Enhanced expression of GABRD predicts poor prognosis in patients with colon adenocarcinoma

The Diagnostic and Prognostic Value of Neurotransmitter Receptor-Related Genes in Colon Adenocarcinoma

Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality in the world. This study aimed to find receptor-related genes (NRGs) with diagnostic and prognostic value in colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) and the Human Protein Atlas database databases were applied to find differential expression NRGs between COAD and normal colonic tissues. Subsequently, Cox regression analysis and minimum absolute contraction and selection operator algorithm were used to construct a prognosis nomogram based on TCGA and Gene Expression Omnibus databases. Expression levels of 35 NRGs were significant differences in COAD and normal colonic tissues. ROC curves showed that 24 NRGs had high diagnostic accuracy (AUC > 0.850) in COAD. Risk score was constructed based on 10 NRGs for the first time. Cox regression analysis revealed risk score was an independent risk factor and a higher risk score predicts a later TNM stage. Finally, a prognostic nomogram containing risk score and clinical features was established. Calibration curves and C-index suggested the powerful predictable value of the model. This study identified the NRGs with diagnostic value and prognostic value, providing a direction for treatment of COAD patients.

UCN-Centric Prognostic Model for Predicting Overall Survival and Immune Response in Colorectal Cancer

Colorectal cancer (CRC), a prevalent malignancy, ranks third in global incidence and second in mortality rates. Despite advances in screening methods such as colonoscopy, the accurate diagnosis of CRC remains challenging due to the absence of reliable biomarkers. This study aimed to develop a robust prognostic model for precise CRC outcome prediction. Employing weighted co-expression network analysis (WGCNA) and Cox regression analysis on data from The Cancer Genome Atlas (TCGA), we identified a panel of 12 genes strongly associated with patient survival. This gene panel facilitated accurate CRC outcome predictions, which is also validated via the external validation cohort GSE17536. We conducted further investigations into the key gene, urocortin (UCN), using single-cell transcriptomic data and immune infiltration analysis in CRC patients. Our results revealed a significant correlation between high UCN expression and the reduced prevalence of key immune cells, including B cells, CD4+ cytotoxic T cells, CD8+ T cells, and NKT cells. Functional experiments showed that UCN gene interference in the CRC cell lines significantly decreased cancer cell proliferation, underscoring UCN's role in intestinal immunity modulation. The UCN-centric prognostic model developed enhances prognosis prediction accuracy and offers critical insights for CRC diagnosis and therapeutic interventions.

A Pyroptosis-Related Gene Signature Predicts Prognosis and Tumor Immune Microenvironment in Colorectal Cancer

Pyroptosis is a programmed cell death, which garners increasing attention by relating to immune and therapy response. However, the role of pyroptosis in colorectal cancer (CRC) remains unclear. Our study mainly to explore the role of pyroptosis in CRC. The mRNA expression data and corresponding clinical information of CRC patients were achieved from The Cancer Genome Atlas (TCGA). Pyroptosis-related genes (PRGs) were identified using DESeq2 R package and biological function was analyzed using cluster Profiler R package. A PRGs-based prognosis model was constructed by a univariate Cox and LASSO regression analyses. Then, the affecting of risk signature to clinicopathological characteristics, immune status and infiltrated immune cells, immune checkpoint and chemotherapy sensitivity was analyzed. qRT-PCR and IHC were performed for the expression level of PRGs. Moreover, a nomogram predict model was constructed. Total 57 PRGs were identified between 500 CRC samples and 44 normal samples. Those PRGs mainly enriched in immune-related and pyroptosis-related pathways. GABRD, NADK, TMEM240, RER1, AGRN, UBE2J2, CALML6, PLCH2, TMEM88B have been identified as gene signature and a prognostic model was constructed and validated. CRC patients with high-risk score showed poor survival, high TMB score, high proportion of CD4 + memory T cells, common lymphoid progenitors, cancer associated fibroblasts, mast cells, and neutrophils. The immune checkpoint related genes, CD160, CD200R1, CD244, CD28, CD40LG, CD44, CD48, CD80, CD86, HHLA2, ICOS, IDO1, TIGIT, TNFRSF25, TNFRSF4, TNFRSF9, TNFSF15, TNFSF18 also increased in high-risk score group. CRC patients with high-risk score more sensitive to docetaxel and rapamycin but resistance to gemcitabine and mitomycin. Moreover, a predictive nomogram for 1-, 3-, 5-year for CRC patients was established and validated. In the study, a PRGs-based prognostic model and a predictive model were constructed. These models are effective and robust in prediction the 1-, 3-, and 5-year survival of CRC patients.

Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

Background

Colon cancer is a highly heterogeneous disease, and identifying molecular subtypes can provide insights into deregulated pathways within tumor subsets, which may lead to personalized treatment options. However, most prognostic models are based on single-pathway genes.

Methods

In this study, we aimed to identify three clinically relevant subtypes of colon cancer based on multiple signaling pathways-related genes. Integrative multi-omics analysis was used to explain the biological processes contributing to colon cancer aggressiveness, recurrence, and progression. Machine learning methods were employed to identify the subtypes and provide medication guidance for distinct subtypes using the L1000 platform. We developed a robust prognostic model (MKPC score) based on gene pairs and validated it in one internal test set and three external test sets. Risk-related genes were extracted and verified by qPCR.

Results

Three clinically relevant subtypes of colon cancer were identified based on multiple signaling pathways-related genes, which had significantly different survival state (Log-Rank test, p<0.05). Integrative multi-omics analysis revealed biological processes contributing to colon cancer aggressiveness, recurrence, and progression. The developed MKPC score, based on gene pairs, was robust in predicting prognosis state (Log-Rank test, p<0.05), and risk-related genes were successfully verified by qPCR (t test, p<0.05). An easy-to-use web tool was created for risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.

Conclusion

In conclusion, our study identified three clinically relevant subtypes of colon cancer and developed a robust prognostic model based on gene pairs. The developed web tool is a valuable resource for researchers and clinicians in risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.

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.

Age-dependent expression of ion channel genes in rat

Ion channels regulate a large number of cellular functions and their functional role in many diseases makes them potential therapeutic targets. Given their diverse distribution across multiple organs, the roles of ion channels, particularly in age-associated transcriptomic changes in specific organs, are yet to be fully revealed. Using RNA-seq data, we investigated the rat transcriptomic profiles of ion channel genes across 11 organs/tissues and 4 developmental stages in both sexes of Fischer 344 rats and identify tissue-specific and age-dependent changes in ion channel gene expression. Organ-enriched ion channel genes were identified. In particular, the brain showed higher tissue-specificity of ion channel genes, including Gabrd, Gabra6, Gabrg2, Grin2a, and Grin2b. Notably, age-dependent changes in ion channel gene expression were prominently observed in the thymus, including in Aqp1, Clcn4, Hvcn1, Itpr1, Kcng2, Kcnj11, Kcnn3, and Trpm2. Our comprehensive study of ion channel gene expression will serve as a primary resource for biological studies of aging-related diseases caused by abnormal ion channel functions.

Gamma-aminobutyric Acid Type A Receptor Subunit Delta as a Potential Therapeutic Target in Gastric Cancer

BACKGROUND

Novel therapeutic targets are needed to improve the poor prognosis of patients with advanced gastric cancer. The aim of this study was to identify a novel therapeutic target for the treatment of GC and to investigate the potential therapeutic value of an antibody raised against the target.

METHODS

We identified gamma-aminobutyric acid type A receptor subunit delta as a candidate therapeutic target by differential transcriptome analysis of metastatic GC tissue and adjacent nontumor tissues. GABRD mRNA levels were analyzed in 230 pairs of gastric tissue by quantitative reverse-transcription polymerase chain reaction. GABRD function was assessed in proliferation, invasion, and apoptosis assays in human GC cell lines expressing control or GABRD-targeting small interfering RNA (siRNA). Mouse anti-human polyclonal GABRD antibodies were generated and assessed for inhibition of GC cell growth in vitro and in a mouse xenograft model of peritoneal GC dissemination.

RESULTS

High GABRD mRNA expression level in primary human GC tissue was associated with poor prognosis. Expression of siGABRD in GC cell lines significantly decreased cell proliferation and invasion and increased apoptosis compared with control siRNA expression. Anti-GABRD polyclonal antibodies inhibited GC cell proliferation in vitro and decreased peritoneal tumor nodule size in the mouse xenograft model.

CONCLUSION

We identified GABRD as novel regulator of GC cell growth and function. GABRD is upregulated in GC tissue and is associated with poor prognosis, suggesting that it may be a potential therapeutic target for GC.

Therapeutic targets and functions of curcumol against COVID-19 and colon adenocarcinoma

Since 2019, the coronavirus disease (COVID-19) has caused 6,319,395 deaths worldwide. Although the COVID-19 vaccine is currently available, the latest variant of the virus, Omicron, spreads more easily than earlier strains, and its mortality rate is still high in patients with chronic diseases, especially cancer patients. So, identifying a novel compound for COVID-19 treatment could help reduce the lethal rate of the viral infection in patients with cancer. This study applied network pharmacology and systematic bioinformatics analysis to determine the possible use of curcumol for treating colon adenocarcinoma (COAD) in patients infected with COVID-19. Our results showed that COVID-19 and COAD in patients shared a cluster of genes commonly deregulated by curcumol. The clinical pathological analyses demonstrated that the expression of gamma-aminobutyric acid receptor subunit delta (GABRD) was associated with the patients' hazard ratio. More importantly, the high expression of GABRD was associated with poor survival rates and the late stages of COAD in patients. The network pharmacology result identified seven-core targets, including solute carrier family 6 member 3, gamma-aminobutyric acid receptor subunit pi, butyrylcholinesterase, cytochrome P450 3A4, 17-beta-hydroxysteroid dehydrogenase type 2, progesterone receptor, and GABRD of curcumol for treating patients with COVID-19 and COAD. The bioinformatic analysis further highlighted their importance in the biological processes and molecular functions in gland development, inflammation, retinol, and steroid metabolism. The findings of this study suggest that curcumol could be an alternative compound for treating patients with COVID-19 and COAD.

Integrative Proteo-Genomic Analysis for Recurrent Survival Prognosis in Colon Adenocarcinoma

Background

The survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD).

Methods

The proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings.

Results

We identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD.

Conclusion

These identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.

The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma

Background: Early detection and precise prognostic evaluation of clear cell renal cell carcinoma (ccRCC) are crucial for patient life expectancy. Ion channel-related genes (ICRGs) are of great diagnostic and prognostic value as components that maintain the normal structure of the kidney. Therefore, we systematically explored the diagnostic, prognostic, and therapeutic value of ICRGs in ccRCC using the multi-database.

Methods: RNA transcriptome profiles and clinical data of ccRCC patients were extracted and integrated from public databases including The Cancer Genome Atlas, ICGC, GEO, and E-MTAB databases. Ion channel-related genes were obtained from the literature collection. The diagnostic signature was performed using the LASSO and SVM-REF analyses. Meanwhile, the prognostic signature was conducted using the LASSO analyses. Molecular subtyping was performed using the ConsensusClusterPlus and the corresponding therapeutic targets were evaluated using the pRRophetic package. In addition, a prognostic nomogram was constructed based on the results of cox regression analyses.

Results: We successfully constructed diagnostic signatures for five ICRGs and prognostic signatures for 10 ICRGs with AUC values greater than 0.7, showing good predictive performance. Based on the median risk score, we found that high-risk patients had a significantly worse prognosis. We also divided ccRCC patients into two clusters according to prognostic ICRGs, and there was a significant survival outcome between the two clusters and different sensitivity to diverse clinical therapeutic strategies. Meanwhile, we constructed a nomogram based on clinical molecules and signatures, and its predictive efficacy was better than the signature or the present tumor-node-metastasis staging system.

Conclusion: In this study, we established useful signatures for early detection, prognosis evaluation, and individualized treatment for ccRCC. Moreover, KCNJ16 deserves to be explored comprehensively in the future.

Clinical Data and Biocalculation Methods of GABRD Determine the Clinical Characteristics and Immune Relevance of Colorectal Cancer

Background

The aim of this study was to clarify the expression of gamma-aminobutyric acid type A receptor delta subunit (GABRD) gene in pan-cancer and its correlation with patient prognosis, and to investigate the function and possible mechanism of GABRD in colorectal cancer (CRC).

Methods

The Cancer Genome Atlas (TCGA) data were used to analyze the expression differences of GABRD in pan-cancer, and the correlation between GABRD and clinical prognosis of various tumors was analyzed by Cox regression method. According to the expression level of GABRD, Gene Function Annotation (GO) and Kyoto Encyclopedia of Genomes (KEGG) functional enrichment analysis were performed on the differentially expressed genes. Expression of GABRD gene and 44 marker genes of three types of RNA modification (m1A (10), m5C (13), m6A (21)) genes in different tumors was observed. Pearson correlation of GABRD gene and marker genes of five immune pathways was measured.

Results

: TCGA data analysis showed that GABRD was significantly upregulated in various tumor tissues, especially COAD and READCOAD. Survival analysis showed that GABRD was a prognostic protective factor in CRC (p < 0.001). The results of survival nomogram showed that GABRD, age, and tumor (T) lymph node (N) distant metastasis (M) stage were independent prognostic factors, and the survival model C-index was 0.724 (0.644-1). Gene enrichment and functional analysis showed that GABRD may be related to protein digestion and absorption, ECM-receptor interaction, extracellular structure organization, extracellular matrix organization, pancreatic secretion, and antimicrobial humoral response. The expression of GABRD was positively correlated in m1A-, m5C-, and m6A-related genes. The GABRD gene was found in B cell, T cell CD4, T cell CD8, neutrophil, macrophage in TCGA-COAD (N = 282), and TCGA-COADREAD (N = 373). The infiltration level and DC was significantly positively correlated (p < 0.05). Also, the Pearson correlation coefficient is the largest.

Conclusion

The involvement of GABRD in the occurrence and development of CRC may be related to protein digestion and absorption, ECM-receptor interaction, extracellular structure organization, extracellular matrix organization, pancreatic secretion, and antimicrobial humoral response. GABRD can be used as a molecular marker for the prognosis of CRC.

DEPDC1B collaborates with GABRD to regulate ESCC progression

Background

Esophageal squamous cell carcinoma (ESCC) is the leading cause of cancer-related death worldwide with a poor prognosis. Given that DEPDC1B plays a key role in multiple cancers, the role of this molecule in ESCC was explored to identify potential targets for ESCC patients.

Method

The expression level of DEPDC1B in ESCC was revealed based on the TCGA database and immunohistochemical experiments on clinical tissues. The correlation between DEPDC1B and survival of ESCC patients was analyzed by Kaplan–Meier method. Small hairpin RNA (shRNA)-mediated silencing of DEPDC1B expression in ESCC cells and performed a series of in vitro and in vivo functional validations.

Result

DEPDC1B was overexpressed in ESCC. High expression of DEPDC1B was significantly negatively correlated with overall survival in patients with ESCC. Moreover, knockdown of DEPDC1B inhibited ESCC cell proliferation, clone formation, migration, tumor formation and promoted apoptosis. Furthermore, knockdown of DEPDC1B leaded to significant downregulation of GABRD in ESCC cells. Meanwhile, GABRD expression was upregulated in ESCC, and its silencing can inhibit the proliferation and migration of the tumor cells. Interestingly, there was a protein interaction between DEPDC1B and GABRD. Functionally, GABRD knockdown partially reversed the contribution of DEPDC1B to ESCC progression. In addition, GABRD regulated ESCC progression may depend on PI3K/AKT/mTOR signaling pathway.

Conclusion

DEPDC1B collaborated with GABRD to regulate ESCC progression, and inhibition of this signaling axis may be a potential therapeutic target for ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02593-z.

HOXC11 Expression Is Associated with the Progression of Colon Adenocarcinoma and Is a Prognostic Biomarker

This study aimed to evaluate the role of HOXC11 in progression and prognosis in colon adenocarcinoma (COAD) patients. The COAD patient data were downloaded from "The Cancer Genome Atlas (TCGA)" database. The Wilcoxon rank-sum test or Kruskal-Wallis test was used to analyze the correlation between HOXC11 expression and clinicopathologic characteristics. The significance of difference in overall survival between different groups was determined by log-rank test. The HOXC11 expression was verified from mRNA and protein level by conducting real-time quantitative PCR, Western blot, and immunohistochemistry analysis. Significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were screened after gene set enrichment analysis. As a result, high HOXC11 expression was closely related to the occurrence of COAD based on the data in TCGA, which was then successfully validated in cell lines and clinical tissues. Enhanced HOXC11 expression was significantly associated with tumor-node-metastasis (TNM) and M stage. Prognosis of highly expressed HOXC11 COAD patients was significantly worse than those with low HOXC11 expression. GRAFT_VERSUS_HOST_DISEASE and other signaling pathways were significantly activated in high HOXC11 expression COAD patients. In conclusion, high expression of HOXC11 was closely associated with the progression of COAD, and HOXC11 was a promising prognostic biomarker in COAD patients.

Research for Expression and Prognostic Value of GABRD in Colon Cancer and Coexpressed Gene Network Construction Based on Data Mining

Colon cancer is one of the top five cancers with the highest incidence rate in the world. In order to better understand the pathogenesis and progression of colon cancer, it is still necessary to investigate the abnormally expressed genes in cancer tissue. In this study, the Oncomine database was used for expression analysis, and it was found that the expression level of gamma-aminobutyric acid type A receptor subunit delta (GABRD) gene was upregulated in colon cancer tissue compared with that in normal tissue. UALCAN was used to analyze the expression of GABRD in different groups of age, gender, cancer stage, N stage, and histological subtype. Then, it was also found that the expression of GABRD in each subgroup of colon cancer tissue was all high compared with that in normal tissue. LinkedOmics was used to screen out the differentially expressed genes related to GABRD expression in colon cancer. GO annotation and KEGG pathway enrichment analyses found that the correlated genes may be related to breast cancer, human papillomavirus infection, Notch signaling pathway, and other pathways. Thereafter, GSEA was performed to obtain GABRD-related kinases, miRNAs, and transcription factors, and gene interaction networks were constructed. It was found that GABRD may be involved in cell cycle regulation. Finally, websites like GEPIA were used to detect the predictive ability of GABRD on the prognosis of patients with colon cancer. Kaplan-Meier analysis suggested that the upregulation of GABRD expression was related to the poor prognosis of patients with colon cancer. Overall, in this study, the potential role and prognostic ability of GABRD in colon cancer were explored through data mining, which can be a clue for further research on GABRD.