Combination of laser microdissection, 2D-DIGE and MALDI-TOF MS to identify protein biomarkers to predict colorectal cancer spread

Probiotics and the Role of Dietary Substrates in Maintaining the Gut Health: Use of Live Microbes and Their Products for Anticancer Effects against Colorectal Cancer

The gut microbiome is an important and the largest endocrine organ linked to the microbes of the GI tract. The bacterial, viral and fungal communities are key regulators of the health and disease status in a host at hormonal, neurological, immunological, and metabolic levels. The useful microbes can compete with microbes exhibiting pathogenic behavior by maintaining resistance against their colonization, thereby maintaining eubiosis. As diagnostic tools, metagenomic, proteomic and genomic approaches can determine various microbial markers in clinic for early diagnosis of colorectal cancer (CRC). Probiotics are live non-pathogenic microorganisms such as lactic acid bacteria, Bifidobacteria, Firmicutes and Saccharomyces that can help maintain eubiosis when administered in appropriate amounts. In addition, the type of dietary intake contributes substantially to the composition of gut microbiome. The use of probiotics has been found to exert antitumor effects at preclinical levels and promote the antitumor effects of immunotherapeutic drugs at clinical levels. Also, modifying the composition of gut microbiota by Fecal Microbiota Transplantation (FMT), and using live lactic acid producing bacteria such as Lactobacillus, Bifidobacteria and their metabolites (termed postbiotics) can contribute to immunomodulation of the tumor microenvironment. This can lead to tumor-preventive effects at early stages and antitumor effects after diagnosis of CRC. To conclude, probiotics are presumably found to be safe to use in humans and are to be studied further to promote their appliance at clinical levels for management of CRC.

Biomarker Identification through Proteomics in Colorectal Cancer

Colorectal cancer (CRC) is a devastating disease that ranks third in diagnosis and as the second leading cause of cancer-related deaths. The early detection of CRC has been shown to be the most effective strategy to improve treatment outcomes and patient survival. Therefore, current lines of research focus on the development of reliable diagnostic tools. Targeted therapies, in combination with standard chemotherapy and immune checkpoint inhibitors, have emerged as promising treatment protocols in CRC. However, their effectiveness is linked to the molecular characteristics of each patient. The importance of discovering biomarkers that help predict response to therapies and assess prognosis is evident as they allow for a fundamental step towards personalized care and successful treatments. Among the ongoing efforts to identify them, mass spectrometry-based translational proteomics presents itself as a unique opportunity as it enables the discovery and application of protein biomarkers that may revolutionize the early detection and treatment of CRC. Our objective is to show the most recent studies focused on the identification of CRC-related protein markers, as well as to provide an updated view of advances in the field of proteomics and cancer.

The ideal reporting of RAS testing in colorectal adenocarcinoma: a pathologists' perspective

RAS gene mutational status represents an imperative predictive biomarker to be tested in the clinical management of metastatic colorectal adenocarcinoma. Even if it is one of the most studied biomarkers in the era of precision medicine, several pre-analytical and analytical factors may still impasse an adequate reporting of RAS status in clinical practice, with significant therapeutic consequences. Thus, pathologists should be aware on the main topics related to this molecular evaluation: (i) adopt diagnostic limit of detections adequate to avoid the interference of sub-clonal cancer cell populations; (ii) choose the most adequate diagnostic strategy according to the available sample and its qualification for molecular testing; (iii) provide all the information regarding the mutation detected, since many RAS mutation-specific targeted therapeutic approaches are in development and will enter into routine clinical practice. In this review, we give a comprehensive description of the current scenario about RAS gene mutational testing in the clinic focusing on the pathologist's role in patient selection for targeted therapies.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

DIGE Saturation Labeling for Scarce Amounts of Protein from Formalin-Fixed Paraffin-Embedded (FFPE) Tissue

In this chapter, we describe the utility of fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) as a proteomics platform for the global detection of expressed proteins in formalin-fixed paraffin-embedded (FFPE) tissues and its use for biomarker discovery/identification of proteins that may contribute to cancer development and progression. Formalin fixation and paraffin embedding of tissue is the standard processing methodology practiced in pathology laboratories worldwide, resulting in a highly stable form of tissue that is easily stored due to its inherent stability at room temperature. Consequently, FFPE tissues represent an attractive reservoir of clinical material for conducting retrospective protein biomarker analysis. A limitation for proteomics research in this type of clinical sample is the amount of viable protein that can be obtained from fixed tissues. Tissue biopsies are precious samples that can generally be acquired in very small amounts due to the invasive nature of the sample collection, mainly during surgery or biopsy. Subsequently, the amount of extracted protein can be, in many cases, very limited. The saturation 2D-DIGE technology has emerged as a useful method for protein analysis where only scarce amounts of protein are available. This approach can be adapted successfully to label low-level protein isolated from FFPE tissue.

CpG Site-Based Signature Predicts Survival of Colorectal Cancer

BACKGROUND

A critical unmet medical need in clinical management of colorectal cancer (CRC) pivots around lack of noninvasive and or minimally invasive techniques for early diagnosis and prognostic prediction of clinical outcomes. Because DNA methylation can capture the regulatory landscape of tumors and can be measured in body fluids, it provides unparalleled opportunities for the discovery of early diagnostic and prognostics markers predictive of clinical outcomes. Here we investigated use of DNA methylation for the discovery of potential clinically actionable diagnostic and prognostic markers for predicting survival in CRC.

METHODS

We analyzed DNA methylation patterns between tumor and control samples to discover signatures of CpG sites and genes associated with CRC and predictive of survival. We conducted functional analysis to identify molecular networks and signaling pathways driving clinical outcomes.

RESULTS

We discovered a signature of aberrantly methylated genes associated with CRC and a signature of thirteen (13) CpG sites predictive of survival. We discovered molecular networks and signaling pathways enriched for CpG sites likely to drive clinical outcomes.

CONCLUSIONS

The investigation revealed that CpG sites can predict survival in CRC and that DNA methylation can capture the regulatory state of tumors through aberrantly methylated molecular networks and signaling pathways.

Identification of Diagnostic Exosomal LncRNA-miRNA-mRNA Biomarkers in Colorectal Cancer Based on the ceRNA Network

Background: Colorectal cancer (CRC) is currently the fourth most common cancer worldwide. The roles of exosomal competing endogenous RNAs (ceRNAs) in CRC remain unclear. In this study, we constructed an exosomal ceRNA network to identify the core ceRNAs and investigate the diagnostic biomarkers in CRC.

Methods and Patients: Serum exosomes were isolated from four CRC patients and two healthy donors by ultracentrifugation, and then subjected to RNA isolation, sequencing and microarray. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were performed to identify functional enrichment implications of differentially expressed exosomal mRNAs. TargetScan and miRanda were used for identifying the miRNA-mRNA and miRNA-LncRNA interactions. The predicted lncRNAs and mRNAs were intersected with the differentially expressed genes, for which the screening criterion was fold change >1.5 in the microarray. Differentially expressed exosomal miRNAs were identified in the GSE71008 dataset, and differentially expressed mRNAs (DEmRNAs) were further summarized from The Cancer Genome Atlas (TCGA) database.

Results: A total of 1186 exosomal DEmRNAs, 2088 exosomal DElncRNAs and 29 exosomal miRNAs were detected in CRC patients compared to the healthy donors. Functional enrichment analysis suggested that exosomal DEmRNAs might participate in pathways related to carcinogenesis and development of cancer. An exosomal ceRNA regulatory network of CRC was constructed based on 40 lncRNAs, two miRNAs, and five mRNAs. Exosomal miR-150-5p and miR-10b-5p expression levels were increased in healthy donors compared with CRC patients in the GSE71008 dataset, and five DEmRNAs (TOMM70A, RBM48, BEND3, RHOBTB1, and ADAMTS2) were significantly upregulated in TCGA database. Two potential exosomal regulatory axes of lncRNA G016261-miR-150-5p-RBM48 and lncRNA XLOC_011677-miR-10b-5p-BEND3 were identified from the network.

Conclusion: The current study revealed potential molecular biological regulation pathways and diagnostic biomarkers through the exosomal ceRNA regulatory network.

Evaluation of the diagnostic value of serum-based proteomics for colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.

AIM

To provide new ideas for the diagnosis of CRC based on serum proteomics.

METHODS

Specimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.

RESULTS

Compared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.

CONCLUSION

We demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils the Characteristics of the Immune Microenvironment and Prognosis Signature in Prostate Cancer

The immune microenvironment is a culmination of the collaborative effort of immune cells and is important in cancer development. The underlying mechanisms of the tumor immune microenvironment in regulating prostate cancer (PRAD) are unclear. In the current study, 144 natural killer cell-related genes were identified using differential expression, single-sample gene set enrichment analysis, and weighted gene coexpression network analysis. Furthermore, VCL, ACTA2, MYL9, MYLK, MYH11, TPM1, ACTG2, TAGLN, and FLNC were selected as hub genes via the protein-protein interaction network. Based on the expression patterns of the hub genes, endothelial, epithelial, and tissue stem cells were identified as key cell subpopulations, which could regulate PRAD via immune response, extracellular signaling, and protein formation. Moreover, 27 genes were identified as prognostic signatures and used to construct the risk score model. Receiver operating characteristic curves revealed the good performance of the risk score model in both the training and testing datasets. Different chemotherapeutic responses were observed between the low- and high-risk groups. Additionally, a nomogram based on the risk score and other clinical features was established to predict the 1-, 3-, and 5-year progression-free interval of patients with PRAD. This study provides novel insights into the molecular mechanisms of the immune microenvironment and its role in the pathogenesis of PARD. The identification of key cell subpopulations has a potential therapeutic and prognostic use in PRAD.

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.

Transthyretin as a target of alkylation and a potential biomarker for sulfur mustard poisoning: Electrophoretic and mass spectrometric identification and characterization

For the verification of exposure to the banned blister agent sulfur mustard (SM) and the better understanding of its pathophysiology, protein adducts formed with endogenous proteins represent an important field of toxicological research. SM and its analogue 2-chloroethyl ethyl sulfide (CEES) are well known to alkylate nucleophilic amino acid side chains, for example, free-thiol groups of cysteine residues. The specific two-dimensional thiol difference gel electrophoresis (2D-thiol-DIGE) technique making use of maleimide dyes allows the staining of free cysteine residues in proteins. As a consequence of alkylation by, for example, SM or CEES, this staining intensity is reduced. 2D-thiol-DIGE analysis of human plasma incubated with CEES and subsequent matrix-assisted laser desorption/ionization time-of-flight (tandem) mass-spectrometry, MALDI-TOF MS(/MS), revealed transthyretin (TTR) as a target of alkylating agents. TTR was extracted from SM-treated plasma by immunomagnetic separation (IMS) and analyzed after tryptic cleavage by microbore liquid chromatography-electrospray ionization high-resolution tandem-mass spectrometry (μLC-ESI MS/HR MS). It was found that the Cys¹⁰ -residue of TTR present in the hexapeptide C(-HETE)PLMVK was alkylated by the hydroxyethylthioethyl (HETE)-moiety, which is characteristic for SM exposure. It was shown that alkylated TTR is stable in plasma in vitro at 37°C for at least 14 days. In addition, C(-HETE)PLMVK can be selectively detected, is stable in the autosampler over 24 h, and shows linearity in a broad concentration range from 15.63 μM to 2 mM SM in plasma in vitro. Accordingly, TTR might represent a complementary protein marker molecule for the verification of SM exposure.

Systems-level biomarkers identification and drug repositioning in colorectal cancer

Colorectal cancer (CRC) is the most commonly diagnosed fatal cancer in both women and men worldwide. CRC ranked second in mortality and third in incidence in 2020. It is difficult to diagnose CRC at an early stage as there are no clinical symptoms. Despite advances in molecular biology, only a limited number of biomarkers have been translated into routine clinical practice to predict risk, prognosis and response to treatment. In the last decades, systems biology approaches at the omics level have gained importance. Over the years, several biomarkers for CRC have been discovered in terms of disease diagnosis and prognosis. On the other hand, a few drugs are being developed and used in clinics for the treatment of CRC. However, the development of new drugs is very costly and time-consuming as the research and development takes about 10 years and more than $1 billion. Therefore, drug repositioning (DR) could save time and money by establishing new indications for existing drugs. In this review, we aim to provide an overview of biomarkers for the diagnosis and prognosis of CRC from the systems biology perspective and insights into DR approaches for the prevention or treatment of CRC.

Identification of Potential Biomarkers and Biological Pathways for Poor Clinical Outcome in Mucinous Colorectal Adenocarcinoma

Simple Summary

Patients with mucinous adenocarcinoma (MAC) have been considered to have a faster disease progression than patients with traditional adenocarcinoma (TAC) in colorectal cancer (CRC). However, to date, the roles of MAC in long-term survival remain controversial due to a small sample size and the nature of its relatively rare occurrence, although it potentially represents entities with different aggressiveness and prognoses. Here, using large-scale population data, we found that the patients with the MAC subtype had a significantly worse overall survival rate and a tendency of worse disease-specific survival rate in stage II compared with the patients with the TAC subtype. Furthermore, key gene signatures were identified using the established predictive models for the disease-specific survival of stage II mucinous CRC.

Abstract

Colorectal cancer (CRC) comprises several histological subtypes, but the influences of the histological subtypes on prognosis remains unclear. We sought to evaluate the prognosis of mucinous adenocarcinoma (MAC), compared to that of traditional adenocarcinoma (TAC). This study used the data of patients diagnosed with CRC between 2004 and 2016, as obtained from the Surveillance, Epidemiology, and End Results database. We established a predictive model for disease-specific survival using conditional survival forest, model, non-linear Cox proportional hazards, and neural multi-task logistic regression model and identified the gene signatures for predicting poor prognosis based on the arrayexpress datasets. In total, 9096 (42.1%) patients with MAC and 12,490 (58.9%) patients with TAC were included. Those with the MAC subtype were more likely to have a poorer overall survival rate compared to those with the TAC subtype in stage II CRC (p = 0.002). The eight major genes including RPS18, RPL30, NME2, USP33, GAB2, RPS3A, RPS25, and CEP57 were found in the interacting network pathway. MAC was found to have a poorer prognosis compared to TAC, especially in Stage II CRC. In addition, our findings suggest that identifying potential biomarkers and biological pathways can be useful in CRC prognosis.

Identification of DNA methylation biomarkers for risk of liver metastasis in early-stage colorectal cancer

Background

Liver metastases can occur even in CRC patients who underwent curative surgery. While evidence suggested that adjuvant chemotherapy can help to reduce the occurrence of liver metastases for certain patients, it is not a recommended routine as the side effects outweigh the potential benefits, especially in Stage II CRC patients. This study aims to construct a model for predicting liver metastasis risk using differential methylation signals in primary CRC tumors, which can facilitate the decision for adjuvant chemotherapy.

Methods

Fifty-nine stage I/II and IV CRC patients were enrolled. Primary tumor, adjacent normal tissue, and metastatic tumor tissues were subject to targeted bisulfite sequencing for DNA methylation. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to identify potential DMRs for predicting liver metastasis of CRC.

Results

We identified a total of 241,573 DMRs by comparing the DNA methylation profile of primary tumors of stage II patients who developed metastasis to those who were metastasis-free during the follow up period. 213 DMRs were associated with poor prognosis, among which 182 DMRS were found to be hypermethylated in the primary tumor of patients with metastases. Furthermore, by using the LASSO regression model, we identified 23 DMRs that contributed to a high probability of liver metastasis of CRC. The leave-one-out cross validation (LOOCV) was used to evaluate model predictive performance at an AUC of 0.701. In particular, 7 out of those 23 DMRs were found to be in the promoter region of genes that were previously reported prognostic biomarkers in diverse tumor types, including TNNI2, PAX8, GUF1, KLF4, EVI2B, CEP112, and long non-coding RNA AC011298. In addition, the model was also able to distinguish metastases of different sites (liver or lung) at an AUC of 0.933.

Conclusion

We have identified DNA methylation biomarkers associated with the risk of cancer liver metastasis in early-stage CRC patients. A risk prediction model based on those epigenetic markers was proposed for outcome assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01108-3.

Mass Spectrometry: A Powerful Method for Monitoring Various Type of Leukemia, Especially MALDI-TOF in Leukemia's Proteomics Studies Review

Recent success in studying the proteome, as a source of biomarkers, has completely changed our understanding of leukemia (blood cancer). The identification of differentially expressed proteins, such as relapse and drug resistance proteins involved in leukemia by using various ionization sources and mass analyzers of mass spectrometry techniques, has helped scientists find better diagnosis, prognosis, and treatment strategies. With the aid of this powerful analytical technique, we can investigate the qualification/quantification of proteins, protein-protein interactions, post-translational modifications, and find the correlation between proteins and their genes with the hope of finding the missing parts of the successful therapy puzzle. In this review, we followed different MS sources and analyzers which used for monitoring various type of leukemia, then focused on MALDI-TOF MS as a quick and reliable method for studying proteins. Due to several review published for other techniques, the present review is the first work in this field. Also, by classifying more than 400 proteins, we have found 42 proteins are involved in two or three different stages of leukemia. Finally, we have suggested six specific biomarkers for AML, one for ALL, three biomarkers with a role in the etiology of leukemia and 13 markers with the potential for further studies.

The mechanobiome: a goldmine for cancer therapeutics

Cancer progression is dependent on heightened mechanical adaptation, both for the cells' ability to change shape and to interact with varying mechanical environments. This type of adaptation is dependent on mechanoresponsive proteins that sense and respond to mechanical stress, as well as their regulators. Mechanoresponsive proteins are part of the mechanobiome, which is the larger network that constitutes the cell's mechanical systems that are also highly integrated with many other cellular systems, such as gene expression, metabolism, and signaling. Despite the altered expression patterns of key mechanobiome proteins across many different cancer types, pharmaceutical targeting of these proteins has been overlooked. Here, we review the biochemistry of key mechanoresponsive proteins, specifically nonmuscle myosin II, α-actinins, and filamins, as well as the partnering proteins 14-3-3 and CLP36. We also examined a wide range of data sets to assess how gene and protein expression levels of these proteins are altered across many different cancer types. Finally, we determined the potential of targeting these proteins to mitigate invasion or metastasis and suggest that the mechanobiome is a goldmine of opportunity for anticancer drug discovery and development.

Prognostic Values for the mRNA Expression of the ADAMTS Family of Genes in Gastric Cancer

The “A Disintegrin and Metalloproteinase with Thrombospondin Motif” (ADAMTS) family of genes is involved in the occurrence and development of different cancers. However, the prognostic value of these genes in gastric cancer (GC) has not been revealed. The present study was thus conducted to determine the prognostic value for the ADAMTS family of genes in GC. First, we evaluated the mRNA expression levels of the ADAMTS family in GC patients using a GEPIA dataset. Thereafter, we determined the prognostic value of these genes by analyzing their mRNA level using the Kaplan–Meier Plotter database. The mRNA expression level of ADAMTS12 was randomly validated by qRT-PCR and meta-analysis while its coexpression genes were derived using Coexpedia. Finally, we performed Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the OmicShare Tools. Compared to normal tissues, expression of ADAMTS2 and 12 was significantly higher while that of ADAMTS1, 13, and 15 was significantly lower in GC tissues. According to the RNA-seq and gene chip data, the ADAMTS family (6, 7, 12, 15, and 18) of genes was closely related to the prognosis of GC, and their high expression levels were associated with poor prognosis and survival time. In addition, ADAMTS12 was highly expressed in 20 pairs of GC tissues based on RT-PCR (P=0.016) and meta-analysis (SMD: 0.73, 95% CI: 0.32–1.14, P < 0.001). GO and KEGG pathway analyses indicated that the ADAMTS12 coexpressed genes were enriched in the pathways of extracellular matrix organization, extracellular matrix structural constituent, extracellular matrix, and protein digestion and absorption. Herein, we discovered the prognostic values and biological roles of the ADAMTS genes in GC.

Overexpression of JAG2 is related to poor outcomes in oral squamous cell carcinoma

OBJECTIVES

JAG2 is one of Notch ligands, which recently appear to exert various carcinogenesis. In the present study, we aimed to unveil the relation of JAG2 expression and clinicopathological features in oral squamous cell carcinoma (OSCC).

MATERIALS AND METHODS

We examined JAG2 expression in OSCC plus adjacent nontumorous epithelia in eight patients. Ninety-one OSCC tissue specimens were immunohistochemically stained with specific antibodies to JAG2. The immunoreactivities of JAG2 were correlated with clinicopathological factors, including the prognosis of patients. Chi-square test, Kaplan-Meier survival, and Cox proportional hazard analysis were used to determine the statistical value of JAG2 expression in OSCC.

RESULTS

JAG2 mRNA expression was much expressed in OSCC tissues compared with adjacent tissue specimens in five of eight patients. JAG2 immunoreactivity was found at invasion front in 31 of 91 OSCC. JAG2 immunoreactivity was significantly associated with age, less than 50 years old of patients (P = .048). Kaplan-Meier analysis demonstrated that the patients with JAG2 immunoreactvty have a short overall survival. With the Cox proportional hazard regression mode, the independent factors predictive of poor overall survival included JAG2 immunoreactivity (P < .05).

CONCLUSIONS

The present findings suggest that JAG2 overexpression, especially at the cancer invasion front, has potential prognostic value.

Biomarkers in Colorectal Cancer: The Role of Translational Proteomics Research

Colorectal cancer is one of the most common cancers in the world, and it is one of the leading causes of cancer-related death. Despite recent progress in the development of screening programs and in the management of patients with colorectal cancer, there are still many gaps to fill, ranging from the prevention and early diagnosis to the determination of prognosis factors and treatment of metastatic disease, to establish a personalized approach. The genetic profile approach has been increasingly used in the decision-making process, especially in the choice of targeted therapies and in the prediction of drug response, but there are still few validated biomarkers of colorectal cancer for clinical practice. The discovery of non-invasive, sensitive, and specific biomarkers is an urgent need, and translational proteomics play a key role in this process, as they enable better comprehension of colorectal carcinogenesis, identification of potential markers, and subsequent validation. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through proteomics studies according to biomarker function and clinical application.