Ion channel gene expression in lung adenocarcinoma: potential role in prognosis and diagnosis

The Emerging Concept of Transportome: State of the Art

The array of ion channels and transporters expressed in cell membranes, collectively referred to as the transportome, is a complex and multifunctional molecular machinery; in particular, at the plasma membrane level it finely tunes the exchange of biomolecules and ions, acting as a functionally adaptive interface that accounts for dynamic plasticity in the response to environmental fluctuations and stressors. The transportome is responsible for the definition of membrane potential and its variations, participates in the transduction of extracellular signals, and acts as a filter for most of the substances entering and leaving the cell, thus enabling the homeostasis of many cellular parameters. For all these reasons, physiologists have long been interested in the expression and functionality of ion channels and transporters, in both physiological and pathological settings and across the different domains of life. Today, thanks to the high-throughput technologies of the postgenomic era, the omics approach to the study of the transportome is becoming increasingly popular in different areas of biomedical research, allowing for a more comprehensive, integrated, and functional perspective of this complex cellular apparatus. This article represents a first effort for a systematic review of the scientific literature on this topic. Here we provide a brief overview of all those studies, both primary and meta-analyses, that looked at the transportome as a whole, regardless of the biological problem or the models they used. A subsequent section is devoted to the methodological aspect by reviewing the most important public databases annotating ion channels and transporters, along with the tools they provide to retrieve such information. Before conclusions, limitations and future perspectives are also discussed.

Ion channels in lung cancer: biological and clinical relevance

Despite improvements in treatment, lung cancer is still a major health problem worldwide. Among lung cancer subtypes, the most frequent is represented by adenocarcinoma (belonging to the Non-Small Cell Lung Cancer class) although the most challenging and harder to treat is represented by Small Cell Lung Cancer, that occurs at lower frequency but has the worst prognosis. For these reasons, the standard of care for these patients is represented by a combination of surgery, radiation therapy and chemotherapy. In this view, searching for novel biomarkers that might help both in diagnosis and therapy is mandatory. In the last 30 years it was demonstrated that different families of ion channels are overexpressed in both lung cancer cell lines and primary tumours. The altered ion channel profile may be advantageous for diagnostic and therapeutic purposes since most of them are localised on the plasma membrane thus their detection is quite easy, as well as their block with specific drugs and antibodies. This review focuses on ion channels (Potassium, Sodium, Calcium, Chloride, Anion and Nicotinic Acetylcholine receptors) in lung cancer (both Non-Small Cell Lung Cancer and Small Cell Lung Cancer) and recapitulate the up-to-date knowledge about their role and clinical relevance for a potential use in the clinical setting, for lung cancer diagnosis and therapy.

30-Min Exposure to Tobacco Smoke Influences Airway Ion Transport-An In Vitro Study

Introduction: Smoking is one of the most important causes of cancer in humans. However, it has not been proven how long exposure to cigarette smoke is sufficient to induce cancerogenesis. Cigarette smoke can cause changes in ion and water transport and the maintenance of mucociliary transport. The conducted research concerned the assessment of changes in ion transport in rabbit tracheal specimens after 30 min of exposure to cigarette smoke. Materials and Methods: A modified Ussing chamber was used to measure the transepithelial electrical potential under stationary conditions (PD) and during mechanical stimulation (PDmin), and the transepithelial electrical resistance (R) in control and cigarette smoke-exposed tracheal fragments. Results: Significant changes in PD (-2.53 vs. -3.92 mV) and PDmin (-2.74 vs. -0.39 mV) were noted for the samples exposed to smoke, which can be associated with a rise in reactivity after applying a mechanical stimulus. In addition, the measured R (108 vs. 136 Ω/cm²) indicated no changes in the vitality of the samples, but an increase in their permeability to ions in the experimental conditions. Conclusions: A single 30-min exposure to cigarette smoke has been shown to be associated with increased permeability of the tracheal epithelium to ions and thus to substances emitted during smoking, which might be sufficient to create the possibility of initiating procarcinogenic processes.

Network-Based Data Analysis Reveals Ion Channel-Related Gene Features in COVID-19: A Bioinformatic Approach

Coronavirus disease 2019 (COVID-19) seriously threatens human health and has been disseminated worldwide. Although there are several treatments for COVID-19, its control is currently suboptimal. Therefore, the development of novel strategies to treat COVID-19 is necessary. Ion channels are located on the membranes of all excitable cells and many intracellular organelles and are key components involved in various biological processes. They are a target of interest when searching for drug targets. This study aimed to reveal the relevant molecular features of ion channel genes in COVID-19 based on bioinformatic analyses. The RNA-sequencing data of patients with COVID-19 and healthy subjects (GSE152418 and GSE171110 datasets) were obtained from the Gene Expression Omnibus (GEO) database. Ion channel genes were selected from the Hugo Gene Nomenclature Committee (HGNC) database. The RStudio software was used to process the data based on the corresponding R language package to identify ion channel-associated differentially expressed genes (DEGs). Based on the DEGs, Gene Ontology (GO) functional and pathway enrichment analyses were performed using the Enrichr web tool. The STRING database was used to generate a protein-protein interaction (PPI) network, and the Cytoscape software was used to screen for hub genes in the PPI network based on the cytoHubba plug-in. Transcription factors (TF)-DEG, DEG-microRNA (miRNA) and DEG-disease association networks were constructed using the NetworkAnalyst web tool. Finally, the screened hub genes as drug targets were subjected to enrichment analysis based on the DSigDB using the Enrichr web tool to identify potential therapeutic agents for COVID-19. A total of 29 ion channel-associated DEGs were identified. GO functional analysis showed that the DEGs were integral components of the plasma membrane and were mainly involved in inorganic cation transmembrane transport and ion channel activity functions. Pathway analysis showed that the DEGs were mainly involved in nicotine addiction, calcium regulation in the cardiac cell and neuronal system pathways. The top 10 hub genes screened based on the PPI network included KCNA2, KCNJ4, CACNA1A, CACNA1E, NALCN, KCNA5, CACNA2D1, TRPC1, TRPM3 and KCNN3. The TF-DEG and DEG-miRNA networks revealed significant TFs (FOXC1, GATA2, HINFP, USF2, JUN and NFKB1) and miRNAs (hsa-mir-146a-5p, hsa-mir-27a-3p, hsa-mir-335-5p, hsa-let-7b-5p and hsa-mir-129-2-3p). Gene-disease association network analysis revealed that the DEGs were closely associated with intellectual disability and cerebellar ataxia. Drug-target enrichment analysis showed that the relevant drugs targeting the hub genes CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5 were gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine. The results of this study provide a valuable basis for exploring the mechanisms of ion channel genes in COVID-19 and clues for developing therapeutic strategies for COVID-19.

Significance of a PTEN Mutational Status-Associated Gene Signature in the Progression and Prognosis of Endometrial Carcinoma

Background

PTEN mutations have been reported to be involved in the development and prognosis of endometrial carcinoma (EC). However, a prognostic gene signature associated with PTEN mutational status has not yet been developed. In this study, we generated a PTEN mutation-associated prognostic gene signature for EC.

Methods

We obtained the single-nucleotide variation and transcriptomic profiling data from The Cancer Genome Atlas database as training data and implemented the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm to establish a PTEN mutation-associated prognostic gene signature. The overall survival rates of the high-risk and low-risk groups were determined with the Kaplan-Meier (K-M) method, and the accuracy of risk score prediction was tested by using the receiver operating characteristic (ROC) curve.

Results

The K-M curves revealed that the EC patients with PTEN mutations augured favorable survival outcomes. Differential expression analysis between the EC patients with PTEN mutation and wild-type PTEN identified 224 differentially expressed genes (DEGs). Eighty-four DEGs that manifested prognostic value were fitted into the LASSO-Cox analysis, and a PTEN gene signature with seven mutation-associated prognostic genes that showed robust prognostic ability was constructed; this signature was then successfully validated in the other two datasets from the cBioPortal database as well as with 60 clinical specimens. Furthermore, the PTEN mutation-associated prognostic gene signature proved to be an independent prognostic predictor of EC. Remarkably, the EC patients in the high-risk group were characterized by higher tumor stages and grades as well as lower tumor mutation burden with respect to EC, with a poor survival outcome. Collectively, the PTEN mutation-associated prognostic gene signature that we developed could now be used as a favorable prognostic biomarker for EC.

Conclusion

In summary, we developed and validated a prognostic predictor for EC associated with PTEN mutational status that may be used as a favorable prognostic biomarker and therapeutic target for EC.

Integrative analyses identified ion channel genes GJB2 and SCNN1B as prognostic biomarkers and therapeutic targets for lung adenocarcinoma

OBJECTIVES

Abnormal expressions of ion channel genes are associated with the occurrence and progression of tumors. At present, their roles in the carcinogenesis of lung adenocarcinoma (LUAD) are not clear.

MATERIALS AND METHODS

Differentially expressed (DE) genes in the tumorigenesis were identified from 328 ion channel genes in 102 LUAD and paired adjacent normal samples. Similar analyses were performed between 177 metastatic and 286 non-metastatic LUAD samples to identify DE ion channel genes in the progression of LUAD. Independent prognostic factors selected from DE ion channel genes were used to construct a prognostic model. Correlation analysis and drugs-drug targets interaction network were used to screen the potential drugs for LUAD patients stratified by GJB2 or SCNN1B.

RESULTS

Six ion channel genes (GJB2, CACNA1D, KCNQ1, SCNN1B, SCNN1G and TRPV6) were continuous differentially expressed in the tumorigenesis and progression of LUAD. The survival analysis in four datasets with 522 LUAD samples showed that GJB2 and SCNN1B were independent prognostic biomarkers. Patients with overexpression of GJB2 or underexpression of SCNN1B had shorter overall survival. Moreover, multi-omics analysis showed that hypomethylation of GJB2 and hypermethylation of SCNN1B in the promoter region may contribute to their aberrant expressions. KEGG enrichment analysis showed that the overexpressed genes in the group with high GJB2 or low SCNN1B were enriched in cancer-related pathways, while the underexpressed genes were enriched in metabolism-related pathways. The prognostic model with GJB2 and SCNN1B can stratify all LUAD patients into two groups with significantly different survival. Correlation analysis and drugs-drug targets interaction network suggested that GJB2 and SCNN1B expression might have indicative therapeutic values for LUAD patients. Finally, pan-cancer analysis in other eight cancer types showed that GJB2 and SCNN1B might be also potential prognostic factors for KIRC.

CONCLUSIONS

GJB2 and SCNN1B were identified as prognostic biomarkers and therapeutic targets for LUAD.

Transcriptomic insight into the translational value of two murine models in human atopic dermatitis

This study sought to develop a novel diagnostic tool for atopic dermatitis (AD). Mouse transcriptome data were obtained via RNA-sequencing of dorsal skin tissues of CBA/J mice affected with contact hypersensitivity (induced by treatment with 1-chloro-2,4-dinitrobenzene) or brush stimulation-induced AD-like skin condition. Human transcriptome data were collected from German, Swedish, and American cohorts of AD patients from the Gene Expression Omnibus database. edgeR and SAM algorithms were used to analyze differentially expressed murine and human genes, respectively. The FAIME algorithm was then employed to assign pathway scores based on KEGG pathway database annotations. Numerous genes and pathways demonstrated similar dysregulation patterns in both the murine models and human AD. Upon integrating transcriptome information from both murine and human data, we identified 36 commonly dysregulated differentially expressed genes, which were designated as a 36-gene signature. A severity score (AD index) was applied to each human sample to assess the predictive power of the 36-gene AD signature. The diagnostic power and predictive accuracy of this signature were demonstrated for both AD severity and treatment outcomes in patients with AD. This genetic signature is expected to improve both AD diagnosis and targeted preclinical research.

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma

Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise to leverage very large datasets for making better predictions of disease biomarkers. Denoising autoencoder (DA) is one of the unsupervised deep learning algorithms, which is a stochastic version of autoencoder techniques. The principle of DA is to force the hidden layer of autoencoder to capture more robust features by reconstructing a clean input from a corrupted one. Here, a DA model was applied to analyze integrated transcriptomic data from 13 published lung cancer studies, which consisted of 1916 human lung tissue samples. Using DA, we discovered a molecular signature composed of multiple genes for lung adenocarcinoma (ADC). In independent validation cohorts, the proposed molecular signature is proved to be an effective classifier for lung cancer histological subtypes. Also, this signature successfully predicts clinical outcome in lung ADC, which is independent of traditional prognostic factors. More importantly, this signature exhibits a superior prognostic power compared with the other published prognostic genes. Our study suggests that unsupervised learning is helpful for biomarker development in the era of precision medicine.

TP53-Associated Ion Channel Genes Serve as Prognostic Predictor and Therapeutic Targets in Head and Neck Squamous Cell Carcinoma

TP53 mutations are the most occurred mutation in HNSCC which might affect the ion channel genes. We aim to investigate the ion channel gene alteration under TP53 mutation and their prognostic implication. The overall mutation status of HNSCC were explored. By screening the TP53-associated ion channel genes (TICGs), an ion channel prognostic signature (ICPS) was established through a series of machine learning algorithms. The ICPS was then evaluated and its clinical significance was explored. 82 TICGs differentially expressed between TP53WT and TP53MUT were screened. Using univariate regression analysis and LASSO regression analysis and multivariate regression analysis, an ICPS containing 7 ion channel genes was established. A series of evaluation was carried out which proved the predictive ability of ICPS. Functional analysis of ICPS revealed that cancer-related pathways were enriched in high-risk group. Next, for clinical application, a nomogram was constructed based on ICPS and other independent clinicopathological factors. TP53 mutation status strongly affects the expression of ion channel genes. The ICPM we have identified is a strong indicator for HNSCC prognosis and could help with patient stratification as well as identification of novel drug targets.

Proteomic analysis enables distinction of early- versus advanced-stage lung adenocarcinomas

Background

A gel‐free proteomic approach was utilized to perform in‐depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long‐term goal of this study is to generate a large‐scale, label‐free proteomics dataset from histologically well‐classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers.

Methods and results

Cases of early‐stage (I‐II) and advanced‐stage (III‐IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung ADCs were analyzed by liquid chromatography‐tandem mass spectrometry. From the analysis of ADC and normal specimens, 4863 protein groups were identified. To examine the protein expression profile of ADC, a peak area‐based quantitation method was used. In early‐ and advanced‐stage ADC, 365 and 366 proteins were differentially expressed, respectively, between normal and tumor tissues (adjusted P‐value < .01, fold change ≥ 4). A total of 155 proteins were dysregulated between early‐ and advanced‐stage ADCs and 18 were suggested as early‐specific stage ADC. In silico functional analysis of the upregulated proteins in both tumor groups revealed that most of the enriched pathways are involved in mRNA metabolism. Furthermore, the most overrepresented pathways in the proteins that were unique to ADC are related to mRNA metabolic processes.

Conclusions

Further analysis of these data may provide an insight into the molecular pathways involved in disease etiology and may lead to the identification of biomarker candidates and potential targets for therapy. Our study provides potential diagnostic biomarkers for lung ADC and novel stage‐specific drug targets for rational intervention.

TASK-3 Gene Knockdown Dampens Invasion and Migration and Promotes Apoptosis in KATO III and MKN-45 Human Gastric Adenocarcinoma Cell Lines

Incidence and mortality of gastric cancer is increasing worldwide, in part, because of the lack of new therapeutic targets to treat this disease. Different types of ion channels participate in the hallmarks of cancer. In this context, ion channels are known to exert control over the cell cycle, mechanisms that support survival, angiogenesis, migration, and cell invasion. In particular, TASK-3 (KCNK9), a member of the K2P potassium channel family, has attracted much interest because of its oncogenic properties. However, despite multiple lines of evidence linking TASK-3 to tumorigenesis in various types of cancer, its relationship with gastric cancer has not been fully examined. Therefore, we set out to assess the effect of TASK-3 gene knockdown on KATO III and MKN-45 human gastric adenocarcinoma cell lines by using a short hairpin RNA (shRNA)-mediated knockdown. Our results demonstrate that knocking down TASK-3 reduces cell proliferation and viability because of an increase in apoptosis without an apparent effect on cell cycle checkpoints. In addition, cell migration and invasion are reduced after knocking down TASK-3 in these cell lines. The present study highlights TASK-3 as a key protein involved in migration and cell survival in gastric cancer and corroborates its potential as a therapeutic target for gastric cancer treatment.

Bioelectric Control of Metastasis in Solid Tumors

As the leading cause of death in cancer, there is an urgent need to develop treatments to target the dissemination of primary tumor cells to secondary organs, known as metastasis. Bioelectric signaling has emerged in the last century as an important controller of cell growth, and with the development of current molecular tools we are now beginning to identify its role in driving cell migration and metastasis in a variety of cancer types. This review summarizes the currently available research for bioelectric signaling in solid tumor metastasis. We review the steps of metastasis and discuss how these can be controlled by bioelectric cues at the level of a cell, a population of cells, and the tissue. The role of ion channel, pump, and exchanger activity and ion flux is discussed, along with the importance of the membrane potential and the relationship between ion flux and membrane potential. We also provide an overview of the evidence for control of metastasis by external electric fields (EFs) and draw from examples in embryogenesis and regeneration to discuss the implications for endogenous EFs. By increasing our understanding of the dynamic properties of bioelectric signaling, we can develop new strategies that target metastasis to be translated into the clinic.

Transient Receptor Potential Channel Expression Signatures in Tumor-Derived Endothelial Cells: Functional Roles in Prostate Cancer Angiogenesis

Background: Transient receptor potential (TRP) channels control multiple processes involved in cancer progression by modulating cell proliferation, survival, invasion and intravasation, as well as, endothelial cell (EC) biology and tumor angiogenesis. Nonetheless, a complete TRP expression signature in tumor vessels, including in prostate cancer (PCa), is still lacking. Methods: In the present study, we profiled by qPCR the expression of all TRP channels in human prostate tumor-derived ECs (TECs) in comparison with TECs from breast and renal tumors. We further functionally characterized the role of the ‘prostate-associated’ channels in proliferation, sprout formation and elongation, directed motility guiding, as well as in vitro and in vivo morphogenesis and angiogenesis. Results: We identified three ‘prostate-associated’ genes whose expression is upregulated in prostate TECs: TRPV2 as a positive modulator of TEC proliferation, TRPC3 as an endothelial PCa cell attraction factor and TRPA1 as a critical TEC angiogenic factor in vitro and in vivo. Conclusions: We provide here the full TRP signature of PCa vascularization among which three play a profound effect on EC biology. These results contribute to explain the aggressive phenotype previously observed in PTEC and provide new putative therapeutic targets.

The ion channels and transporters gene expression profile indicates a shift in excitability and metabolisms during malignant progression of Follicular Lymphoma

The definition of the gene expression profile of genes encoding Ion Channels and Transporters (ICT-GEP) represents a novel and attracting aspect in cancer. We determined the ICT-GEP of Follicular Lymphoma (FL), and compared it with that of the more aggressive Diffuse Large B Cell Lymphoma (DLBCL). cDNA microarray data were collected both from patients enrolled for this study, and from public datasets. In FL the ICT-GEP indicated the overexpression of both the K⁺ channel encoding gene KCNN4, and SLC2A1, which encodes the Glut1 glucose transporter. SLC2A1 turned out to represent the hub of a functional network, connecting channels and transporters in FL. Relapsed FL patients were characterised by 38 differentially expressed ICT genes, among which ATP9A, SLC2A1 and KCNN4 were under-expressed, indicating a down-regulation of both excitability and glycolysis. A completely different profile of K⁺ channel encoding genes emerged in DLBCL accompanied by the over-expression of the fatty acid transporter-encoding gene SLC27A1 as well as of the metabolism regulator NCoR1. This indicates a change in excitability and a shift towards an oxidative metabolism in DLBCL. Overall, the ICT-GEP may contribute to identifying novel lymphoma biomarkers related to excitability and metabolic pathways, with particular relevance for drug resistant, relapsed FL.

A Pathway-Based Strategy to Identify Biomarkers for Lung Cancer Diagnosis and Prognosis

Current research has identified several potential biomarkers for lung cancer diagnosis or prognosis. However, most of these biomarkers are derived from a relatively small number of samples using algorithms at the gene level. Hence, gene expression signatures discovered in these studies have little overlaps. In this study, we proposed a new strategy to identify biomarkers from multiple datasets at the pathway level. We integrated the genome-wide expression data of lung cancer tissues from 13 published studies and applied our strategy to identify lung cancer diagnostic and prognostic biomarkers. We identified a 32-gene signature that differentiates lung adenocarcinomas from other lung cancer subtypes. We also discovered a 43-gene signature that can predict the outcome of human lung cancers. We tested their performance in several independent cohorts, which confirmed their robust prognostic and diagnostic power. Furthermore, we showed that the proposed gene expression signatures were independent of several traditional clinical indicators in lung cancer management. Our results suggest that the pathway-based strategy is useful to identify transcriptomic biomarkers from large-scale gene expression datasets that were collected from multiple sources.

Repurposed Biguanide Drugs in Glioblastoma Exert Antiproliferative Effects via the Inhibition of Intracellular Chloride Channel 1 Activity

The lack of in-depth knowledge about the molecular determinants of glioblastoma (GBM) occurrence and progression, combined with few effective and BBB crossing-targeted compounds represents a major challenge for the discovery of novel and efficacious drugs for GBM. Among relevant molecular factors controlling the aggressive behavior of GBM, chloride intracellular channel 1 (CLIC1) represents an emerging prognostic and predictive biomarker, as well as a promising therapeutic target. CLIC1 is a metamorphic protein, co-existing as both soluble cytoplasmic and membrane-associated conformers, with the latter acting as chloride selective ion channel. CLIC1 is involved in several physiological cell functions and its abnormal expression triggers tumor development, favoring tumor cell proliferation, invasion, and metastasis. CLIC1 overexpression is associated with aggressive features of various human solid tumors, including GBM, in which its expression level is correlated with poor prognosis. Moreover, increasing evidence shows that modification of microglia ion channel activity, and CLIC1 in particular, contributes to the development of different neuropathological states and brain tumors. Intriguingly, CLIC1 is constitutively active within cancer stem cells (CSCs), while it seems less relevant for the survival of non-CSC GBM subpopulations and for normal cells. CSCs represent GBM development and progression driving force, being endowed with stem cell-like properties (self-renewal and differentiation), ability to survive therapies, to expand and differentiate, causing tumor recurrence. Downregulation of CLIC1 results in drastic inhibition of GBM CSC proliferation in vitro and in vivo, making the control of the activity this of channel a possible innovative pharmacological target. Recently, drugs belonging to the biguanide class (including metformin) were reported to selectively inhibit CLIC1 activity in CSCs, impairing their viability and invasiveness, but sparing normal stem cells, thus representing potential novel antitumor drugs with a safe toxicological profile. On these premises, we review the most recent insights into the biological role of CLIC1 as a potential selective pharmacological target in GBM. Moreover, we examine old and new drugs able to functionally target CLIC1 activity, discussing the challenges and potential development of CLIC1-targeted therapies.

Ion Channels in Cancer: Are Cancer Hallmarks Oncochannelopathies?

Genomic instability is a primary cause and fundamental feature of human cancer. However, all cancer cell genotypes generally translate into several common pathophysiological features, often referred to as cancer hallmarks. Although nowadays the catalog of cancer hallmarks is quite broad, the most common and obvious of them are 1) uncontrolled proliferation, 2) resistance to programmed cell death (apoptosis), 3) tissue invasion and metastasis, and 4) sustained angiogenesis. Among the genes affected by cancer, those encoding ion channels are present. Membrane proteins responsible for signaling within cell and among cells, for coupling of extracellular events with intracellular responses, and for maintaining intracellular ionic homeostasis ion channels contribute to various extents to pathophysiological features of each cancer hallmark. Moreover, tight association of these hallmarks with ion channel dysfunction gives a good reason to classify them as special type of channelopathies, namely oncochannelopathies. Although the relation of cancer hallmarks to ion channel dysfunction differs from classical definition of channelopathies, as disease states causally linked with inherited mutations of ion channel genes that alter channel's biophysical properties, in a broader context of the disease state, to which pathogenesis ion channels essentially contribute, such classification seems absolutely appropriate. In this review the authors provide arguments to substantiate such point of view.

A three ion channel genes-based signature predicts prognosis of primary glioblastoma patients and reveals a chemotherapy sensitive subtype

Increasing evidence suggests that ion channels not only regulate electric signaling in excitable cells but also play important roles in the development of brain tumor. However, the roles of ion channels in glioma remain controversial. In the present study, we systematically analyzed the expression patterns of ion channel genes in a cohort of Chinese patients with glioma using RNAseq expression profiling. First, a molecular signature comprising three ion channel genes (KCNN4, KCNB1 and KCNJ10) was identified using Univariate Cox regression and two-tailed student's t test conducted in overall survival (OS) and gene expression. We assigned a risk score based on three ion channel genes to each primary Glioblastoma multiforme (pGBM) patient. We demonstrated that pGBM patients who had a high risk of unfavorable outcome were sensitive to chemotherapy. Next, we screened the three ion genes-based signature in different molecular glioma subtypes. The signature showed a Mesenchymal subtype and wild-type IDH1 preference. Gene ontology (GO) analysis for the functional annotation of the signature showed that patients with high-risk scores tended to exhibit the increased expression of proteins associated with apoptosis, immune response, cell adhesion and motion and vasculature development. Gene Set Enrichment Analysis (GSEA) results showed that pathways associated with negative regulation of programmed cell death, cell proliferation and locomotory behavior were highly expressed in the high-risk group. These results suggest that ion channel gene expression could improve the subtype classification in gliomas at the molecular level. The findings in the present study have been validated in two independent cohorts.

KCa3.1 channel inhibition leads to an ICAM-1 dependent increase of cell-cell adhesion between A549 lung cancer and HMEC-1 endothelial cells

Early metastasis leads to poor prognosis of lung cancer patients, whose 5-year survival rate is only 15%. We could recently show that the Ca²⁺ sensitive K⁺ channel K_Ca3.1 promotes aggressive behavior of non-small cell lung cancer (NSCLC) cells and that it can serve as a prognostic marker in NSCLC. Since NSCLC patients die of metastases, we investigated whether K_Ca3.1 channels contribute to poor patient prognosis by regulating distinct steps of the metastatic cascade. We investigated the extravasation of NSCLC cells and focused on their adhesion to endothelial cells and on transendothelial migration. We quantified the adhesion forces between NSCLC cells and endothelial cells by applying single cell force spectroscopy, and we monitored transendothelial migration using live-cell imaging. Inhibition of K_Ca3.1 channels with senicapoc or K_Ca3.1 silencing increases the adhesion force of A549 lung cancer cells to human microvascular endothelial cells (HMEC-1). Western blotting, immunofluorescence staining and biotinylation assays indicate that the elevated adhesion force is due to increased expression of ICAM-1 in both cell lines when K_Ca3.1 channels are downregulated. Consistent with this interpretation, an anti-ICAM-1 blocking antibody abolishes the K_Ca3.1-dependent increase in adhesion. Senicapoc inhibits transendothelial migration of A549 cells by 50%. Selectively silencing K_Ca3.1 channels in either NSCLC or endothelial cells reveals that transendothelial migration depends predominantly on endothelial K_Ca3.1 channels.

In conclusion, our findings disclose a novel function of K_Ca3.1 channels in cancer. K_Ca3.1 channels regulate ICAM-1 dependent cell-cell adhesion between endothelial and cancer cells that affects the transmigration step of the metastatic cascade.

Voltage-Dependent Anion Channel 1 As an Emerging Drug Target for Novel Anti-Cancer Therapeutics

Cancer cells share several properties, high proliferation potential, reprogramed metabolism, and resistance to apoptotic cues. Acquiring these hallmarks involves changes in key oncogenes and non-oncogenes essential for cancer cell survival and prosperity, and is accompanied by the increased energy requirements of proliferating cells. Mitochondria occupy a central position in cell life and death with mitochondrial bioenergetics, biosynthesis, and signaling are critical for tumorigenesis. Voltage-dependent anion channel 1 (VDAC1) is situated in the outer mitochondrial membrane (OMM) and serving as a mitochondrial gatekeeper. VDAC1 allowing the transfer of metabolites, fatty acid ions, Ca²⁺, reactive oxygen species, and cholesterol across the OMM and is a key player in mitochondrial-mediate apoptosis. Moreover, VDAC1 serves as a hub protein, interacting with diverse sets of proteins from the cytosol, endoplasmic reticulum, and mitochondria that together regulate metabolic and signaling pathways. The observation that VDAC1 is over-expressed in many cancers suggests that the protein may play a pivotal role in cancer cell survival. However, VDAC1 is also important in mitochondria-mediated apoptosis, mediating release of apoptotic proteins and interacting with anti-apoptotic proteins, such as B-cell lymphoma 2 (Bcl-2), Bcl-xL, and hexokinase (HK), which are also highly expressed in many cancers. Strategically located in a “bottleneck” position, controlling metabolic homeostasis and apoptosis, VDAC1 thus represents an emerging target for anti-cancer drugs. This review presents an overview on the multi-functional mitochondrial protein VDAC1 performing several functions and interacting with distinct sets of partners to regulate both cell life and death, and highlights the importance of the protein for cancer cell survival. We address recent results related to the mechanisms of VDAC1-mediated apoptosis and the potential of associated proteins to modulate of VDAC1 activity, with the aim of developing VDAC1-based approaches. The first strategy involves modification of cell metabolism using VDAC1-specific small interfering RNA leading to inhibition of cancer cell and tumor growth and reversed oncogenic properties. The second strategy involves activation of cancer cell death using VDAC1-based peptides that prevent cell death induction by anti-apoptotic proteins. Finally, we discuss the potential therapeutic benefits of treatments and drugs leading to enhanced VDAC1 expression or targeting VDAC1 to induce apoptosis.

Orai3 is a predictive marker of metastasis and survival in resectable lung adenocarcinoma

Orai3 channel has emerged as important player in malignant transformation. Indeed, its expression is increased in cancer and favors cell proliferation and survival by permitting calcium influx. In this study, Orai3 was overexpressed in lung adenocarcinoma as compared to their matched non-tumour samples and was associated with tumoural aggressiveness. Moreover, its expression was associated with estrogen receptor alpha (ERα) expression and visceral pleural invasion in multivariate analysis. Furthermore, both the overall survival (OS) median and the metastasis free survival (MFS) median of tumors with high Orai3 expression were lower than in low Orai3 expression regardless of cancer stage (35.01 months vs. 51.11 months for OS and 46.01 months vs. 62.04 months for MFS). In conclusion, Orai3 protein level constitutes an independent prognostic marker in lung adenocarcinoma, and a novel prognostic marker that could help selecting the patients with worst prognosis to be treated with adjuvant chemotherapy in resectable stage.

In vitro evaluation of antitumoral efficacy of catalase in combination with traditional chemotherapeutic drugs against human lung adenocarcinoma cells

Lung cancer is the most lethal cancer-related disease worldwide. Since survival rates remain poor, there is an urgent need for more effective therapies that could increase the overall survival of lung cancer patients. Lung tumors exhibit increased levels of oxidative markers with altered levels of antioxidant defenses, and previous studies demonstrated that the overexpression of the antioxidant enzyme catalase (CAT) might control tumor proliferation and aggressiveness. Herein, we evaluated the effect of CAT treatment on the sensitivity of A549 human lung adenocarcinoma cells toward various anticancer treatments, aiming to establish the best drug combination for further therapeutic management of this disease. Exponentially growing A549 cells were treated with CAT alone or in combination with chemotherapeutic drugs (cisplatin, 5-fluorouracil, paclitaxel, daunorubicin, and hydroxyurea). CalcuSyn(®) software was used to assess CAT/drug interactions (synergism or antagonism). Growth inhibition, NFκB activation status, and redox parameters were also evaluated in CAT-treated A549 cells. CAT treatment caused a cytostatic effect, decreased NFκB activation, and modulated the redox parameters evaluated. CAT treatment exhibited a synergistic effect among most of the anticancer drugs tested, which is significantly correlated with an increased H2O2 production. Moreover, CAT combination caused an antagonism in paclitaxel anticancer effect. These data suggest that combining CAT (or CAT analogs) with traditional chemotherapeutic drugs, especially cisplatin, is a promising therapeutic strategy for the treatment of lung cancer.

Ion channel gene expression predicts survival in glioma patients

Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients.

Expression of tumor necrosis factor-alpha-mediated genes predicts recurrence-free survival in lung cancer

In this study, we conducted a meta-analysis on high-throughput gene expression data to identify TNF-α-mediated genes implicated in lung cancer. We first investigated the gene expression profiles of two independent TNF-α/TNFR KO murine models. The EGF receptor signaling pathway was the top pathway associated with genes mediated by TNF-α. After matching the TNF-α-mediated mouse genes to their human orthologs, we compared the expression patterns of the TNF-α-mediated genes in normal and tumor lung tissues obtained from humans. Based on the TNF-α-mediated genes that were dysregulated in lung tumors, we developed a prognostic gene signature that effectively predicted recurrence-free survival in lung cancer in two validation cohorts. Resampling tests suggested that the prognostic power of the gene signature was not by chance, and multivariate analysis suggested that this gene signature was independent of the traditional clinical factors and enhanced the identification of lung cancer patients at greater risk for recurrence.

Ion channel expression as promising cancer biomarker

Cancer is a disease with marked heterogeneity in both response to therapy and survival. Clinical and histopathological characteristics have long determined prognosis and therapy. The introduction of molecular diagnostics has heralded an explosion in new prognostic factors. Overall, histopathology, immunohistochemistry and molecular biology techniques have described important new prognostic subgroups in the different cancer categories. Ion channels and transporters (ICT) are a new class of membrane proteins which are aberrantly expressed in several types of human cancers. Besides regulating different aspect of cancer cell behavior, ICT can now represent novel cancer biomarkers. A summary of the data obtained so far and relative to breast, prostate, lung, colorectal, esophagus, pancreatic and gastric cancers are reported. Special emphasis is given to those studies aimed at relating specific ICT or a peculiar ICT profile with current diagnostic methods. Overall, we are close to exploit ICTs for diagnostic, prognostic or predictive purposes in cancer. This article is part of a Special Issue entitled: Membrane channels and transporters in cancers.

Apolipoprotein C1 (APOC1) as a novel diagnostic and prognostic biomarker for lung cancer: A marker phase I trial

BACKGROUND

Tumor cells continuously evolve over time in response to host pressures. However, explanations as to how tumor cells are influenced by the inflammatory tumor microenvironment over time are, to date, poorly defined. We hypothesized that prognostic biomarkers could be obtained by exploring the expression of inflammation-associated genes between early and late stage lung cancer tumor samples.

METHODS

Candidate inflammation-associated genes, apolipoprotein C-1 (APOC1), MMP1, KMO)1, CXCL5, CXCL)7, IL-1α, IL-1β, TNF-α and IL-6 were verified by real-time quantitative polymerase chain reaction. Gene expression profiles and immunofluorescence staining of 30 lung cancer tissues were compared.

RESULTS

Expressions of APOC1 and IL-6 mRNA on tumor tissues in late stage disease were significantly higher than in early stage lung cancer samples. Immunofluorescence staining of tumor samples showed that the expression of APOC1 gradually increased from early to late stage in lung cancer patients. The expression levels of IL-6 and APOC1 in tumor samples were positively correlated; however, no prognostic value of APOC1 can be identified in serum samples.

CONCLUSIONS

We found that the level of tumor APOC1 was highly expressed in late stage lung cancer. Further research is warranted to determine the molecular mechanisms underlying the cross talk of APOC1 and IL-6 in tumor progression. An expanded sample size marker phase II study may lead to the discovery of new lung cancer therapeutics targeting APOC1.

Expression profiling of mitochondrial voltage-dependent anion channel-1 associated genes predicts recurrence-free survival in human carcinomas

Background

Mitochondrial voltage-dependent anion channels (VDACs) play a key role in mitochondria-mediated apoptosis. Both in vivo and in vitro evidences indicate that VDACs are actively involved in tumor progression. Specifically, VDAC-1, one member of the VDAC family, was thought to be a potential anti-cancer therapeutic target. Our previous study demonstrated that the human gene VDAC1 (encoding the VDAC-1 isoform) was significantly up-regulated in lung tumor tissue compared with normal tissue. Also, we found a significant positive correlation between the gene expression of VDAC1 and histological grade in breast cancer. However, the prognostic power of VDAC1 and its associated genes in human cancers is largely unknown.

Methods

We systematically analyzed the expression pattern of VDAC1 and its interacting genes in breast, colon, liver, lung, pancreatic, and thyroid cancers. The genes differentially expressed between normal and tumor tissues in human carcinomas were identified.

Results

The expression level of VDAC1 was uniformly up-regulated in tumor tissue compared with normal tissue in breast, colon, liver, lung, pancreatic, and thyroid cancers. Forty-four VDAC1 interacting genes were identified as being commonly differentially expressed between normal and tumor tissues in human carcinomas. We designated VDAC1 and the 44 dysregulated interacting genes as the VDAC1 associated gene signature (VAG). We demonstrate that the VAG signature is a robust prognostic biomarker to predict recurrence-free survival in breast, colon, and lung cancers, and is independent of standard clinical and pathological prognostic factors.

Conclusions

VAG represents a promising prognostic biomarker in human cancers, which may enhance prediction accuracy in identifying patients at higher risk for recurrence. Future therapies aimed specifically at VDAC1 associated genes may lead to novel agents in the treatment of cancer.

Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling

Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).

Expression of nicotinamide phosphoribosyltransferase-influenced genes predicts recurrence-free survival in lung and breast cancers

Nicotinamide phosphoribosyltransferase (NAMPT) is a rate-limiting enzyme in the salvage pathway of nicotinamide adenine dinucleotide biosynthesis. NAMPT protein is a secreted plasma biomarker in inflammation and in cancer. The NAMPT enzymatic inhibitor, FK866, acts as an inducer of apoptosis and is a cancer therapeutic candidate, however, little is known regarding the influence of NAMPT on cancer biological mechanisms or on the prognosis of human cancers. We interrogated known microarray data sets to define NAMPT knockdown-influenced gene expression to demonstrate that reduced NAMPT expression strongly dysregulates cancer biology signaling pathways. Comparisons of gene expression datasets of four cancer types generated a N39 molecular signature exhibiting consistent dysregulated expression in multiple cancer tissues. The N39 signature provides a significant and independent prognostic tool of human recurrence-free survival in lung and breast cancers. Despite the absence of clear elucidation of molecular mechanisms, this study validates NAMPT as a novel “oncogene” with a central role in carcinogenesis. Furthermore, the N39 signature provides a potentially useful tool for prediction of recurrence-free survival in lung and breast cancer and validates NAMPT as a novel and effective therapeutic target in cancer.