T-cell Differentiation Protein Research Articles

Multi-Omics Analysis of the Therapeutic Value of MAL2 Based on Data Mining in Human Cancers

Recent studies have reported that T-cell differentiation protein 2 (MAL2) is an important regulator in cancers. Here, we downloaded data from multiple databases to analyze MAL2 expression and function in pan-cancers, especially in ovarian cancer (OC). Gene Expression Profiling Interactive Analysis (GEPIA) databases was used to examine MAL2 expression in 13 types of cancer. Kaplan–Meier plotter database was used to analyze the overall survival rate of MAL2 in pan-cancers. The Catalog of Somatic Mutations in Cancer (COSMIC), cBioPortal, and UCSC databases were used to examine MAL2 mutation in human cancers. Metascape, STRING, and GeneMANIA websites were used to explore MAL2 function in OC. Furthermore, ggplot2 package and ROC package were performed to analyze hub gene expression and undertake receiver operating characteristic (ROC) analysis. Drug sensitivity of MAL2 in OC was examined by the GSCALite database. In order to verify the results from databases above, real-time quantitative polymerase chain reaction (qRT-PCR) and western blotting were conducted to detect the expression of MAL2 in OC cells. CRISPR/Cas9 system was used to knockout the MAL2 gene in the OC cell lines HO8910 and OVCAR3, using specific guide RNA targeting the exons of MAL2. Then, we performed proliferation, colony formation, migration, and invasion assays to investigate the impact of MAL2 in OC cell lines in vivo and in vitro. Epithelial-mesenchymal transition (EMT)-associated biomarkers were significantly altered in vitro via western blotting and qRT-PCR. Taken together, we observed that MAL2 was remarkably dysregulated in multiple cancers and was related to patient overall survival (OS), mutation, and drug sensitivity. Furthermore, experimental results showed that MAL2 deletion negatively regulated the proliferation, migration, invasion, and EMT of OC, indicating that MAL2 is a novel oncogene that can activate EMT, significantly promote both the proliferation and migration of OC in vitro and in vivo, and provide new clues for treatment strategies.

Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer.

Detection of epithelial ovarian cancer (EOC) poses a critical medical challenge. However, novel biomarkers for diagnosis remain to be discovered. Therefore, innovative approaches are of the utmost importance for patient outcome. Here, we present a concept for blood-based biomarker discovery, investigating both epithelial and specifically stromal compartments, which have been neglected in search for novel candidates. We queried gene expression profiles of EOC including microdissected epithelium and adjacent stroma from benign and malignant tumours. Genes significantly differentially expressed within either the epithelial or the stromal compartments were retrieved. The expression of genes whose products are secreted yet absent in the blood of healthy donors were validated in tissue and blood from patients with pelvic mass by NanoString analysis. Results were confirmed by the comprehensive gene expression database, CSIOVDB (Ovarian cancer database of Cancer Science Institute Singapore). The top 25% of candidate genes were explored for their biomarker potential, and twelve were able to discriminate between benign and malignant tumours on transcript levels (p < 0.05). Among them T-cell differentiation protein myelin and lymphocyte (MAL), aurora kinase A (AURKA), stroma-derived candidates versican (VCAN), and syndecan-3 (SDC), which performed significantly better than the recently reported biomarker fibroblast growth factor 18 (FGF18) to discern malignant from benign conditions. Furthermore, elevated MAL and AURKA expression levels correlated significantly with a poor prognosis. We identified promising novel candidates and found the stroma of EOC to be a suitable compartment for biomarker discovery.

Immune landscape of neoadjuvant/preoperative chemoradiotherapy in pancreatic cancer.

e15709 Background: Neoadjuvant/preoperative chemoradiotherapy in pancreatic cancer has been implicated to induce a local anti-tumor immunity, however the molecular mechanism remains a conundrum. Methods: Two patients’ cohort samples with/without preoperative chemoradiotherapy were used (n = 26 and n = 20, respectively). The treatment-driven immune microenvironment changes were analyzed by stratified bioinformatic approaches i.e. heat map analysis of immune-related genes selected by Gene Ontology, GSEA with Immunologic Signature data base, and Ingenuity Pathway Analysis (IPA). The results were further validated by immunohistochemical approaches. Results: Preoperative treatment induced 212 genes including DC-SIGN (CD209) and 13 immune-associated pathways such as TCR signaling, with an increasing shift of CD8 T-cell population by upregulation of MAL (T-cell differentiation protein). Consistently, immunohistochemical findings showed that the accumulation of DC-SIGN (+) dendritic cells and MAL (+) lymphocytes were significantly increased in patients with preoperative therapy. Conclusions: Preoperative chemoradiotherapy induces a shift toward CD8 T-cell generation mediated by DC-SIGN (+) dendritic cells and MAL (+) lymphocytes, leading to enhance anti-tumor immunity.

Identification of crucial genes associated with esophageal squamous cell carcinoma by gene expression profile analysis.

To uncover the genes associated with the development of esophageal squamous cell carcinoma (ESCC), an ESCC microarray dataset was used to identify genes differentially expressed between ESCC and normal control tissues. The dataset GSE17351 was downloaded from the Gene Expression Omnibus, containing 5 tumor esophageal mucosa samples and 5 adjacent normal esophageal mucosa samples from 5 male patients with ESCC. The differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Data R package. Then, a co-expression network was constructed using the Weighted Correlation Network Analysis (WGCNA) package, and co-expression network modules were obtained with a hierarchical clustering algorithm. Additionally, functional enrichment analyses for DEGs in the top 2 modules with the highest significance were respectively conducted using the WGCNA package and the cluster Profiler package. In total, 487 upregulated and 468 downregulated DEGs were identified. A total of 24 modules were obtained from the co-expression network, and the top 2 modules with the highest significance, designated as ‘blue4’ and ‘magenta’, were further analyzed. In the module blue4, DEGs were significantly enriched in a number of Gene Ontology terms, including ‘spindle organization’ [e.g., ubiquitin conjugating enzyme E2 C (UBE2C) and SAC3 domain containing 1] and ‘cell cycle process’ [e.g., UBE2C, minichromosome maintenance complex component 6 (MCM6) and cell division cycle 20 (CDC20)]. Furthermore, a number of DEGs (e.g., UBE2C, CDC20 and MCM6) were enriched in the ‘cell cycle’ and ‘ubiquitin mediated proteolysis’ pathways. In the module ‘magenta’, a number of DEGs [e.g., transferrin receptor (TFRC) and TEA domain transcription factor 4 (TEAD4)] were enriched in the primary metabolic process and intracellular membrane-bounded organelle. Additionally, 308 upregulated genes and 215 downregulated genes were differentially expressed in the same pattern in another dataset, GSE20347, including UBE2C, CDC20, MCM6, TFRC, TEAD4, protein phosphatase 1 regulatory subunit 3C and MAL, T-cell differentiation protein. These DEGs may function in the development of ESCC.

Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles.

The aim of the present study was to identify the biomarkers involved in the development of hepatocellular adenoma (HCA) through integrated analysis of gene expression and methylation microarray. The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database. The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the limma package of R. A t-test was conducted on the differentially methylated sites. Functional enrichment analysis of DEGs was performed through the Database for Annotation, Visualization and Integrated Analysis. The genes corresponding to the differentially methylated sites were obtained by the annotation files of methylation chip platform. A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA. In addition, 238 enriched GO terms, including organic acid metabolic process and carboxylic acid metabolic process, and 14 KEGG pathways, including chemical carcinogenesis, were identified. Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels. The DNA methylation levels may be potential targets of HCA. The present study revealed that the 8 overlapped genes, including annexin A2, chitinase 3-like 1, fibroblast growth factor receptor 4, mal, T-cell differentiation protein like, palladin, cytoskeletal associated protein, plasmalemma vesicle associated protein and SLC22A1, may be potential therapeutic targets of HCA.

MAL gene overexpression as a marker of high-grade serous ovarian carcinoma stem-like cells that predicts chemoresistance and poor prognosis

BackgroundThe existence of cancer stem cells (CSCs) within a tumor bulk has been demonstrated for many solid tumors including epithelial ovarian carcinoma (EOC). CSCs have been associated to tumor invasion, metastasis and development of chemoresistant recurrences. In this context, we aim to characterize EOC CSCs from the molecular point of view in order to identify potential biomarkers associated with chemoresistance.MethodsWe isolated a population of cells with stem-like characteristics (OVA-BS4 spheroids) from a primary human EOC cell line under selective conditions. OVA-BS4 spheroids were characterized for drug response by cytotoxicity assays and their molecular profile was investigated by microarray and RT-qPCR. Finally, we performed a gene expression study in a cohort of 74 high-grade serous EOC (HGSOC) patients by RT-qPCR.ResultsSpheroids exhibited properties of self-renewal and a pronounced expression of well-known stem cell genes. Moreover, they demonstrated greater resistance towards several anticancer drugs compared to parent cell line, consistent with their higher ABCG2 gene expression. From microarray studies MAL (T-cell differentiation protein) emerged as the most up-regulated gene in spheroids, compared to parent cell line. In HGSOC patients, MAL was significantly overexpressed in platinum-resistant compared to platinum-sensitive patients and resulted as an independent prognostic marker of survival.ConclusionsThis investigation provides an important contribution to the identification of molecular markers of ovarian CSCs and chemoresistance. Successful translation of molecular findings would lead to a better comprehension of the mechanisms triggering chemoresistant recurrences, to the individuation of novel therapeutic targets and to the personalization of treatment regimens.

Lower expression of CADM1 and higher expression of MAL in Merkel cell carcinomas are associated with Merkel cell polyomavirus infection and better prognosis

Merkel cell carcinoma (MCC) is a clinically aggressive neuroendocrine skin cancer; 80% of the cases are associated with the Merkel cell polyomavirus (MCPyV). We previously reported that MCPyV-negative MCCs have more irregular nuclei with abundant cytoplasm and significantly unfavorable outcomes than do MCPyV-positive MCCs. These results suggest that some cell adhesion or structural stabilization molecules are differently expressed depending on MCPyV infection status. Thus, we investigated the association of prognosis or MCPyV infection status in MCCs with cell adhesion molecule 1 (CADM1)/differentially expressed in adenocarcinoma of the lung protein 1 (DAL-1)/membrane protein, palmitoylated 3 (MPP3) tripartite complex and mal T-cell differentiation protein (MAL) expression, which play important roles in cell adhesion and oncogenesis and are related to cancer outcomes in various malignancies, to elucidate the role of these molecules. We analyzed the pathological and molecular characteristics of 26 MCPyV-positive and 15 MCPyV-negative MCCs. Univariate Cox regression analysis showed that advanced age (hazard ratio [HR], 8.249; P = .007) and high CADM1 expression (HR, 5.214; P = .012) were significantly unfavorable overall survival parameters, whereas MCPyV infection (HR, 0.043, P < .001) and lower MAL expression (HR, 0.273; P = .018) were significantly favorable. On multivariate analysis, only MCPyV infection was significantly favorable for overall survival (HR, 0.04; P = .005). Hypermethylation of CADM1, DAL-1, and MAL promoters was detected in 1 of 18, 15 of 27, and 1 of 13 cases, respectively. Double immunostaining for cytokeratin 20 and CADM1, DAL-1, or MAL showed that nonneoplastic Merkel cells expressed DAL-1 and MAL but not CADM1. This study revealed that MCPyV-negative MCCs significantly expressed higher CADM1 and lower MAL than MCPyV-positive MCCs; these expression levels were markedly related to unfavorable outcomes. These data will give us important insights to develop novel molecular target therapies for MCCs.

Suppression of MAL gene expression is associated with colorectal cancer metastasis.

Mal, T-cell differentiation protein (MAL) is a candidate tumor suppressor gene that functions in membrane trafficking processes in polarized epithelial cells. The aim of the present study was to determine its clinical significance in colorectal cancer (CRC). The RNA and protein expression levels of MAL in 30 colorectal specimens were detected by semi-quantitative polymerase chain reaction and immunohistochemistry analysis. Statistical analysis was performed using SPSS software. The RNA level of MAL was significantly downregulated in the CRC tissues compared with the adjacent healthy tissue (P<0.05). MAL was only positively expressed in 20% of the CRC tissues, but in 66.7% of the adjacent tissues, as determined by immunohistochemistry analysis. The expression of the MAL RNA transcript exhibited a positive correlation with protein expression. The expression levels of MAL were significantly associated with different tumor-node-metastasis stages and lymph node metastasis (P<0.05), but not with age, gender, tumor site, differentiation status and pathological type (P>0.05). Suppression of MAL expression was significantly correlated with metastasis in CRC. The present study indicated that MAL may function as an anti-metastasis factor and represent a potential biomarker for malignant colorectal tumors.

In Silico Gene Expression Data Analysis of Head and Neck Paired Squamous Cell Carcinoma

The recent explosion in the number of gene expression experiments and the need to extract useful biological information from the resulting volumes of data has presented a new challenge, that is, to identify the most significant changes in gene expression and to interpret the results in terms of biological relationships. There are a number of web resources that provide data annotation services for gene expression datasets. Microarray Analysis has become a huge widely used tool for the generation of gene expression data on functional genomic scale. The information gained offers an unprecedented opportunity to fully characterize biological processes. The global burden of cancer continues to increase largely because of the aging and growth of the world population alongside an increasing adoption of cancer-causing behaviours, particularly smoking, in economically developing countries. Mainly the Head and Neck squamous cell carcinoma, and is one of the leading causes of human death worldwide and the deaths from cancer are projected to continue rising. With the help of Bioinformatics techniques the analysis of gene expression data is done through BRB Array tool .Microarray data is analysed using PAM and Hierarchical clustering. The two genes i.e. Keratin 4 and Mal, Tcell differentiation protein are predicted through PAM. These genes can have important role in the Head and Neck squamous cell carcinoma.

MAL2 expression predicts distant metastasis and short survival in pancreatic cancer

Pancreatic cancer is associated with a devastating prognosis, partially because of its aggressive metastatic ability. Identification of prognostic markers of metastasis would be useful in the clinical management of postoperative patients with pancreatic cancer. Mal, T-cell differentiation protein 2 (MAL2) has been identified as a molecule predictive of metastases; the clinical relevance of MAL2 in pancreatic cancer is unknown. Orthotopic human pancreatic cancer xenografts from the pancreatic cancer cell line SUIT-2 were established in nude mice. Only liver metastasis was harvested and cultured. These metastatic cycles were repeated 5 times to establish a highly metastatic cell line, termed metastatic SUIT-2 (MS). We investigated proliferation and motility of MS cells compared with those of the parent SUIT-2. Microarray analysis was performed to investigate differences in gene expression. We also performed immunohistochemical analysis of 89 formalin-fixed, paraffin-embedded human pancreatic cancer tissue samples to investigate the clinical significance of MAL2 expression. MS cells showed a greater metastatic rate after orthotopic implantation than parental SUIT-2. MS cells had increased motility but decreased proliferation compared with parental SUIT-2. Microarray analyses showed that 26 genes were significantly upregulated (>10-fold) in MS cells compared with parental SUIT-2, particularly MAL2 expression. Immunohistochemical analysis showed that high expression of MAL2 was associated with a lesser survival of postoperative patients (P = .03) and a high rate of distant metastasis (P = .008). We characterized a newly established pancreatic cancer cell line with highly metastatic potential. MAL2 is a promising predictive marker for distant metastasis and short survival in patients with resected pancreatic cancer.

MAL (mal, T-cell differentiation protein)

Review on MAL (mal, T-cell differentiation protein), with data on DNA, on the protein encoded, and where the gene is implicated.

Investigation of the Role of Glypican 3 in Liver Regeneration and Hepatocyte Proliferation

Glypicans are heparan sulfate proteoglycans that are bound to the cell surface by glycosylphosphatidylinositol. While six members of the glypican family are known in mammals, our study focused on glypican 3 (GPC3). Loss-of-function mutations of GPC3 result in the Simpson-Golabi-Behmel syndrome, an X-linked disorder characterized by pre- and postnatal liver and other organ overgrowth. GPC3 is overexpressed in human hepatocellular carcinoma; however, its role in normal liver regeneration and hepatocyte proliferation is unknown. Here we investigated the role of GPC3 in hepatocyte proliferation. GPC3 mRNA and protein levels begin to increase 2 days after hepatectomy with peak expression levels by day 5. In hepatocyte cultures, GPC3 reaches a plateau when hepatocyte proliferation decreases. In vitro studies using Morpholino oligonucleotides showed that blocking GPC3 expression promoted hepatocyte growth. Yeast two-hybrid assays revealed that GPC3 interacts with CD81, a member of the tetraspanin family that is reported to be involved in hepatitis C virus infection and cell proliferation. We found that CD81 levels also increased 2 days after partial hepatectomy and toward the end of regeneration. Immunofluorescence showed that CD81 and GPC3 colocalize by 2 and 6 days after hepatectomy. Co-immunoprecipitation validated the interaction of GPC3 and CD81. Our results indicate that GPC3 may be a negative regulator of liver regeneration and hepatocyte proliferation, and that this regulation may involve CD81.

Hypermethylated MAL gene – a silent marker of early colon tumorigenesis

BackgroundTumor-derived aberrantly methylated DNA might serve as diagnostic biomarkers for cancer, but so far, few such markers have been identified. The aim of the present study was to investigate the potential of the MAL (T-cell differentiation protein) gene as an early epigenetic diagnostic marker for colorectal tumors.MethodsUsing methylation-specific polymerase chain reaction (MSP) the promoter methylation status of MAL was analyzed in 218 samples, including normal mucosa (n = 44), colorectal adenomas (n = 63), carcinomas (n = 65), and various cancer cell lines (n = 46). Direct bisulphite sequencing was performed to confirm the MSP results. MAL gene expression was investigated with real time quantitative analyses before and after epigenetic drug treatment. Immunohistochemical analysis of MAL was done using normal colon mucosa samples (n = 5) and a tissue microarray with 292 colorectal tumors.ResultsBisulphite sequencing revealed that the methylation was unequally distributed within the MAL promoter and by MSP analysis a region close to the transcription start point was shown to be hypermethylated in the majority of colorectal carcinomas (49/61, 80%) as well as in adenomas (45/63, 71%). In contrast, only a minority of the normal mucosa samples displayed hypermethylation (1/23, 4%). The hypermethylation of MAL was significantly associated with reduced or lost gene expression in in vitro models. Furthermore, removal of the methylation re-induced gene expression in colon cancer cell lines. Finally, MAL protein was expressed in epithelial cells of normal colon mucosa, but not in the malignant cells of the same type.ConclusionPromoter hypermethylation of MAL was present in the vast majority of benign and malignant colorectal tumors, and only rarely in normal mucosa, which makes it suitable as a diagnostic marker for early colorectal tumorigenesis.

Studies of a human T lymphocyte antigen recognized by a monoclonal antibody.

A monoclonal antibody (designated L17F12) detects an antigen present on 95-100% of human peripheral T lymphocytes, the majority of thymocytes, and acute lymphocytic leukemia T cells but not B cells, B-cell lines, or monocytes. Examination of frozen tissue sections by the immunoperoxidase method revealed that the cells expressing this antigen were found predominantly in the medulla of thymus and in T-cell zones of lymph node and spleen. The antigen recognized by L17F12 was associated with a cell-surface glycoprotein of 67,000 daltons. L17F12 was used to isolate this molecule from human thymocytes, normal peripheral T cells, leukemic T cells, and T-cell lines. Expression of this antigen on normal T cells was not diminished by prolonged exposure in vitro to various T-cell stimuli. In the absence of complement, L17F12 bound to T cells without altering proliferative functions, thus enabling rapid purification of functionally intact T cells. In the presence of complement, L17F12 was cytolytic for T cells, providing the basis for depletion of T cells from heterogeneous populations. These data suggest that the monoclonal antibody L17F12 recognizes a specific T-cell differentiation protein. This antibody will be useful in studies of the human immune system.