Are Gastric Cancer Resection Margin Proteomic Profiles More Similar to Those from Controls or Tumors?

Collagen 1A1 (COL1A1) and Collagen11A1(COL11A1) as diagnostic biomarkers in Breast, colorectal and gastric cancers

PURPOSE

Collagen family genes (CFGs) play a significant role in the pathogenesis of cancers. This study aimed to evaluate changes in the expression levels (Els) of CFGs related to epithelial-mesenchymal transition (EMT) and metastasis in gastric (GC), breast (BC), and colorectal (CRC) cancers to introduce these genes as potential diagnostic biomarkers for these three types of cancer.

METHODS

The Cancer Genome Atlas (TCGA) examined ELS changes in CFGs associated with EMT and metastasis to determine their diagnostic value for GC, BC, and CRC. InteractiVenn was used to find genes shared by these three cancers. The biomarker role of CFGs was determined using the receiver operating characteristic (ROC) analysis. GC, BC, and CRC samples were analyzed using the RT-qPCR method to verify the bioinformatics results and evaluate the EL of the selected genes as biomarkers for these cancers.

RESULTS

The in-silico results showed a significant increase in the EL of several CFGs involved in EMT and metastasis in GC, BC, and CRC samples compared to healthy samples. Six common genes (COL11A1, COL12A1, COL1A1, COL1A2, COL5A1, and COL5A2) showed significantly increased in these three cancers, therebysupporting their oncogenic role. Furthermore, the biomarker-related analyses indicated that COL11A1 and COL1A1 were common diagnostic biomarkers for the three cancers. The RT-qPCR method confirmed that the ELs of COL11A1 and COL1A1 in the GC, BC, and CRC samples increased significantly compared to the adjacent normal samples.

CONCLUSION

CFGs in EMT and metastasis of GC, BC, and CRC are strong common diagnostic biomarkers for these cancers.

Data-independent acquisition (DIA) mass spectrometry reveals related proteins involved in the occurrence of early intestinal-type gastric cancer

Identifying proteins associated with the onset of early intestinal-type gastric cancer (EIGC) can yield valuable insights into the pathogenesis of this specific subtype of gastric cancer. Data-independent acquisition mass spectroscopy (DIA-MS) was utilized to identify the differential protein between 10 cases of EIGC and atrophic gastritis with intestinal metaplasia (NGC). The expressions of IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were verified by immunohistochemistry (IHC) in 20 EIGC samples, 17 gastric low-grade intraepithelial neoplasia (LGIN) samples, and 21 healthy controls. The prognostic values of the five genes were validated in the transcriptome data by survival analysis. A total of 4,028 proteins were identified using DIA-MS and a total of 177 differential proteins were screened with log2(fold change) > 1.5. Among them, 113 proteins were significantly up-regulated, and 64 proteins were significantly down-regulated in EIGC tissues. IHC results showed that proteins IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were highly expressed in the cytoplasm of EIGC and LGIN, which was consistent with the results of DIA-MS. Among them, p62/SQSTM1 may undergo nuclear-cytoplasmic transfer. The five protein-coding genes were associated with intestinal-type gastric cancer survival and exhibited differential expression across various disease stages. The study successfully identified differentially expressed proteins between EIGC and NGC, providing potential biomarkers and valuable insights into the mechanism underlying intestinal-type gastric cancer.

Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.

Collagen XI alpha 1 chain, a potential therapeutic target for cancer

Extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and it is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) has been found to be upregulated in a variety of cancers including ovarian cancer, breast cancer, thyroid cancer, pancreatic cancer, non-small-cell lung cancer, and transitional cell carcinoma of the bladder. High levels of COL11A1 usually predict poor prognosis, while COL11A1 is related to angiogenesis, invasion, and drug resistance of cancer. However, little is known about the specific mechanism by which COL11A1 regulates tumor progression. Here, we have organized and summarized the recent developments regarding elucidation of the relationship between COL11A1 and various cancers, as well as the interaction between COL11A1 and intracellular signaling pathways. In addition, we have selected therapeutic agents targeting COL11A1. All these indicate the possibility of using COL11A1 as a target for cancer treatment.

Risk Factors of Microscopic Invasion in Early Gastric Cancer

PURPOSE

This study aimed to evaluate the clinical significance of microscopic invasion to determine the adequate resection margin in early gastric cancer (EGC).

MATERIALS AND METHODS

A retrospective review was performed that included patients who underwent gastrectomy for clinical early gastric cancer (cEGC) at Seoul National University Hospital between January 2007 and December 2010. After subtracting the microscopic resection margin from the gross resection margin for each proximal or distal resection margin, microscopic invasion was represented by the larger value. Microscopic invasion and its risk factors were analyzed according to the clinicopathologic characteristics.

RESULTS

In total, 861 patients were enrolled in the study. Microscopic invasion of cEGC was 6.0±12.8 mm, and the proportion of patients with microscopic invasion ≥0 mm was 78.4%. In the risk group, tumor location, pT stage, and differentiation did not significantly discriminate the presence of microscopic invasion. The microscopic invasion of EGC-IIb was 13.9±16.8 mm, which was significantly greater than that of EGC-I. No linear correlation was observed between the overall tumor size and microscopic invasion (R=0.030). The independent risk factors for microscopic invasion ≥20 mm were EGC-IIb vs. EGC-I/IIa/IIc/III (odds ratio [OR], 3.103; 95% confidence interval [CI], 1.533-6.282; P=0.002) and male vs. female sex (OR, 1.655; 95% CI, 1.012-2.705; P=0.045).

CONCLUSIONS

Male sex and EGC-IIb were independent risk factors for microscopic invasion ≥20 mm. Examination of intraoperative frozen sections is highly recommended to avoid resection margin involvement, especially in cases of EGC-IIb.

Gene expression study and pathway analysis of histological subtypes of intestinal metaplasia that progress to gastric cancer

Background

Intestinal metaplasia (IM) is a precursor lesion that precedes gastric cancer (GC). There are two IM histological subtypes, complete (CIM) and incomplete (IIM), the latter having higher progression rates to GC. This study was aimed at analysing gene expression and molecular processes involved in the progression from normal mucosa to IM, and also from IM subtypes to GC.

Methodology

We used expression data to compare the transcriptome of healthy gastric mucosa to that of IM not progressing to GC, and the transcriptome of IM subtypes that had progressed to GC to those that did not progress. Some deregulated genes were validated and pathway analyses were performed.

Results

Comparison of IM subtypes that had progressed to GC with those that did not progress showed smaller differences in the expression profiles than the comparison of IM that did not progress with healthy mucosa. New transcripts identified in IM not progressing to GC included TRIM, TMEM, homeobox and transporter genes and SNORD116. Comparison to normal mucosa identified non tumoral Warburg effect and melatonin degradation as previously unreported processes involved in IM. Overexpressed antigen processing is common to both IM-subtypes progressing to GC, but IIM showed more over-expressed oncogenic genes and molecular processes than CIM.

Conclusions

There are greater differences in gene expression and molecular processes involved in the progression from normal healthy mucosa to IM than from IM to gastric cancer. While antigen processing is common in both IM-subtypes progressing to GC, more oncogenic processes are observed in the progression of IIM.

Considerations about gastric cancer proteomics

ABSTRACT The frequency of molecular studies aimed to analyze promoter methylation of tumor suppressor genes and global proteomics in gastric carcinogenesis is increasing. Nonetheless, only a few considered the different types of stomach cells, the tumor location and the influence of Helicobacter pylori and Epstein Barr virus infection (EBV). Molecular differences relating to anatomical and histological tumor areas were also recently described. The authors propose a molecular classification of gastric cancer, dividing it into four subtypes: tumors positive for EBV; microsatellite unstable tumors; genomically stable tumors and tumors with chromosomal instability.

A Time-Based and Intratumoral Proteomic Assessment of a Recurrent Glioblastoma Multiforme

Tumors consist of cells in different stages of transformation with molecular and cellular heterogeneity. By far, heterogeneity is the hallmark of glioblastoma multiforme (GBM), the most malignant and aggressive type of glioma. Most proteomic studies aim in comparing tumors from different patients, but here we dive into exploring the intratumoral proteome diversity of a single GBM. For this, we profiled tumor fragments from the profound region of the same patient’s GBM but obtained from two surgeries a year’s time apart. Our analysis also included GBM‘s fragments from different anatomical regions. Our quantitative proteomic strategy employed 4-plex iTRAQ peptide labeling followed by a four-step strong cation chromatographic separation; each fraction was then analyzed by reversed-phase nano-chromatography coupled on-line with an Orbitrap-Velos mass spectrometer. Unsupervised clustering grouped the proteomic profiles into four major distinct groups and showed that most changes were related to the tumor’s anatomical region. Nevertheless, we report differentially abundant proteins from GBM’s fragments of the same region but obtained 1 year apart. We discuss several key proteins (e.g., S100A9) and enriched pathways linked with GBM such as the Ras pathway, RHO GTPases activate PKNs, and those related to apoptosis, to name a few. As far as we know, this is the only report that compares GBM fragments proteomic profiles from the same patient. Ultimately, our results fuel the forefront of scientific discussion on the importance in exploring the richness of subproteomes within a single tissue sample for a better understanding of the disease, as each tumor is unique.

What gastric cancer proteomic studies show about gastric carcinogenesis?

Gastric cancer is a complex, heterogeneous, and multistep disease. Over the past decades, several studies have aimed to determine the molecular factors that lead to gastric cancer development and progression. After completing the human genome sequencing, proteomic technologies have presented rapid progress. Differently from the relative static state of genome, the cell proteome is dynamic and changes in pathologic conditions. Proteomic approaches have been used to determine proteome profiles and identify differentially expressed proteins between groups of samples, such as neoplastic and nonneoplastic samples or between samples of different cancer subtypes or stages. Therefore, proteomic technologies are a useful tool toward improving the knowledge of gastric cancer molecular pathogenesis and the understanding of tumor heterogeneity. This review aimed to summarize the proteins or protein families that are frequently identified by using high-throughput screening methods and which thus may have a key role in gastric carcinogenesis. The increased knowledge of gastric carcinogenesis will clearly help in the development of new anticancer treatments. Although the studies are still in their infancy, the reviewed proteins may be useful for gastric cancer diagnosis, prognosis, and patient management.

Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients’ tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

Filamin C, a dysregulated protein in cancer revealed by label-free quantitative proteomic analyses of human gastric cancer cells

Gastric cancer (GC) is the fourth and fifth most common cancer in men and women, respectively. We identified 2,750 proteins at false discovery rates of 1.3% (protein) and 0.03% (spectrum) by comparing the proteomic profiles of three GC and a normal gastric cell lines. Nine proteins were significantly dysregulated in all three GC cell lines, including filamin C, a muscle-specific filamin and a large actin-cross-linking protein. Downregulation of filamin C in GC cell lines and tissues were verified using quantitative PCR and immunohistochemistry. Data-mining using public microarray datasets shown that filamin C was significantly reduced in many human primary and metastasis cancers. Transient expression or silencing of filamin C affected the proliferation and colony formation of cancer cells. Silencing of endogenous filamin C enhanced cancer cell migration and invasion, whereas ectopic expression of filamin C had opposing effects. Silencing of filamin C increased the expression of matrix metallopeptidase 2 and improved the metastasis of prostate cancer in a zebrafish model. High filamin C associated with better prognosis of prostate cancer, leukemia and breast cancer patients. These findings establish a functional role of filamin C in human cancers and these data will be valuable for further study of its mechanisms.

Metabolomic Analysis Using Liquid Chromatography/Mass Spectrometry for Gastric Cancer

Metabolomics is a post-genomics research field for analysis of low molecular weight compounds in biological samples and has shown great potentials for elucidating complex mechanisms associated with diseases. However, metabolomics studies on gastric cancer (GC), which is the second leading cause of cancer death worldwide, remain scarce, and the molecular mechanisms to metabolomics phenotypes are also still not fully understood. This study reports that the metabolic pathways can be exploited as biomarkers for diagnosis and treatment of GC progression as a case study. Importantly, the urinary metabolites and metabolic patterns were analyzed by high-throughput liquid chromatography mass spectrometry (LC-MS) metabolomics strategy coupled with chemometric evaluation. Sixteen metabolites (nine upregulated and seven downregulated) were differentially expressed and may thus serve as potential urinary biomarkers for human GC. These metabolites were mainly involved in multiple metabolic pathways, including citrate cycle (malic acid, succinic acid, 2-oxoglutarate, citric acid), cyanoamino acid metabolism (glycine, alanine), primary bile acid biosynthesis (glycine, taurine, glycocholic acid), arginine and proline metabolism (urea, L-proline), and fatty acid metabolism (hexadecanoic acid), among others. Network analysis validated close association between these identified metabolites and altered metabolic pathways in a variety of biological processes. These results suggest that urine metabolic profiles have great potential in detecting GC and may aid in understanding its underlying mechanisms. It provides insight into disease pathophysiology and can serve as the basis for developing disease biomarkers and therapeutic interventions for GC diseases.

Tumor matrix protein collagen XIα1 in cancer

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

Comparative evaluation of 5-15-kDa salivary proteins from patients with different oral diseases by MALDI-TOF/TOF mass spectrometry

OBJECTIVES

The present study aimed to determine the potential use of matrix-assisted laser desorption/ionization with time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF MS) for analyzing specific patterns of mass signals of low-molecular-weight proteins in saliva from patients with different oral diseases.

MATERIALS AND METHODS

Unstimulated whole saliva samples were collected from healthy subjects (n = 30) and patients with oral diseases including oral cancer (n = 30), oral lichen planus (n = 30), and chronic periodontitis (n = 30). Proteomic profiles of 5,000-15,000-Da salivary proteins were evaluated by MALDI-TOF/TOF MS. Quantification of mass signals was performed by FlexAnalysis and ClinProTool software.

RESULTS

In oral cancer, the percentages of mass signals at 5,592.26 and 8,301.46 Da were significantly increased as compared with other groups (p = 0.002 and p = 0.030, respectively). In oral lichen planus, the percentages of mass signals at 12,964.55 and 13,279.08 Da were significantly increased as compared with other groups (p < 0.001, and p < 0.001, respectively). In chronic periodontitis, the percentages of mass signals at 5,835.73 and 9,801.83 Da were significantly decreased as compared with other groups (p = 0.003 and p = 0.005, respectively).

CONCLUSIONS

The present study demonstrated a potential use of MALDI-TOF/TOF as a rapid screening method to differentiate one oral disease from others by identifying specific patterns of mass signals in saliva from patients. However, MALDI-TOF/TOF has several limitations regarding the identification of the candidate mass signals.

CLINICAL RELEVANCE

MALDI-TOF/TOF MS can be used as a rapid screening method to differentiate one oral disease from others with a caution concerning peptide identity.

Proteome analysis of the inner integument from developing Jatropha curcas L. seeds

In this study, we performed a systematic proteomic analysis of the inner integument from developing seeds of Jatropha curcas and further explored the protein machinery responsible for generating the carbon and nitrogen sources to feed the growing embryo and endosperm. The inner integument of developing seeds was dissected into two sections called distal and proximal, and proteins were extracted from these sections and from the whole integument and analyzed using an EASY-nanoLC system coupled to an ESI-LTQ-Orbitrap Velos mass spectrometer. We identified 1526, 1192, and 1062 proteins from the proximal, distal, and whole inner integuments, respectively. The identifications include those of peptidases and other hydrolytic enzymes that play a key role in developmental programmed cell death and proteins associated with the cell-wall architecture and modification. Because many of these proteins are differentially expressed within the integument cell layers, these findings suggest that the cells mobilize an array of hydrolases to produce carbon and nitrogen sources from proteins, carbohydrates, and lipids available within the cells. Not least, the identification of several classes of seed storage proteins in the inner integument provides additional evidence of the role of the seed coat as a transient source of reserves for the growing embryo and endosperm.

Tumor protein D52 (TPD52) and cancer-oncogene understudy or understudied oncogene?

The Tumor protein D52 (TPD52) gene was identified nearly 20 years ago through its overexpression in human cancer, and a substantial body of data now strongly supports TPD52 representing a gene amplification target at chromosome 8q21.13. This review updates progress toward understanding the significance of TPD52 overexpression and targeting, both in tumors known to be characterized by TPD52 overexpression/amplification, and those where TPD52 overexpression/amplification has been recently or variably reported. We highlight recent findings supporting microRNA regulation of TPD52 expression in experimental systems and describe progress toward deciphering TPD52's cellular functions, particularly in cancer cells. Finally, we provide an overview of TPD52's potential as a cancer biomarker and immunotherapeutic target. These combined studies highlight the potential value of genes such as TPD52, which are overexpressed in many cancer types, but have been relatively understudied.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Deciphering the human brain proteome: characterization of the anterior temporal lobe and corpus callosum as part of the Chromosome 15-centric Human Proteome Project

Defining the proteomes encoded by each chromosome and characterizing proteins related to human illnesses are among the goals of the Chromosome-centric Human Proteome Project (C-HPP) and the Biology and Disease-driven HPP. Following these objectives, we investigated the proteomes of the human anterior temporal lobe (ATL) and corpus callosum (CC) collected post-mortem from eight subjects. Using a label-free GeLC-MS/MS approach, we identified 2454 proteins in the ATL and 1887 in the CC through roughly 7500 and 5500 peptides, respectively. Considering that the ATL is a gray-matter region while the CC is a white-matter region, they presented proteomes specific to their functions. Besides, 38 proteins were found to be differentially expressed between the two regions. Furthermore, the proteome data sets were classified according to their chromosomal origin, and five proteins were evidenced at the MS level for the first time. We identified 70 proteins of the chromosome 15 - one of them for the first time by MS - which were submitted to an in silico pathway analysis. These revealed branch point proteins associated with Prader-Willi and Angelman syndromes and dyskeratosis congenita, which are chromosome-15-associated diseases. Data presented here can be a useful for brain disorder studies as well as for contributing to the C-HPP initiative. Our data are publicly available as resource data to C-HPP participant groups at http://yoda.iq.ufrj.br/Daniel/chpp2013. Additionally, the mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000547 for the corpus callosum and PXD000548 for the anterior temporal lobe.

Exploring the proteomic landscape of a gastric cancer biopsy with the shotgun imaging analyzer

Accessing localized proteomic profiles has emerged as a fundamental strategy to understand the biology of diseases, as recently demonstrated, for example, in the context of determining cancer resection margins with improved precision. Here, we analyze a gastric cancer biopsy sectioned into 10 parts, each one subjected to MudPIT analysis. We introduce a software tool, named Shotgun Imaging Analyzer and inspired in MALDI imaging, to enable the overlaying of a protein's expression heat map on a tissue picture. The software is tightly integrated with the NeXtProt database, so it enables the browsing of identified proteins according to chromosomes, quickly listing human proteins never identified by mass spectrometry (i.e., the so-called missing proteins), and the automatic search for proteins that are more expressed over a specific region of interest on the biopsy, all of which constitute goals that are clearly well-aligned with those of the C-HPP. Our software has been able to highlight an intense expression of proteins previously known to be correlated with cancers (e.g., glutathione S-transferase Mu 3), and in particular, we draw attention to Gastrokine-2, a "missing protein" identified in this work of which we were able to clearly delineate the tumoral region from the "healthy" with our approach. Data are available via ProteomeXchange with identifier PXD000584.