ANO6 promotes cell proliferation and invasion in glioma through regulating the ERK signaling pathway

An immune-related exosome signature predicts the prognosis and immunotherapy response in ovarian cancer

BACKGROUND

Cancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived exosomes (IOCEs) subgroups in ovarian cancer (OC) and establish a prognostic model for OC patients based on immune-related IOCEs.

METHODS

The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq data, as well as clinical and prognostic information. Consensus clustering analysis was performed to identify two IOCEs-associated subgroups. Kaplan-Meier analysis was used to compare the overall survival (OS) between IOCEs-high and IOCEs-low subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the mechanisms and biological effects of differentially expressed genes (DEGs) between the two subtypes. Besides, an IOCE-related prognostic model of OC was constructed by Lasso regression analysis, and the signature was validated using GSE140082 as the validation set.

RESULTS

In total, we obtained 21 differentially expressed IOCEs in OC, and identified two IOCE-associated subgroups by consensus clustering. IOCE-low subgroup showed a favorable prognosis while IOCE-high subgroup had a higher level of immune cell infiltration and immune response. GSEA showed that pathways in cancer and immune response were mainly enriched in IOCE-high subgroup. Thus, IOCE-high subgroup may benefit more in immunotherapy treatment. In addition, we constructed a risk model based on nine IOCE-associated genes (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6).

CONCLUSION

We developed a novel stratification system for OV based on IOCE signature, which could be used to estimate the prognosis as well as immunotherapy for OC patient.

ANO6 is a reliable prognostic biomarker and correlates to macrophage polarization in breast cancer

To investigate the value of Anoctamin 6 (ANO6) in breast cancer (BC) by analyzing its expression, prognostic impact, biological function, and its association with immune characteristics. We initially performed the expression and survival analyses, followed by adopting restricted cubic spline to analyze the nonlinear relationship between ANO6 and overall survival (OS). Stratified and interaction analyses were conducted to further evaluate its prognostic value in BC. Next, we performed enrichment analyses to explore the possible pathways regulated by ANO6. Finally, the correlations between ANO6 and immune characteristics were analyzed to reveal its role in immunotherapy. Lower ANO6 expression was observed in BC than that in the normal breast group, but its overexpression independently predicted poor OS among BC patients (P < .05). Restricted cubic spline analysis revealed a linear relationship between ANO6 and OS (P-Nonlinear > 0.05). Interestingly, menopause status was an interactive factor in the correlation between ANO6 and OS (P for interaction = 0.016). Additionally, ANO6 was involved in stroma-associated pathways, and its elevation was significantly linked to high stroma scores and macrophage polarization (P < .05). Moreover, ANO6 was notably correlated with immune checkpoint expression levels, and scores of tumor mutation burden and microsatellite instability (all P < .05). ANO6 was an independent prognostic factor for BC, and might be a potential target for the BC treatment. Besides, ANO6 might affect BC progression via the regulation of stroma-related pathways and macrophage polarization.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.

Analysis of a new therapeutic target and construction of a prognostic model for breast cancer based on ferroptosis genes

Breast cancer, which is the most common malignant tumor among women worldwide and an important cause of death in women. The existing prognostic model for patients with breast cancer is not accurate as breast cancer is resistant to commonly used antitumor drugs. Ferroptosis is a novel mechanism of programmed cell death that depends on iron accumulation and lipid peroxidation. Various studies have confirmed the role of ferroptosis in tumor regulation and ferroptosis is now considered to play an important role in breast cancer development. At present, the association between breast cancer prognosis and ferroptosis-related gene expression remains unclear. Further exploration of this research area may optimize the evaluation and prediction of prognosis of patients with breast cancer and finding of new therapeutic targets. In this study, clinical factors and the expression of multiple genes were evaluated in breast cancer samples from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database database. Eleven prognostication-related genes (TP63, IFNG, MT3, ANO6, FLT3, PTGS2, SLC1A4, JUN, SLC7A5, CHAC1, and TF) were identified from differentially expressed genes to construct a survival prediction model, which showed a good prediction ability. KEGG pathway analysis revealed that immune-related pathways were the primary pathways. ssGSEA analysis showed significant differences in the distribution of certain immune-related cell subsets, such as CD8+T cells and B cells, and in the expression of multiple immune genes, including type II IFN response and APC coinhibition. In addition, 10 immune targets related to ferroptosis in breast cancer were found: CD276, CD80, HHLA2, LILRA2, NCR3LG1, NECTIN3, PVR, SLAMF9,TNFSF4, and BTN1A1. Using TCGA, new ferroptosis genes related to breast cancer prognosis were identified, a new reliable and accurate prognosis model was developed, and 10 new potential therapeutic targets different from the traditional targeted drugs were identified to provide a reference for improving the poor prognosis of patients with breast cancer.

A novel immune score model predicting the prognosis and immunotherapy response of breast cancer

Breast cancer (BC) is one of the most common malignancies. However, the existing pathological grading system cannot accurately and effectively predict the survival rate and immune checkpoint treatment response of BC patients. In this study, based on The Cancer Genome Atlas (TCGA) database, a total of 7 immune-related genes (IRGs) were screened out to construct a prognostic model. Subsequently, the clinical prognosis, pathological characteristics, cancer-immunity cycle, tumour immune dysfunction and exclusion (TIDE) score, and immune checkpoint inhibitor (ICI) response were compared between the high- and low-risk groups. In addition, we determined the potential regulatory effect of NPR3 on BC cell proliferation, migration, and apoptosis. The model consisting of 7 IRGs was an independent prognostic factor. Patients with lower risk scores exhibited longer survival times. Moreover, the expression of NPR3 was increased but the expression of PD-1, PD-L1, and CTLA-4 was decreased in the high-risk group compared to the low-risk group. In addition, compared with si-NC, si-NPR3 suppressed proliferation and migration but promoted apoptosis in both MDA-MB-231 and MCF-7 cells. This study presents a model for predicting survival outcomes and provides a strategy to guide effective personalized immunotherapy in BC patients.

Anoctamins and Calcium Signalling: An Obstacle to EGFR Targeted Therapy in Glioblastoma?

Glioblastoma is the most common form of high-grade glioma in adults and has a poor survival rate with very limited treatment options. There have been no significant advancements in glioblastoma treatment in over 30 years. Epidermal growth factor receptor is upregulated in most glioblastoma tumours and, therefore, has been a drug target in recent targeted therapy clinical trials. However, while many inhibitors and antibodies for epidermal growth factor receptor have demonstrated promising anti-tumour effects in preclinical models, they have failed to improve outcomes for glioblastoma patients in clinical trials. This is likely due to the highly plastic nature of glioblastoma tumours, which results in therapeutic resistance. Ion channels are instrumental in the development of many cancers and may regulate cellular plasticity in glioblastoma. This review will explore the potential involvement of a class of calcium-activated chloride channels called anoctamins in brain cancer. We will also discuss the integrated role of calcium channels and anoctamins in regulating calcium-mediated signalling pathways, such as epidermal growth factor signalling, to promote brain cancer cell growth and migration.

Significance of Anoctamin 6 in progression and prognostic prediction of gastric adenocarcinoma

BACKGROUND

Gastric cancer is one of the most lethal malignancies worldwide with surgery as the only curative therapy. However, postoperative overall survival of gastric cancer is far from satisfactory although significant improvement has been made in adjuvant therapies. Gastric cancer is characterized as highly heterogeneous and illustrating the molecular mechanisms is invaluable for both identification of novel prognostic biomarkers and development of therapeutic drugs. Here we aimed to investigate the participation of Anoctamin 6 (ANO6) in gastric adenocarcinoma.

METHODS

Immunohistochemical (IHC) staining was used to explore the expression pattern of ANO6 in tumor tissues from gastric adenocarcinoma patients (n=108). Clinicopathological data was subjected to Kaplan-Meier survival and Cox multivariate analyses to evaluate prognostic predictors. Overexpression and silencing procedures were performed on gastric cancer cell lines to investigate the functional mechanisms of ANO6 in regulating tumor development.

RESULTS

Higher ANO6 expression showed a positive correlation with advanced tumor stage of gastric cancer. Univariate and multivariate analyses revealed that ANO6 was an independent prognostic factor for overall survival of gastric cancer. An in vitro study demonstrated that ANO6 can promote cell proliferation while silencing ANO6 significantly downregulated cell viability.

CONCLUSION

High ANO6 expression in gastric cancer indicates poor clinical outcomes, and ANO6 may act as a potential target for novel therapy development targeting gastric cancer.

Development of a Novel Immune-Related Gene Prognostic Index for Breast Cancer

Objective

To construct an immune-related gene prognostic index (IRGPI) for breast cancer (BC) and investigate its prognostic specificity and the molecular and immune characteristics.

Methods

BC hub genes were identified from The Cancer Genome Atlas and immune-related databases using weighted gene co-expression network analysis (WGCNA). IRGPI was constructed using univariate, LASSO, and multivariate regression analyses, and was validated with GSE58812 and GSE97342 in the Gene Expression Omnibus database (GEO). At the same time, we evaluated the predictive ability of IRGPI for different BC subtypes. Subsequently, the molecular and immune characteristics, clinical relevance, and benefits of immune checkpoint inhibitor treatment were analyzed for different IRGPI subgroups.

Results

IRGPI consisted of six genes: SOCS3, TCF7L2, TSLP NPR3, ANO6, and HMGB3. The IRGPI 1-, 5-, and 10-years area under curve (AUC) values were 0.635, 0.752, and 0.753, respectively, indicating that IRGPI has good potential in predicting the long-term survival of BC patients, consistent with the results in the GEO cohort. IRGPI showed good predictive power in four different breast cancer subtypes: ER positive, PR positive, HER2 positive and triple-negative (P<0.01). Compared with the low-IRGPI group, the high-IRGPI group had a worse prognosis and a lower degree of immune infiltrating cells (p < 0.05). IRGPI showed specificity in distinguishing age, TNM stage, ER, and HER2 statuses, and our study found that the high-IRGPI group had low tumor immune dysfunction and exclusion (TIDE), microsatellite instability (MSI), and T cell dysfunction scores (p < 0.05). In addition, compared with the TIDE and TIS models, showed that the AUCs of IRGPI were better during the 5-year follow-up.

Conclusion

IRGPI can be used as an independent prognostic indicator of breast cancer, providing a method for monitoring the long-term treatment of BC.

CD44-Mediated Poor Prognosis in Glioma Is Associated With M2-Polarization of Tumor-Associated Macrophages and Immunosuppression

Background

Glioma is the most common primary brain tumor with a poor prognosis. Key genes that are negatively related to prognosis may provide the therapy targets to cure glioma. To clarify the role of CD44 in glioma, we explored its function at bulk-transcriptome, spatial and single-cell transcriptome levels.

Methods

In total, expression profiles with survival data of whole-grade glioma from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), RNA-seq data with anatomic information of glioblastoma (GBM) from the Ivy Glioblastoma Atlas Project, RNA-sequencing (RNA-seq) data from recurrent GBM receiving adjuvant anti-PD-1 immunotherapy accessed through GSE121810, and single-cell RNA-seq data of GBM under accession GSE103224 were enrolled in this study. CD44-specific findings were further analyzed by R language.

Results

CD44 is positively correlated with WHO grade of malignancy and is negatively related to prognosis in glioma. Meanwhile, CD44 predominantly expresses in GBM mesenchymal subtype, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses reveal that CD44 positively coexpressed genes are closely related to glioma immunity. Moreover, CD44+ cells mainly distribute in perinecrotic region with high expression of immune factors. At single-cell resolution, only malignant tumor cells, tumor-associated macrophages (TAMs), and T cells express CD44 in GBM. CD44+ malignant tumor cells are in mesenchymal-1-like (MES1-like) cellular state, and CD44+ TAMs are in M2 phenotype. CD44+ T cells have high expression of both PD-1 and PD-L1. CD44 and its directly interacted inhibitory immunomodulators are upregulated in patients with nonresponder recurrent GBM treated with PD-1 blockade therapy.

Conclusion

Our work demonstrates that CD44, a new M2 TAM biomarker, is involved in immune suppressor and promote glioma progression in glioma microenvironment. These results expand our understanding of CD44-specific clinical and immune features in glioma.

Post-translational protein deimination signatures in sea lamprey (Petromyzon marinus) plasma and plasma-extracellular vesicles

Lampreys are a jawless vertebrate species belonging to an ancient vertebrate lineage that diverged from a common ancestor with humans ~500 million years ago. The sea lamprey (Petromyzon marinus) has a filter feeding ammocoete larval stage that metamorphoses into a parasitic adult, feeding both on teleost and elasmobranch fish. Lampreys are a valuable comparative model species for vertebrate immunity and physiology due to their unique phylogenetic position, unusual adaptive immune system, and physiological adaptions such as tolerance to salinity changes and urea. Peptidylarginine deiminases (PADs) are a phylogenetically conserved enzyme family which catalyses post-translational deimination/citrullination in target proteins, enabling proteins to gain new functions (moonlighting). The identification of deiminated protein targets in species across phylogeny may provide novel insights into post-translational regulation of physiological and pathophysiological processes. Extracellular vesicles (EVs) are membrane vesicles released from cells that carry cargos of small molecules and proteins for cellular communication, involved in both normal and pathological processes. The current study identified deimination signatures in proteins of both total plasma and plasma-EVs in sea lamprey and furthermore reports the first characterisation of plasma-EVs in lamprey. EVs were poly-dispersed in the size range of 40-500 nm, similar to what is observed in other taxa, positive for CD63 and Flotillin-1. Plasma-EV morphology was confirmed by transmission electron microscopy. Assessment of deimination/citrullination signatures in lamprey plasma and plasma-EVs, revealed 72 deimination target proteins involved in immunity, metabolism and gene regulation in whole plasma, and 37 target proteins in EVs, whereof 24 were shared targets. Furthermore, the presence of deiminated histone H3, indicative of gene-regulatory mechanisms and also a marker of neutrophil extracellular trap formation (NETosis), was confirmed in lamprey plasma. Functional protein network analysis revealed some differences in KEGG and GO pathways of deiminated proteins in whole plasma compared with plasma-EVs. For example, while common STRING network clusters in plasma and plasma-EVs included Peptide chain elongation, Viral mRNA translation, Glycolysis and gluconeogenesis, STRING network clusters specific for EVs only included: Cellular response to heat stress, Muscle protein and striated muscle thin filament, Nucleosome, Protein processing in endoplasmic reticulum, Nucleosome and histone deacetylase complex. STRING network clusters specific for plasma were: Adipokinetic hormone receptor activity, Fibrinogen alpha/beta chain family, peptidase S1A, Glutathione synthesis and recycling-arginine, Fructose 1,6-bisphosphate metabolic process, Carbon metabolism and lactate dehydrogenase activity, Post-translational protein phosphorylation, Regulation of insulin-like growth factor transport and clotting cascade. Overall, for the EV citrullinome, five STRING network clusters, 10 KEGG pathways, 15 molecular GO pathways and 29 Reactome pathways were identified, compared with nine STRING network clusters, six KEGG pathways, two Molecular GO pathways and one Reactome pathway specific for whole plasma; while further pathways were shared. The reported findings indicate that major pathways relevant for immunity and metabolism are targets of deimination in lamprey plasma and plasma-EVs, with some differences, and may help elucidating roles for the conserved PAD enzyme family in regulation of immune and metabolic function throughout phylogeny.

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value

Background

Ovarian cancer is one of the most common malignant tumors in female genital organs, and its incidence rate is high. However, the pathogenesis and prognostic markers of ovarian cancer are unclear. This study sought to screen potential markers of ovarian cancer and to explore their prognostic value.

Methods

The Cancer Genome Atlas, Gene Expression Omnibus, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used in this study. The least absolute shrinkage and selection operator (LASSO), multivariate Cox regression and stepwise regression analysis were chosen to screen genes and construct risk model. Gene Set Enrichment Analysis (GSEA) and an immune-infiltration analysis were performed.

Results

One hundred thirty two co-expressed genes were found. They involved in metabolism, protein phosphorylation, mitochondria, and immune signaling pathways. Twelve genes significantly related to the survival of ovarian cancer were identified. Eight risk genes (i.e., CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11) were further screened and used to construct the risk model. The risk status might be an independent prognostic factor of ovarian cancer, and most of the biological functions of genes expressed in high-risk ovarian cancer were related to synapse, adhesion, and immune-related functions. The clusters of CD4+ T cells and M2 macrophages were high in high-risk status samples.

Conclusions

In ovarian cancer, the abnormal expression of 8 genes, including CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11, is closely related to ovarian cancer progression, and these genes can serve as independent prognosis markers of ovarian cancer.

Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer

Background

Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data.

Methods

Breast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance.

Results

A total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC.

Conclusion

The current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00823-y.

Anoctamin 5 promotes osteosarcoma development by increasing degradation of Nel-like proteins 1 and 2

Anoctamin 5 (ANO5) is a member of the Anoctamin (ANO) family of calcium-activated chloride channels. Although ANO5 expression is upregulated in various cancers, its role in osteosarcoma remains largely unknown. In this study, bioinformatics analysis, western blot, and immunohistochemical staining revealed that ANO5 was upregulated in osteosarcoma cell lines and osteosarcoma tissues, and ANO5 expression was positively associated with tumor size, tumor grade, and metastasis. Functional experiments demonstrated that inhibition of ANO5 decreased, while ANO5 overexpression increased, osteosarcoma cell proliferation and mobility in vitro. Immunoprecipitation, western blot, and confocal microscopy experiments showed that ANO5 bound to and promoted the degradation of Nel-like proteins 1 (NELL1) and 2 (NELL2). Moreover, a subcutaneous tumor transplantation model revealed that ANO5 knockdown reduced osteosarcoma cell proliferation and increased NELL1 and NELL2 expression in vivo. Finally, rescue experiments showed that knockdown of NELL1 or NELL2 reversed the inhibitory effects of ANO5 knockdown on osteosarcoma cell proliferation and migration. These results demonstrated that upregulation of ANO5 promoted osteosarcoma development by decreasing the stability of the NELL1 and NELL2 proteins and that ANO5 may be an effective target for the treatment of osteosarcoma.

Molecular underpinning of intracellular pH regulation on TMEM16F

TMEM16F, a dual-function phospholipid scramblase and ion channel, is important in blood coagulation, skeleton development, HIV infection, and cell fusion. Despite advances in understanding its structure and activation mechanism, how TMEM16F is regulated by intracellular factors remains largely elusive. Here we report that TMEM16F lipid scrambling and ion channel activities are strongly influenced by intracellular pH (pHi). We found that low pHi attenuates, whereas high pHi potentiates, TMEM16F channel and scramblase activation under physiological concentrations of intracellular Ca2+ ([Ca2+]i). We further demonstrate that TMEM16F pHi sensitivity depends on [Ca2+]i and exhibits a bell-shaped relationship with [Ca2+]i: TMEM16F channel activation becomes increasingly pHi sensitive from resting [Ca2+]i to micromolar [Ca2+]i, but when [Ca2+]i increases beyond 15 µM, pHi sensitivity gradually diminishes. The mutation of a Ca2+-binding residue that markedly reduces TMEM16F Ca2+ sensitivity (E667Q) maintains the bell-shaped relationship between pHi sensitivity and Ca2+ but causes a dramatic shift of the peak [Ca2+]i from 15 µM to 3 mM. Our biophysical characterizations thus pinpoint that the pHi regulatory effects on TMEM16F stem from the competition between Ca2+ and protons for the primary Ca2+-binding residues in the pore. Within the physiological [Ca2+]i range, the protonation state of the primary Ca2+-binding sites influences Ca2+ binding and regulates TMEM16F activation. Our findings thus uncover a regulatory mechanism of TMEM16F by pHi and shine light on our understanding of the pathophysiological roles of TMEM16F in diseases with dysregulated pHi, including cancer.