Identification of EFEMP2 as a Serum Biomarker for the Early Detection of Colorectal Cancer with Lectin Affinity Capture Assisted Secretome Analysis of Cultured Fresh Tissues

Potassium voltage‑gated channel subfamily E member 4 facilitates the malignant progression of colon cancer by enhancing EGF containing fibulin extracellular matrix protein 2 expression

Colon cancer is a highly invasive and metastatic cancer with a poor prognosis. The University of Alabama at Birmingham Cancer data analysis portal (UALCAN) database indicates that potassium voltage-gated channel subfamily E member 4 (KCNE4) is highly expressed in colon cancer tissues. UALCAN data also show that KCNE4 expression is positively associated with individual cancer stages and negatively associated with patient survival. Therefore, the aim of the current study was to elucidate the functional role of KCNE4 in the biological behaviors of colon cancer cells and to investigate the underlying molecular mechanism. The gene EGF containing fibulin extracellular matrix protein 2 (EFEMP2) was found to be positively correlated with KCNE4 in colon cancer based on analysis performed using the LinkedOmics database; notably, upregulated EFEMP2 expression has been reported to be closely associated with the malignant phenotypes of colon cancer cells. The differences in the expression levels of KCNE4 and EFEMP2 between human colon cancer and normal colonic mucosa cell lines were assessed via reverse transcription-quantitative PCR and western blot assays. In addition, the proliferation, migration and invasion of colon cancer cells were determined using Cell Counting kit-8, colony formation, would healing and Transwell assays, and a co-immunoprecipitation assay was performed to confirm the interaction between KCNE4 and EFEMP2. The results of the study demonstrated that KCNE4 and EFEMP2 are markedly upregulated in colon cancer cells. In addition, KCNE4 interacted with and bound to EFEMP2. The suppressive effects of KCNE4 knockdown on the proliferation, colony formation, migration and invasion of colon cancer cells were attenuated by EFEMP2 overexpression. On the basis of these findings, it may be concluded that KCNE4 acts as an oncogene in colon cancer via the promotion of EFEMP2 expression.

EFEMP2 upregulates PD-L1 expression via EGFR/ERK1/2/c-Jun signaling to promote the invasion of ovarian cancer cells

BACKGROUND

Fibulin-like extracellular matrix protein 2 (EFEMP2) has been reported to be related to the progression of various cancers. We have previously reported that EFEMP2 was highly expressed in ovarian cancer and was strongly associated with poor prognosis in patients. This study intends to further explore its interacting proteins and possible downstream signaling pathways.

METHOD

The expression of EFEMP2 was detected by RT-qPCR, ICC and western blot in 4 kinds of ovarian cancer cells with different migration and invasion ability. Cell models with strong or weak EFEMP2 expression were constructed by lentivirus transfection. The effects of the down-regulation and up-regulation of EFEMP2 on the biological behavior of ovarian cancer cells were studied through in-vitro and in-vivo functional tests. The phosphorylation pathway profiling array and KEGG database analyses identified the downstream EGFR/ERK1/2/c-Jun signaling pathway and the programmed death-1 (PD-L1) pathway enrichment. Additionally, the protein interaction between EFEMP2 and EGFR was detected by immunoprecipitation.

RESULT

EFEMP2 was positively correlated with the invasion ability of ovarian cancer cells, its down-regulation inhibited the migrative, invasive and cloning capacity of cancer cells in vitro and suppressed the tumor proliferation and intraperitoneal diffusion in vivo, while its up-regulation did the opposite. Moreover, EFEMP2 could bind to EGFR to induce PD-L1 regulation in ovarian cancer, which was caused by the activation of EGFR/ERK1/2/c-Jun signaling. Similar to EFEMP2, PD-L1 was also highly expressed in aggressive cells and had the ability to promote the invasion and metastasis of ovarian cancer cells both in vitro and in vivo, and PD-L1 upregulation was partly caused by EFEMP2 activation. Afatinib combined with trametinib had an obvious effect of inhibiting the intraperitoneal diffusion of ovarian cancer cells, especially in the group with low expression of EFEMP2, while overexpression of PD-L1 could reverse this phenomenon.

CONCLUSION

EFEMP2 could bind to EGFR to activate ERK1/2/c-Jun pathway and regulate PD-L1 expression, furthermore PD-L1 was extremely essential for EFEMP2 to promote ovarian cancer cells invasion and dissemination in vitro and in vivo. Targeted therapy against the source gene EFEMP2 is our future research direction, which may better inhibit the invasion and metastasis of ovarian cancer cells.

Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer

Background

It is generally accepted that colorectal cancer (CRC) originates from cancer stem cells (CSCs), which are responsible for CRC progression, metastasis and therapy resistance. The high heterogeneity of CSCs has precluded clinical application of CSC-targeting therapy. Here, we aimed to characterize the stemness landscapes and screen for certain patients more responsive to immunotherapy.

Methods

Twenty-six stem cell gene sets were acquired from StemChecker database. Consensus clustering algorithm was applied for stemness subtypes identification on 1,467 CRC samples from TCGA and GEO databases. The differences in prognosis, tumor microenvironment (TME) components, therapy responses were evaluated among subtypes. Then, the stemness-risk model was constructed by weighted gene correlation network analysis (WGCNA), Cox regression and random survival forest analyses, and the most important marker was experimentally verified.

Results

Based on single-sample gene set enrichment analysis (ssGSEA) enrichments scores, CRC patients were classified into three subtypes (C1, C2 and C3). C3 subtype exhibited the worst prognosis, highest macrophages M0 and M2 infiltrations, immune and stromal scores, and minimum sensitivity to immunotherapies, but was more sensitive to drugs like Bosutinib, Docetaxel, Elesclomol, Gefitinib, Lenalidomide, Methotrexate and Sunitinib. The turquoise module was identified by WGCNA that it was most positively correlated with C3 but most negatively with C2, and five hub genes in turquoise module were identified for stemness model construction. CRC patients with higher stemness scores exhibited worse prognosis, more immunosuppressive components in TME and lower immunotherapeutic responses. Additionally, the model’s immunotherapeutic prediction efficacy was further confirmed from two immunotherapy cohorts (anti-PD-L1 in IMvigor210 cohort and anti-PD-1 in GSE78220 cohort). Mechanistically, Gene Set Enrichment Analysis (GSEA) results revealed high stemness score group was enriched in interferon gamma response, interferon alpha response, P53 pathway, coagulation, apoptosis, KRAS signaling upregulation, complement, epithelial–mesenchymal transition (EMT) and IL6-mediated JAK-STAT signaling gene sets.

Conclusions

Our study characterized three stemness-related subtypes with distinct prognosis and TME patterns in CRC patients, and a 5-gene stemness-risk model was constructed by comprehensive bioinformatic analyses. We suggest our stemness model has prospective clinical implications for prognosis evaluation and might facilitate physicians selecting prospective responders for preferential use of current immune checkpoint inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02913-0.

Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases

Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.

Conditioned medium derived from 3D tooth germs: A novel cocktail for stem cell priming and early in vivo pulp regeneration

OBJECTIVES

Conditioned medium (CM) from 2D cell culture can mitigate the weakened regenerative capacity of the implanted stem cells. However, the capacity of 3D CM to prime dental pulp stem cells (DPSCs) for pulp regeneration and its protein profile are still elusive. We aim to investigate the protein profile of CM derived from 3D tooth germs, and to unveil its potential for DPSCs-based pulp regeneration.

MATERIALS AND METHODS

We prepared CM of 3D ex vivo cultured tooth germ organs (3D TGO-CM) and CM of 2D cultured tooth germ cells (2D TGC-CM) and applied them to prime DPSCs. Influences on cell behaviours and protein profiles of CMs were compared. In vivo pulp regeneration of CMs-primed DPSCs was explored using a tooth root fragment model on nude mice.

RESULTS

TGO-CM enhanced DPSCs proliferation, migration, in vitro mineralization, odontogenic differentiation, and angiogenesis performances. The TGO-CM group generated superior pulp structures, more odontogenic cells attachment, and enhanced vasculature at 4 weeks post-surgery, compared with the TGC-CM group. Secretome analysis revealed that TGO-CM contained more odontogenic and angiogenic growth factors and fewer pro-inflammatory cytokines. Mechanisms leading to the differential CM profiles may be attributed to the cytokine-cytokine receptor interaction and PI3K-Akt signalling pathway.

CONCLUSIONS

The unique secretome profile of 3D TGO-CM made it a successful priming cocktail to enhance DPSCs-based early pulp regeneration.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

EFEMP2 indicates assembly of M0 macrophage and more malignant phenotypes of glioma

Immune response mediated by macrophages is critical in tumor progression and implicates new targets in potential efficient immunotherapies. Tumor associated macrophages (TAM) are divided into either polarized M1 or M2 phenotype depending on different regulators of polarization and pro- or anti-oncogenic roles they play. Glioma-infiltrated TAMs have been newly reported contrary to the current polarization dogma. Instead, macrophages in glioma exhibit a continuum phenotype between the M1- and M2-like TAM that resembling M0 macrophage. Here we proposed an OS (overall survival)-correlated gene EFEMP2 (EGF containing fibulin-like extracellular matrix protein 2) via screening with transcriptional expression levels and methylation data in two glioma databases. EFEMP2 was found highly expressed in glioma of higher WHO grade and Mesenchymal subtype glioma, and its transcriptional level could predict OS efficiently in validation datasets. EFEMP2 exhibited a remarkable preference of intercellular expression. In vitro assay showed that EFEMP2's level in medium was closely related to glioma cells' growth. Moreover, EFEMP2 expression level was remarkably correlated with immunological responses. M0-like macrophage as a feature of malignancy of glioblastoma revealed distinct assembly in glioma with high level of EFEMP2. These results revealed EFEMP2's role as a potential characteristic marker of malignant glioma, which are enriched of M0 macrophage.

EFEMP2 Suppresses the Invasion of Lung Cancer Cells by Inhibiting Epithelial-Mesenchymal Transition (EMT) and Down-Regulating MMPs

Background

Epidermal growth factor-containing fibulin-like extracellular matrix protein 2 (EFEMP2), also known as fibulin-4, MBP1 and UPH1, is an extracellular matrix protein associated with a variety of tumors. The purpose of this study was to investigate the prognostic value and the function of EFEMP2 in lung cancer.

Methods

The mRNA and protein expression of EFEMP2 in lung normal and cancer tissues, lung cancer cell lines (A549, H460, H1299 and H1650) and normal epithelial cell line BEAS-2B were evaluated by immunohistochemistry, RT-qPCR and Western blotting. The Public databases (Oncomine and Kaplan-Meier plotter) were used to investigate the prognostic value of EFEMP2 in lung cancer. RNA interference (RNAi) and overexpression transfection were performed to detect the effects of EFEMP2 up- or down-regulation on lung normal and cancer cell proliferation, invasion and metastasis in vitro and in vivo.

Results

EFEMP2 was lowly expressed in lung cancer tissues and cells, and its low expression was associated with malignant phenotype and poor prognosis of lung cancer. The same conclusion had been drawn from the Public databases. EFEMP2 overexpression significantly inhibited the invasion of lung cancer cells, hampered the process of EMT, and decreased the expression and activity of MMP2 and MMP9, while EFEMP2 knockdown remarkably enhanced the invasion of lung cancer cells, promoted EMT, and increased the expression and activity of MMP2 and MMP9.

Conclusion

The low expression of EFEMP2 was detected in lung cancer and was positively correlated with the poor prognosis of patients. EFEMP2 was a tumor suppressor gene that inhibited the progress of lung cancer, which suggested a new research objective for the future studies.

Transcriptome stability profiling using 5'-bromouridine IP chase (BRIC-seq) identifies novel and functional microRNA targets in human melanoma cells

RNA half-life is closely related to its cellular physiological function, so stability determinants may have regulatory functions. Micro(mi)RNAs have primarily been studied with respect to post-transcriptional mRNA regulation and target degradation. Here we study the impact of the tumour suppressive melanoma miRNA miR-211 on transcriptome stability and phenotype in the non-pigmented melanoma cell line, A375. Using 5'-bromouridine IP chase (BRIC)-seq, transcriptome-wide RNA stability profiles revealed highly regulated genes and pathways important in this melanoma cell line. By combining BRIC-seq, RNA-seq and in silico predictions, we identified both existing and novel direct miR-211 targets. We validated DUSP3 as one such novel miR-211 target, which itself sustains colony formation and invasion in A375 cells via MAPK/PI3K signalling. miRNAs have the capacity to control RNA turnover as a gene expression mechanism, and RNA stability profiling is an excellent tool for interrogating functionally relevant gene regulatory pathways and miRNA targets when combined with other high-throughput and in silico approaches.

Urinary Cysteine-Rich Protein 61 and Trefoil Factor 3 as Diagnostic Biomarkers for Colorectal Cancer

Since a fecal occult blood test for colorectal cancer (CRC) does not offer sufficient diagnostic power for CRC, novel non-invasive biomarkers are hopeful for CRC screening. We conducted the current study to discover non-invasive urinary biomarkers for diagnosing CRC. Among urine samples from 258 patients (CRC, n = 148; healthy controls, n = 110), a cohort of 176 patients composed of 88 patients with GC and 88 healthy controls was selected after age- and sex-matching using propensity score. This cohort was then randomly divided into 2 groups: 53 pairs (106 patients) in the training cohort, and 35 pairs (70 patients) in the validation cohort. No significant differences were found for baseline characteristics between the CRC and healthy control groups in both training and validation cohorts. On multivariate analysis in the training cohort, urinary levels of cysteine-rich protein 61 (uCyr61) and trefoil factor 3 (uTFF3) were identified as independent significant diagnostic markers for CRC. Moreover, uCyr61 alone and the combination of uCyr61 and uTFF3 allowed significant differentiation between healthy controls and CRC groups in the training set (uCyr61: area under the curve (AUC) = 0.745 [95% CI, 0.653–0.838]; uCyr61 + uTFF3: AUC = 0.753 [95% CI, 0.659–0.847]). In the validation cohort, uCyr61 and uTFF3 were significantly higher in the CRC group than in the healthy control group, and they also allowed significant differentiation between healthy control and CRC groups (uCyr61: AUC = 0.696 [95% CI, 0.571–0.822]; uTFF3: AUC = 0.639 [95% CI, 0.508–0.770]; uCyr61 + uTFF3: AUC = 0.720 [95% CI, 0.599–0.841]), as in the training cohort. A panel combining uCyr61 and uTFF3 offers a promising non-invasive biomarker for diagnosing CRC.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network

Background

Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment targets.

Methods

The genetic and clinical data of GC patients in The Cancer Genome Atlas (TCGA) was analyzed by weighted gene co-expression network analysis (WGCNA). Modules with clinical significance and preservation were distinguished, and gene ontology and pathway enrichment analysis were performed. Hub genes of these modules were validated in the TCGA dataset and another independent dataset from the Gene Expression Omnibus (GEO) database by t-test. Furthermore, the significance of these genes was confirmed via survival analysis.

Results

We found a preserved module consisting of 506 genes was associated with clinical traits including pathologic T stage and histologic grade. PDGFRB, COL8A1, EFEMP2, FBN1, EMILIN1, FSTL1 and KIRREL were identified as candidate genes in the module. Their expression levels were correlated with pathologic T stage and histologic grade, also affected overall survival of GC patients.

Conclusion

These candidate genes may be involved in proliferation and differentiation of GC cells. They may serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in GC and deserved further research.

Secretomes reveal several novel proteins as well as TGF-β1 as the top upstream regulator of metastatic process in breast cancer

PURPOSE

Metastatic breast cancer is resistant to many conventional treatments and novel therapeutic targets are needed. We previously isolated subsets of 4T1 murine breast cancer cells which metastasized to liver (4TLM), brain (4TBM), and heart (4THM). Among these cells, 4TLM is the most aggressive one, demonstrating mesenchymal phenotype. Here we compared secreted proteins from 4TLM, 4TBM, and 4THM cells and compared with that of hardly metastatic 67NR cells to detect differentially secreted factors involved in organ-specific metastasis.

METHOD AND RESULTS

Label-free LC-MS/MS proteomic technique was used to detect the differentially secreted proteins. Eighty-five of over 500 secreted proteins were significantly altered in metastatic breast cancer cells. Differential expression of several proteins such as fibulin-4, Bone Morphogenetic Protein 1, TGF-β1 MMP-3, MMP-9, and Thymic Stromal Lymphopoietin were further verified using ELISA or Western blotting. Many of these identified proteins were also present in human metastatic breast carcinomas. Annexin A1 and A5, laminin beta 1, Neutral alpha-glucosidase AB were commonly found at least in three out of six studies examined here. Ingenuity Pathway Analysis showed that proteins differentially secreted from metastatic cells are involved primarily in carcinogenesis and TGF-β1 is the top upstream regulator in all metastatic cells.

CONCLUSIONS

Cells metastasized to different organs displayed significant differences in several of secreted proteins. Proteins differentially altered were fibronectin, insulin-like growth factor-binding protein 7, and Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1. On the other hand, many exosomal proteins were also common to all metastatic cells, demonstrating involvement of key universal factors in distant metastatic process.

Cell Line Secretome and Tumor Tissue Proteome Markers for Early Detection of Colorectal Cancer: A Systematic Review

Objective: In order to find low abundant proteins secretome and tumor tissue proteome data have been explored in the last few years for the diagnosis of colorectal cancer (CRC). In this review we aim to summarize the results of studies evaluating markers derived from the secretome and tumor proteome for blood based detection of colorectal cancer. Methods: Observing the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines PubMed and Web of Science databases were searched systematically for relevant studies published up to 18 July 2017. After screening for predefined eligibility criteria a total of 47 studies were identified. Information on diagnostic performance indicators, methodological procedures and validation was extracted. Functions of proteins were identified from the UniProt database and the the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess study quality. Results: Forty seven studies meeting inclusion criteria were identified. Overall, 83 different proteins were identified, with carcinoembryonic Antigen (CEA) being by far the most commonly reported (reported in 24 studies). Evaluation of the markers or marker combinations in blood samples from CRC cases and controls yielded apparently very promising diagnostic performances, with area under the curve >0.9 in several cases, but lack of internal or external validation, overoptimism due to overfitting and spectrum bias due to evaluation in clinical setting rather than screening settings are major concerns. Conclusions: Secretome and tumor proteome-based biomarkers when validated in blood yield promising candidates. However, for discovered protein markers to be clinically applicable as screening tool they have to be specific for early stages and need to be validated externally in larger studies with participants recruited in true screening setting.

Colon cancer recurrence‑associated genes revealed by WGCNA co‑expression network analysis

The present study aimed to identify the recurrence-associated genes in colon cancer, which may provide theoretical evidence for the development of novel methods to prevent tumor recurrence. Colon cancer and matched normal samples microarray data (E-GEOD-39582) were downloaded from ArrayExpress. Genes with significant variation were identified, followed by the screening of differentially expressed genes (DEGs). Subsequently, the co-expression network of DEGs was constructed using the weighted correlation network analysis (WGCNA) method, which was verified using the validation dataset. The significant modules associated with recurrence in the network were subsequently screened and verified in another independent dataset E-GEOD-33113. Function and pathway enrichment analyses were also conducted to determine the roles of selected genes. Survival analysis was performed to identify the association between these genes and survival. A total of 434 DEGs were identified in the colon samples, and stress-associated endoplasmic reticulum protein family member 2 (SERP2) and long non-coding RNA-0219 (LINC0219) were determined to be the vital DEGs between all the three sub-type groups with different clinical features. The brown module was identified to be the most significant module in the co-expression network associated with the recurrence of colon cancer, which was verified in the E-GEOD-33113 dataset. Top 10 genes in the brown module, including EGF containing fibulin like extracellular matrix protein 2 (EFEMP2), fibrillin 1 (FBN1) and secreted protein acidic and cysteine rich (SPARC) were also associated with survival time of colon cancer patients. Further analysis revealed that the function of cell adhesion, biological adhesion, extracellular matrix (ECM) organization, pathways of ECM-receptor interaction and focal adhesion were the significantly changed terms in colon cancer. In conclusion, SERP2, EFEMP2, FBN1, SPARC, and LINC0219 were revealed to be the recurrence-associated molecular and prognostic indicators in colon cancer by WGCNA co-expression network analysis.

Proteomic profiling of the cancer cell secretome: informing clinical research

INTRODUCTION

Cancer represents one of the major causes of human deaths. Identification of proteins as biomarkers for early detection of cancer and therapeutic targets for cancer treatment are important issues in precision medicine. Secretome of cancer cells represents the collection of proteins secreted or shed from cancer cells. Proteomic profiling of the cancer cell secretome has been proven to be a convenient and efficient way to discover cancer biomarker and/or therapeutic targets. Areas covered: There have been numerous reviews describing the history and application of secretome analysis in cancer biomarker/therapeutic target research. The present review focuses on the technological advancement for profiling low-molecular-mass proteins in secretome, the latest information regarding the new candidate biomarkers and molecular mechanisms discovered on the basis of cancer cell secretome analysis, as well as the previously discovered candidate biomarkers that enter into clinical trials. Expert commentary: Current technologies for protein sample preparation/separation and MS-based protein identification have allowed in-depth analysis of cancer cell secretome. Future efforts should focus on the comprehensiveness of cancer cell secretome, meta-analysis of different secretome datasets and integrated analysis via combining other omics datasets, as well as the incorporation of MS-based biomarker verification pipeline into both preclinical studies and clinical trials.

Chemical composition and the potential for proteomic transformation in cancer, hypoxia, and hyperosmotic stress

The changes of protein expression that are monitored in proteomic experiments are a type of biological transformation that also involves changes in chemical composition. Accompanying the myriad molecular-level interactions that underlie any proteomic transformation, there is an overall thermodynamic potential that is sensitive to microenvironmental conditions, including local oxidation and hydration potential. Here, up- and down-expressed proteins identified in 71 comparative proteomics studies were analyzed using the average oxidation state of carbon (Z_C) and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O), calculated using elemental abundances and stoichiometric reactions to form proteins from basis species. Experimental lowering of oxygen availability (hypoxia) or water activity (hyperosmotic stress) generally results in decreased Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of up-expressed compared to down-expressed proteins. This correspondence of chemical composition with experimental conditions provides evidence for attraction of the proteomes to a low-energy state. An opposite compositional change, toward higher average oxidation or hydration state, is found for proteomic transformations in colorectal and pancreatic cancer, and in two experiments for adipose-derived stem cells. Calculations of chemical affinity were used to estimate the thermodynamic potentials for proteomic transformations as a function of fugacity of O₂ and activity of H₂O, which serve as scales of oxidation and hydration potential. Diagrams summarizing the relative potential for formation of up- and down-expressed proteins have predicted equipotential lines that cluster around particular values of oxygen fugacity and water activity for similar datasets. The changes in chemical composition of proteomes are likely linked with reactions among other cellular molecules. A redox balance calculation indicates that an increase in the lipid to protein ratio in cancer cells by 20% over hypoxic cells would generate a large enough electron sink for oxidation of the cancer proteomes. The datasets and computer code used here are made available in a new R package, canprot.

Fibulin-4 promotes osteosarcoma invasion and metastasis by inducing epithelial to mesenchymal transition via the PI3K/Akt/mTOR pathway

This study explored the role of fibulin-4 in osteosarcoma progression and the possible signaling pathway involved. Fibulin-4 mRNA and protein expression in normal tissue, benign fibrous dysplasia, osteosarcoma, osteosarcoma cell lines, the normal osteoblastic cell line hFOB, and different invasive subclones were evaluated by immunohistochemistry (IHC) or immunocytochemistry (ICC) and real-time reverse transcriptase-polymerase chain reaction (real-time qRT-PCR). Using in vitro functional assays, we analyzed the invasive and proliferative abilities of different osteosarcoma cell lines and subclones with differing invasive potential. To assess the role of fibulin-4 in the invasion and metastasis of osteosarcoma cells, lentiviral vectors with fibulin-4 small hairpin RNA (shRNA) and pLVX-fibulin-4 were constructed and used to infect the highly invasive and low invasive subclones and osteosarcoma cell lines. The effects of fibulin-4 knockdown and upregulation on the biological behavior of osteosarcoma cells were investigated by functional in vitro and in vivo assays. The results revealed that fibulin-4 expression was upregulated in osteosarcoma, and was positively correlated with low differentiation, lymph node metastasis, and poor prognosis. Fibulin-4 was also found to be over-expressed in highly invasive cell lines and in the highly invasive subclones. Fibulin-4 could promote osteosarcoma cell invasion and metastasis by inducing EMT via the PI3K/AKT/mTOR pathway. Collectively, our findings demonstrate that fibulin-4 is a promoter of osteosarcoma development and progression, and suggest a novel therapeutic target for future studies.

FBLN4 as candidate gene associated with long-term and short-term survival with primary glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common malignant and lethal type of primary central nervous system tumor in humans. In spite of its high lethality, a small percentage of patients have a relatively good prognosis, with median survival times of 36 months or longer. The identification of clinical subsets of GBM associated with distinct molecular genetic profiles has made it possible to design therapies tailored to treat individual patients.

Methods

We compared microarray data sets from long-term survivors (LTSs) and short-term survivors (STSs) to screen for prognostic biomarkers in GBM patients using the WebArrayDB platform. We focused on FBLN4, IGFBP-2, and CHI3L1, all members of a group of 10 of the most promising, differentially regulated gene candidates. Using formalin-fixed paraffin-embedded GBM samples, we corroborated the relationship between these genes and patient outcomes using methylation-specific polymerase chain reaction (PCR) for MGMT methylation status and quantitative reverse transcription PCR for expression of these genes.

Results

Expression levels of the mRNAs of these 3 genes were higher in the GBM samples than in normal brain samples and these 3 genes were significantly upregulated in STSs compared to the levels in LTS samples (P<0.01). Furthermore, Kaplan–Meier analysis showed that the expression patterns of FBLN4 and IGFBP-2 serve as independent prognostic indicators for overall survival (P<0.01 and P<0.05, respectively).

Conclusion

To our knowledge, this is the first report describing FBLN4 as a prognostic factor for GBM patient survival, demonstrating that increased GBM survival time correlates with decreased FBLN4 expression. Understanding FBLN4 expression patterns could aid in the creation of powerful tools to predict clinical prognoses of GBM patients.

Extracellular Matrix and Colorectal Cancer: How Surrounding Microenvironment Affects Cancer Cell Behavior?

Colorectal cancer (CRC) whit more than a million of new cases per year is one of the most common registered cancers worldwide with few treatment options especially for advanced and metastatic patients.The tumor microenvironment is composed by extracellular matrix (ECM), cells, and interstitial fluids. Among all these constituents, in the last years an increased interest around the ECM and its potential role in cancer tumorigenesis is arisen. During cancer progression the ECM structure and composition became disorganized, allowing cellular transformation and metastasis. Up to now, the focus has mainly been on the characterization of CRC microenvironment analyzing separately structural ECM components or cell secretome modifications. A more extensive view that interconnects these aspects should be addressed. In this review, biochemical (secretome) and biomechanical (structure and architecture) changes of tumor microenvironment will be discussed, giving suggestions on how these changes can affect cancer cell behavior. J. Cell. Physiol. 232: 967-975, 2017. © 2016 Wiley Periodicals, Inc.

Proteomic indicators of oxidation and hydration state in colorectal cancer

New integrative approaches are needed to harness the potential of rapidly growing datasets of protein expression and microbial community composition in colorectal cancer. Chemical and thermodynamic models offer theoretical tools to describe populations of biomacromolecules and their relative potential for formation in different microenvironmental conditions. The average oxidation state of carbon (Z_C) can be calculated as an elemental ratio from the chemical formulas of proteins, and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O) is computed by writing the overall formation reactions of proteins from basis species. Using results reported in proteomic studies of clinical samples, many datasets exhibit higher mean Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of proteins in carcinoma or adenoma compared to normal tissue. In contrast, average protein compositions in bacterial genomes often have lower Z_C for bacteria enriched in fecal samples from cancer patients compared to healthy donors. In thermodynamic calculations, the potential for formation of the cancer-related proteins is energetically favored by changes in the chemical activity of H₂O and fugacity of O₂ that reflect the compositional differences. The compositional analysis suggests that a systematic change in chemical composition is an essential feature of cancer proteomes, and the thermodynamic descriptions show that the observed proteomic transformations in host tissue could be promoted by relatively high microenvironmental oxidation and hydration states.

iTRAQ-based quantitative analysis of cancer-derived secretory proteome reveals TPM2 as a potential diagnostic biomarker of colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. We aimed to find novel molecules as potential biomarkers for the early diagnosis of CRC. A serum-free conditioned medium was successfully collected from three pairs of CRC tissue and adjacent normal tissue. iTRAQ-based quantitative proteomic analysis was applied to compare the differences in secretome between primary CRC mucosa and adjacent normal mucosa. A total of 145 kinds of proteins were identified. Of these proteins, 29 were significantly different between CRC and normal tissue. Tropomyosin 2 β (TPM2) exhibited the most significant differences; as such, this protein was selected for further validation. Quantitative real-time PCR indicated that the mRNA expression of TPM2 significantly decreased in the CRC tissue compared with the paired adjacent normal tissue. Immunohistochemical analysis also confirmed that TPM2 was barely detected at protein levels in the CRC tissue. In summary, this study revealed potential molecules for future biomarker applications and provided an efficient approach for the differential analysis of cancer-associated secretome. TPM2 may be valuable for the early diagnosis of CRC.

The extracellular matrix: Tools and insights for the "omics" era

The extracellular matrix (ECM) is a fundamental component of multicellular organisms that provides mechanical and chemical cues that orchestrate cellular and tissue organization and functions. Degradation, hyperproduction or alteration of the composition of the ECM cause or accompany numerous pathologies. Thus, a better characterization of ECM composition, metabolism, and biology can lead to the identification of novel prognostic and diagnostic markers and therapeutic opportunities. The development over the last few years of high-throughput ("omics") approaches has considerably accelerated the pace of discovery in life sciences. In this review, we describe new bioinformatic tools and experimental strategies for ECM research, and illustrate how these tools and approaches can be exploited to provide novel insights in our understanding of ECM biology. We also introduce a web platform "the matrisome project" and the database MatrisomeDB that compiles in silico and in vivo data on the matrisome, defined as the ensemble of genes encoding ECM and ECM-associated proteins. Finally, we present a first draft of an ECM atlas built by compiling proteomics data on the ECM composition of 14 different tissues and tumor types.

Liquid phase based separation systems for depletion, prefractionation, and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis-An update covering the period 2011-2014

This review article expands on the previous one (S. Selvaraju and Z. El Rassi, Electrophoresis 2012, 33, 74-88) by reviewing pertinent literature in the period extending from early 2011 to present. As the previous review article, the present one is concerned with proteomic sample preparation (e.g., depletion of high-abundance proteins, reduction of the protein dynamic concentration range, enrichment of a particular subproteome), and the subsequent chromatographic and/or electrophoretic prefractionation prior to peptide separation and identification by LC-MS/MS. This review article, however, is distinguished from its earlier version by expanding on capturing/enriching subphosphoproteomes by immobilized metal affinity chromatography and metal oxide affinity chromatography. Seventy-seven papers published in the period extending from mid-2011 to the present have been reviewed. By no means this review article is exhaustive, given the fact that its aim is to give a concise treatment of the latest developments in the field.

Discovery of melanotransferrin as a serological marker of colorectal cancer by secretome analysis and quantitative proteomics

To discover serological colorectal cancer (CRC) markers, we analyzed cell line secretome to gather proteins of higher potential to be secreted from tissues into circulation. A total of 898 human proteins were identified, of which 62.2% were predicted to be released or shed from cells. The identified proteins were compared with tissue proteomes to find candidate proteins whose expressions were elevated in tumor tissues compared with normal tissues as revealed by (i) quantitative proteomic analysis based on cICAT and mTRAQ or (ii) data mining of immunohistochemical images piled in Human Protein Atlas database. By applying various stringent criteria, 11 candidate proteins were selected. Among these, we validated an significant increase (p = 0.0018) of melanotransferrin (TRFM) at the plasma level of CRC patients through Western blotting, using 130 plasma samples containing 30 healthy controls, 80 CRC patients, and 20 patients of other diseases. Finally, we measured the expression level of TRFM in 325 plasma samples containing 77 healthy controls and 228 CRC patients (34.6 ± 4.2 ng/mL and 67.0 ± 6.4 ng/mL, p < 0.0001) through ELISA and demonstrated the area under the receiver operating characteristic curve of 0.723 (p < 0.0001) with a 92.5% specificity, 48.2% sensitivity, and 95.7% positive predictive value. Furthermore, unlike CEA and PAI-1, up-regulation of TRFM in pathological stages I & II groups compared with stages III & IV groups lead us to expect the use TRFM for early-stage diagnosis of CRC. In this study, we suggest TRFM as a potential serological marker for CRC and expect our discovery strategy to help identify highly cancer-specific and body-fluid-accessible biomarkers.

Extracellular matrix signatures of human primary metastatic colon cancers and their metastases to liver

BACKGROUND

Colorectal cancer is the third most frequently diagnosed cancer and the third cause of cancer deaths in the United States. Despite the fact that tumor cell-intrinsic mechanisms controlling colorectal carcinogenesis have been identified, novel prognostic and diagnostic tools as well as novel therapeutic strategies are still needed to monitor and target colon cancer progression. We and others have previously shown, using mouse models, that the extracellular matrix (ECM), a major component of the tumor microenvironment, is an important contributor to tumor progression. In order to identify candidate biomarkers, we sought to define ECM signatures of metastatic colorectal cancers and their metastases to the liver.

METHODS

We have used enrichment of extracellular matrix (ECM) from human patient samples and proteomics to define the ECM composition of primary colon carcinomas and their metastases to liver in comparison with normal colon and liver samples.

RESULTS

We show that robust signatures of ECM proteins characteristic of each tissue, normal and malignant, can be defined using relatively small samples from small numbers of patients. Comparisons with gene expression data from larger cohorts of patients confirm the association of subsets of the proteins identified by proteomic analysis with tumor progression and metastasis.

CONCLUSIONS

The ECM protein signatures of metastatic primary colon carcinomas and metastases to liver defined in this study, offer promise for development of diagnostic and prognostic signatures of metastatic potential of colon tumors. The ECM proteins defined here represent candidate serological or tissue biomarkers and potential targets for imaging of occult metastases and residual or recurrent tumors and conceivably for therapies. Furthermore, the methods described here can be applied to other tumor types and can be used to investigate other questions such as the role of ECM in resistance to therapy.

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Developing proteomics-based biomarkers for colorectal neoplasms for clinical practice: opportunities and challenges

Colorectal cancer (CRC) arises from the normal colon epithelium through the accumulation of genetic mutations and epigenetic alterations that are associated with progression along the histological adenoma-adenocarcinoma sequence. Elucidating the molecular alterations underlying disease progression will not only provide insight into the behavior of the tumors, but also could lead to the discovery of useful biomarkers for diagnosis, monitoring treatment responsiveness, or predicting disease outcomes. In the past a few years, there have been several evaluating differentially expressed protein biomarkers by employing proteomics technologies coupled with mass spectrometry. In the current review, we will briefly summarize the results from selected recent studies using tissue or serum samples from CRC patients in the past 5 years and discuss the opportunities and challenges in translating these findings from the research setting to clinical practice.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

Rare coding variants and breast cancer risk: evaluation of susceptibility Loci identified in genome-wide association studies

BACKGROUND

To date, common genetic variants in approximately 70 loci have been identified for breast cancer via genome-wide association studies (GWAS). It is unknown whether rare variants in these loci are also associated with breast cancer risk.

METHODS

We investigated rare missense/nonsense variants with minor allele frequency (MAF) ≤5% located in flanking 500 kb of each of the index single-nucleotide polymorphism (SNP) in 67 GWAS loci. Included in the study were 3,472 cases and 3,595 controls from the Shanghai Breast Cancer Study. Both single marker and gene-based analyses were conducted to investigate the associations.

RESULTS

Single marker analyses identified 38 missense variants being associated with breast cancer risk at P < 0.05 after adjusting for the index SNP. SNP rs146217902 in the EDEM1 gene and rs200340088 in the EFEMP2 gene were only observed in 8 cases (P = 0.004 for both). SNP rs200995432 in the EFEMP2 gene was associated with increased risk with an OR of 6.2 [95% confidence interval (CI), 1.4-27.6; P = 6.2 × 10(-3)]. SNP rs80358978 in the BRCA2 gene was associated with 16.5-fold elevated risk (95% CI, 2.2-124.5; P = 2.2 × 10(-4)). Gene-based analyses suggested eight genes associated with breast cancer risk at P < 0.05, including the EFEMP2 gene (P = 0.002) and the FBXO18 gene (P = 0.008).

CONCLUSION

Our results identified associations of several rare coding variants neighboring common GWAS loci with breast cancer risk. Further investigation of these rare variants and genes would help to understand the biologic mechanisms underlying the associations.

IMPACT

Independent studies with larger sample size are warranted to clarify the relationship between these rare variants and breast cancer risk.

Cancer secretomes and their place in supplementing other hallmarks of cancer

The secretome includes all macromolecules secreted by cells, in particular conditions at defined times, allowing cell-cell communication. Cancer cell secretomes that are altered compared to normal cells have shown significant potential for elucidating cancer biology. Proteins of secretomes are secreted by various secretory pathways and can be studied using different methods. Cancer secretomes seem to play an important role in known hallmarks of cancers such as excessive proliferation, reduced apoptosis, immune invasion, angioneogenesis, alteration in energy metabolism, and development of resistance against anti-cancer therapy [1, 2]. If a significant role of an altered secretome can be identified in cancer cells, using advanced mass spectrometry-based techniques, this may allow researchers to screen and characterize the secretome proteins involved in cancer progression and open up new opportunities to develop new therapies. We aim to elaborate upon recent advances in cancer cell secretome analysis using different proteomics techniques. In this review, we highlight the role of the altered secretome in contributing to already recognized and emerging hallmarks of cancer and we discuss new challenges in the field of secretome analysis.

Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

Sieving through the cancer secretome

Cancer is among the most prevalent and serious health problems worldwide. Therefore, there is an urgent need for novel cancer biomarkers with high sensitivity and specificity for early detection and management of the disease. The cancer secretome, encompassing all the proteins that are secreted by cancer cells, is a promising source of biomarkers as the secreted proteins are most likely to enter the blood circulation. Moreover, since secreted proteins are responsible for signaling and communication with the tumor microenvironment, studying the cancer secretome would further the understanding of cancer biology. Latest developments in proteomics technologies have significantly advanced the study of the cancer secretome. In this review, we will present an overview of the secretome sample preparation process and summarize the data from recent secretome studies of six common cancers with high mortality (breast, colorectal, gastric, liver, lung and prostate cancers). In particular, we will focus on the various platforms that were employed and discuss the clinical applicability of the key findings in these studies. This article is part of a Special Issue entitled: An Updated Secretome.

The cancer secretome, current status and opportunities in the lung, breast and colorectal cancer context

Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.

TAZ expression as a prognostic indicator in colorectal cancer

The Hippo pathway restricts the activity of transcriptional coactivators TAZ (WWTR1) and YAP. TAZ and YAP are reported to be overexpressed in various cancers, however, their prognostic significance in colorectal cancers remains unstudied. The expression levels of TAZ and YAP, and their downstream transcriptional targets, AXL and CTGF, were extracted from two independent colon cancer patient datasets available in the Gene Expression Omnibus database, totaling 522 patients. We found that mRNA expressions of both TAZ and YAP were positively correlated with those of AXL and CTGF (p<0.05). High level mRNA expression of TAZ, AXL or CTGF significantly correlated with shorter survival. Importantly, patients co-overexpressing all 3 genes had a significantly shorter survival time, and combinatorial expression of these 3 genes was an independent predictor for survival. The downstream target genes for TAZ-AXL-CTGF overexpression were identified by Java application MyStats. Interestingly, genes that are associated with colon cancer progression (ANTXR1, EFEMP2, SULF1, TAGLN, VCAN, ZEB1 and ZEB2) were upregulated in patients co-overexpressing TAZ-AXL-CTGF. This TAZ-AXL-CTGF gene expression signature (GES) was then applied to Connectivity Map to identify small molecules that could potentially be utilized to reverse this GES. Of the top 20 small molecules identified by connectivity map, amiloride (a potassium sparing diuretic,) and tretinoin (all-trans retinoic acid) have shown therapeutic promise in inhibition of colon cancer cell growth. Using MyStats, we found that low level expression of either ANO1 or SQLE were associated with a better prognosis in patients who co-overexpressed TAZ-AXL-CTGF, and that ANO1 was an independent predictor of survival together with TAZ-AXL-CTGF. Finally, we confirmed that TAZ regulates Axl, and plays an important role in clonogenicity and non-adherent growth in vitro and tumor formation in vivo. These data suggest that TAZ could be a therapeutic target for the treatment of colon cancer.

Identification of MXRA5 as a novel biomarker in colorectal cancer

In our previous study, significantly high expression levels of matrix-remodeling associated 5 (MXRA5) were identified in fresh-cultured colorectal cancer (CRC) tissues compared with their normal adjacent mucosa by differential secretome analysis. Whether MXRA5 is a potential serum biomarker of CRC has not been evaluated. The aim of this study was to investigate the association between MXRA5 expression and clinicopathological characteristics of CRC patients. The MXRA5 expression levels were determined by quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) in 20 colorectal adenoma tissues, 156 CRC tissues and their corresponding adjacent normal mucosa. Relative quantity (RQ) value and immunoreactive score (IRS) were used for quantitative assessment. The staining for MXRA5 protein was mainly located in the cytoplasm of CRC cells. All CRC tissues were positively stained, with a higher expression rate (IRS>4) of 67% (105/156), and a lower expression rate (IRS≤4) of 33% (51/156). Meanwhile, their corresponding normal tissues exhibited little positive staining; the higher expression rate was 0% (0/156) and the lower expression rate was 25% (16/156). Additionally, more than half of the adenoma tissues were positively stained; the higher expression rate was 15% (3/20) and the lower expression rate was 50% (10/20). The MXRA5 protein positive staining rates were significantly correlated with the lesion sites (colon vs. rectum, 76 vs. 59%), TNM staging (I+II vs. III+IV, 56 vs. 73%) and metastasis (present vs. absent; 76 vs. 61%) with the most high positive staining rate observable in omental metastasis (82%). However, MXRA5 mRNA expression levels showed no significant differences between CRC tissues and their corresponding normal tissues, and no significant correlation between IRS and corresponding RQ value was observed. In this study, we present the first evaluation of MXRA5 protein expression in CRC tissue. Our results revealed that MXRA5 protein is aberrantly expressed in CRC tissues, and has potential value in early detection of CRC and prediction of omental metastasis.