GABA(A) receptor pi (GABRP) stimulates basal-like breast cancer cell migration through activation of extracellular-regulated kinase 1/2 (ERK1/2)

Prelude to malignancy: A gene expression signature in normal mammary gland from breast cancer patients suggests pre-tumorous alterations and is associated with adverse outcomes

Despite advances in early detection and treatment strategies, breast cancer recurrence and mortality remain a significant health issue. Recent insights suggest the prognostic potential of microscopically healthy mammary gland, in the vicinity of the breast lesion. Nonetheless, a comprehensive understanding of the gene expression profiles in these tissues and their relationship to patient outcomes remain missing. Furthermore, the increasing trend towards breast-conserving surgery may inadvertently lead to the retention of existing cancer-predisposing mutations within the normal mammary gland. This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling, followed by whole-transcriptome verification experiments and statistical analyses to discern molecular signatures and their clinical relevance. A distinct gene expression signature was identified in uninvolved mammary gland samples, featuring key cellular components encoding keratins, CDH1, CDH3, EPCAM cell adhesion proteins, matrix metallopeptidases, oncogenes, tumor suppressors, along with crucial genes (FOXA1, RAB25, NRG1, SPDEF, TRIM29, and GABRP) having dual roles in cancer. Enrichment analyses revealed disruptions in epithelial integrity, cell adhesion, and estrogen signaling. This signature, named KAOS for Keratin-Adhesion-Oncogenes-Suppressors, was significantly associated with reduced tumor size but increased mortality rates. Integrating molecular assessment of non-malignant mammary tissue into disease management could enhance survival prediction and facilitate personalized patient care.

GABA Type A receptors expressed in triple negative breast cancer cells mediate chloride ion flux

Triple negative breast cancer (TNBC) is known for its heterogeneous nature and aggressive onset, limited unresponsiveness to hormone therapies and immunotherapy as well as high likelihood of metastasis and recurrence. Since no targeted standard treatment options are available for TNBC, novel and effective therapeutic targets are urgently needed. Ion channels have emerged as possible novel therapeutic candidates for cancer therapy. We previously showed that GABAA β3 subunit are expressed at higher levels in TNBC cell lines than non-tumorigenic MCF10A cells. GABAA β3 subunit knockdown causes cell cycle arrest in TNBC cell lines via decreased cyclin D1 and increased p21 expression. However, it is not known if the upregulated GABAAR express at the cell-surface in TNBC and mediate Cl- flux. Cl- ions are known to play a role in cell-cycle progression in other cancers such as gastric cancer. Here, using surface biotinylation and (N-(Ethoxycarbonylmethyl)-6-Methoxyquinolinium Bromide) MQAE-dye based fluorescence quenching, we show that upregulated GABAAR are on the cell-surface in TNBC cell lines and mediate significantly higher chloride (Cl-) flux as compared to non-tumorigenic MCF10A cells. Moreover, this GABAAR mediated Cl- flux can be modulated by pharmacological agents and is decreased in TNBC cells with GABAA β3 subunit knockdown. Further, treatment of TNBC cells with bicuculline, a GABAAR antagonist reduced cell viability in TNBC cells Overall, these results point to an unexplored role of GABAAR mediated Cl- flux in TNBC.

GABRP inhibits the progression of oesophageal cancer by regulating CFTR: Integrating bioinformatics analysis and experimental validation

Oesophageal cancer (EC) is a malignancy which accounts for a substantial number of cancer-related deaths worldwide. The molecular mechanisms underlying the pathogenesis of EC have not been fully elucidated. GSE17351 and GSE20347 data sets from the Gene Expression Omnibus (GEO) database were employed to screen differentially expressed genes (DEGs). Reverse transcription quantitative PCR (RT-qPCR) was used to examine hub gene expression. ECA-109 and TE-12 cells were transfected using the pcDNA3.1 expression vector encoding GABRP. The cell counting kit-8 (CCK-8), cell scratch and Transwell assays were performed to assess the effect of GABRP on EC cell proliferation, migration and invasion. Epithelial-mesenchymal transition (EMT)-associated protein levels were measured by Western blotting. Subsequently, CFTR was knocked down to verify whether GABRP affected biological events in EC cells by targeting CFTR. Seven hub genes were identified, including GABRP, FLG, ENAH, KLF4, CD24, ABLIM3 and ABLIM1, which all could be used as diagnostic biomarkers for EC. The RT-qPCR results indicated that the expression levels of GABRP, FLG, KLF4, CD24, ABLIM3 and ABLIM1 were downregulated, whereas the expression level of ENAH was upregulated. In vitro functional assays demonstrated that GABRP overexpression suppressed the proliferation, migration, invasion and EMT of EC cells. Mechanistically, GABRP promoted the expression of CFTR, and CFTR knockdown significantly counteracted the influence of GABRP overexpression on biological events in EC cells. Overexpression of GABRP inhibited EC progression by increasing CFTR expression, which might be a new target for EC treatment.

Community cohesion looseness in gene networks reveals individualized drug targets and resistance

Community cohesion plays a critical role in the determination of an individual's health in social science. Intriguingly, a community structure of gene networks indicates that the concept of community cohesion could be applied between the genes as well to overcome the limitations of single gene-based biomarkers for precision oncology. Here, we develop community cohesion scores which precisely quantify the community ability to retain the interactions between the genes and their cellular functions in each individualized gene network. Using breast cancer as a proof-of-concept study, we measure the community cohesion score profiles of 950 case samples and predict the individualized therapeutic targets in 2-fold. First, we prioritize them by finding druggable genes present in the community with the most and relatively decreased scores in each individual. Then, we pinpoint more individualized therapeutic targets by discovering the genes which greatly contribute to the community cohesion looseness in each individualized gene network. Compared with the previous approaches, the community cohesion scores show at least four times higher performance in predicting effective individualized chemotherapy targets based on drug sensitivity data. Furthermore, the community cohesion scores successfully discover the known breast cancer subtypes and we suggest new targeted therapy targets for triple negative breast cancer (e.g. KIT and GABRP). Lastly, we demonstrate that the community cohesion scores can predict tamoxifen responses in ER+ breast cancer and suggest potential combination therapies (e.g. NAMPT and RXRA inhibitors) to reduce endocrine therapy resistance based on individualized characteristics. Our method opens new perspectives for the biomarker development in precision oncology.

Oleanolic acid inhibits the tumor progression by regulating Lactobacillus through the cytokine-cytokine receptor interaction pathway in 4T1-induced mice breast cancer model

The therapeutic mechanism of oleanolic acid (OA) in breast cancer has been widely reported, but little has been known about the combined effects of transcriptome and gut microbiome. In this study, the phenotypic effect of oleanolic acid on mice was tested at the end of the administration cycle, and RNA sequencing on murine tumor tissue and 16S-rRNA sequencing on intestinal contents were conducted to analyze gene expression profiles and microbial diversity between the control group and OA treated group using 4T1-induced mice breast cancer model. As a result, it has been confirmed that oleanolic acid would play a significant inhibitory effect on the development of breast tumors in mice. Based on the integrative analysis of the transcriptomic and metagenomic data, it was found that the abundance of Lactobacillus in the intestinal flora of mice significantly increased in the OA group. Moreover, the up-regulation of Il10 had a significant effect on inhibiting the tumor progression, which played a role through cytokine-cytokine receptor interaction pathway.

Role of β3 subunit of the GABA type A receptor in triple negative breast cancer proliferation, migration, and cell cycle progression

Triple negative breast cancer (TNBC) is known for its heterogeneous nature and aggressive onset. The unresponsiveness to hormone therapies and immunotherapy and the toxicity of chemotherapeutics account for the limited treatment options for TNBC. Ion channels have emerged as possible therapeutic candidates for cancer therapy, but little is known about how ligand gated ion channels, specifically, GABA type A ligand-gated ion channel receptors (GABAAR), affect cancer pathogenesis. Our results show that the GABAA β3 subunit is expressed at higher levels in TNBC cell lines than non-tumorigenic cells, therefore contributing to the idea that limiting the GABAAR via knockdown of the GABAA β3 subunit is a potential strategy for decreasing the proliferation and migration of TNBC cells. We employed pharmacological and genetic approaches to investigate the role of the GABAA β3 subunit in TNBC proliferation, migration, and cell cycle progression. The results suggest that pharmacological antagonism or genetic knockdown of GABAA β3 subunit decreases TNBC proliferation and migration. In addition, GABAA β3 subunit knockdown causes cell cycle arrest in TNBC cell lines via decreased cyclin D1 and increased p21 expression. Our findings suggest that membrane bound GABAA receptors containing the β3 subunit can be further developed as a potential novel target for the treatment of TNBC.

GABRP Promotes the Metastasis of Pancreatic Cancer by Activation of the MEK/ERK Signaling Pathway

Pancreatic cancer remains the common cancer with the worst prognosis because of its late diagnosis and extensive metastasis. This study aimed to investigate the effects of GABRP on pancreatic cancer metastasis and the molecular mechanism. The expression of GABRP was measured using the quantitative real-time PCR and western blot. The biological behaviors of cancer cells were assessed using the cell counting kit-8, Transwell assay, and western blot. The regulation of GABRP on the MEK/ERK pathway was detected by western blot. The results indicated that GABRP was overexpressed in pancreatic cancer tissues and cells. Knockdown of GABRP suppressed cell viability, invasion, migration, and epithelial-mesenchymal transition (EMT), whereas GABRP overexpression facilitated these biological behaviors. Inactivation of the MEK/ERK pathway reversed the effects on cellular processes induced by GABRP. Moreover, silencing of GABRP inhibited tumor growth. In conclusion, GABRP promoted the progression of pancreatic cancer by facilitating cell metastasis and tumor growth via activating the MEK/ERK pathway. The findings suggest that GABRP has the potential to be a therapeutic target for the metastatic pancreatic cancer.

Epiberberine induced p53/p21-dependent G2/M cell cycle arrest and cell apoptosis in gastric cancer cells by activating γ-aminobutyric acid receptor- β3

BACKGROUND AND PURPOSE

Epiberberine (EPI) is one of the most important bioalkaloid found in the rhizome of Coptis chinensis, which has been observed to exhibit pharmaceutical effects against gastric cancer (GC). Nevertheless, the potential mechanism of EPI against GC cells still remains unclear. This study aimed to identify the core receptor on GC cells through which EPI inhibited the growth of GC cells and to explore the underlying inhibitory mechanisms.

METHODS

To identify hub receptor targets that respond to EPI treatment, RNA sequencing (RNA-Seq) data from a tumor-bearing mouse model were analyzed using bioinformatics method and molecular docking. The binding interaction between EPI and GABRB3 was validated through western blotting based-cellular thermal shift assay (WB-CETSA). To further verify the binding region between EPI and GABRB3 through circular dichroism (CD) chromatography, fragments of the extracellular and transmembrane domains of the GABRB3 protein were expressed and purified in vitro. Stable cell lines with the overexpression or knockdown of GABRB3 were established using the recombinant lentivirus system. MTT ((3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide)) assay, colony formation assay, invasion and migration experiments, and flow cytometry were conducted to validate the inhibitory effect of EPI on the GC cells via GABRB3. Additionally, western blotting was utilized to explore the potential inhibitory mechanisms.

RESULTS

Through the combination of multiple bioinformatics methods and molecular docking, we found that the γ-aminobutyric acid type A receptor subunit -β3 (GABRB3) might be the critical receptor target in response to EPI treatment. The results of WB-CETSA analysis indicated that EPI significantly promoted the thermostability of the GABRB3 protein. Importantly, EPI could directly bind to GABRB3 and alter the secondary structure of GABRB3 fragments similar to the natural agonist, γ-aminobutyric acid (GABA). The EPI-induced suppression of the malignant phenotype of GC cells was dependent on the presence of GABRB3. GABRB3 expression was positively correlated with TP53 in patients with GC. The binding of EPI to GABRB3 stimulated p53 accumulation in GC cells. This activated the p21/CDK1/cyclinB1 pathway, resulting in G2/M cell cycle arrest, and induced the Bcl-2/BAX/Caspase axis-dependent cell apoptosis.

CONCLUSION

This study revealed the target receptor for EPI in GC cells and provided new insights into its anticancer mechanisms.

GAD1-mediated GABA elicits aggressive characteristics of human oral cancer cells

Studies suggest that the expression of glutamate decarboxylase 1 (GAD1), γ-aminobutyric acid (GABA), and GABA receptors are involved in tumor progression. However, the underlying mechanisms of high expression and potential functions of GAD1 and GABA in oral squamous cell carcinoma (OSCC) are not known. In this study, we found that the expressions of GAD1 and GABA were considerably increased in OSCC samples, which were closely associated with clinical stage and lymph node metastasis. The knockdown of GAD1 expression significantly inhibited the proliferation, migration and invasion abilities of OSCC cells by reducing the expression of GABA-mediated GABAB receptors, which could be reversed by exogenous GABA, but did not cause excessive OSCC cell proliferation. And GABA secreted by OSCC cells promoted M2 macrophage polarization for inhibiting anti-tumor immunity by activating GABBR1/ERK/Ca2+. In addition, GABA/GABABR promoted the proliferation and progression of OSCC xenograft tumor. Altogether, our results showed that GAD1 synthetized GABA to promote the malignant progression of OSCC and limits the anti-tumor immunity of macrophages, thereby targeting GABA can be a novel strategy for treating OSCC.

Identification of a gene set that maintains tumorigenicity of the hepatocellular carcinoma cell line Li-7

The identification and development of therapeutic targets in cancer stem cells that lead to tumor development, recurrence, metastasis, and drug resistance is an important goal in cancer research. The hepatocellular carcinoma cell line Li-7 contains functionally different types of cells. Cells with tumor-forming activity are enriched in cancer stem cell-like CD13+CD166- cells and this cell population gradually decreases during culture in conventional culture medium (RPMI1640 containing 10% fetal bovine serum). When Li-7 cells are cultured in mTeSR1, a medium developed for human pluripotent stem cells, CD13+CD166- cells, and their tumorigenicity is maintained. Here, we sought to identify the mechanisms of tumorigenicity in this sub-population. We compared gene expression profiles of CD13+CD166- cells with other cell sub-populations and identified nine overexpressed genes (ENPP2, SCGN, FGFR4, MCOLN3, KCNJ16, SMIM22, SMIM24, SERPINH1, and TMPRSS2) in CD13+CD166- cells. After transfer from mTeSR1 to RPMI1640 containing 10% fetal bovine serum, the expression of these nine genes decreased in Li-7 cells and they lost tumorigenicity. In contrast, when these genes of Li-7 cells were forcibly expressed in cultures using RPMI1640 containing 10% fetal bovine serum, Li-7 cells maintained tumorigenicity. A metabolome analysis using capillary electrophoresis-mass spectrometry showed that two metabolic pathways, "Alanine, aspartate and glutamate metabolism" and "Arginine biosynthesis" were activated in cancer stem-cell-like cells. Our analyses here showed potential therapeutic target genes and metabolites for treatment of cancer stem cells in hepatocellular carcinoma.

Spatial Transcriptomics Identifies Expression Signatures Specific to Lacrimal Gland Adenoid Cystic Carcinoma Cells

Although primary tumors of the lacrimal gland are rare, adenoid cystic carcinoma (ACC) is the most common and lethal epithelial lacrimal gland malignancy. Traditional management of lacrimal gland adenoid cystic carcinoma (LGACC) involves the removal of the eye and surrounding socket contents, followed by chemoradiation. Even with this radical treatment, the 10-year survival rate for LGACC is 20% given the propensity for recurrence and metastasis. Due to the rarity of LGACC, its pathobiology is not well-understood, leading to difficulties in diagnosis, treatment, and effective management. Here, we integrate bulk RNA sequencing (RNA-seq) and spatial transcriptomics to identify a specific LGACC gene signature that can inform novel targeted therapies. Of the 3499 differentially expressed genes identified by bulk RNA-seq, the results of our spatial transcriptomic analysis reveal 15 upregulated and 12 downregulated genes that specifically arise from LGACC cells, whereas fibroblasts, reactive fibrotic tissue, and nervous and skeletal muscle account for the remaining bulk RNA-seq signature. In light of the analysis, we identified a transitional state cell or stem cell cluster. The results of the pathway analysis identified the upregulation of PI3K-Akt signaling, IL-17 signaling, and multiple other cancer pathways. This study provides insights into the molecular and cellular landscape of LGACC, which can inform new, targeted therapies to improve patient outcomes.

The tumor-nerve circuit in breast cancer

It is well established that innervation is one of the updated hallmarks of cancer and that psychological stress promotes the initiation and progression of cancer. The breast tumor environment includes not only fibroblasts, adipocytes, endothelial cells, and lymphocytes but also neurons, which is increasingly discovered important in breast cancer progression. Peripheral nerves, especially sympathetic, parasympathetic, and sensory nerves, have been reported to play important but different roles in breast cancer. However, their roles in the breast cancer progression and treatment are still controversial. In addition, the brain is one of the favorite sites of breast cancer metastasis. In this review, we first summarize the innervation of breast cancer and its mechanism in regulating cancer growth and metastasis. Next, we summarize the neural-related molecular markers in breast cancer diagnosis and treatment. In addition, we review drugs and emerging technologies used to block the interactions between nerves and breast cancer. Finally, we discuss future research directions in this field. In conclusion, the further research in breast cancer and its interactions with innervated neurons or neurotransmitters is promising in the clinical management of breast cancer.

Endorsement of TNBC Biomarkers in Precision Therapy by Nanotechnology

Breast cancer is a heterogeneous disease which accounts globally for approximately 1 million new cases annually, wherein more than 200,000 of these cases turn out to be cases of triple-negative breast cancer (TNBC). TNBC is an aggressive and rare breast cancer subtype that accounts for 10-15% of all breast cancer cases. Chemotherapy remains the only therapy regimen against TNBC. However, the emergence of innate or acquired chemoresistance has hindered the chemotherapy used to treat TNBC. The data obtained from molecular technologies have recognized TNBC with various gene profiling and mutation settings that have helped establish and develop targeted therapies. New therapeutic strategies based on the targeted delivery of therapeutics have relied on the application of biomarkers derived from the molecular profiling of TNBC patients. Several biomarkers have been found that are targets for the precision therapy in TNBC, such as EGFR, VGFR, TP53, interleukins, insulin-like growth factor binding proteins, c-MET, androgen receptor, BRCA1, glucocorticoid, PTEN, ALDH1, etc. This review discusses the various candidate biomarkers identified in the treatment of TNBC along with the evidence supporting their use. It was established that nanoparticles had been considered a multifunctional system for delivering therapeutics to target sites with increased precision. Here, we also discuss the role of biomarkers in nanotechnology translation in TNBC therapy and management.

GABAergic signaling beyond synapses: an emerging target for cancer therapy

Traditionally, γ-aminobutyric acid (GABA) is best known for its role as a primary inhibitory neurotransmitter reducing neuronal excitability in the mammalian central nervous system (CNS), thereby producing calming effects. However, an emerging body of data now supports a function for GABA beyond neurotransmission as a potent factor regulating cancer cell growth and metastasis, as well as the antitumor immune response, by shaping the tumor microenvironment (TME). Here, we review the current knowledge on GABA's effects on the function of tumor cells, tumor-immune interactions, and the underlying molecular mechanisms. Since altered GABAergic signaling is now recognized as a feature of certain types of solid tumors, we also discuss the potential of repurposing existing GABAergic agents as a new class of anticancer therapy.

Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major health problem around the world. The management of this disease is complicated by the lack of noninvasive diagnostic tools and the few treatment options available. Better clinical outcomes can be achieved if HCC is detected early, but unfortunately, clinical signs appear when the disease is in its late stages. We aim to identify novel genes that can be targeted for the diagnosis and therapy of HCC. We performed a meta-analysis of transcriptomics data to identify differentially expressed genes and applied network analysis to identify hub genes. Fatty acid metabolism, complement and coagulation cascade, chemical carcinogenesis and retinol metabolism were identified as key pathways in HCC. Furthermore, we integrated transcriptomics data into a reference human genome-scale metabolic model to identify key reactions and subsystems relevant in HCC. We conclude that fatty acid activation, purine metabolism, vitamin D, and E metabolism are key processes in the development of HCC and therefore need to be further explored for the development of new therapies. We provide the first evidence that GABRP, HBG1 and DAK (TKFC) genes are important in HCC in humans and warrant further studies.

GABAergic signaling as a potential therapeutic target in cancers

GABA is the most common inhibitory neurotransmitter in the vertebrate central nervous system. Synthesized by glutamic acid decarboxylase, GABA could specifically bind with two GABA receptors to transmit inhibition signal stimuli into cells: GABAA receptor and GABAB receptor. In recent years, emerging studies revealed that GABAergic signaling not only participated in traditional neurotransmission but was involved in tumorigenesis as well as regulating tumor immunity. In this review, we summarize the existing knowledge of the GABAergic signaling pathway in tumor proliferation, metastasis, progression, stemness, and tumor microenvironment as well as the underlying molecular mechanism. We also discussed the therapeutical advances in targeting GABA receptors to provide the theoretical basis for pharmacological intervention of GABAergic signaling in cancer treatment especially immunotherapy.

Aquaporins and Ion Channels as Dual Targets in the Design of Novel Glioblastoma Therapeutics to Limit Invasiveness

Current therapies for Glioblastoma multiforme (GBM) focus on eradicating primary tumors using radiotherapy, chemotherapy and surgical resection, but have limited success in controlling the invasive spread of glioma cells into a healthy brain, the major factor driving short survival times for patients post-diagnosis. Transcriptomic analyses of GBM biopsies reveal clusters of membrane signaling proteins that in combination serve as robust prognostic indicators, including aquaporins and ion channels, which are upregulated in GBM and implicated in enhanced glioblastoma motility. Accumulating evidence supports our proposal that the concurrent pharmacological targeting of selected subclasses of aquaporins and ion channels could impede glioblastoma invasiveness by impairing key cellular motility pathways. Optimal sets of channels to be selected as targets for combined therapies could be tailored to the GBM cancer subtype, taking advantage of differences in patterns of expression between channels that are characteristic of GBM subtypes, as well as distinguishing them from non-cancerous brain cells such as neurons and glia. Focusing agents on a unique channel fingerprint in GBM would further allow combined agents to be administered at near threshold doses, potentially reducing off-target toxicity. Adjunct therapies which confine GBM tumors to their primary sites during clinical treatments would offer profound advantages for treatment efficacy.

The delta subunit of the GABAA receptor is necessary for the GPT2-promoted breast cancer metastasis

Objectives: Glutamic pyruvate transaminase (GPT2) catalyzes the reversible transamination between alanine and α-ketoglutarate (α-KG) to generate pyruvate and glutamate during cellular glutamine catabolism. The glutamate could be further converted to γ-aminobutyric acid (GABA). However, the role of GPT2 in tumor metastasis remains unclear. Methods: The wound healing and transwell assays were carried out to analyze breast cancer cell migration and invasion in vitro. Gene ontology analysis was utilized following RNA-sequencing to discover the associated molecule function. The mass spectrometry analysis following phosphoprotein enrichment was performed to discover the associated transcription factors. Most importantly, both the tail vein model and Mammary gland conditional Gpt2^-/- spontaneous tumor mouse models were used to evaluate the effect of GPT2 on breast cancer metastasis in vivo. Results: GPT2 overexpression increases the content of GABA and promotes breast cancer metastasis by activating GABA_A receptors. The delta subunit GABRD is necessary for the GPT2/GABA-induced breast cancer metastasis in xenograft and transgenic mouse models. Gpt2 knockout reduces the lung metastasis of the genetic Gpt2^-/- breast cancer in mice and prolongs the overall survival of tumor burden mice. Mechanistically, GPT2-induced GABA_A receptor activation increases Ca²⁺ influx by turning on its associated calcium channel, and the surged intracellular calcium triggers the PKC-CREB pathway activation. The activated transcription factor CREB accelerates breast cancer metastasis by upregulating metastasis-related gene expressions, such as PODXL, MMP3, and MMP9. Conclusion: In summary, this study demonstrates that GPT2 promotes breast cancer metastasis through up-regulated GABA activation of GABA_AR-PKC-CREB signaling, suggesting it is a potential target for breast cancer therapy.

Exploring neurotransmitters and their receptors for breast cancer prevention and treatment

While psychological factors have long been linked to breast cancer pathogenesis and outcomes, accumulating evidence is revealing how the nervous system contributes to breast cancer development, progression, and treatment resistance. Central to the psychological-neurological nexus are interactions between neurotransmitters and their receptors expressed on breast cancer cells and other types of cells in the tumor microenvironment, which activate various intracellular signaling pathways. Importantly, the manipulation of these interactions is emerging as a potential avenue for breast cancer prevention and treatment. However, an important caveat is that the same neurotransmitter can exert multiple and sometimes opposing effects. In addition, certain neurotransmitters can be produced and secreted by non-neuronal cells including breast cancer cells that similarly activate intracellular signaling upon binding to their receptors. In this review we dissect the evidence for the emerging paradigm linking neurotransmitters and their receptors with breast cancer. Foremost, we explore the intricacies of such neurotransmitter-receptor interactions, including those that impinge on other cellular components of the tumor microenvironment, such as endothelial cells and immune cells. Moreover, we discuss findings where clinical agents used to treat neurological and/or psychological disorders have exhibited preventive/therapeutic effects against breast cancer in either associative or pre-clinical studies. Further, we elaborate on the current progress to identify druggable components of the psychological-neurological nexus that can be exploited for the prevention and treatment of breast cancer as well as other tumor types. We also provide our perspectives regarding future challenges in this field where multidisciplinary cooperation is a paramount requirement.

GABRP is a Promising Prognostic Biomarker and Associated with Immune Cell Infiltration in Lung Squamous Cell Carcinoma

Background

GABRP has been reported to play an oncogenic role in various carcinomas. However, no report has been found for its involvement in lung squamous cell carcinoma (LUSC) development yet. We aimed to explore the expression and prognostic roles of GABRP and assessment of its association with tumor microenvironment in LUSC.

Methods

The GABRP expression in LUSC was analyzed using TCGA, GEO, and HPA databases. The Kaplan-Meier, Cox regression analysis, and receiver operating characteristic (ROC) curve were applied to assess the prognostic and diagnostic values of GABRP in LUSC. We also performed ESTIMATE and ssGSEA to explore the association between GABRP expression and immune cell infiltrations. GABRP was highly expressed in LUSC patients, and up-regulation of GABRP was associated with shorter overall survival (OS). Cox regression analysis indicated that GABRP was an independent prognostic factor for LUSC patients. KEGG analysis revealed that GABRP may play an important role in starch and sucrose metabolism and nicotine addiction. Specifically, GABRP expression showed significant positive correlations with the infiltration levels of most types of immune cells, as well as immune checkpoint molecules expression.

Conclusion

Up-regulation of GABRP in LUSC could be severed as a prognostic marker and a potential target for immunotherapy in LUSC.

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles

BACKGROUND

Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them.

METHODS

Lehman's TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set.

RESULTS

We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug-target interactions were found among the upregulated genes in the M, IM and MSL subsets.

CONCLUSIONS

Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

Simple Summary

Breast cancer involves changes in the healthy cells of the breast resulting in rapid and abnormal division of cells that later spread to other parts of the body through the process of metastasis, which involves epithelial mesenchymal transition (EMT). Ion channels play a significant role in the switch from epithelial to mesenchymal transition through their contributions to cellular motility, cell volume regulation and cell cycle progression. Comprehensive computational analyses were performed to understand the role of ion channels in tumor/metastatic samples of breast cancer and their correlation with EMT.

Abstract

Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.

A pan-cancer analysis of the oncogenic role of Keratin 17 (KRT17) in human tumors

Background

Although new evidence from cells or animals suggests a relationship between Keratin 17 (KRT17) and cancer, no pan-cancer analysis is currently available.

Methods

The expression level of KRT17 in generalized carcinoma was detected by the Tumor Immune Estimation Resource, version 2 (TIMER2) database, and then verified the protein expression of KRT17 in different cancer species in UALCAN database, and analyzed the relationship between the expression level of KRT17 and the clinical stage and survival of different cancers. We further explored the genetic variation of KRT17 in different tumor types included in The Cancer Genome Atlas (TCGA) and the specific mutations in each domain. The changes of KRT17 protein phosphorylation levels and protein expression levels at different phosphorylation sites in different tumors were explored. TIMER2 database was used to explore the potential relationship between the infiltration level of different immune cells and KRT17 gene expression in different TCGA cancer types. Finally, the protein binding to KRT17 and genes related to KRT17 expression were explored by STRING database and TCGA database.

Results

KRT17 is overexpressed in most malignancies, and we observed a distinct relationship between KRT17 expression and tumor patient prognosis. Enhanced phosphorylation levels of S13, S24, S32, and S39 were observed in several tumors, such as lung adenocarcinoma (LUAD), colon and ovarian cancers, and uterine corpus endometrial carcinoma (UCEC). Intermediate filament cytoskeleton and keratinization may be simultaneously acting with KRT17 on tumor pathogenesis.

Conclusions

Our pan-cancer analysis provides relatively complete information on the oncogenic functions of KRT17 in various cancers.

Metabolite profiling reveals a connection between aldehyde dehydrogenase 1A3 and GABA metabolism in breast cancer metastasis

INTRODUCTION

Aldehyde dehydrogenase 1A3 (ALDH1A3) is a cancer stem cell (CSC) marker and in breast cancer it is associated with triple-negative/basal-like subtypes and aggressive disease. Studies on the mechanisms of ALDH1A3 in cancer have primarily focused on gene expression changes induced by the enzyme; however, its effects on metabolism have thus far been unstudied and may reveal novel mechanisms of pathogenesis.

OBJECTIVE

Determine how ALDH1A3 alters the metabolite profile in breast cancer cells and assess potential impacts.

METHOD

Triple-negative MDA-MB-231 tumors and cells with manipulated ALDH1A3 levels were assessed by HPLC-MS metabolomics and metabolite data was integrated with transcriptome data. Mice harboring MDA-MB-231 tumors with or without altered ALDH1A3 expression were treated with γ-aminobutyric acid (GABA) or placebo. Effects on tumor growth, and lungs and brain metastasis were quantified by staining of fixed thin sections and quantitative PCR. Breast cancer patient datasets from TCGA, METABRIC and GEO were used to assess the co-expression of GABA pathway genes with ALDH1A3.

RESULTS

Integrated metabolomic and transcriptome data identified GABA metabolism as a primary dysregulated pathway in ALDH1A3 expressing breast tumors. Both ALDH1A3 and GABA treatment enhanced metastasis. Patient dataset analyses revealed expression association between ALDH1A3 and GABA pathway genes and corresponding increased risk of metastasis.

CONCLUSION

This study revealed a novel pathway affected by ALDH1A3, GABA metabolism. Like ALDH1A3 expression, GABA treatment promotes metastasis. Given the clinical use of GABA mimics to relieve chemotherapy-induced peripheral nerve pain, further study of the effects of GABA in breast cancer progression is warranted.

An Efficient Algorithm for the Detection of Outliers in Mislabeled Omics Data

High dimensionality and noise have made it difficult to detect related biomarkers in omics data. Through previous study, penalized maximum trimmed likelihood estimation is effective in identifying mislabeled samples in high-dimensional data with mislabeled error. However, the algorithm commonly used in these studies is the concentration step (C-step), and the C-step algorithm that is applied to robust penalized regression does not ensure that the criterion function is gradually optimized iteratively, because the regularized parameters change during the iteration. This makes the C-step algorithm runs very slowly, especially when dealing with high-dimensional omics data. The AR-Cstep (C-step combined with an acceptance-rejection scheme) algorithm is proposed. In simulation experiments, the AR-Cstep algorithm converged faster (the average computation time was only 2% of that of the C-step algorithm) and was more accurate in terms of variable selection and outlier identification than the C-step algorithm. The two algorithms were further compared on triple negative breast cancer (TNBC) RNA-seq data. AR-Cstep can solve the problem of the C-step not converging and ensures that the iterative process is in the direction that improves criterion function. As an improvement of the C-step algorithm, the AR-Cstep algorithm can be extended to other robust models with regularized parameters.

The molecular mechanism of chronic stress affecting the occurrence and development of breast cancer and potential drug therapy

According to the 2020 data released by the International Agency for Research on Cancer, breast cancer has surpassed lung cancer as the world's most newly diagnosed first-time cancer. Compared with patients with other types of cancer, those with breast cancer experience greater mental stress and more severe psychological impacts because of the life-threatening diagnosis, physical changes, treatment side effects, and family and social life dysfunctions. These usually manifest as anxiety, depression, nervousness, and insomnia, all of which elicit stress responses. Particularly under chronic stress, the continuous release of neurotransmitters from the neuroendocrine system can have a highly profound impact on the occurrence and prognosis of breast cancer. However, because of the complex mechanisms underlying chronic stress and the variability in individual tolerance, evidence of the role of chronic stress in the occurrence and evolution of breast cancer remains unclear. This article reviewed previous research on the correlation between chronic stress and the occurrence and development of breast cancer, particularly the molecular mechanism through which chronic stress promotes breast cancer via neurotransmitters secreted by the nervous system. We also review the progress in the development of potential drugs or blockers for the treatment of breast cancer by targeting the neuroendocrine system.

Overexpression of GABRP Gene in Triple Negative Breast Cancer: Molecular Mechanisms and Interpretation

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease that characterized by aggressiveness features with increased metastasis and poor clinical prognosis. However, the molecular mechanisms underlying this highly malignant phenotype are still poorly understood. It has been well documented that the dysregulation of neural genes is profoundly implicated in cancer development and metastasis. Objectives: In the present study, the expression level of GABA receptor π subunit (GABRP) as the most up-regulated gene in TNBC and a hub node in the co-expression network were investigated. Methods: In this study, the importance of GABRP as the most up-regulated gene in TNBC was discovered through integrative analysis of multiple microarray expression datasets, containing about 1000 samples. Furthermore, the co-expression network analysis was constructed based on the up-regulated genes. Quantitative Real‐time polymerase chain reaction (qRT-PCR) was used to evaluate of the GABRP expression in 50 TNBC compared to 33 non-TNBC tumors. Results: According to the bioinformatics analysis, GABRP occupies a key position in the co-expression network which is mainly enriched in the nervous systems development. The qRT-PCR results indicated that up-regulation of GABRP was highly concordant with integrative analysis findings. Moreover, the receiver operating characteristic (ROC) curve analysis revealed that GABRP can be a potential biomarker to distinguish TNBC from non-TNBC samples. Conclusions: Our study revealed that up-regulation of GABRP is among the most remarkable molecular signature in TNBC and may play a critical role in tumorigenesis. The results may provide a deeper insight into molecular mechanisms underlying the brain metastasis in TNBC tumors and propose the potential targets for therapeutic interventions.

Therapeutically leveraging GABAA receptors in cancer

γ-aminobutyric acid or GABA is an amino acid that functionally acts as a neurotransmitter and is critical to neurotransmission. GABA is also a metabolite in the Krebs cycle. It is therefore unsurprising that GABA and its receptors are also present outside of the central nervous system, including in immune cells. This observation suggests that GABAergic signaling impacts events beyond brain function and possibly human health beyond neurological disorders. Indeed, GABA receptor subunits are expressed in pathological disease states, including in disparate cancers. The role that GABA and its receptors may play in cancer development and progression remains unclear. If, however, those cancers have functional GABA receptors that participate in GABAergic signaling, it raises an important question whether these signaling pathways might be targetable for therapeutic benefit. Herein we summarize the effects of modulating Type-A GABA receptor signaling in various cancers and highlight how Type-A GABA receptors could emerge as a novel therapeutic target in cancer.

Use of a human embryonic stem cell model to discover GABRP, WFDC2, VTCN1 and ACTC1 as markers of early first trimester human trophoblast

Human placental development during early pregnancy is poorly understood. Many conceptuses are lost at this stage. It is thought that preeclampsia, intrauterine growth restriction and other placental syndromes that manifest later in pregnancy may originate early in placentation. Thus, there is a need for models of early human placental development. Treating human embryonic stem cells (hESCs) with BMP4 (bone morphogenic protein 4) plus A83-01 (ACTIVIN/NODAL signaling inhibitor) and PD173074 (fibroblast growth factor 2 or FGF2 signaling inhibitor) (BAP conditions) induces differentiation to the trophoblast lineage (hESCBAP), but it is not clear which stage of trophoblast differentiation these cells resemble. Here, comparison of the hESCBAP transcriptome to those of trophoblasts from human blastocysts, trophoblast stem cells and placentas collected in the first-third trimester of pregnancy by principal component analysis suggests that hESC after 8 days BAP treatment most resemble first trimester syncytiotrophoblasts. To further test this hypothesis, transcripts were identified that are expressed in hESCBAP but not in cultures of trophoblasts isolated from term placentas. Proteins encoded by four genes, GABRP (gamma-aminobutyric acid type A receptor subunit Pi), WFDC2 (WAP four-disulfide core domain 2), VTCN1 (V-set domain containing T-cell activation inhibitor 1) and ACTC1 (actin alpha cardiac muscle 1), immunolocalized to placentas at 4-9 weeks gestation, and their expression declined with gestational age (R2 = 0.61-0.83). None are present at term. Expression was largely localized to syncytiotrophoblast of both hESCBAP cells and placental material from early pregnancy. WFDC2, VTCN1 and ACTC1 have not previously been described in placenta. These results support the hypothesis that hESCBAP represent human trophoblast analogous to that of early first trimester and are a tool for discovery of factors important to this stage of placentation.

Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is an aggressive disease. Recent studies have identified genome instability-derived genes for patient outcomes. However, most of the studies mainly focused on only one or a few genome instability-related genes. Prognostic potential and clinical significance of genome instability-associated genes in TNBC have not been well explored.

Methods

In this study, we developed a computational approach to identify TNBC prognostic signature. It consisted of (1) using somatic mutations and copy number variations (CNVs) in TNBC to build a binary matrix and identifying the top and bottom 25% mutated samples, (2) comparing the gene expression between the top and bottom 25% samples to identify genome instability-related genes, and (3) performing univariate Cox proportional hazards regression analysis to identify survival-associated gene signature, and Kaplan–Meier, log-rank test, and multivariate Cox regression analyses to obtain overall survival (OS) information for TNBC outcome prediction.

Results

From the identified 111 genome instability-related genes, we extracted a genome instability-derived gene signature (GIGenSig) of 11 genes. Through survival analysis, we were able to classify TNBC cases into high- and low-risk groups by the signature in the training dataset (log-rank test p = 2.66e−04), validated its prognostic performance in the testing (log-rank test p = 2.45e−02) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (log-rank test p = 2.57e−05) datasets, and further validated the predictive power of the signature in five independent datasets.

Conclusion

The identified novel signature provides a better understanding of genome instability in TNBC and can be applied as prognostic markers for clinical TNBC management.

GABAergic signaling by cells of the immune system: more the rule than the exception

Gamma-aminobutyric acid (GABA) is best known as an essential neurotransmitter in the evolved central nervous system (CNS) of vertebrates. However, GABA antedates the development of the CNS as a bioactive molecule in metabolism and stress-coupled responses of prokaryotes, invertebrates and plants. Here, we focus on the emerging findings of GABA signaling in the mammalian immune system. Recent reports show that mononuclear phagocytes and lymphocytes, for instance dendritic cells, microglia, T cells and NK cells, express a GABAergic signaling machinery. Mounting evidence shows that GABA receptor signaling impacts central immune functions, such as cell migration, cytokine secretion, immune cell activation and cytotoxic responses. Furthermore, the GABAergic signaling machinery of leukocytes is implicated in responses to microbial infection and is co-opted by protozoan parasites for colonization of the host. Peripheral GABA signaling is also implicated in inflammatory conditions and diseases, such as type 1 diabetes, rheumatoid arthritis and cancer cell metastasis. Adding to its role in neurotransmission, growing evidence shows that the non-proteinogenic amino acid GABA acts as an intercellular signaling molecule in the immune system and, as an interspecies signaling molecule in host–microbe interactions. Altogether, the data raise the assumption of conserved GABA signaling in a broad range of mammalian cells and diversification of function in the immune system.

GABRP sustains the stemness of triple-negative breast cancer cells through EGFR signaling

Effective treatment regimens for triple-negative breast cancer (TNBC) are relatively scarce due to a lack of specific therapeutic targets. Epidermal growth factor receptor (EGFR) signaling is highly active in TNBC and is associated with poor prognosis. Most EGFR antagonists, which significantly improve outcome in lung and colon cancer, have shown limited clinical effects in breast cancer. However, limiting EGFR expression in TNBC is a potential strategy for improving the clinical efficacy of EGFR antagonists. Here, we found that the gamma-aminobutyric acid type A receptor π subunit (GABRP), as a membrane protein enriched in TNBC stem cells, interacted with EGFR and significantly sustained its expression, resulting in stemness maintenance and chemotherapy resistance. Silencing GABRP induced down-regulation of EGFR signaling, which hindered cell stemness and enhanced sensitivity to chemotherapies, including paclitaxel, doxorubicin, and cisplatin. We also identified that retigabine, an FDA-approved drug for adjunctive treatment of seizures, increased the sensitivity of EGFR to gefitinib in gefitinib-resistant cells. Our findings show that GABRP can sustain the stemness of TNBC via modulating EGFR expression, suggesting that GABRP may be a potential therapeutic target that can address EGFR inhibitor resistance in TNBC.

A Case Control Study on Serum Levels of Potential Biomarkers in Male Breast Cancer Patients

The global incidence of breast cancer among men is steadily growing. Despite this, compared to female breast cancer patients, there are very few studies on biomarkers in male breast cancer patients. A cross-sectional case control study was carried out to determine the serum levels of melatonin, ghrelin, dopamine, serotonin, epinephrine, and GABA in male breast cancer. All the recruited patients were obese, old, and had recently been diagnosed with the disease. They had not received any treatment for the cancer until the time of the study. Melatonin and epinephrine serum levels were significantly higher in breast cancer patients compared to their age-matched controls, whereas ghrelin, dopamine, GABA, and serotonin serum levels were lower in patients compared to the control group. The serum levels of most of the studied biomarkers in male breast cancer patients were similar to those observed in female breast cancer patients, except for serum melatonin levels.

The Emerging Roles of π Subunit-Containing GABAA Receptors in Different Cancers

Cancer is one of the leading causes of death in both developed and developing countries. Due to its heterogenous nature, it occurs in various regions of the body and often goes undetected until later stages of disease progression. Feasible treatment options are limited because of the invasive nature of cancer and often result in detrimental side-effects and poor survival rates. Therefore, recent studies have attempted to identify aberrant expression levels of previously undiscovered proteins in cancer, with the hope of developing better diagnostic tools and pharmaceutical options. One class of such targets is the π-subunit-containing γ-aminobutyric acid type A receptors. Although these receptors were discovered more than 20 years ago, there is limited information available. They possess atypical functional properties and are expressed in several non-neuronal tissues. Prior studies have highlighted the role of these receptors in the female reproductive system. New research focusing on the higher expression levels of these receptors in ovarian, breast, gastric, cervical, and pancreatic cancers, their physiological function in healthy individuals, and their pro-tumorigenic effects in these cancer types is reviewed here.

A motogenic GABAergic system of mononuclear phagocytes facilitates dissemination of coccidian parasites

Gamma-aminobutyric acid (GABA) serves diverse biological functions in prokaryotes and eukaryotes, including neurotransmission in vertebrates. Yet, the role of GABA in the immune system has remained elusive. Here, a comprehensive characterization of human and murine myeloid mononuclear phagocytes revealed the presence of a conserved and tightly regulated GABAergic machinery with expression of GABA metabolic enzymes and transporters, GABA-A receptors and regulators, and voltage-dependent calcium channels. Infection challenge with the common coccidian parasites Toxoplasma gondii and Neospora caninum activated GABAergic signaling in phagocytes. Using gene silencing and pharmacological modulators in vitro and in vivo in mice, we identify the functional determinants of GABAergic signaling in parasitized phagocytes and demonstrate a link to calcium responses and migratory activation. The findings reveal a regulatory role for a GABAergic signaling machinery in the host-pathogen interplay between phagocytes and invasive coccidian parasites. The co-option of GABA underlies colonization of the host by a Trojan horse mechanism.

A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression

Adrenocortical carcinoma (ACC) is a rare but deadly cancer for which few treatments exist. Here, we have undertaken a targeted bioinformatics study of The Cancer Genome Atlas (TCGA) ACC dataset focusing on the 30 genes encoding the γ-aminobutyric acid (GABA) system—an under-studied, evolutionarily-conserved system that is an emerging potential player in cancer progression. Our analysis identified a subset of ACC patients whose tumors expressed a distinct GABA system transcriptome. Transcript levels of ABAT (encoding a key GABA shunt enzyme), were upregulated in over 40% of tumors, and this correlated with several favorable clinical outcomes including patient survival; while enrichment and ontology analysis implicated two cancer-related biological pathways involved in metastasis and immune response. The phenotype associated with ABAT upregulation revealed a potential metabolic heterogeneity among ACC tumors associated with enhanced mitochondrial metabolism. Furthermore, many GABA_A receptor subunit-encoding transcripts were expressed, including two (GABRB2 and GABRD) prognostic for patient survival. Transcripts encoding GABA_B receptor subunits and GABA transporters were also ubiquitously expressed. The GABA system transcriptome of ACC tumors is largely mirrored in the ACC NCI-H295R cell line, suggesting that this cell line may be appropriate for future functional studies investigating the role of the GABA system in ACC cell growth phenotypes and metabolism.

Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data

Background

Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the identification of reliable biomarkers for a particular disease. Three methods have been proposed to address the problem: sparse label-noise-robust logistic regression (Rlogreg), robust elastic net based on the least trimmed square (enetLTS), and Ensemble. Ensemble is an ensembled classification based on distinct feature selection and modeling strategies. The accuracy of biomarker selection and outlier detection of these methods needs to be evaluated and compared so that the appropriate method can be chosen.

Results

The accuracy of variable selection, outlier identification, and prediction of three methods (Ensemble, enetLTS, Rlogreg) were compared for simulated and an RNA-seq dataset. On simulated datasets, Ensemble had the highest variable selection accuracy, as measured by a comprehensive index, and lowest false discovery rate among the three methods. When the sample size was large and the proportion of outliers was ≤5%, the positive selection rate of Ensemble was similar to that of enetLTS. However, when the proportion of outliers was 10% or 15%, Ensemble missed some variables that affected the response variables.

Overall, enetLTS had the best outlier detection accuracy with false positive rates < 0.05 and high sensitivity, and enetLTS still performed well when the proportion of outliers was relatively large. With 1% or 2% outliers, Ensemble showed high outlier detection accuracy, but with higher proportions of outliers Ensemble missed many mislabeled samples. Rlogreg and Ensemble were less accurate in identifying outliers than enetLTS. The prediction accuracy of enetLTS was better than that of Rlogreg. Running Ensemble on a subset of data after removing the outliers identified by enetLTS improved the variable selection accuracy of Ensemble.

Conclusions

When the proportion of outliers is ≤5%, Ensemble can be used for variable selection. When the proportion of outliers is > 5%, Ensemble can be used for variable selection on a subset after removing outliers identified by enetLTS. For outlier identification, enetLTS is the recommended method. In practice, the proportion of outliers can be estimated according to the inaccuracy of the diagnostic methods used.

Four genes predict the survival of osteosarcoma patients based on TARGET database

Osteosarcoma represents one of the most aggressive tumors of bone among adolescents and young adults. Despite improvements in treatment, osteosarcoma has a grave prognosis. The identification of prognostic factors is still in its infancy. Weighted gene correlation network analysis (WGCNA) was conducted on mRNA-sequencing and clinical information (gender, survival and metastasis) of osteosarcoma patients from the TARGET database to obtain genes in modules associated with metastasis of osteosarcoma. The Cox regression analysis was then performed on the gene expression profile from TARGET to screen genes associated with patients' survival. Known genes related to osteosarcoma were obtained by intersecting osteosarcoma-related genes from DisGeNET and DiGSeE, followed by the construction of PPI network of osteosarcoma-related genes and survival-related genes in modules. The screened key genes were subject to multi-factor Cox proportional hazards model, and osteosarcoma patients were classified into high- and low- risk groups according to the risk score to evaluate the potential of key genes to predict the survival of osteosarcoma patients. The WGCNA showed that 4 genes in tan and 19 genes in pink modules were related to the survival of osteosarcoma patients. Osteosarcoma-related known genes (9) were obtained in intersection of DisGeNET and DiGSeE. PPI network identified 4 key genes (KRT5, HIPK2, MAP3K5 and CD5) closely associated with survival of osteosarcoma patients. HIPK2, MAP3K5 and CD5 expression was inversely correlated with survival risk, while KRT5 expression was positively correlated with survival risk. These results show KRT5, HIPK2, MAP3K5 and CD5 serve as prognostic factors of osteosarcoma patients.

Small Molecules as Drugs to Upregulate Metastasis Suppressors in Cancer Cells

It is well-recognized that the majority of cancer-related deaths is attributed to metastasis, which can arise from virtually any type of tumor. Metastasis is a complex multistep process wherein cancer cells must break away from the primary tumor, intravasate into the circulatory or lymphatic systems, extravasate, proliferate and eventually colonize secondary sites. Since these molecular processes involve the coordinated actions of numerous proteins, targeted disruptions of key players along these pathways represent possible therapeutic interventions to impede metastasis formation and reduce cancer mortality. A diverse group of proteins with demonstrated ability to inhibit metastatic colonization have been identified and they are collectively known as metastasis suppressors. Given that the metastasis suppressors are often downregulated in tumors, drug-induced re-expression or upregulation of these proteins represents a promising approach to limit metastasis. Indeed, over 40 compounds are known to exhibit efficacy in upregulating the expression of metastasis suppressors via transcriptional or post-transcriptional mechanisms, and the most promising ones are being evaluated for their translational potentials. These small molecules range from natural products to drugs in clinical use and they apparently target different molecular pathways, reflecting the diverse nature of the metastasis suppressors. In this review, we provide an overview of the different classes of compounds known to possess the ability to upregulate one or more metastasis suppressors, with an emphasis on their mechanisms of action and therapeutic potentials.

Multiplatform biomarker identification using a data-driven approach enables single-sample classification

BACKGROUND

High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify a set of reliable and reproducible biomarkers across various gene expression platforms and laboratories for single sample diagnosis and prognosis. We address this need with our Data-Driven Reference (DDR) approach, which employs stably expressed housekeeping genes as references to eliminate platform-specific biases and non-biological variabilities.

RESULTS

Our method identifies biomarkers with "built-in" features, and these features can be interpreted consistently regardless of profiling technology, which enable classification of single-sample independent of platforms. Validation with RNA-seq data of blood platelets shows that DDR achieves the superior performance in classification of six different tumor types as well as molecular target statuses (such as MET or HER2-positive, and mutant KRAS, EGFR or PIK3CA) with smaller sets of biomarkers. We demonstrate on the three microarray datasets that our method is capable of identifying robust biomarkers for subgrouping medulloblastoma samples with data perturbation due to different microarray platforms. In addition to identifying the majority of subgroup-specific biomarkers in CodeSet of nanoString, some potential new biomarkers for subgrouping medulloblastoma were detected by our method.

CONCLUSIONS

In this study, we present a simple, yet powerful data-driven method which contributes significantly to identification of robust cross-platform gene signature for disease classification of single-patient to facilitate precision medicine. In addition, our method provides a new strategy for transcriptome analysis.

Coupled Genome-Wide DNA Methylation and Transcription Analysis Identified Rich Biomarkers and Drug Targets in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) has poor clinical prognosis. Lack of TNBC-specific biomarkers prevents active clinical intervention. We reasoned that TNBC must have its specific signature due to the lack of three key receptors to distinguish TNBC from other types of breast cancer. We also reasoned that coupling methylation and gene expression as a single unit may increase the specificity for the detected TNBC signatures. We further reasoned that choosing the proper controls may be critical to increasing the sensitivity to identify TNBC-specific signatures. Furthermore, we also considered that specific drugs could target the detected TNBC-specific signatures. We developed a system to identify potential TNBC signatures. It consisted of (1) coupling methylation and expression changes in TNBC to identify the methylation-regulated signature genes for TNBC; (2) using TPBC (triple-positive breast cancer) as the control to detect TNBC-specific signature genes; (3) searching in the drug database to identify those targeting TNBC signature genes. Using this system, we identified 114 genes with both altered methylation and expression, and 356 existing drugs targeting 10 of the 114 genes. Through docking and molecular dynamics simulation, we determined the structural basis between sapropterin, a drug used in the treatment of tetrahydrobiopterin deficiency, and PTGS2, a TNBC signature gene involved in the conversion of arachidonic acid to prostaglandins. Our study reveals the existence of rich TNBC-specific signatures, and many can be drug target and biomarker candidates for clinical applications.

GABRP regulates chemokine signalling, macrophage recruitment and tumour progression in pancreatic cancer through tuning KCNN4-mediated Ca2+ signalling in a GABA-independent manner

BACKGROUND AND AIMS

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related death worldwide. Neurotransmitter-initiated signalling pathway is profoundly implicated in tumour initiation and progression. Here, we investigated whether dysregulated neurotransmitter receptors play a role during pancreatic tumourigenesis.

METHODS

The Cancer Genome Atlas and Gene Expression Omnibus datasets were used to identify differentially expressed neurotransmitter receptors. The expression pattern of gamma-aminobutyric acid type A receptor pi subunit (GABRP) in human and mouse PDAC tissues and cells was studied by immunohistochemistry and western blot analysis. The in vivo implications of GABRP in PDAC were tested by subcutaneous xenograft model and lung metastasis model. Bioinformatics analysis, transwell experiment and orthotopic xenograft model were used to identify the in vitro and in vivo effects of GABRP on macrophages in PDAC. ELISA, co-immunoprecipitation, proximity ligation assay, electrophysiology, promoter luciferase activity and quantitative real-time PCR analyses were used to identify molecular mechanism.

RESULTS

GABRP expression was remarkably increased in PDAC tissues and associated with poor prognosis, contributed to tumour growth and metastasis. GABRP was correlated with macrophage infiltration in PDAC and pharmacological deletion of macrophages largely abrogated the oncogenic functions of GABRP in PDAC. Mechanistically, GABRP interacted with KCNN4 to induce Ca²⁺ entry, which leads to activation of nuclear factor κB signalling and ultimately facilitates macrophage infiltration by inducing CXCL5 and CCL20 expression.

CONCLUSIONS

Overexpressed GABRP exhibits an immunomodulatory role in PDAC in a neurotransmitter-independent manner. Targeting GABRP or its interaction partner KCNN4 may be an effective therapeutic strategy for PDAC.

Identification and Validation of a Novel Biologics Target in Triple Negative Breast Cancer

The goal of this study was to identify a novel target for antibody-drug conjugate (ADC) development in triple negative breast cancer (TNBC), which has limited treatment options, using gene expression datasets and in vitro siRNA/CRISPR and in vivo functional assays. We analyzed 4467 breast cancers and identified GABRP as top expressed gene in TNBC with low expression in most normal tissues. GABRP protein was localized to cell membrane with broad range of receptors/cell (815–53,714) and expressed by nearly half of breast cancers tissues. GABRP gene knockdown inhibited TNBC cell growth and colony formation in vitro and growth of MDA-MB-468 xenografts in nude mice. Commercially available anti-GABRP antibody (5–100 μg/ml) or de novo generated Fabs (20 μg/ml) inhibited TNBC cell growth in vitro. The same antibody conjugated to mertansine (DM1) also showed significant anticancer activity at nanomolar concentrations. Our results indicate that GABRP is a potential novel therapeutic target for ADC development.

ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction

BACKGROUND

Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information.

RESULTS

In this paper, a novel supervised feature scoring method named ClearF is proposed. The proposed method is suitable for continuous-valued data, which is similar to the principle of feature selection using mutual information, with the added advantage of a reduced computation time. The proposed score calculation is motivated by the association between the reconstruction error and the information-theoretic measurement. Our method is based on class-wise low-dimensional embedding and the resulting reconstruction error. Given multi-class datasets such as a case-control study dataset, low-dimensional embedding is first applied to each class to obtain a compressed representation of the class, and also for the entire dataset. Reconstruction is then performed to calculate the error of each feature and the final score for each feature is defined in terms of the reconstruction errors. The correlation between the information theoretic measurement and the proposed method is demonstrated using a simulation. For performance validation, we compared the classification performance of the proposed method with those of various algorithms on benchmark datasets.

CONCLUSIONS

The proposed method showed higher accuracy and lower execution time than the other established methods. Moreover, an experiment was conducted on the TCGA breast cancer dataset, and it was confirmed that the genes with the highest scores were highly associated with subtypes of breast cancer.

Invadopodia are chemosensing protrusions that guide cancer cell extravasation to promote brain tropism in metastasis

Invadopodia are cell protrusions that mediate cancer cell extravasation but the microenvironmental cues and signaling factors that induce invadopodia formation during extravasation remain unclear. Using intravital imaging and loss of function experiments, we determined invadopodia contain receptors involved in chemotaxis, namely GABA receptor and EGFR. These chemotaxis capabilities are mediated in part by PAK1 which controls invadopodia responsiveness to ligands such as GABA and EGF via assembly, stability, and turnover of invadopodia in vivo. PAK1 knockdown rendered cells unresponsive to chemotactic stimuli present in the stroma, resulting in dramatically lower rates of cancer cell extravasation and metastatic colony formation compared to stimulated cancer cells. In an experimental mouse model of brain metastasis, inhibition of PAK1 significantly reduced overall tumor burden and reduced the average size of brain metastases. In summary, invadopodia contain chemotaxis receptors that can respond to microenvironmental cues to guide cancer cell extravasation, and when PAK1 is depleted, brain tropism of metastatic breast cancer cells is significantly reduced, blocking secondary colony growth at sites otherwise permissive for metastatic outgrowth.

Profiling of GABAA and GABAB receptor expression in the myometrium of the human uterus

AIMS

γ-aminobutyric acid (GABA) mediates its physiological effects through the GABA_A and GABA_B receptors. In this study the putative expression of GABA_AR and GABA_BR subunits in human myometrium tissue was investigated.

MAIN METHODS

The expression levels of the 19 GABA_AR subunits (α₁-α₆, β₁-β₃, γ₁-γ₃, δ, ε, π, θ, ρ₁-ρ₃) and the three GABA_BR subunits (GABA_B1a, GABA_B1b, GABA_B2) were characterized by RT-qPCR analysis on two commercial samples and six samples derived from surgically removed myometrial tissues from different women. We probed for functional GABA_AR expression in primary human myometrial smooth muscle cells (HMSMCs) by whole-cell patch-clamp electrophysiology.

KEY FINDINGS

The absolute mRNA levels of the 22 GABA_AR and GABA_BR genes varied considerably across the eight samples, but a pronounced overlap existed between the specific subunits detected in the samples, with α₂, β₂, β₃, ε, π, θ, GABA_B1a and GABA_B1b mRNAs being detected in most samples. The expression profile of GABA_AR and GABA_BR subunit mRNAs in HMSMCs correlated with that observed in the eight tissue samples, albeit the subunit transcripts were detected at lower relative levels. Neither muscimol nor GABA evoked significant currents in these cells in the patch-clamp recordings.

SIGNIFICANCE

While the expression of the GABA_B1 subunits on their own is unlikely to give rise to functional GABA_BR expression, the GABA_AR subunits identified at mRNA level would be able to form functional receptors in the human myometrial tissue. Although GABA_AR-mediated currents could not be recorded from HMSMCs in this study, this suggests a role for GABAergic transmission in the human myometrium.

A novel microRNA signature predicts survival in liver hepatocellular carcinoma after hepatectomy

Liver hepatocellular carcinoma (LIHC) is the most common type of primary liver cancer. In the current study, genome-wide miRNA-Seq and mRNA profiles in 318 LIHC patients derived from The Cancer Genome Atlas (TCGA) were analysed to identify miRNA-based signatures for LIHC prognosis with survival analysis and a semi-supervised principal components (SPC) method. A seven-miRNA signature was confirmed for overall survival (OS) prediction by comparing miRNA profiles in paired primary tumour and solid tumour normal tissues. Thereafter, a linear prognostic model that consisted of seven miRNAs was established and used to divide patients into high- and low-risk groups according to prognostic scores. Subsequent Kaplan-Meier analysis revealed that the seven-miRNA signature correlated with a good predictive clinical outcome for 5-year survival in LIHC patients. Additionally, this miRNA-based prognostic model could also be used for OS prognosis of LIHC patients in early stages, which could guide the future therapy of those patients and promote the OS rate. Moreover, the seven-miRNA signature was an independent prognostic factor. In conclusion, this signature may serve as a prognostic biomarker and guide LIHC therapy, and it could even be used as an LIHC therapeutic target in the future.

Robust method for identification of prognostic gene signatures from gene expression profiles

In the last decade, many attempts have been made to use gene expression profiles to identify prognostic genes for various types of cancer. Previous studies evaluating the prognostic value of genes suffered by failing to solve the critical problem of classifying patients into different risk groups based on specific gene expression threshold levels. Here, we present a novel method, called iterative patient partitioning (IPP), which was inspired by the receiver operating characteristic (ROC) curve, is based on the log-rank test and overcomes the threshold decision problem. We applied IPP to analyze datasets pertaining to various subtypes of breast cancer. Using IPP, we discovered both novel and well-studied prognostic genes related to cell cycle/proliferation or the immune response. The novel genes were further analyzed using copy-number alteration and mutation data, and these results supported their relationship with prognosis.