The Landscape of Transmembrane Protein Family Members in Head and Neck Cancers: Their Biological Role and Diagnostic Utility

Expression, DNA methylation pattern and transcription factor EPB41L3 in gastric cancer: a study of 262 cases

PURPOSE

DNA methylation prominently inactivates tumor suppressor genes and facilitates oncogenesis. Previously, we delineated a chromosome 18 deletion encompassing the erythrocyte membrane protein band 4.1-like 3 (EPB41L3) gene, a progenitor for the tumor suppressor that is differentially expressed in adenocarcinoma of the lung-1 (DAL-1) in gastric cancer (GC).

METHODS

Our current investigation aimed to elucidate EPB41L3 expression and methylation in GC, identify regulatory transcription factors, and identify affected downstream pathways. Immunohistochemistry demonstrated that DAL-1 expression is markedly reduced in GC tissues, with its downregulation serving as an independent prognostic marker.

RESULTS

High-throughput bisulfite sequencing of 70 GC patient tissue pairs revealed that higher methylation of non-CpGs in the EPB41L3 promoter was correlated with more malignant tumor progression and higher-grade tissue classification. Such hypermethylation was shown to diminish DAL-1 expression, thus contributing to the malignancy of GC phenotypes. The DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine (5-aza-CdR) was found to partially restore DAL-1 expression. Moreover, direct binding of the transcription factor CDC5L to the upstream region of the EPB41L3 promoter was identified via chromosome immunoprecipitation (ChIP)-qPCR and luciferase reporter assays. Immunohistochemistry confirmed the positive correlation between CDC5L and DAL-1 protein levels. Subsequent RNA-seq analysis revealed that DAL-1 significantly influences the extracellular matrix and space-related pathways. GC cell RNA-seq post-5-Aza-CdR treatment and single-cell RNA-seq data of GC tissues confirmed the upregulation of AREG and COL17A1, pivotal tumor suppressors, in response to EPB41L3 demethylation or overexpression in GC epithelial cells.

CONCLUSION

In conclusion, this study elucidates the association between non-CpG methylation of EPB41L3 and GC progression and identifies the key transcription factors and downstream molecules involved. These findings enhance our understanding of the role of EPB41L3 in gastric cancer and provide a solid theoretical foundation for future research and potential clinical applications.

Immunoassays for Extracellular Vesicle Detection via Transmembrane Proteins Using Surface Plasmon Resonance Biosensors

Extracellular vesicles (EVs) are preeminent carriers of biomarkers and have become the subject of intense biomedical research for medical diagnostics using biosensors. To create effective EV-based immunoassays, it is imperative to develop surface chemistry approaches with optimal EV detection targeting transmembrane protein biomarkers that are not affected by cell-to-cell variability. Here, we developed a series of immunoassays for the detection of EVs derived from mouse monocyte cells using surface plasmon resonance (SPR) biosensors. We chemically immobilized antibodies onto mixed self-assembled monolayers of oligo ethylene glycol (OEG) alkanethiolates with carboxylic and hydroxylic terminal groups. The effects of antibody clonality (monoclonal vs polyclonal) and antibody surface coverage in targeting EVs via CD81 tetraspanins were investigated. We determined binding kinetic parameters, establishing trends from steric hindrance effects and epitope recognition properties of antibodies. Our results indicate that a 40% surface coverage of polyclonal antibodies covalently linked onto a mixed SAM with 10% of terminated -COOH groups yields a promising approach for EV detection with a linear range of 1.9 × 108-1.9 × 109 EVs/mL and a limit of detection of 5.9 × 106 EVs/mL. This optimal immunoassay exhibits a 1.92 nM equilibrium dissociation constant for bound EVs, suggesting a high binding affinity when CD81 is targeted. Our study provides important insights into surface chemistry development for EV detection targeted via transmembrane protein biomarkers using antibodies, which has promising applications for disease diagnostics.

Transcriptomic analysis of Porphyromonas gingivalis-infected head and neck cancer cells: Identification of PLAU as a candidate prognostic biomarker

Periodontal disease is a risk factor for head and neck squamous cell carcinoma (HNSCC), and Porphyromonas gingivalis, a major periodontal pathogen, has been identified as a specific and potentially independent microbial factor that increases the risk of cancer mortality. Gene expression in HNSCC due to P. gingivalis infection and how changes in gene expression affect the prognosis of HNSCC patients are not clarified. When P. gingivalis was cultured with HNSCC cells, it efficiently adhered to these cells and enhanced their invasive ability. A transcriptome analysis of P. gingivalis -infected HNSCC cells showed that genes related to migration, including CCL20, CITED2, CTGF, C8orf44-SGK3, DUSP10, EGR3, FUZ, HBEGF, IL1B, IL24, JUN, PLAU, PTGS2, P2RY1, SEMA7A, SGK1 and SIX2, were highly up- or down-regulated. The expression of up-regulated genes was examined using the expression data of HNSCC patients obtained from The Cancer Genome Atlas (TCGA) database, and the expression of 5 genes, including PLAU, was found to be higher in cancer tissue than in solid normal tissue. An analysis of protein-protein interactions revealed that these 5 genes formed a dense network. A Cox regression analysis showed that high PLAU expression levels were associated with a poor prognosis in patients with TCGA-HNSCC. Furthermore, the prognostic impact correlated with tumour size and the presence or absence of lymph node metastasis. Collectively, these results suggest the potential of PLAU as a molecular prognostic marker in HNSCC patients. Further in vivo and in vitro studies are needed to verify the findings of this study.

SRY-Related Transcription Factors in Head and Neck Squamous Cell Carcinomas: In Silico Based Analysis

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer and the fifth cause of cancer-related deaths worldwide with a poor 5-year survival. SOX family genes play a role in the processes involved in cancer development such as epithelial-mesenchymal transition (EMT), the maintenance of cancer stem cells (CSCs) and the regulation of drug resistance. We analyzed the expression of SOX2-OT, SOX6, SOX8, SOX21, SOX30 and SRY genes in HNSCC patients using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, to assess their biological role and their potential utility as biomarkers. We demonstrated statistically significant differences in expression between normal and primary tumor tissues for SOX6, SOX8, SOX21 and SOX30 genes and pointed to SOX6 as the one that met the independent diagnostic markers criteria. SOX21 or SRY alone, or the panel of six SRY-related genes, could be used to estimate patient survival. SRY-related genes are positively correlated with immunological processes, as well as with keratinization and formation of the cornified envelope, and negatively correlated with DNA repair and response to stress. Moreover, except SRY, all analyzed genes were associated with a different tumor composition and immunological profiles. Based on validation results, the expression of SOX30 is higher in HPV(+) patients and is associated with patients' survival. SRY-related transcription factors have vast importance in HNSCC biology. SOX30 seems to be a potential biomarker of HPV infection and could be used as a prognostic marker, but further research is required to fully understand the role of SOX family genes in HNSCC.

[TMEM64 is highly expressed in hepatocellular carcinoma and promotes tumor cell proliferation and invasion]

OBJECTIVE

To analyze the expression of TMEM64 in hepatocellular carcinoma (HCC) and investigate the effect of TMEM64 expression level on proliferation and invasion of HCC cells in vitro.

METHODS

We analyzed the expression level of TMEM64 in HCC and adjacent tissues based on data from TCGA and GTEx databases. The prognostic value of TMEM64 for HCC patients was examined using Kaplan-Meier survival analysis and a Cox regression model, and a nomogram was constructed based on TMEM64 expression and clinical characteristics of the patients. Functional enrichment analysis was performed to explore the potential signaling pathways, and immune cell infiltration was assessed using single sample gene set enrichment analysis. We also performed cell experiment to observe the changes in proliferation, migration, and invasion in HCCLM3 cells with TMEM64 knockdown and in Huh7 cells with TMEM64 overexpression using CCK-8, EdU, colony formation, Transwell, and wound healing assays.

RESULTS

The expression level of TMEM64 was significantly higher in HCC than in the adjacent tissues (P < 0.05). Kaplan-Meier analysis suggested that a high expression of TMEM64 was associated with poor outcomes of the patients (P < 0.05). Multivariate Cox regression analysis indicated that a high TMEM64 expression was an independent risk factor for overall survival of HCC patients (P < 0.05). TMEM64 expression level was negatively correlated with the levels of immune cell infiltration by NK cells, CD8 + T cells, and plasma pDCs cells (P < 0.05). GO, KEGG, and GSEA enrichment analyses showed that TMEM64 was significantly enriched with tumor invasion and metastasis pathways. The nomogram and calibration curves indicated a moderate prediction reliability of the model. In the cell experiment, TMEM64 knockdown obviously suppressed and TMEM64 overexpression markedly promoted the proliferation, migration, and invasion of HCC cells (P < 0.01).

CONCLUSION

A high TMEM64 expression may serve as an independent risk factor for poor prognosis of HCC and promotes proliferation, migration, and invasion of HCC cells in vitro.

Biological role and diagnostic utility of ribosomal protein L23a pseudogene 53 in cutaneous melanoma

Background

Skin melanoma is one of the deadliest types of skin cancer and develops from melanocytes. The genetic aberrations in protein-coding genes are well characterized, but little is known about changes in non-coding RNAs (ncRNAs) such as pseudogenes. Ribosomal protein pseudogenes (RPPs) have been described as the largest group of pseudogenes which are dispersed in the human genome.

Materials and methids

We looked deeply at the role of one of them, ribosomal protein L23a pseudogene 53 (RPL23AP53), and its potential diagnostic use. The expression level of RPL23AP53 was profiled in melanoma cell lines using real time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and analyzed based on the Cancer Genome Atlas (TCGA) data depending on BRAF status and clinicopathological parameters. Cellular phenotype, which was associated with RPL23AP53 levels, was described based on the REACTOME pathway browser, Gene Set Enrichment Analysis (GSEA) analysis as well as Immune and ESTIMATE Scores.

Results

We indicted in vitro changes in RPL23AP53 level depending on a cell line, and based on in silico analysis of TCGA samples demonstrated significant differences in RPL23AP53 expression between primary and metastatic melanoma, as well as correlation between RPL23AP53 and overall survival. No differences depending on BRAF status were observed. RPL23AP53 is associated with several signaling pathways and cellular processes.

Conclusions

This study showed that patients with higher expression of RPL23AP53 displayed changed infiltration of lymphocytes, macrophages, and neutrophils compared to groups with lower expression of RPL23AP53. RPL23AP53 pseudogene is differently expressed in melanoma compared with normal tissue and its expression is associated with cellular proliferation. Thus, it may be considered as an indicator of patients' survival and a marker for the immune profile assessment.

TMEM211 Promotes Tumor Progression and Metastasis in Colon Cancer

Colon cancer is the third most important cancer type, leading to a remarkable number of deaths, indicating the necessity of new biomarkers and therapeutic targets for colon cancer patients. Several transmembrane proteins (TMEMs) are associated with tumor progression and cancer malignancy. However, the clinical significance and biological roles of TMEM211 in cancer, especially in colon cancer, are still unknown. In this study, we found that TMEM211 was highly expressed in tumor tissues and the increased TMEM211 was associated with poor prognosis in colon cancer patients from The Cancer Genome Atlas (TCGA) database. We also showed that abilities regarding migration and invasion were reduced in TMEM211-silenced colon cancer cells (HCT116 and DLD-1). Moreover, TMEM211-silenced colon cancer cells showed decreased levels of Twist1, N-cadherin, Snail and Slug but increased levels of E-cadherin. Levels of phosphorylated ERK, AKT and RelA (NF-κB p65) were also decreased in TMEM211-silenced colon cancer cells. Our findings indicate that TMEM211 regulates epithelial-mesenchymal transition for metastasis through coactivating the ERK, AKT and NF-κB signaling pathways, which might provide a potential prognostic biomarker or therapeutic target for colon cancer patients in the future.

The expression characteristics of transmembrane protein genes in pancreatic ductal adenocarcinoma through comprehensive analysis of bulk and single-cell RNA sequence

Background

Transmembrane (TMEM) protein genes are a class of proteins that spans membranes and function to many physiological processes. However, there is very little known about TMEM gene expression, especially in cancer tissue. Using single-cell and bulk RNA sequence may facilitate the understanding of this poorly characterized protein genes in PDAC.

Methods

We selected the TMEM family genes through the Human Protein Atlas and characterized their expression by single-cell and bulk transcriptomic datasets. Identification of the key TMEM genes was performed through three machine learning algorithms: LASSO, SVM-RFE and RF-SRC. Then, we established TMEM gene riskscore and estimate its implication in predicting survival and response to systematic therapy. Additionally, we explored the difference and impact of TMEM gene expression in PDAC through immunohistochemistry and cell line research.

Results

5 key TMEM genes (ANO1, TMEM59, TMEM204, TMEM205, TMEM92) were selected based on the single-cell analysis and machine learning survival outcomes. Patients stratified into the high and low-risk groups based on TMEM riskscore, were observed with distinct overall survival in internal and external datasets. Moreover, through bulk RNA-sequence and immunohistochemical staining we verified the protein expression of TMEM genes in PDAC and revealed TMEM92 as an essential regulator of pancreatic cancer cell proliferation, migration, and invasion.

Conclusion

Our study on TMEM gene expression and behavior in PDAC has revealed unique characteristics, offering potential for precise therapeutic approaches. Insights into molecular mechanisms expand understanding of PDAC complexity and TMEM gene roles. Such knowledge may inform targeted therapy development, benefiting patients.

Structural, topological, and functional characterization of transmembrane proteins TMEM213, 207, 116, 72 and 30B provides a potential link to ccRCC etiology

Due to their involvement in the development of various cancers Transmembrane Proteins (TMEMs) are the focus of many recent studies. Previously we reported TMEM de-regulation in clear cell Renal Cell Carcinoma (ccRCC) with TMEM213, 207, 116, 72 and 30B being among the most downregulated on mRNA level. TMEM down-regulation was also more pronounced in advanced ccRCC tumors and was potentially linked to clinical parameters such as: metastasis (TMEM72 and 116), Fuhrman grade (TMEM30B) and overall survival (TMEM30B). To further investigate these findings, first, we set off to prove experimentally that selected TMEMs are indeed membrane-bound as predicted in silico, we verified the presence of signaling peptides on their N-termini, orientation of TMEMs within the membrane and validated their predicted cellular localization. To investigate the potential role of selected TMEMs in cellular processes overexpression studies in HEK293 and HK-2 cell lines were carried out. Additionally, we tested TMEM isoform expression in ccRCC tumors, identified mutations in TMEM genes and examined chromosomal aberrations in their loci. We confirmed the membrane-bound status of all selected TMEMs, assigned TMEM213, and 207 to early endosomes, TMEM72 to early endosomes and plasma membrane, TMEM116 and 30B to the endoplasmic reticulum. The N-terminus of TMEM213 was found to be exposed to the cytoplasm, the C-terminus of TMEM207, 116 and 72 were directed toward the cytoplasm, and both termini of TMEM30B faced the cytoplasm. Interestingly, TMEM mutations and chromosomal aberrations were infrequent in ccRCC tumors, yet we identified potentially damaging mutations in TMEM213 and TMEM30B and found deletions in the TMEM30B locus in nearly 30% of the tumors. Overexpression studies suggested selected TMEMs may take part in carcinogenesis processes such as cell adhesion, regulation of epithelial cell proliferation, and regulation of adaptive immune response, which could indicate a link to the development and progression of ccRCC.

High expression of TMEM200A is associated with a poor prognosis and immune infiltration in gastric cancer

Background: Gastric cancer (GC) is one of the global malignant tumors with high incidence and poor prognosis. Exploring new GC molecular markers is important to improve GC prognosis. Transmembrane protein 200A (TMEM200A) is a member of the family of transmembrane proteins (TMEM). This study is the first to investigate the potential function of TMEM200A and its relationship with immune infiltration in GC. Methods: The differential expression of TMEM200A was determined through the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The receiver operating characteristic (ROC) curve was drawn to assess the diagnostic value of TMEM200A for GC. The relationship between TMEM200A and the clinical characteristics of patients with GC was investigated using the Wilcoxon test and the Kruskal-Wallis test. The effect of TMEM200A on overall survival (OS) was identified using the Kaplan-Meier method, the Log-rank test, the univariate/multivariate Cox regression analysis, and the nomogram prediction model. The co-expressed genes and gene set enrichment analysis (GSEA) were used to explore the potential biological functions of TMEM200A. We used the Tumor Immune Estimation Resource (TIMER) database and the ssGSEA algorithm to estimate the relationship between TMEM200A and immune cell infiltration. Furthermore, we investigated the correlation of TMEM200A with immune checkpoint/immune cell surface markers using the TCGA-STAD data set. Finally, we identified prognosis-related methylation sites in TMEM200A using MethSurv. Results: TMEM200A was highly expressed in GC tissues. TMEM200A had a good diagnostic value for GC. High expression of TMEM200A may shorten the OS of GC patients and may be an independent risk factor for OS in GC patients. TMEM200A participates in the construction of a predictive model with a good predictive effect on the survival rate of GC patients at 1, 3, and 5 years. Co-expressed genes and GSEA indicated that TMEM200A may be an adhesion molecule closely associated with tumor invasion and metastasis. In addition, TMEM200A may be significantly associated with immune cell infiltration and immune checkpoint expression. We also found that TMEM200A contains three methylation sites associated with a poor prognosis. Conclusion: Upregulated TMEM200A may be a promising prognostic marker for GC and is closely associated with the tumor microenvironment (TME).

A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC

BACKGROUND

Tumor microenvironment (TME) is of great importance to regulate the initiation and advance of cancer. The immune infiltration patterns of TME have been considered to impact the prognosis and immunotherapy sensitivity in Head and Neck squamous cell carcinoma (HNSCC). Whereas, specific molecular targets and cell components involved in the HNSCC tumor microenvironment remain a twilight zone.

METHODS

Immune scores of TCGA-HNSCC patients were calculated via ESTIMATE algorithm, followed by weighted gene co-expression network analysis (WGCNA) to filter immune infiltration-related gene modules. Univariate, the least absolute shrinkage and selection operator (LASSO), and multivariate cox regression were applied to construct the prognostic model. The predictive capacity was validated by meta-analysis including external dataset GSE65858, GSE41613 and GSE686. Model candidate genes were verified at mRNA and protein levels using public database and independent specimens of immunohistochemistry. Immunotherapy-treated cohort GSE159067, TIDE and CIBERSORT were used to evaluate the features of immunotherapy responsiveness and immune infiltration in HNSCC.

RESULTS

Immune microenvironment was significantly associated with the prognosis of HNSCC patients. Total 277 immune infiltration-related genes were filtered by WGCNA and involved in various immune processes. Cox regression identified nine prognostic immune infiltration-related genes (MORF4L2, CTSL1, TBC1D2, C5orf15, LIPA, WIPF1, CXCL13, TMEM173, ISG20) to build a risk score. Most candidate genes were highly expressed in HNSCC tissues at mRNA and protein levels. Survival meta-analysis illustrated high prognostic accuracy of the model in the discovery cohort and validation cohort. Higher proportion of progression-free outcomes, lower TIDE scores and higher expression levels of immune checkpoint genes indicated enhanced immunotherapy responsiveness in low-risk patients. Decreased memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells, and increased activated dendritic cells and activated mast cells were identified as crucial immune cells in the TME of high-risk patients.

CONCLUSIONS

The immune infiltration-related gene model was well-qualified and provided novel biomarkers for the prognosis of HNSCC.

TMEM92 acts as an immune-resistance and prognostic marker in pancreatic cancer from the perspective of predictive, preventive, and personalized medicine

Background

Pancreatic cancer presents extremely poor prognosis due to the difficulty of early diagnosis, low resection rate, and high rates of recurrence and metastasis. Immune checkpoint blockades have been widely used in many cancer types but showed limited efficacy in pancreatic cancer. The current study aimed to evaluate the landscape of tumor microenvironment (TME) of pancreatic cancer and identify the potential markers of prognosis and immunotherapy efficacy which might contribute to improve the targeted therapy strategy and efficacy in pancreatic cancer in the context of predictive, preventive, and personalized medicine (PPPM).

Methods

In the current study, a total of 382 pancreatic samples from the datasets of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were selected. LM22 gene signature matrix was applied to quantify the fraction of immune cells based on "CIBERSORT" algorithm. Weighted Gene Co-expression Network Analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm was applied to confirm the hub-network of immune-resistance phenotype. A nomogram model based on COX and Logistic regression was constructed to evaluate the prognostic value and the predictive value of hub-gene in immune-response. The role of transmembrane protein 92 (TMEM92) in regulating cell proliferation was evaluated by MTS assay. Western blot and Real-time PCR were applied to assess the biological effects of PD-L1 inhibition by TMEM92. Moreover, the effect of TMEM92 in immunotherapy was evaluated with PBMC co-culture and by MTS assay.

Results

Two tumor-infiltrating immune cell (TIIC) phenotypes were identified and a weighted gene co-expression network was constructed to confirm the 167 gene signatures correlated with immune-resistance TIIC subtype. TMEM92 was further identified as a core gene of 167 gene signature network based on MCODE algorithm. High TMEM92 expression was significantly correlated with unfavorable prognosis, characterizing by immune resistance. A nomogram model and external validation confirmed that TMEM92 was an independent prognostic factor in pancreatic cancer. An elevated tumor mutation burden (TMB), mostly is consistent with commonly mutations of KRAS and TP53, was found in the high TMEM92 group. The predictive role of TMEM92 in immunotherapeutic response was also confirmed by IMvigor210 datasets. In addition, the specific biological roles of TMEM92 in cancer was explored in vitro. The results showed that abnormal overexpression of TMEM92 was significantly associated with the poor survival rate of pancreatic cancer. Moreover, we demonstrated that TMEM92 inhibit tumour immune responses of the anti-PD-1 antibody with PBMC co-culture.

Conclusion

The current study explored for the first time the immune-resistance phenotype of pancreatic cancer and identified TMEM92 as an innovative marker in predicting clinical outcomes and immunotherapeutic efficacy. These findings not only help to recognize high-risk and immune-resistance population which could be supplied targeted prevention, but also provide personalized medical services by intervening TMEM92 function to improve the prognosis of pancreatic cancer. In addition, the biological role of TMEM92 might reveal the potential molecular mechanisms of pancreatic cancer and lead to a novel sight for development of a PPPM approach for pancreatic cancer management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00287-0.

A transmembrane protein family gene signature for overall survival prediction in osteosarcoma

The transmembrane (TMEM) protein family is constituted by a large number of proteins that span the lipid bilayer. Dysregulation of TMEM protein genes widely occurs and is associated with clinical outcomes of patients with multiple tumors. Nonetheless, the significance of TMEM genes in the prognosis prediction of patients with osteosarcoma remains largely unclear. Here, we comprehensively analyzed TMEM protein family genes in osteosarcoma using public resources and bioinformatics methods. Prognosis-related TMEM protein family genes were identified by the univariate Cox regression analysis and were utilized to construct a signature based on six TMEM protein family genes (TMEM120B, TMEM147, TMEM9B, TMEM8A, TMEM59, and TMEM39B) in osteosarcoma. The prognostic signature stratified patients into high- and low-risk groups, and validation in the internal and external cohorts confirmed the risk stratification ability of the signature. Functional enrichment analyses of differentially expressed genes between high- and low-risk groups connected immunity with the prognostic signature. Moreover, we found that M2 and M0 macrophages were the most abundant infiltrated immune cell types in the immune microenvironment, and samples of the high-risk group showed a decreased proportion of M2 macrophages. Single-sample gene set enrichment analysis revealed that the scores of neutrophils and Treg were markedly lower in the high-risk group than these in the low-risk group in The Cancer Genome Atlas and GSE16091 cohorts. As for the related immune functions, APC co-inhibition and cytolytic activity exhibited fewer active levels in the high-risk group than that in the low-risk group in both cohorts. Of the six TMEM genes, the expression of TMEM9B was lower in the high-risk group than in the low-risk group and was positively associated with the overall survival of osteosarcoma patients. In conclusion, our TMEM protein family gene-based signature is a novel and clinically useful prognostic biomarker for osteosarcoma patients, and TMEM9B might be a potential therapeutic target in osteosarcoma.

TMEM16A as a potential treatment target for head and neck cancer

Transmembrane protein 16A (TMEM16A) forms a plasma membrane-localized Ca²⁺-activated Cl- channel. Its gene has been mapped to an area on chromosome 11q13, which is amplified in head and neck squamous cell carcinoma (HNSCC). In HNSCC, TMEM16A overexpression is associated with not only high tumor grade, metastasis, low survival, and poor prognosis, but also deterioration of clinical outcomes following platinum-based chemotherapy. Recent study revealed the interaction between TMEM16A and transforming growth factor-β (TGF-β) has an indirect crosstalk in clarifying the mechanism of TMEM16A-induced epithelial-mesenchymal transition. Moreover, human papillomavirus (HPV) infection can modulate TMEM16A expression along with epidermal growth factor receptor (EGFR), whose phosphorylation has been reported as a potential co-biomarker of HPV-positive cancers. Considering that EGFR forms a functional complex with TMEM16A and is a co-biomarker of HPV, there may be crosstalk between TMEM16A expression and HPV-induced HNSCC. EGFR activation can induce programmed death ligand 1 (PD-L1) synthesis via activation of the nuclear factor kappa B pathway and JAK/STAT3 pathway. Here, we describe an interplay among EGFR, PD-L1, and TMEM16A. Combination therapy using TMEM16A and PD-L1 inhibitors may improve the survival rate of HNSCC patients, especially those resistant to anti-EGFR inhibitor treatment. To the best of our knowledge, this is the first review to propose a biological validation that combines immune checkpoint inhibition with TMEM16A inhibition.

Identification of Potential mRNA Biomarkers in Milk Small Extracellular Vesicles of Enzootic Bovine Leukosis Cattle

Enzootic bovine leukosis (EBL) is a disease caused by bovine leukemia virus (BLV); only a small percentage of BLV-infected cattle develop EBL and present with B-cell lymphosarcoma. There is no vaccine against BLV, treatment for EBL, or method for predicting the possibility of EBL onset, thus making EBL control difficult. Herein, to explore biomarkers for EBL in milk, we examined the mRNA profiles of small extracellular vesicles (sEVs) in milk from four BLV-uninfected and four EBL cattle by microarray analysis. It was revealed that 14 mRNAs were encapsulated in significantly higher quantities, and these mRNAs were therefore selected as biomarker candidates. Primers for these mRNAs were designed, and nine primer sets were available for quantitative real-time PCR. Nine mRNAs were evaluated for their availability as biomarkers for EBL using sEVs from newly-collected milk of 7 uninfected and 10 EBL cattle. The quantities of eight mRNAs (TMEM156, SRGN, CXCL8, DEFB4A, FABP5, LAPTM5, LGALS1, and VIM) were significantly higher in milk sEVs of EBL cattle than in those of uninfected cattle. Therefore, our findings indicate that these eight mRNAs in milk sEVs can be used as potential EBL biomarkers with combination use, although single mRNA use is not enough. Consequently, cattle at risk of EBL onset can be identified by monitoring the fluctuation in quantities of these mRNAs in milk before they develop EBL.

Decoding the Mechanism of Shen Qi Sha Bai Decoction in Treating Acute Myeloid Leukemia Based on Network Pharmacology and Molecular Docking

Traditional Chinese Medicine (TCM) has been shown to be efficacious in treating leukemia for thousands of years. It has been shown that Shen Qi Sha Bai Decoction (SQSBD) has been extensively used in the treatment of acute myeloid leukemia (AML). However, the mechanism of SQSBD in treating AML remains unclear. In this study, we employed network pharmacology to analyze the potential active components and elucidate molecular mechanism of SQSBD in treating AML. A total of 268 active components were identified from SQSBD, among which 9 key components (Quercetin, luteolin, kaempferol, licochalcone A, formononetin, wogonin, β-sitosterol, oroxylin A, naringenin, and baicalein) were hit by the 6 hub targets (CDK1, MAPK1, JUN, PCNA, HSB1, STAT3) associated with leukemia. Molecular docking showed that two core active components, quercetin and licochalcone A, exhibited the highest component-like properties (DL), and could bind well to CDK1 and MAPK1 protein. The experimental validation of these two components showed that quercetin inhibited cell growth through CDK1 dephosphorylation-mediated cell cycle arrest at G2/M phase in human AML U937 and HL60 cells, and licochalcone A induced cell differentiation in these leukemia cells via activation of MAPK1 and upregulation of CD11b. All these results indicate that SQSBD is effective in the treatment of AML, and quercetin and licochalcone A are the major candidate compounds for AML treatment.