The non-OA specimens were obtained at the time of arthroscopic partial meniscectomy. Real-time PCR was performed on selected transcripts. Biological processes and gene-networking was examined computationally. Transcriptome signatures were mapped with 37 OA-related transcripts to evaluate how meniscus gene expression relates to that of OA cartilage. Results We identified 168 transcripts significantly DE between OA (75 elevated, 93 repressed) and non-OA samples (≥1.5-fold). Among these, CSN1S1 , COL10A1 , WIF1 , and SPARCL1 were the most prominent transcripts elevated in OA meniscus, POSTN and VEGFA were most highly repressed in OA meniscus. Transcripts elevated in OA meniscus represented response to external stimuli, cell migration and cell localization while those repressed in OA meniscus represented histone deacetylase activity (related to epigenetics) and skeletal development. Numerous long non-coding RNAs (lncRNAs) were DE between the two groups. When segregated by OA-related transcripts, two distinct clustering patterns appeared: OA meniscus appeared to be more inflammatory while non-OA meniscus exhibited a "repair" phenotype. Conclusions Numerous transcripts with potential relevance to the pathogenesis of OA are DE in OA and non-OA meniscus. These data suggest an involvement of epigenetically regulated histone deacetylation in meniscus tears as well as expression of lncRNAs. Patient clustering based on transcripts related to OA in articular cartilage confirmed distinct phenotypes between injured (non-OA) and OA meniscus.