Overexpression of SLC6A1 associates with drug resistance and poor prognosis in prostate cancer

Structural Studies of the Taurine Transporter: A Potential Biological Target from the GABA Transporter Subfamily in Cancer Therapy

The taurine transporter (TauT, SLC6A6) is a member of the solute carrier 6 (SLC6) family, which plays multiple physiological roles. The SLC6 family is divided into four subfamilies: GABA (γ-aminobutyric acid), monoamine, glycine and neutral amino acid transporters. Proteins from the GABA group, including the taurine transporter, are primarily considered therapeutic targets for treating central nervous system disorders. However, recent studies have suggested that inhibitors of SLC6A6 could also serve as anticancer agents. Overexpression of TauT has been associated with the progression of colon and gastric cancer. The pool of known ligands of this transporter is limited and the exact spatial structure of taurine transporter remains unsolved. Understanding its structure could aid in the development of novel inhibitors. Therefore, we utilized homology modelling techniques to create models of TauT. Docking studies and molecular dynamics simulations were conducted to describe protein-ligand interactions. We compared the obtained information for TauT with literature data on other members of the GABA transporter group. Our in silico analysis allowed us to characterize the transporter structure and point out amino acids crucial for ligand binding: Glu406, Gly62 and Tyr138. The significance of selected residues was confirmed through structural studies of mutants. These results will aid in the development of novel taurine transporter inhibitors, which can be explored as anticancer agents.

Innate differences in the molecular signature of normal inferior & superior human parathyroid glands: potential implications for parathyroid adenoma

Primary hyperparathyroidism is a common endocrine disorder. Interestingly, the majority (75%) of parathyroid tumors are localized to the inferior parathyroid glands. To date, the reason for this natural bias has not been investigated. We assessed the global gene expression profile of superior and inferior glands obtained from forensic autopsies. The genes with significant differential expression between superior and inferior parathyroids were further assessed by RT-PCR in 19 pairs. As an iterative approach, additional genes with an established role in parathyroid disorders, i.e., CASR, MAFB, PAX9, TBCE, TBX1, VDR, MEN1, CCND1, and CDC73 were also evaluated by RT-PCR in all 19 pairs of superior and inferior parathyroid glands. Seven homeobox genes, namely HOXA4, HOXA5, HOXBAS3, HOXB4, HOXB6, HOXB9, IRX1, and one encoding for ALDH1A2 showed a lower expression in the inferior parathyroid glands than in the superior. Conversely, SLC6A1 showed a higher expression in the inferior glands. Of the nine genes with significant differential mRNA expression among superior and inferior glands HOXB9, HOXB4 and IRX1 could be detected by western blotting/mass spectrometry. The study is the first to show the differential expression of nine genes HOXA4, HOXA5, HOXBAS3, HOXB4, HOXB6, HOXB9, IRX1, ALDH1A2, and SLC6A1 in inferior versus the superior parathyroid glands. This could have potential implications for the preferential localization of parathyroid tumors to the inferior parathyroid glands as observed in patients with primary hyperparathyroidism.

A novel risk score model based on gamma-aminobutyric acid signature predicts the survival prognosis of patients with breast cancer

Background

Gamma-aminobutyric acid (GABA) participates in the migration, differentiation, and proliferation of tumor cells. However, the GABA-related risk signature has never been investigated. Hence, we aimed to develop a reliable gene signature based on GABA pathways-related genes (GRGs) to predict the survival prognosis of breast cancer patients.

Methods

GABA-related gene sets were acquired from the MSigDB database, while mRNA gene expression profiles and corresponding clinical data of breast cancer patients were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate Cox regression analysis was used to identify prognostic-associated GRGs. Subsequently, LASSO analysis was applied to establish a risk score model. We also constructed a clinical nomogram to perform the survival evaluation. Besides, ESTIMATE and ssGSEA algorithms were used to assess the immune cell infiltration among the risk score subgroups.

Results

A GRGs-related risk score model was constructed in the TCGA cohort, and validated in the GSE21653 cohort. The risk score was significantly related to the overall survival of breast cancer patients, which could predict the survival prognosis of breast cancer patients independently of other clinical features. Breast cancer patients in the low-risk score group exhibited higher immune cell infiltration levels.

Conclusion

A novel prognostic model containing five GRGs could accurately predict the survival prognosis and immune infiltration of breast cancer patients. Our findings provided a novel insight into investigating the immunoregulation roles of GRGs.

A draft conceptual model of SLC6A1 neurodevelopmental disorder

Introduction

SLC6A1 Neurodevelopmental Disorder (SLC6A1-NDD), first described in 2015, is a rare syndrome caused by a mutation in the SLC6A1 gene which encodes for the GABA Transporter 1 (GAT-1) protein. Epilepsy is one of the most common symptoms in patients and is often the primary treatment target, though the severity of epilepsy is variable. The impact of seizures and other symptoms of SLC6A1-NDD on patients and caregivers is wide-ranging and has not been described in a formal disease concept study.

Methods

A literature search was performed using the simple search term, "SLC6A1." Papers published before 2015, and those which did not describe the human neurodevelopmental disorder were removed from analysis. Open-ended interviews on lived experiences were conducted with two patient advocate key opinion leaders. An analysis of de-identified conversations between families of people with SLC6A1-NDD on social media was performed to quantify topics of concern.

Results

Published literature described symptoms in all of the following domains: neurological, visual, motor, cognitive, communication, behavior, gastrointestinal, sleep, musculo-skeletal, and emotional in addition to epilepsy. Key opinion leaders noted two unpublished features: altered hand use in infants, and developmental regression with onset of epilepsy. Analysis of social media interactions confirmed that the core symptoms of epilepsy and autistic traits were prominent concerns, but also demonstrated that other symptoms have a large impact on family life.

Discussion

For rare diseases, analysis of published literature is important, but may not be as comprehensive as that which can be gleaned from spontaneous interactions between families and through qualitative interviews. This report reflects our current understanding of the lived experience of SLC6A1-NDD. The discrepancy between the domains of disease reported in the literature and those discussed in patient conversations suggests that a formal qualitative interview-based disease concept study of SLC6A1-NDD is warranted.

Establishment of a five-enzalutamide-resistance-related-gene-based classifier for recurrence-free survival predicting of prostate cancer

To identify prostate cancer (PCa) patients with a high risk of recurrence is critical before delivering adjuvant treatment. We developed a classifier based on the Enzalutamide treatment resistance‐related genes to assist the currently available staging system in predicting the recurrence‐free survival (RFS) prognosis of PCa patients. We overlapped the DEGs from two datasets to obtain a more convincing Enzalutamide‐resistance‐related‐gene (ERRG) cluster. The five‐ERRG‐based classifier obtained good predictive values in both the training and validation cohorts. The classifier precisely predicted RFS of patients in four cohorts, independent of patient age, pathological tumour stage, Gleason score and PSA levels. The classifier and the clinicopathological factors were combined to construct a nomogram, which had an increased predictive accuracy than that of each variable alone. Besides, we also compared the differences between high‐ and low‐risk subgroups and found their differences were enriched in cancer progression‐related pathways. The five‐ERRG‐based classifier is a practical and reliable predictor, which adds value to the existing staging system for predicting the RFS prognosis of PCa after radical prostatectomy, enabling physicians to make more informed treatment decisions concerning adjuvant therapy.

Neurotransmitter release cycle-related genes predict the prognosis of lung adenocarcinoma

Because of the limitations of therapeutic approaches, patients suffering from lung adenocarcinoma (LUAD) have unsatisfactory prognoses. Studies have shown that neurotransmitters participated in tumorigenesis and development. In LUAD, the expression of neurotransmitter release cycle-related genes (NRCRGs) has been reported to be disordered. This study aimed to study the correlation between NRCRGs and LUAD. In this study, based on the Cancer Genome Atlas cohort, consensus clustering analyses were performed on ten neurotransmitter release cycle-related (NRCR) differentially expressed genes. Neurotransmitter release cycle (NRC) scores were derived by the Least Absolute Shrinkage and Selection Operator-Cox regression model constituted by 3 NRCRGs. Univariate and multivariate Cox regression analyses were performed to evaluate the prognosis value of the NRC score. In addition, single-Sample Gene Set Enrichment Analysis and CIBERSORT were conducted in the Cancer Genome Atlas cohort. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses were also performed. As a result, the NRC-low group showed a good prognosis instead of the NRC-high group. NRC score was identified to be an independent prognosis factor for LUAD. In general, the NRC score based on the prognostic model was found to be closely correlated with immunotherapy-related anti-cancer immunity and inflamed tumor microenvironment. Functional enrichment results demonstrated that differentially expressed genes between 2 NRC groups were closely correlated with DNA replication, cell-substrate adhesion, Golgi vesicle transport, MAPK signal pathway, and many others. Novel biomarkers were offered for predicting the prognoses of LUAD patients. The NRC score might contribute to guiding LUAD patients with immunotherapy selection.

Integrated Analysis of DNA Repair Genes Identifies SLC6A1 as a New Marker for the Clinical Outcome of Patients with Colorectal Cancer

Colorectal cancer (CRC) remains an important malignancy worldwide with poor prognosis. It has been known that DNA repair genes are involved in the development and progression of various tumors. Therefore, the purpose of this study was to explore DNA repair gene-based prognostic biomarkers for CRC. In this study, the expressing pattern and prognostic values of DNA repair genes in CRC patients were analyzed using TCGA database. GO and KEGG enrichment analyses were conducted to clarify the functional roles of dysregulated genes. We observed 358 differentially expressed DNA repair genes in CRC specimens, including 84 downregulated genes and 275 upregulated genes. 36 survival-related DNA repair genes were correlated with CRC patients' five-year survival, including 6 low-risk genes and 30 high-risk genes. Among the 10 overlapping genes, we focused on SLC6A1 which was highly expressed in CRC, and multivariate analysis confirmed that SLC6A1 expression as well as age and clinical stage could be regarded as an independent predicting factor for CRC prognosis. KEGG assays revealed that SLC6A1 may influence the clinical progression via regulating TGF-beta and PI3K-Akt signaling pathways. In addition, we observed that SLC6A1 was negatively regulated by SLC6A1 methylation, leading to its low expression in CRC specimens. Overall, SLC6A1 is upexpressed in CRC and can be used as a marker of poor prognosis in CRC patients.

A miR-212-3p/SLC6A1 Regulatory Sub-Network for the Prognosis of Hepatocellular Carcinoma

Introduction

Hepatocellular carcinoma (HCC) is a liver cancer with a poor prognosis. Owing to the complexity and limited pathogenic mechanism research on HCC, the molecular targeted therapy has been hindered.

Methods

In this study, we categorized transcriptome data into low-Myc and high-Myc expression groups in 365 HCC samples, screened the differentially expressed RNAs, including 441 DE-lncRNAs, 99 DE-miRNAs and 612 DE-mRNAs, constructed a lncRNA-miRNA-mRNA regulatory network, and selected a hub triple regulatory network through cytoHubba analysis. Through Gene ontology and KEGG pathway, a hub regulatory network was particularly enriched in the “Wnt signaling pathway” and “Cytochrome P450-arranged by substrate type” by Metascape. The prognostic genes in the hub regulatory network were evaluated by the RNA expression analysis, Kaplan–Meier (KM) survival analysis, and correlation analysis.

Results

The results showed that miR-212-3p/SLC6A1 axis was a potential prognostic model for HCC. Furthermore, IHC analysis showed down-regulated expression of SLC6A1 in HCC tissues and Alb-Cre;Myc mouse liver cancer tissues. The genetics and epigenetic analysis indicated that SLC6A1 expression was negatively correlated with DNA methylation. Immune infiltration analysis showed a negative relation between SLC6A1 and T cell exhaustion/monocyte in liver cancer tissues.

Conclusion

In summary, the study revealed that miR-212-3p/SLC6A1 axis could serve as a crucial therapeutic target for HCC.

Construction of a Myc-associated ceRNA network reveals a prognostic signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an extremely lethal disease worldwide. High-throughput methods have revealed global transcriptome dysregulation; however, a comprehensive investigation of the complexity and behavioral characteristics of the competing endogenous RNA (ceRNA) network in HCC is lacking. In this study, we extracted the transcriptome (RNA) sequencing data of 371 HCC patients from The Cancer Genome Atlas platform. With the comparison of the high Myc expression (Myc^high) tumor and low Myc expression (Myc^low) tumor groups in HCC, we identified 1,125 differentially expressed (DE) mRNAs, 589 long non-coding RNAs (lncRNAs), and 93 microRNAs (miRNAs). DE RNAs predicted the interactions necessary to construct an associated Myc ceRNA network, including 19 DE lncRNAs, 5 miRNAs, and 72 mRNAs. We identified a significant signature (long intergenic non-protein-coding [LINC] RNA 2691 [LINC02691] and LINC02499) that effectively predicted overall survival and had protective effects. The target genes of microRNA (miR)-212-3p predicted to intersect with DE mRNAs included SEC14-like protein 2 (SEC14L2) and solute carrier family 6 member 1 (SLC6A1), which were strongly correlated with survival and prognosis. With the use of the lncRNA-miRNA-mRNA axis, we constructed a ceRNA network containing four lncRNAs (LINC02691, LINC02499, LINC01354, and NAV2 antisense RNA 4), one miRNA (miR-212-3p), and two mRNAs (SEC14L2 and SLC6A1). Overall, we successfully constructed a mutually regulated ceRNA network and identified potential precision-targeted therapies and prognostic biomarkers.

SLC6A8 is involved in the progression of non-small cell lung cancer through the Notch signaling pathway

Background

Solute carrier family 6 member 8 (SLC6A8) is known to be involved in the development of human tumors; however, the effect of SLC6A8 on the growth of non-small cell lung cancer (NSCLC) remains unclear. Here, we explored the role and potential action mechanism of SLC6A8 in NSCLC.

Methods

We used public databases [Oncomine, Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA)] to explore the expression of SLC6A8 in NSCLC. Additionally, we used immunohistochemistry to detect the expression of SLC6A8 in NSCLC clinicopathological tissues (cancer and adjacent tissues) and Western blotting to detect the expression of SLC6A8 in NSCLC clinicopathological tissues, NSCLC cell lines (A549, H1299, H520, and H1975), and a normal epithelial cell line (BEAS-2B). Using overexpression and knockdown of the SLC6A8 gene, we analyzed the in vitro effects of SLC6A8 on the proliferation, invasion, and epithelial-mesenchymal transition (EMT) of NSCLC and also the possible molecular mechanism with Notch signaling pathway.

Results

Bioinformatic analysis demonstrated that SLC6A8 is highly expressed in NSCLC and is related to poor prognosis. We found that the expression of the SLC6A8 protein in human lung cancer tissues was significantly higher than that in adjacent tissues. In addition, it was also significantly higher in lung cancer cell lines (A549, H1299, H520, and H1975) than that in normal lung epithelium-BEAS-2B. Moreover, SLC6A8 overexpression promotes the proliferation, migration and invasion in vitro in NSCLC, accompanied by the activation of notch signaling pathway and the up-regulation of MMP9 and E-cadherin proteins. Knocking down SLC6A8 can inhibit the above effects on cells.

Conclusions

SLC6A8 promotes the malignant progression of NSCLC and activates the Notch signaling pathway. Therefore, SLC6A8 is expected to become a molecular target for NSCLC treatment.