Integrated analysis of microfibrillar-associated proteins reveals MFAP4 as a novel biomarker in human cancers

Competing endogenous RNAs regulatory crosstalk networks: The messages from the RNA world to signaling pathways directing cancer stem cell development

Cancer stem cells (CSCs) are one of the cell types that account for cancer heterogeneity. The cancer cells arrest in G0 and generate non-CSC progeny through self-renewal and pluripotency, resulting in tumor recurrence, metastasis, and resistance to chemotherapy. They can stimulate tumor relapse and re-grow a metastatic tumor. So, CSCs is a promising target for eradicating tumors, and developing an anti-CSCs therapy has been considered. In recent years competing endogenous RNA (ceRNA) has emerged as a significant class of post-transcriptional regulators that affect gene expression via competition for microRNA (miRNA) binding. Furthermore, aberrant ceRNA expression is associated with tumor progression. Recent findings show that ceRNA network can cause tumor progression through the effect on CSCs. To overcome therapeutic resistance due to CSCs, we need to improve our current understanding of the mechanisms by which ceRNAs are implicated in CSC-related relapse. Thus, this review was designed to discuss the role of ceRNAs in CSCs' function. Targeting ceRNAs may open the path for new cancer therapeutic targets and can be used in clinical research.

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer

Background

Cancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA.

Methods

CAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA.

Results

Integrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA.

Conclusions

A novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.

PathExpSurv: pathway expansion for explainable survival analysis and disease gene discovery

BACKGROUND

In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop neural networks-based methods, so as to provide some insights and interpretability for the models. However, the prior biological knowledge may be incomplete and there still exists some unknown information to be explored.

RESULTS

We proposed a novel method, named PathExpSurv, to gain an insight into the black-box model of neural network for cancer survival analysis. We demonstrated that PathExpSurv could not only incorporate the known prior information into the model, but also explore the unknown possible expansion to the existing pathways. We performed downstream analyses based on the expanded pathways and successfully identified some key genes associated with the diseases and original pathways.

CONCLUSIONS

Our proposed PathExpSurv is a novel, effective and interpretable method for survival analysis. It has great utility and value in medical diagnosis and offers a promising framework for biological research.

Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes

Healing wounds and cancers present remarkable cellular and molecular parallels, but the specific roles of the healing phases are largely unknown. We developed a bioinformatics pipeline to identify genes and pathways that define distinct phases across the time-course of healing. Their comparison to cancer transcriptomes revealed that a resolution phase wound signature is associated with increased severity in skin cancer and enriches for extracellular matrix-related pathways. Comparisons of transcriptomes of early- and late-phase wound fibroblasts vs skin cancer-associated fibroblasts (CAFs) identified an "early wound" CAF subtype, which localizes to the inner tumor stroma and expresses collagen-related genes that are controlled by the RUNX2 transcription factor. A "late wound" CAF subtype localizes to the outer tumor stroma and expresses elastin-related genes. Matrix imaging of primary melanoma tissue microarrays validated these matrix signatures and identified collagen- vs elastin-rich niches within the tumor microenvironment, whose spatial organization predicts survival and recurrence. These results identify wound-regulated genes and matrix patterns with prognostic potential in skin cancer.

Declined plasma microfibrillar-associated protein 4 levels in acute coronary syndrome

BACKGROUND

Microfibrillar-associated protein (MFAP4), initially identified as an extracellular matrix protein, has been demonstrated in multiple human disorders, but it is yet to be discovered following acute coronary syndrome (ACS) in clinical practice. Therefore, this study aimed to investigate the relationship between circulating MFAP4 levels and coronary stenosis in ACS.

METHODS

We performed the study in 148 ACS subjects, including 75 ST-segment elevation myocardial infarction (STEMI), 27 non-ST-segment elevation myocardial infarction (non-STEMI) and 46 unstable angina (UA). Clinical variables were collected and Gensini and Syntax stenosis scoring systems were applied to assess the severity of coronary stenosis. Kaplan-Meier and logistic regression analysis were used to analyze the relationship between MFAP4 and the severity of coronary stenosis or ACS outcomes. Spearman analysis was used to describe the correlation between MFAP4 and clinical parameters.

RESULTS

Circulating MFAP4 levels were significantly decreased in the STEMI group (0.008 ng/ml) compared with the non-STEMI group (0.014 ng/ml) and UA group (0.019 ng/ml) (p < 0.001). After adjusting for confounding factors, we found that MFAP4 was an independent risk factor for STEMI (odds ratio = 0.395, 95% CI 0.174-0.895, p = 0.026). MFAP4 level was negatively correlated with Gensini score and Syntax score (r = - 0.311 and - 0.211, p < 0.001 and 0.01, respectively). Based on the MFAP4 level of 0.117 ng/ml, ACS patients were divided into two groups: the low-MFAP4 group (< 0.117 ng/ml, n = 60) and the high-MFAP4 group (≥ 0.117 ng/ml, n = 88). After the median follow-up of 165 days, Kaplan-Meier survival analysis revealed that the MACE-free rate was significantly lower in ACS patients with lower MFAP4 levels (p = 0.009).

CONCLUSIONS

MFAP4 has a potential as a biomarker for the degree of coronary stenosis in ACS. Confirmation of observations in larger cohorts and longer follow-up periods is warranted.

Chronic Inhalation Exposure to Antimony Trioxide Exacerbates the MAPK Signaling in Alveolar Bronchiolar Carcinomas in B6C3F1/N Mice

Antimony trioxide (AT) is used as a flame retardant in fabrics and plastics. Occupational exposure in miners and smelters is mainly through inhalation and dermal contact. Chronic inhalation exposure to AT particulates in B6C3F1/N mice and Wistar Han rats resulted in increased incidences and tumor multiplicities of alveolar/bronchiolar carcinomas (ABCs). In this study, we demonstrated Kras (43%) and Egfr (46%) hotspot mutations in mouse lung tumors (n = 80) and only Egfr (50%) mutations in rat lung tumors (n = 26). Interestingly, there were no differences in the incidences of these mutations in ABCs from rats and mice at exposure concentrations that did and did not exceed the pulmonary overload threshold. There was increased expression of p44/42 mitogen-activated protein kinase (MAPK) (Erk1/2) protein in ABCs harboring mutations in Kras and/or Egfr, confirming the activation of MAPK signaling. Transcriptomic analysis indicated significant alterations in MAPK signaling such as ephrin receptor signaling and signaling by Rho-family GTPases in AT-exposed ABCs. In addition, there was significant overlap between transcriptomic data from mouse ABCs due to AT exposure and human pulmonary adenocarcinoma data. Collectively, these data suggest chronic AT exposure exacerbates MAPK signaling in ABCs and, thus, may be translationally relevant to human lung cancers.

MFAP4-Mediated Effects in Elastic Fiber Homeostasis, Integrin Signaling and Cancer, and Its Role in Teleost Fish

Microfibrillar-associated protein 4 (MFAP4) is an extracellular matrix (ECM) protein belonging to the fibrinogen-related domain superfamily. MFAP4 is highly expressed in elastin-rich tissues such as lung, blood vessels and skin. MFAP4 is involved in organization of the ECM, regulating proper elastic fiber assembly. On the other hand, during pathology MFAP4 actively contributes to disease development and progression due to its interactions with RGD-dependent integrin receptors. Both tissue expression and circulating MFAP4 levels are associated with various disorders, including liver fibrosis and cancer. In other experimental models, such as teleost fish, MFAP4 appears to participate in host defense as a macrophage-specific innate immune molecule. The aim of this review is to summarize the accumulating evidence that indicates the importance of MFAP4 in homeostasis as well as pathological conditions, discuss its known biological functions with special focus on elastic fiber assembly, integrin signaling and cancer, as well as describe the reported functions of non-mammalian MFAP4 in fish. Overall, our work provides a comprehensive overview on the role of MFAP4 in health and disease.

A methylation-driven genes prognostic signature and the immune microenvironment in epithelial ovarian cancer

Aberrant gene methylation has been implicated in the development and progression of tumors. In this study, we aimed to identity methylation driven genes involved in epithelial ovarian cancer (EOC) to establish a prognostic signature for patients with EOC. We identified and verified 6 MDGs that are closely related to the prognosis of ovarian cancer. A prognostic risk score model and nomogram for predicting the prognosis of ovarian cancer were constructed based on the six MDGs. It can also effectively reflect the immune environment and immunotherapy response of ovarian cancer. These MDGs have great significance to the implementation of individualized treatment and disease monitoring of ovarian cancer patients.

iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

Gene Expression Monotonicity across Bladder Cancer Stages Informs on the Molecular Pathogenesis and Identifies a Prognostic Eight-Gene Signature

Despite advancements in molecular classification, tumor stage and grade still remain the most relevant prognosticators used by clinicians to decide on patient management. Here, we leverage publicly available data to characterize bladder cancer (BLCA)’s stage biology based on increased sample sizes, identify potential therapeutic targets, and extract putative biomarkers. A total of 1135 primary BLCA transcriptomes from 12 microarray studies were compiled in a meta-cohort and analyzed for monotonal alterations in pathway activities, gene expression, and co-expression patterns with increasing stage (Ta–T1–T2–T3–T4), starting from the non-malignant tumor-adjacent urothelium. The TCGA-2017 and IMvigor-210 RNA-Seq data were used to validate our findings. Wnt, MTORC1 signaling, and MYC activity were monotonically increased with increasing stage, while an opposite trend was detected for the catabolism of fatty acids, circadian clock genes, and the metabolism of heme. Co-expression network analysis highlighted stage- and cell-type-specific genes of potentially synergistic therapeutic value. An eight-gene signature, consisting of the genes AKAP7, ANLN, CBX7, CDC14B, ENO1, GTPBP4, MED19, and ZFP2, had independent prognostic value in both the discovery and validation sets. This novel eight-gene signature may increase the granularity of current risk-to-progression estimators.

Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).

Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.

Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.

Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

Cobalt-induced oxidative stress contributes to alveolar/bronchiolar carcinogenesis in B6C3F1/N mice

Rodent alveolar/bronchiolar carcinomas (ABC) that arise either spontaneously or due to chemical exposure are similar to a subtype of lung adenocarcinomas in humans. B6C3F1/N mice and F344/NTac rats exposed to cobalt metal dust (CMD) by inhalation developed ABCs in a dose dependent manner. In CMD-exposed mice, the incidence of Kras mutations in ABCs was 67% with 80% of those being G to T transversions on codon 12 suggesting a role of oxidative stress in the pathogenesis. In vitro studies, such as DMPO (5,5-dimethyl-1-pyrroline N-oxide) immune-spin trapping assay, and dihydroethidium (DHE) fluorescence assay on A549 and BEAS-2B cells demonstrated increased oxidative stress due to cobalt exposure. In addition, significantly increased 8-oxo-dG adducts were demonstrated by immunohistochemistry in lungs from mice exposed to CMD for 90 days. Furthermore, transcriptomic analysis on ABCs arising spontaneously or due to chronic CMD-exposure demonstrated significant alterations in canonical pathways related to MAPK signaling (IL-8, ErbB, Integrin, and PAK pathway) and oxidative stress (PI3K/AKT and Melatonin pathway) in ABCs from CMD-exposed mice. Oxidative stress can stimulate PI3K/AKT and MAPK signaling pathways. Nox4 was significantly upregulated only in CMD-exposed ABCs and NOX4 activation of PI3K/AKT can lead to increased ROS levels in human cancer cells. The gene encoding Ereg was markedly up-regulated in CMD-exposed mice. Oncogenic KRAS mutations have been shown to induce EREG overexpression. Collectively, all these data suggest that oxidative stress plays a significant role in CMD-induced pulmonary carcinogenesis in rodents and these findings may also be relevant in the context of human lung cancers.

Alterations in protein expression and site-specific N-glycosylation of prostate cancer tissues

Identifying molecular alterations occurring during cancer progression is essential for a deeper understanding of the underlying biological processes. Here we have analyzed cancerous and healthy prostate biopsies using nanoLC-MS(MS) to detect proteins with altered expression and N-glycosylation. We have identified 75 proteins with significantly changing expression during disease progression. The biological processes involved were assigned based on protein-protein interaction networks. These include cellular component organization, metabolic and localization processes. Multiple glycoproteins were identified with aberrant glycosylation in prostate cancer, where differences in glycosite-specific sialylation, fucosylation, and galactosylation were the most substantial. Many of the glycoproteins with altered N-glycosylation were extracellular matrix constituents, and are heavily involved in the establishment of the tumor microenvironment.

Screening and Identification of Key Microenvironment-Related Genes in Non-functioning Pituitary Adenoma

Purpose

Non-functioning pituitary adenoma (NFPA) is a very common type of intracranial tumor, which can be locally invasive and can have a high recurrence rate. The tumor microenvironment (TME) shows a high correlation with tumor pathogenesis and prognosis. The current study aimed to identify microenvironment-related genes in NFPAs and assess their prognostic value.

Methods

73 NFPA tumor samples were collected from Beijing Tiantan Hospital and transcriptional expression profiles were obtained through microarray analysis. The immune and stromal scores of each sample were calculated through the ESTIMATE algorithm, and the patients were divided into high and low immune/stromal score groups. Intersection differentially expressed genes (DEGs) were then obtained to construct a protein–protein interaction (PPI) network. Potential functions and pathways of intersection DEGs were then analyzed through Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. The prognostic value of these genes was evaluated. The quantitative real-time polymerase chain reaction in another set of NFPA samples was used to confirm the credibility of the bioinformatics analysis.

Results

The immune/stromal scores were significantly correlated with cavernous sinus (CS) invasion. The Kaplan–Meier curve indicated that the high immune score group was significantly related to poor recurrence-free survival. We identified 497 intersection DEGs based on the high vs. low immune/stromal score groups. Function enrichment analyses of 497 DEGs and hub genes from the PPI network showed that these genes are mainly involved in the immune/inflammatory response, T cell activation, and the phosphatidylinositol 3 kinase-protein kinase B signaling pathway. Among the intersection DEGs, 88 genes were further verified as significantly expressed between the CS invasive group and the non-invasive group, and five genes were highly associated with NFPA prognosis.

Conclusion

We screened out a series of critical genes associated with the TME in NFPAs. These genes may play a fundamental role in the development and prognosis of NFPA and may yield new therapeutic targets.

Convergent network effects along the axis of gene expression during prostate cancer progression

Background

Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues.

Results

Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers.

Conclusions

This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.

Immunoglobulin superfamily member 10 is a novel prognostic biomarker for breast cancer

Background

Immunoglobulin superfamily member 10 (IGSF10) is a member of the immunoglobulin superfamily that is expressed at high levels in both the gallbladder and ovary. Currently, the role and possible mechanism of IGSF10 in breast cancer remain unclear.

Method

By applying real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), the expression of IGSF10 in breast cancer cells and tissues was detected. We collected the clinical information from 700 patients with breast cancer in The Cancer Genome Atlas (TCGA), and analyzed the relationship between IGSF10 expression and the clinicopathological features and survival outcomes of these patients. The potential mechanisms and pathways associated with IGSF10 in breast cancer were explored by performing a gene set enrichment analysis (GSEA).

Results

According to TCGA data, qRT-PCR and IHC experiments, levels of the IGSF10 mRNA and protein were significantly decreased in breast cancer tissues. IGSF10 expression was significantly correlated with age, tumor size, and tumor stage. Moreover, shorter overall survival (OS) and relapse-free survival (RFS) correlated with lower IGSF10 expression, according to the survival analysis. The multivariate analysis identified that IGSF10 as an independent prognostic factor for the OS (hazard ratio (HR) = 1.793, 95% confidence interval (CI) [1.141–2.815], P = 0.011) and RFS (HR = 2.298, 95% CI [1.317–4.010], P = 0.003) of patients with breast cancer. Based on the GSEA, IGSF10 was involved in DNA repair, cell cycle, and glycolysis. IGSF10 was also associated with the PI3K/Akt/mTOR and mTORC1 signaling pathways.

Conclusions

This study revealed a clear relationship between IGSF10 expression and the tumorigenesis of breast cancer for the first time. Therefore, further studies are needed to understand the mechanism of IGSF10 in breast cancer.

Identification of a Novel Cancer Stemness-Associated ceRNA Axis in Lung Adenocarcinoma via Stemness Indices Analysis

The aim of this study was to identify a novel cancer stemness-related ceRNA regulatory axis in lung adenocarcinoma (LUAD) via weighted gene coexpression network analysis of a stemness index. The RNA sequencing expression profiles of 513 cancer samples and 60 normal samples were obtained from the TCGA database. Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) were identified with R software. Functional enrichment analysis was conducted using DAVID 6.8. The ceRNA network was constructed via multiple bioinformatics analyses, and the correlations between possible ceRNAs and prognosis were analyzed using Kaplan–Meier plots. WGCNA was then applied to distinguish key genes related to the mRNA expression-based stemness index (mRNAsi) in LUAD. After combining the weighted gene coexpression and ceRNA networks, a novel ceRNA regulatory axis was identified, and its biological functions were explored in vitro and vivo. In total, 1,825 DElncRNAs, 291 DEmiRNAs, and 3,742 DEmRNAs were identified. Functional enrichment analysis revealed that the DEmRNAs might be associated with LUAD onset and progression. The ceRNA network was constructed with 14 lncRNAs, 10 miRNAs, and 52 mRNAs. Kaplan–Meier analysis identified 2 DEmiRNAs, 5 DElncRNAs, and 41 DEmRNAs with remarkable prognostic power. One gene (MFAP4) in the ceRNA network was found to be closely related to mRNAsi by using WGCNA. Functional investigation further confirmed that the C8orf34-as1/miR-671-5p/MFAP4 regulatory axis has important functions in LUAD cell migration and stemness. This study provides a deeper understanding of the lncRNA–miRNA–mRNA ceRNA network and, more importantly, reveals a novel ceRNA regulatory axis, which may provide new insights into novel molecular therapeutic targets for inhibiting LUAD stem characteristics.

Microfibril associated protein 4 (MFAP4) is a carrier of the tumor associated carbohydrate sialyl-Lewis x (sLex) in pancreatic adenocarcinoma

Late diagnosis of pancreatic ductal adenocarcinoma (PDA) is one of the reasons of its low 5-year survival rate and it is due to its unspecific symptoms during the first stages of the disease and the lack of reliable serological markers. Since PDA shows an altered glycan expression, here we have focused on finding novel potential biomarkers, namely glycoproteins that express the tumor associated carbohydrate structure sialyl-Lewis x (sLe^x), which is described in PDA. Through a glycoproteomic approach, we have analyzed target proteins containing sLe^x from PDA tissues by 2DE and immunodetection techniques, and have identified by mass spectrometry the protein MFAP4 as a carrier of sLe^x in PDA. MFAP4 showed a higher expression in PDA tissues compared with pancreatic control tissues. In addition, the colocalization of sLe^x over MFAP4 was found only in PDA and not in control pancreatic tissues. The analysis of MFAP4 expression in PDA cell lines and their secretome, in combination with immunohistochemistry of pancreatic tissues, revealed that MFAP4 was not produced by PDA cells, but it was found in the pancreatic extracellular matrix. The specificity of MFAP4 glycoform containing sLe^x in PDA tissues shows its relevance as a potential PDA biomarker. SIGNIFICANCE: Despite advances in the field of cancer research, pancreatic ductal adenocarcinoma (PDA) lacks of a specific and sensitive biomarker for its early detection, when curative resection is still possible before metastases arise. Thus, efforts to discover new PDA biomarkers represent the first line in the fight against the increase of its incidence reported in recent years. Glycan alterations on glycoconjugates, such as glycoproteins have emerged as a rich source for the identification of novel cancer markers. In the present work, we aimed to shed light on novel biomarkers based on altered glycosylation in PDA, in particular those glycoproteins of PDA tissues carrying the tumor carbohydrate antigen sialyl-Lewis x (sLe^x). Through a glycoproteomic approach, we have shown that the glycoprotein MFAP4 carries sLe^x in PDA tissues and not in control pancreatic tissues. MFAP4 is found in the extracellular matrix in PDA and although its role in cancer progression is unclear, its sLe^x glycoform could be a potential biomarker in pancreatic ductal adenocarcinoma.

Mass spectrometry-based analysis of formalin-fixed, paraffin-embedded distal cholangiocarcinoma identifies stromal thrombospondin-2 as a potential prognostic marker

Background

Distal cholangiocarcinoma is an aggressive malignancy with a dismal prognosis. Diagnostic and prognostic biomarkers for distal cholangiocarcinoma are lacking. The aim of the present study was to identify differentially expressed proteins between distal cholangiocarcinoma and normal bile duct samples.

Methods

A workflow utilizing discovery mass spectrometry and verification by parallel reaction monitoring was used to analyze surgically resected formalin-fixed, paraffin-embedded samples from distal cholangiocarcinoma patients and normal bile duct samples. Bioinformatic analysis was used for functional annotation and pathway analysis. Immunohistochemistry was performed to validate the expression of thrombospondin-2 and investigate its association with survival.

Results

In the discovery study, a total of 3057 proteins were identified. Eighty-seven proteins were found to be differentially expressed (q < 0.05 and fold change ≥ 2 or ≤ 0.5); 31 proteins were upregulated and 56 were downregulated in the distal cholangiocarcinoma samples compared to controls. Bioinformatic analysis revealed an abundance of differentially expressed proteins associated with the tumor reactive stroma. Parallel reaction monitoring verified 28 proteins as upregulated and 18 as downregulated in distal cholangiocarcinoma samples compared to controls. Immunohistochemical validation revealed thrombospondin-2 to be upregulated in distal cholangiocarcinoma epithelial and stromal compartments. In paired lymph node metastases samples, thrombospondin-2 expression was significantly lower; however, stromal thrombospondin-2 expression was still frequent (72%). Stromal thrombospondin-2 was an independent predictor of poor disease-free survival (HR 3.95, 95% CI 1.09–14.3; P = 0.037).

Conclusion

Several proteins without prior association with distal cholangiocarcinoma biology were identified and verified as differentially expressed between distal cholangiocarcinoma and normal bile duct samples. These proteins can be further evaluated to elucidate their biomarker potential and role in distal cholangiocarcinoma carcinogenesis. Stromal thrombospondin-2 is a potential prognostic marker in distal cholangiocarcinoma.

Microfibril-associated glycoprotein 4 (Mfap4) regulates haematopoiesis in zebrafish

Microfibril-associated glycoprotein 4 (MFAP4) is an extracellular matrix protein belonging to the fibrinogen-related protein superfamily. MFAP4 is produced by vascular smooth muscle cells and is highly enriched in the blood vessels of the heart and lung, where it is thought to contribute to the structure and function of elastic fibers. Genetic studies in humans have implicated MFAP4 in the pathogenesis of Smith-Magenis syndrome, in which patients present with multiple congenital abnormalities and mental retardation, as well as in the severe cardiac malformation left-sided congenital heart disease. Comprehensive genetic analysis of the role of MFAP4 orthologues in model organisms during development and tissue homeostasis is however lacking. Here, we demonstrate that zebrafish mfap4 transcripts are detected embryonically, resolving to the macrophage lineage by 24 h post fertilization. mfap4 null mutant zebrafish are unexpectedly viable and fertile, without ostensible phenotypes. However, tail fin amputation assays reveal that mfap4 mutants have reduced numbers of macrophages, with a concomitant increase in neutrophilic granulocytes, although recruitment of both cell types to the site of injury was unaffected. Molecular analyses suggest that loss of Mfap4 alters the balance between myeloid and lymphoid lineages during both primitive and definitive haematopoiesis, which could significantly impact the downstream function of the immune system.

Bioinformatic screening and identification of downregulated hub genes in adrenocortical carcinoma

The molecular mechanisms of adrenocortical carcinoma (ACC) carcinogenesis and progression remain unclear. In the present study, three microarray datasets from the Gene Expression Omnibus database were screened, which identified a total of 96 differentially expressed genes (DEGs). A protein-protein interaction network (PPI) was established for these DEGs and module analysis was performed using STRING and Cytoscape. A total of eight hub genes were identified from the most significant module; namely, calponin 1 (CNN1), myosin light chain kinase (MYLK), cysteine and glycine rich protein 1 (CSRP1), myosin heavy chain 11 (MYH11), fibulin extracellular matrix protein 2 (EFEMP2), fibulin 1 (FBLN1), microfibril associated protein 4 (MFAP4) and fibulin 5 (FBLN5). The biological functions of these hub genes were analyzed using the DAVID online tool. Changes in the expression of hub genes did not affect overall survival; however, downregulated EFEMP2 decreased disease-free survival. CSRP1 and MFAP4 expression levels were associated with adverse clinicopathological features. In conclusion, although all eight hub genes were downregulated in ACC, they appeared to have important functions in ACC carcinogenesis and progression. Identification of these genes complements the genetic expression profile of ACC and provides insight for the diagnosis, treatment and prognosis of ACC.

Molecular structure and function of microfibrillar-associated proteins in skeletal and metabolic disorders and cancers

Microfibrillar-associated proteins (MFAPs) are extracellular matrix glycoproteins, which play a role in microfibril assembly, elastinogenesis, and tissue homeostasis. MFAPs consist of five subfamily members, including MFAP1, MFAP2, MFAP3, MFAP4, and MFAP5. Among these, MFAP2 and MFAP5 are most closely related, and exhibit very limited amino acid sequence homology with MFAP1, MFAP3, and MFAP4. Gene expression profiling analysis reveals that MFAP2, MFAP5, and MFAP4 are specifically expressed in osteoblastic like cells, whereas MFAP1 and MFAP3 are more ubiquitously expressed, indicative of their diverse role in the tropism of tissues. Molecular structural analysis shows that each MFAP family member has distinct features, and functional evidence reveals discrete purposes of individual MFAPs. Animal studies indicate that MFAP2-deficient mice exhibit progressive osteopenia with elevated receptor activator of NF-κB ligand (RANKL) expression, whereas MFAP5-deficient mice are neutropenic, and MFAP4-deficient mice displayed emphysema-like pathology and the impaired formation of neointimal hyperplasia. Emerging data also suggest that MFAPs are involved in cancer progression and fat metabolism. Further understanding of tissue-specific pathophysiology of MFAPs might offer potential novel therapeutic targets for related diseases, such as skeletal and metabolic disorders, and cancers.

Systemic analysis of the expression and prognostic significance of PAKs in breast cancer

PAKs (p21-activated kinases) are reported to play crucial roles in a variety of cellular processes and participate in the progression of human cancers. However, the expression and prognostic values of PAKs remain poorly explored in breast cancers. In our study, we examined the mRNA and protein expression levels of PAKs and the prognostic value. We also analyzed the interaction network, genetic alteration, and functional enrichment of PAKs. The results showed that the mRNA levels of PAK1, PAK2, PAK4 and PAK6 were significantly up-regulated in breast cancer compared with normal tissues, while the reverse trend for PAK3 and PAK5 was found, furthermore, the proteins expression of PAK1, PAK2 and PAK4 in breast cancer tissues were higher than that in normal breast tissues. Survival analysis revealed breast cancer patients with low mRNA expression of PAK3 and PAK5 showed worse RFS, conversely, elevated PAK4 levels predicted worse RFS. In addition, the breast cancer patients with PAKs genetic alterations correlated with worse OS. These results indicated that PAKs might be promising potential biomarkers for breast cancer.

Key modules and hub genes identified by coexpression network analysis for revealing novel biomarkers for larynx squamous cell carcinoma

Larynx squamous cell carcinoma (LSCC) is the second most aggressive head and neck squamous cell carcinoma. Numerous genes have been identified to be aberrantly expressed during the development of LSCC. However, currently, researchers focus more on the individual molecule and downstream genes, leaving the coexpression among genes and key upstream disease driver genes unexploited. In this study, we applied weighted gene coexpression analysis (WGCNA) to decipher potential hub genes driving the development of LSCC. After downloading of LSCC microarray profile from gene expression omnibus, different expression analysis was performed, which was used to conduct functional enrichment analysis. Then, we applied WGCNA to highlight the hub genes which were relevant to the carcinogenesis and progression. A total of 2858 differentially expressed genes were identified in LSCC samples compared with adjacent non-neoplastic tissues. WGCNA revealed three LSCC set-specific modules having significant Kyoto Encyclopedia of Genes and Genomes enrichment effect, including pink, cyan, and black module. Nine hub genes were identified to be crucial in LSCC onset and progression, which may assist clinical decisions and serve as potential targets for LSCC treatment.

Combinatorial perturbation analysis reveals divergent regulations of mesenchymal genes during epithelial-to-mesenchymal transition

Epithelial-to-mesenchymal transition (EMT), a fundamental transdifferentiation process in development, produces diverse phenotypes in different physiological or pathological conditions. Many genes involved in EMT have been identified to date, but mechanisms contributing to the phenotypic diversity and those governing the coupling between the dynamics of epithelial (E) genes and that of the mesenchymal (M) genes are unclear. In this study, we employed combinatorial perturbations to mammary epithelial cells to induce a series of EMT phenotypes by manipulating two essential EMT-inducing elements, namely TGF-β and ZEB1. By measuring transcriptional changes in more than 700 E-genes and M-genes, we discovered that the M-genes exhibit a significant diversity in their dependency to these regulatory elements and identified three groups of M-genes that are controlled by different regulatory circuits. Notably, functional differences were detected among the M-gene clusters in motility regulation and in survival of breast cancer patients. We computationally predicted and experimentally confirmed that the reciprocity and reversibility of EMT are jointly regulated by ZEB1. Our integrative analysis reveals the key roles of ZEB1 in coordinating the dynamics of a large number of genes during EMT, and it provides new insights into the mechanisms for the diversity of EMT phenotypes.