Identification of SEC61G as a Novel Prognostic Marker for Predicting Survival and Response to Therapies in Patients with Glioblastoma

Identification of SEC61G as a Diagnostic and Prognostic Biomarker in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is a heterogeneous malignancy originating from the oral mucosal epithelium. Detecting novel biomarkers can offer crucial information on disease aggressiveness and expected clinical outcomes for individual patients. SEC61G, an aberrantly expressed gene in various cancers, has been associated with negative clinical outcomes. However, its expression and clinical significance in OSCC is still unclear. In the present study, we investigated the SEC61G expression level in OSCC using bioinformatic and immunohistochemical analyses. Additionally, our findings revealed a significant correlation between SEC61G expression and clinicopathological characteristics, as well as a worse prognosis in OSCC patients. Notably, flow cytometry analysis on patient samples revealed that SEC61G expression was also linked to decreased immune infiltration in OSCC patients. In conclusion, our study provides evidence supporting SEC61G's role as a potential diagnostic, prognostic, and therapeutic marker in OSCC.

SEC61G assists EGFR-amplified glioblastoma to evade immune elimination

Amplification of chromosome 7p11 (7p11) is the most common alteration in primary glioblastoma (GBM), resulting in gains of epidermal growth factor receptor (EGFR) copy number in 50 to 60% of GBM tumors. However, treatment strategies targeting EGFR have thus far failed in clinical trials, and the underlying mechanism remains largely unclear. We here demonstrate that EGFR amplification at the 7p11 locus frequently encompasses its neighboring genes and identifies SEC61G as a critical regulator facilitating GBM immune evasion and tumor growth. We found that SEC61G is always coamplified with EGFR and is highly expressed in GBM. As an essential subunit of the SEC61 translocon complex, SEC61G promotes translocation of newly translated immune checkpoint ligands (ICLs, including PD-L1, PVR, and PD-L2) into the endoplasmic reticulum and promotes their glycosylation, stabilization, and membrane presentation. Depletion of SEC61G promotes the infiltration and cytolytic activity of CD8+ T cells and thus inhibits GBM occurrence. Further, SEC61G inhibition augments the therapeutic efficiency of EGFR tyrosine kinase inhibitors in mice. Our study demonstrates a critical role of SEC61G in GBM immune evasion, which provides a compelling rationale for combination therapy of EGFR-amplified GBMs.

Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers

Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDKN3, ARHGEF10, CLN8, SEC61G and PTDSS1 genes. The literature search reveals that the identified biomarkers are associated with the same or different types of cancers. Our method does not only identify known cancer-specific biomarker genes, but also proposes new potential biomarkers. Thus, this study provides a rationale for identifying new gene targets and expanding treatment options across cancer types.

Sec61γ is a vital protein in the endoplasmic reticulum membrane promoting tumor metastasis and invasion in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors worldwide. Finding effective prognostic markers and therapeutic targets is of great significance for controlling metastasis and invasion clinically.

METHODS

The open copy-number aberrations and gene expression datasets were analysed, and the data of 102 LUAD patients was used for further validation. The cell proliferation, colony formation, migration, invasion assays and mice tumor models were used to detect the function of SEC61G. The epidermal growth factor receptor (EGFR) pathway was also detected to find the mechanism of Sec61γ.

RESULTS

Based on the open datasets, we found that the high level of SEC61G mRNA may drive LUAD metastasis. Furthermore, the overexpression of Sec61γ protein was significantly associated with poor prognosis and greater tumor cell proliferation and metastasis. The SEC61G knockdown could inhibit the EGFR pathway, including STAT3, AKT and PI3K, which can be reversed by Sec61γ overexpression and epithelial growth factor (EGF) supplement.

CONCLUSIONS

Sec61γ promoted the proliferation, metastasis, and invasion of LUAD through EGFR pathways. Sec61γ might be a potential target for the treatment of LUAD metastases.

Effect of the 3q26-coding oncogene SEC62 as a potential prognostic marker in patients with ovarian neoplasia

With approximately 220,000 newly diagnosed cases per year, ovarian cancer is among the most frequently occurring cancers among women and the second leading cause of death from gynecological malignancies worldwide. About 70% of these cancers are diagnosed in advanced stages (FIGO IIB-IV), with a 5-year survival rate of 20-30%. Due to the poor prognosis of this disease, research has focused on its pathogenesis and the identification of prognostic factors. One possible approach for the identification of biological markers is the identification of tumor entity-specific genetic "driver mutations". One such mutation is 3q26 amplification in the tumor driver SEC62, which has been identified as relevant to the pathogenesis of ovarian cancer. This study was conducted to investigate the role of SEC62 in ovarian malignancies. Patients with ovarian neoplasias (borderline tumors of the ovary and ovarian cancer) who were treated between January 2007 and April 2019 at the Department of Gynecology and Obstetrics, Saarland University Hospital, were included in this retrospective study. SEC62 expression in tumor tissue samples taken during clinical treatment was assessed immunohistochemically, with the calculation of immunoreactivity scores according to Remmele and Stegner, Pathologe, 1987, 8, 138-140. Correlations of SEC62 expression with the TNM stage, histological subtype, tumor entity, and oncological outcomes (progression-free and overall survival) were examined. The sample comprised 167 patients (123 with ovarian cancer and 44 with borderline tumors of the ovary) with a median age of 60 (range, 15-87) years. At the time of diagnosis, 77 (46%) cases were FIGO stage III. All tissue slides showed SEC62 overexpression in tumor cells and no SEC62 expression in other cells. Median immunoreactivity scores were 8 (range, 2-12) for ovarian cancer and 9 (range, 4-12) for borderline tumors of the ovary. Patients with borderline tumors of the ovary as well as patients with ovarian cancer and an immunoreactive score (IRS) ≤ 9 showed an improved overall survival compared to those presenting with an IRS score >9 (p = 0.03). SEC62 seems to be a prognostic biomarker for the overall survival of patients with ovarian malignancies.

T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma

Despite the recent increase in the use of immune checkpoint blockade (ICB), no ICB medications have been approved or are undergoing large-scale clinical trials for glioma. T cells, the main mediators of adaptive immunity, are important components of the tumor immune microenvironment. Depletion of T cells in tumors plays a key role in assessing the sensitivity of patients to immunotherapy. In this study, the bioinformatics approach was applied to construct T cell depletion-related risk assessment to investigate the impact of T cell depletion on prognosis and ICB response in glioma patients. The Cancer Genome Atlas (TCGA) and GSE108474 glioma cohorts and IMvigor210 immunotherapy datasets were collected, including complete mRNA expression profiles and clinical information. We used cell lines to verify the gene expression and the R 3.6.3 tool and GraphPad for bioinformatics analysis and mapping. T cell depletion in glioma patients displayed significant heterogeneity. The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma. The overall survival of patients with a high TEXScore was significantly lower than that of patients with a low TEXScore. In addition, high TEXScore scores were followed by intense immune responses and a more complex tumor immune microenvironment. The “hot tumors” were predominantly enriched in the high-risk group, which patients expressed high levels of suppressive immune checkpoints, such as PD1, PD-L1, and TIM3. However, patients with a low TEXScore had a more significant clinical response to immunotherapy. In addition, HSPB1 expression was higher in the U251 cells than in the normal HEB cells. In conclusion, the TEXScore related to T cell exhaustion combined with other pathological profiles can effectively assess the clinical status of glioma patients. The TEXScore constructed in this study enables the effective assessment of the immunotherapy response of glioma patients and provides therapeutic possibilities.

NXPH4 Used as a New Prognostic and Immunotherapeutic Marker for Muscle-Invasive Bladder Cancer

Background

One of the most common malignant tumors of the urinary system is muscle-invasive bladder cancer (MIBC). With the increased use of immunotherapy, its importance in the field of cancer is becoming abundantly evident. This study classifies MIBC according to GSVA score from the perspective of the GSEA immune gene set.

Methods

This study integrated the sequencing and clinical data of MIBC patients in TCGA and GEO databases, then scored the data using the GSVA algorithm, the CNMF algorithm was implemented to divide the subtypes of GEO and TCGA datasets, respectively, and finally screened and determined the key pathways in combination with clinical data. Simultaneously, LASSO Cox regression model was constructed based on key pathway genes to assess the model's predictive ability (ROC) and describe the immune landscape differences between high- and low-risk groups; key genes were further analyzed and verified in patient tissues.

Results

404 TCGA and 297 GEO datasets were divided into C1-3 groups (TCGA-C1:120/C2:152/C3:132; GEO- C1:112/C2:101/C3:84), of which TCGA-C2 (n = 152) subtype and GEO-C1 (n = 112) subtype had the worst prognosis. LASSO Cox regression model with ROC (train set = 0.718, test set = 0.667) could be constructed. When combined with the Cancer Immunome Atlas database, it was found that patients with high-risk scores were more sensitive to PD-1 inhibitor and PD-1 inhibitor combined with CTLA-4. NXPH4, as a key gene, plays a role in MIBC with tissue validation results show that nxph4 is highly expressed in tumor.

Conclusion

The immune gene score of MIBC data in TCGA and GEO databases was successfully evaluated using GSVA in this research. The lasso Cox expression model was successfully constructed by screening immune genes, the high-risk group had a worse prognosis and higher sensitivity to immunotherapy, PD-1 inhibitors or PD-1 combined with CTLA-4 inhibitors can be preferentially used in high-risk patients who are sensitive to immunotherapy, and NXPH4 may be a molecular target to adjust the effect of immunotherapy.

The endoplasmic reticulum membrane protein Sec62 as potential therapeutic target in SEC62 overexpressing tumors

The human SEC62 gene is located on chromosome 3q, was characterized as a tumor driver gene and is found to be overexpressed in an ever-growing number of tumors, particularly those with 3q26 amplification. Where analyzed, SEC62 overexpression was associated with poor prognosis. Sec62 protein is a membrane protein of the endoplasmic reticulum (ER) and has functions in endoplasmic reticulum protein import, endoplasmic reticulum-phagy and -in cooperation with the cytosolic protein calmodulin- the maintenance of cellular calcium homeostasis. Various human tumors show SEC62 overexpression in immunohistochemistry and corresponding cell lines confirm this phenomenon in western blots and immunofluorescence. Furthermore, these tumor cells are characterized by increased stress tolerance and migratory as well as invasive potential, three hallmarks of cancer cells. Strikingly, plasmid-driven overexpression of SEC62 in non-SEC62 overexpressing cells introduces the same three hallmarks of cancer into the transfected cells. Depletion of Sec62 from either type of SEC62 overexpressing tumor cells by treatment with SEC62-targeting siRNAs leads to reduced stress tolerance and reduced migratory as well as invasive potential. Where tested, treatment of SEC62 overexpressing tumor cells with the small molecule/calmodulin antagonist trifluoperazine (TFP) phenocopied the effect of SEC62-targeting siRNAs. Recently, first phase II clinical trials with the prodrug mipsagargin/G202, which targets cellular calcium homeostasis in prostate cells as well as neovascular tissue in various tumors were started. According to experiments with tumor cell lines, however, SEC62 overexpressing tumor cells may be less responsive or resistant against such treatment. Therefore, murine tumor models for tumor growth or metastasis were evaluated with respect to their responsiveness to treatment with a mipsagargin analog (thapsigargin), or trifluoperazine, which had previously been in clinical use for the treatment of schizophrenia, or with the combination of both drugs. So far, no additive effect of the two drugs was observed but trifluoperazine had an inhibitory effect on tumor growth and metastatic potential in the models. Here, we review the state of affairs.

SEC61G Promotes Cervical Cancer Proliferation by Activating MAPK Signaling Pathway

Objective

The abnormal expression of SEC61G plays an important role in the development of various tumors. This study explored the effects of SEC61G on MAPK signaling pathway and proliferation of cervical cancer (CC) cells.

Methods

shRNA was used to inhibit the expression of SEC61G and EdU to observe its effect on the proliferation of CC cell SiHa. The effect of SEC61G on invasion was evaluated by Transwell assay. TCGA database was used to analyze the influence of high or low SEC61G expression level on the overall survival of CC patients. Western blot was used to detect the expressions of SEC61G, p-RAF1, Raf1, p-MEK1/2, MEK1/2, and p-ERK1/2 in cells. SiHa cells overexpressing SEC61G (SiHa-SEC61G) and control group (SiHa-mock) were subcutaneously implanted in nude mice. The tumor growth curve was measured at the specified time points between SiHa-SEC61G and SiHa-mock. The inhibitory effect of gefitinib on SEC61G was further evaluated.

Results

In patients with CC, high SEC61G expression predicted poor prognosis. Silencing SEC61G inhibited proliferation and invasion of CC cells in vitro. Overexpression of SEC61G can promote the proliferation and invasion of CC cells in vitro. Meanwhile, overexpression of SEC61G promoted the proliferation of CC xenografts. Knocking down SEC61G can inhibit MAPK signaling pathway. Gefitinib can inhibit CC proliferation and tumor growth by SEC61G.

Conclusion

SEC61G is highly expressed in CC and has poor prognosis. Inhibition of SEC61G expression can effectively inhibit the growth and proliferation of human CC cells. The mechanism may be related to the inhibition of MAPK signaling pathway.

Differences in the Expression Patterns of TGFβ Isoforms and Associated Genes in Astrocytic Brain Tumors

Genes associated with the TGFβ isoforms are involved in a number of different cancers, and their effect on the progression of brain tumors is also being discussed. Using an oligonucleotide microarray method, we assessed differences in expression patterns of genes in astrocytic brain tumor sections from 43 patients at different stages of disease. Quantitative mRNA assessment of the three TGFβ isoforms was also performed by real-time RT-qPCR. Oligonucleotide microarray data were analyzed using the PL-Grid Infrastructure. The microarray analysis showed a statistically significant (p < 0.05) increase in TGFβ1 and TGFβ2 expression in G3/G4 stage relative to G2, whereas real-time RT-qPCR validation confirmed this change only for the TGFβ2 isoform (p < 0.05). The oligonucleotide microarray method allowed the identification of 16 differential genes associated with TGFβ isoforms. Analysis of the STRING database showed that the proteins encoded by the analyzed genes form a strong interaction network (p < 0.001), and a significant number of proteins are involved in carcinogenesis. Differences in expression patterns of transcripts associated with TGFβ isoforms confirm that they play a role in astrocytic brain tumor transformation. Quantitative assessment of TGFβ2 mRNA may be a valuable method to complement the diagnostic process in the future.

Current Understanding of Exosomal MicroRNAs in Glioma Immune Regulation and Therapeutic Responses

Exosomes, the small extracellular vesicles, are released by multiple cell types, including tumor cells, and represent a novel avenue for intercellular communication via transferring diverse biomolecules. Recently, microRNAs (miRNAs) were demonstrated to be enclosed in exosomes and therefore was protected from degradation. Such exosomal miRNAs can be transmitted to recipient cells where they could regulate multiple cancer-associated biological processes. Accumulative evidence suggests that exosomal miRNAs serve essential roles in modifying the glioma immune microenvironment and potentially affecting the malignant behaviors and therapeutic responses. As exosomal miRNAs are detectable in almost all kinds of biofluids and correlated with clinicopathological characteristics of glioma, they might be served as promising biomarkers for gliomas. We reviewed the novel findings regarding the biological functions of exosomal miRNAs during glioma pathogenesis and immune regulation. Furthermore, we elaborated on their potential clinical applications as biomarkers in glioma diagnosis, prognosis and treatment response prediction. Finally, we summarized the accessible databases that can be employed for exosome-associated miRNAs identification and functional exploration of cancers, including glioma.

Role of Calcium Signaling Pathway-Related Gene Regulatory Networks in Ischemic Stroke Based on Multiple WGCNA and Single-Cell Analysis

Background

This study is aimed at investigating the changes in relevant pathways and the differential expression of related gene expression after ischemic stroke (IS) at the single-cell level using multiple weighted gene coexpression network analysis (WGCNA) and single-cell analysis.

Methods

The transcriptome expression datasets of IS samples and single-cell RNA sequencing (scRNA-seq) profiles of cerebrovascular tissues were obtained by searching the Gene Expression Omnibus (GEO) database. First, gene pathway scoring was calculated via gene set variation analysis (GSVA) and was imported into multiple WGCNA to acquire key pathways and pathway-related hub genes. Furthermore, SCENIC was used to identify transcription factors (TFs) regulating these core genes using scRNA-seq data. Finally, the pseudotemporal trajectory analysis was used to analyse the role of these TFs on various cell types under hypoxic and normoxic conditions.

Results

The scores of 186 KEGG pathways were obtained via GSVA using microarray expression profiles of 40 specimens. WGCNA of the KEGG pathways revealed the two following pathways: calcium signaling pathway and neuroactive ligand-receptor interaction pathways. Subsequently, WGCNA of the gene expression matrix of the samples revealed the calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) that were identified as core genes via correlation analysis. Furthermore, SCENIC and pseudotemporal analysis revealed JUN, IRF9, ETV5, and PPARA score gene-related TFs. Jun was found to be associated with hypoxia in endothelial cells, whereas Irf9 and Etv5 were identified as astrocyte-specific TFs associated with oxygen concentration in the mouse cerebral cortex.

Conclusions

Calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) and TFs (JUN, IRF9, ETV5, and PPARA) were identified to play a key role in IS. This study provides a new perspective and basis for investigating the pathogenesis of IS and developing new therapeutic approaches.

A Novel Gene Prognostic Signature Based on Differential DNA Methylation in Breast Cancer

Background: DNA methylation played essential roles in regulating gene expression. The impact of DNA methylation status on the occurrence and development of cancers has been well demonstrated. However, little is known about its prognostic role in breast cancer (BC).

Materials: The Illumina Human Methylation450 array (450k array) data of BC was downloaded from the UCSC xena database. Transcriptomic data of BC was downloaded from the Cancer Genome Atlas (TCGA) database. Firstly, we used univariate and multivariate Cox regression analysis to screen out independent prognostic CpGs, and then we identified methylation-associated prognosis subgroups by consensus clustering. Next, a methylation prognostic model was developed using multivariate Cox analysis and was validated with the Illumina Human Methylation27 array (27k array) dataset of BC. We then screened out differentially expressed genes (DEGs) between methylation high-risk and low-risk groups and constructed a methylation-based gene prognostic signature. Further, we validated the gene signature with three subgroups of the TCGA-BRCA dataset and an external dataset GSE146558 from the Gene Expression Omnibus (GEO) database.

Results: We established a methylation prognostic signature and a methylation-based gene prognostic signature, and there was a close positive correlation between them. The gene prognostic signature involved six genes: IRF2, KCNJ11, ZDHHC9, LRP11, PCMT1, and TMEM70. We verified their expression in mRNA and protein levels in BC. Both methylation and methylation-based gene prognostic signatures showed good prognostic stratification ability. The AUC values of 3-years, 5-years overall survival (OS) were 0.737, 0.744 in the methylation signature and 0.725, 0.715 in the gene signature, respectively. In the validation groups, high-risk patients were confirmed to have poorer OS. The AUC values of 3 years were 0.757, 0.735, 0.733 in the three subgroups of TCGA dataset and 0.635 in GSE146558 dataset.

Conclusion: This study revealed the DNA methylation landscape and established promising methylation and methylation-based gene prognostic signatures that could serve as potential prognostic biomarkers and therapeutic targets.

Prognostic value of SEC61G in lung adenocarcinoma: a comprehensive study based on bioinformatics and in vitro validation

BACKGROUND

Studies have shown that the Sec61 gamma subunit (SEC61G) is overexpressed in several tumors and could serve as a potential prognostic marker. However, the correlation between SEC61G and lung adenocarcinoma (LUAD) remains unclear. In the current study, we aimed to demonstrate the prognostic value and potential biological function of the SEC61G gene in LUAD.

METHODS

Public datasets were used for SEC61G expression analyses. The prognostic value of SEC61G in LUAD was investigated using the Kaplan-Meier survival and Cox analyses. The correlation between the methylation level of SEC61G and its mRNA expression was evaluated via cBioPortal. Additionally, MethSurv was used to determine the prognostic value of the SEC61G methylation levels in LUAD. Functional enrichment analysis was conducted to explore the potential mechanism of SEC61G. Also, single sample GSEA (ssGSEA) and TIMER online tool were applied to identify the correlation between SEC61G and immune filtration. Furthermore, cell functional experiments were conducted to verify the biological behavior of SEC61G in lung adenocarcinoma cells (LAC).

RESULTS

SEC61G was upregulated in pan-cancers, including LUAD. High SEC61G expression was significantly correlated with worse prognosis in LUAD patients. Multivariate analysis demonstrated that high SEC61G expression was an independent prognostic factor in the TCGA cohort. (HR = 1.760 95% CI: 1.297-2.388, p < 0.001). The methylation level of SEC61G negatively correlated with the SEC61G expression (R = - 0.290, p < 0.001), and patients with low SEC61G methylation had worse overall survival. (p = 0.0014). Proliferation-associated terms such as cell cycle and cell division were significantly enriched in GO and KEGG analysis. Vitro experiments demonstrated that knockdown of SEC61G resulted in decreased cell proliferation, invasion and facilitated apoptosis in LAC. GSEA analysis found that SEC61G expression was associated with the E2F targets. Moreover, SEC61G expression was negatively correlated with the immune cell infiltration including CD4+ T cell, CD8+ T cell, B cell, macrophage, neutrophil, and dendritic cell.

CONCLUSION

Our study indicated that overexpression of SEC61G was significantly associated with poor prognosis of LUAD patients and the malignant phenotypes of LUAD cells, suggesting that it could be a novel prognostic biomarker and potential therapeutic target of LUAD.

SEC61G overexpression and DNA amplification correlates with prognosis and immune cell infiltration in head and neck squamous cell carcinoma

Background

The SEC61 translocon gamma subunit (SEC61G) is a component of the SEC61 complex, which import protein into the endoplasmic reticulum. However, the correlation between SEC61G and disease prognosis in head and neck squamous cell carcinoma (HNSCC) remains unclear.

Methods

SEC61G expression was analyzed using publicly available datasets. The association between SEC61G and disease prognosis was evaluated. SEC61G methylation and copy number variation were investigated and gene set enrichment analysis and gene ontology analyses identified SEC61G‐associated functions. We also investigated the correlation between SEC61G and immune cell infiltration. Finally, immunohistochemistry was used to detect SEC61G expression in oropharyngeal carcinoma.

Results

SEC61G was overexpressed in pan‐cancers, including HNSCC, and negatively correlated with overall survival (OS) (p < 0.001 for TCGA‐HNSCC and p = 0.019 for GSE65858). Moreover, SEC61G was an independent prognostic factor for OS in TCGA and GSE65858 [hazard ratio (HR) = 1.80, 95% CI: 1.35–2.39, p < 0.001; HR = 1.87, 95% CI: 1.14–3.07, p = 0.013, respectively). SEC61G DNA amplification (9.66% of patients) was significantly associated with poor OS (p = 0.034). SEC61G overexpression and DNA amplification negatively correlated with B cell (p < 0.001), CD8⁺ T cell (p < 0.001), CD4⁺ T cell (p < 0.001), macrophage (p < 0.05), neutrophil (p < 0.001), and dendritic cell infiltration (p < 0.001). Among patients with metastatic urothelial cancer received atezolizumab, patients with high SEC61G expression had an inferior OS (p = 0.006). Furthermore, SEC61G protein expression was also an independent prognostic factor of OS (HR = 2.46, 95% CI: 1.15–5.28, p = 0.021) and progression‐free survival (HR = 2.82, 95% CI: 1.36–5.85, p = 0.005) for oropharyngeal cancer.

Conclusions

SEC61G is overexpressed in HNSCC and is an independent prognostic factor for OS. SEC61G DNA amplification contributes to overexpression and poor outcome. Interestingly, SEC61G correlates with immune cell infiltration in HNSCC. These findings suggest that SEC61G is a potential broad‐spectrum biomarker for prognosis in HNSCC.

MOUSSE: Multi-Omics Using Subject-Specific SignaturEs

Simple Summary

Modern profiling technologies have led to relevant progress toward precision medicine and disease management. A new trend in patient classification is to integrate multiple data types for the same subjects to increase the chance of identifying meaningful phenotype groups. However, these methodologies are still in their infancy, with their performance varying widely depending on the biological conditions analyzed. We developed MOUSSE, a new unsupervised and normalization-free tool for multi-omics integration able to maintain good clustering performance across a wide range of omics data. We verified its efficiency in clustering patients based on survival for ten different cancer types. The results we obtained show a higher average score in classification performance than ten other state-of-the-art algorithms. We have further validated the method by identifying a list of biological features potentially involved in patient survival, finding a high degree of concordance with the literature.

Abstract

High-throughput technologies make it possible to produce a large amount of data representing different biological layers, examples of which are genomics, proteomics, metabolomics and transcriptomics. Omics data have been individually investigated to understand the molecular bases of various diseases, but this may not be sufficient to fully capture the molecular mechanisms and the multilayer regulatory processes underlying complex diseases, especially cancer. To overcome this problem, several multi-omics integration methods have been introduced but a commonly agreed standard of analysis is still lacking. In this paper, we present MOUSSE, a novel normalization-free pipeline for unsupervised multi-omics integration. The main innovations are the use of rank-based subject-specific signatures and the use of such signatures to derive subject similarity networks. A separate similarity network was derived for each omics, and the resulting networks were then carefully merged in a way that considered their informative content. We applied it to analyze survival in ten different types of cancer. We produced a meaningful clusterization of the subjects and obtained a higher average classification score than ten state-of-the-art algorithms tested on the same data. As further validation, we extracted from the subject-specific signatures a list of relevant features used for the clusterization and investigated their biological role in survival. We were able to verify that, according to the literature, these features are highly involved in cancer progression and differential survival.

SEC61G identified as a prognostic biomarker of head and neck squamous cell carcinoma

Purpose

It is of obvious interest to identify clinical prognosis-related oncogenes in HNSCC (head and neck squamous cell carcinoma).

Methods

Based on the available datasets within the TCGA (The Cancer Genome Atlas) and the GEO (Gene Expression Omnibus) databases, the potential mechanism of action of the SEC61G (SEC61 translocon subunit gamma) gene in HNSCC tumorigenesis was explored by several bioinformatics approaches.

Results

There was a higher expression level of SEC61G in primary HNSCC tumor tissues than in normal tissues. Moreover, highly expressed SEC61G was statistically associated with the poor survival prognosis of HNSCC patients. When HPV (human papilloma virus) was considered, we also observed a relatively lower proportion of “arm-level gain” and “high amplification” types of CNA (copy-number alteration) in the HNSCC-HPV (+) group than in the HNSCC-HPV (−) group. Additionally, we identified SEC61G CAN-correlated genes, such as CCT6A (chaperonin-containing TCP1 subunit 6A) and HUS1 (HUS1 checkpoint clamp component), and found a correlation between SEC61G copy-number segments and prognosis related to overall and progression-free survival intervals of HNSCC patients. Moreover, the molecular regulation mechanisms of the spliceosome, ribosome, proteasome degradation, cell adhesion, and immune infiltration of B and CD8⁺ T cells may contribute to the involvement of SEC61G in the pathogenesis of HNSCC.

Conclusions

The SEC61G gene was identified for the first time as a prognostic biomarker of HNSCC. The detailed underlying mechanism merits further research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00405-021-06955-7.

SEC61G promotes breast cancer development and metastasis via modulating glycolysis and is transcriptionally regulated by E2F1

Breast cancer is the most common cancer in women and its incidence rates are rapidly increasing in China. Understanding the molecular mechanisms of breast cancer tumorigenesis enables the development of novel therapeutic strategies. SEC61G is a subunit of the endoplasmic reticulum translocon that plays critical roles in various tumors. We aimed to investigate the expression and function of SEC61G in breast cancer. By analyzing The Cancer Genome Atlas breast cancer cohort, we found that SEC61G was highly expressed in breast cancer and predicted poor prognosis of breast cancer patients. Overexpression of SEC61G and its prognostic role was also confirmed in the Nanjing Medical University (NMU) breast cancer cohort. Functionally, we demonstrated that knockdown of SEC61G suppressed breast cancer cell proliferation, migration, invasion, and promoted breast cancer cell apoptosis in vitro. Xenograft breast tumor model revealed that knockdown of SEC61G inhibited breast tumor development in vivo. Furthermore, we demonstrated that SEC61G positively regulated glycolysis in breast cancer cells. Mechanistically, we showed that transcription factor E2F1 directly bound to the promoter of SEC61G and regulated its expression in breast cancer cells. SEC61G overexpression antagonized the effect of E2F1 knockdown in regulating breast cancer cell proliferation, invasion, and apoptosis. Finally, we demonstrated that the E2F1/SEC61G axis regulated glycolysis and chemo-sensitivity of Herceptin in breast cancer cells. Taken together, these results of in vitro and in vivo studies demonstrate that SEC61G promotes breast cancer development and metastasis via modulating glycolysis and is transcriptionally regulated by E2F1, which might be utilized as a promising therapeutic target of breast cancer treatment.

High SEC61G expression predicts poor prognosis in patients with Head and Neck Squamous Cell Carcinomas

Background: Overexpression of the membrane protein SEC61 translocon gamma subunit (SEC61G) has been observed in a variety of cancers; however, its role in head and neck squamous cell carcinomas (HNSCC) is unknown. This study aimed to elucidate the relationship between SEC61G and HNSCC based on data from The Cancer Genome Atlas (TCGA) database. Methods: Data for HNSCC patients were collected from TCGA and the expression level of SEC61G was compared between paired HNSCC and normal tissues using the Wilcoxon rank-sum test. The relationship between clinicopathologic features and SEC61G expression was also analyzed using the Wilcoxon rank-sum test and logistic regression. Receiver operating characteristic (ROC) curves were generated to evaluate the value of SEC61G as a binary classifier using the area under the curve (AUC value). The association of clinicopathologic characteristics with prognosis in HNSCC patients was assessed using Cox regression and the Kaplan-Meier methods. A nomogram, based on Cox multivariate analysis, was used to predict the impact of SEC61G on prognosis. Functional enrichment analysis was performed to determine the hallmark pathways associated with differentially expressed genes in HNSCC patients exhibiting high and low SEC61G expression. Results: The expression of SEC61G was significantly elevated in HNSCC tissues compared to normal tissues (P < 0.001). The high expression of SEC61G was significantly correlated with the T stage, M stage, clinical stage, TP53 mutation status, PIK3CA mutation status, primary therapy outcome, and cervical lymph node dissection (all P < 0.05). Meanwhile, ROC curves suggested the significant diagnostic ability of SEC61G for HNSCC (AUC = 0.923). Kaplan-Meier survival analysis showed that patients with HNSCC characterized by high SEC61G expression had a poorer prognosis than patients with low SEC61G expression (hazard ratio = 1.95, 95% confidence interval 1.48-2.56, P < 0.001). Univariate and multivariate analyses revealed that SEC61G was independently associated with overall survival (P = 0.027). Functional annotations indicated that SEC61G is involved in pathways related to translation and regulation of SLITs/ROBOs expression, SRP-dependent co-translational protein targeting to the membrane, nonsense-mediated decay, oxidative phosphorylation, and Parkinson's disease. Conclusion: SEC61G plays a vital role in HNSCC progression and prognosis; it may, therefore, serve as an effective biomarker for the prediction of patient survival.

Complexity and Specificity of Sec61-Channelopathies: Human Diseases Affecting Gating of the Sec61 Complex

The rough endoplasmic reticulum (ER) of nucleated human cells has crucial functions in protein biogenesis, calcium (Ca2+) homeostasis, and signal transduction. Among the roughly one hundred components, which are involved in protein import and protein folding or assembly, two components stand out: The Sec61 complex and BiP. The Sec61 complex in the ER membrane represents the major entry point for precursor polypeptides into the membrane or lumen of the ER and provides a conduit for Ca2+ ions from the ER lumen to the cytosol. The second component, the Hsp70-type molecular chaperone immunoglobulin heavy chain binding protein, short BiP, plays central roles in protein folding and assembly (hence its name), protein import, cellular Ca2+ homeostasis, and various intracellular signal transduction pathways. For the purpose of this review, we focus on these two components, their relevant allosteric effectors and on the question of how their respective functional cycles are linked in order to reconcile the apparently contradictory features of the ER membrane, selective permeability for precursor polypeptides, and impermeability for Ca2+. The key issues are that the Sec61 complex exists in two conformations: An open and a closed state that are in a dynamic equilibrium with each other, and that BiP contributes to its gating in both directions in cooperation with different co-chaperones. While the open Sec61 complex forms an aqueous polypeptide-conducting- and transiently Ca2+-permeable channel, the closed complex is impermeable even to Ca2+. Therefore, we discuss the human hereditary and tumor diseases that are linked to Sec61 channel gating, termed Sec61-channelopathies, as disturbances of selective polypeptide-impermeability and/or aberrant Ca2+-permeability.

The Role of Network Science in Glioblastoma

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.

Digital microfluidic isolation of single cells for -Omics

We introduce Digital microfluidic Isolation of Single Cells for -Omics (DISCO), a platform that allows users to select particular cells of interest from a limited initial sample size and connects single-cell sequencing data to their immunofluorescence-based phenotypes. Specifically, DISCO combines digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to collect the contents of single cells from heterogeneous populations, followed by analysis of single-cell genomes and transcriptomes by next-generation sequencing, and proteomes by nanoflow liquid chromatography and tandem mass spectrometry. The results described herein confirm the utility of DISCO for sequencing at levels that are equivalent to or enhanced relative to the state of the art, capable of identifying features at the level of single nucleotide variations. The unique levels of selectivity, context, and accountability of DISCO suggest potential utility for deep analysis of any rare cell population with contextual dependencies.

Multi-Omic approaches are a powerful way for obtaining in-depth understanding of a cell’s state. Here the authors present DISCO, combining digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to analyze single-cell genomes, transcriptomes and proteomes in a mixed population.

SEC61G plays an oncogenic role in hepatocellular carcinoma cells

Hepatocellular carcinoma (HCC) is one of the most aggressive malignant diseases and requires more effective prevention and treatment strategies. Mutations or overexpression of endoplasmic reticulum (ER) proteins have been frequently identified in a solid tumor, suggesting that ER proteins play an important role in tumor development. SEC61G, a component of Sec61 complex located in the membrane of the human ER, has been revealed a potential relevance in glioblastoma multiforme. Analyses from TCGA database showed that SEC61G was overexpressed in HCC. Additionally, the expression of SEC61G mRNA was associated with the survival time of HCC patients. We verified that the higher expression of SEC61G in HCC tissues than paracancerous tissues. Moreover, knockdown of SEC61G inhibited cell proliferation and induced cell apoptosis in vitro. Besides, SEC61G was required for cell migration and invasion, conferring a potential role for SEC61G in tumor transfer. Taken together, our results revealed the role of SEC61G in HCC cells. Further detailed understanding of the signaling networks underlying SEC61G involvement in HCC cells would make SEC61G as a viable therapeutic target for pharmaceutical intervention of HCC.

Establishing and validating a pathway prognostic signature in pancreatic cancer based on miRNA and mRNA sets using GSVA

Pancreatic cancer (PC) is a severe disease with the highest mortality rate among various cancers. It is urgent to find an effective and accurate way to predict the survival of PC patients. Gene set variation analysis (GSVA) was used to establish and validate a miRNA set-based pathway prognostic signature for PC (miPPSPC) and a mRNA set-based pathway prognostic signature for PC (mPPSPC) in independent datasets. An optimized miPPSPC was constructed by combining clinical parameters. The miPPSPC, optimized miPPSPC and mPPSPC were established and validated to predict the survival of PC patients and showed excellent predictive ability. Four metabolic pathways and one oxidative stress pathway were identified in the miPPSPC, whereas linoleic acid metabolism and the pentose phosphate pathway were identified in the mPPSPC. Key factors of the pentose phosphate pathway and linoleic acid metabolism, G6PD and CYP2C8/9/18/19, respectively, are related to the survival of PC patients according to our tissue microarray. Thus, the miPPSPC, optimized miPPSPC and mPPSPC can predict the survival of PC patients efficiently and precisely. The metabolic and oxidative stress pathways may participate in PC progression.

Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC

Background: Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC.

Methods: Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5′-C-phosphate-G- 3′ (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes.

Results: Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (CETN3, DCAF7, GPX4, HNRNPA0, NUP54, SERPINB1, STARD5, TRIM52, C4orf3, C12orf51, and C17orf65) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients.

Conclusion: Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.

Dietary Erythrodiol Modifies Hepatic Transcriptome in Mice in a Sex and Dose-Dependent Way

Erythrodiol is a terpenic compound found in a large number of plants. To test the hypotheses that its long-term administration may influence hepatic transcriptome and this could be influenced by the presence of APOA1-containing high-density lipoproteins (HDL), Western diets containing 0.01% of erythrodiol (10 mg/kg dose) were provided to Apoe- and Apoa1-deficient mice. Hepatic RNA-sequencing was carried out in male Apoe-deficient mice fed purified Western diets differing in the erythrodiol content. The administration of this compound significantly up- regulated 68 and down-regulated 124 genes at the level of 2-fold change. These genes belonged to detoxification processes, protein metabolism and nucleic acid related metabolites. Gene expression changes of 21 selected transcripts were verified by RT-qPCR. Ccl19-ps2, Cyp2b10, Rbm14-rbm4, Sec61g, Tmem81, Prtn3, Amy2a5, Cyp2b9 and Mup1 showed significant changes by erythrodiol administration. When Cyp2b10, Dmbt1, Cyp2b13, Prtn3 and Cyp2b9 were analyzed in female Apoe-deficient mice, no change was observed. Likewise, no significant variation was observed in Apoa1- or in Apoe-deficient mice receiving doses ranging from 0.5 to 5 mg/kg erythrodiol. Our results give evidence that erythrodiol exerts a hepatic transcriptional role, but this is selective in terms of sex and requires a threshold dose. Furthermore, it requires an APOA1-containing HDL.

Preoperative Neutrophil/Lymphocyte Ratio Is an Independent Prognostic Biomarker in Patients with Low-Grade Gliomas

BACKGROUND

There are no standardized criteria to predict the prognosis of patients with low-grade gliomas. Therefore, novel prognostic biomarkers that can guide follow-up schedules and therapeutic approaches urgently are required in patients with low-grade gliomas.

METHODS

One hundred nineteen patients with World Health Organization (WHO) II gliomas were recruited between January 2010 and December 2016 from Xiangya Hospital for this study. We collected neutrophil and lymphocyte values from the full blood counts measured 24 h before surgery. Neutrophil-to-lymphocyte ratios (NLRs) were then calculated. The significance of the NLR was determined based on a nonparametric test. The Kaplan-Meier method was used to estimate survival rates. The influence of the NLR on progression-free survival and overall survival was evaluated using univariate and multivariate Cox proportional hazards models.

RESULTS

Preoperative NLRs were upregulated in patients with WHO II gliomas who relapsed or died. Preoperative NLRs were also significantly correlated with age, preoperative neutrophil values, and preoperative lymphocyte values. Compared with the low preoperative NLR group, patients with WHO II gliomas in the high preoperative NLR group had significantly higher relapse and lower survival rates. In addition, the preoperative NLR and tumor type were independent prognostic parameters of progression-free survival for WHO II gliomas, whereas only the preoperative NLR was an independent prognostic parameter of overall survival for WHO II gliomas.

CONCLUSIONS

High preoperative NLRs were significantly associated with greater relapse and poor prognosis in patients with WHO II gliomas.