DYNLL1 is hypomethylated and upregulated in a tumor stage- and grade-dependent manner and associated with increased mortality in hepatocellular carcinoma

DYNLL1 ubiquitinated and degraded by E3 ligase PRKN regulates cell cycle arrest and apoptosis in lung adenocarcinoma cells

This study was intended to investigate the role of DYNLL1 in lung adenocarcinoma (LUAD) and reveal the relevant molecular mechanism. To this end, we manipulated the expression of DYNLL1 and PRKN with shRNA and/or overexpression to assess their effects on A549 cell phenotypes including cell proliferation, cycle arrest and apoptosis using CCK-8 assay, EdU staining, colony formation assay, flow cytometry, TUNEL and western blot. DYNLL1 is a carcinogenic factor in LUAD since it is highly expressed and DYNLL1 upregulation is associated with the low overall survival rate of LUAD patients. Silencing DYNLL1 inhibited the proliferation of LUAD cells while accelerating cell cycle arrest and apoptosis. The regulatory effects of silencing DYNLL1 were counteracted by PRKN deficiency, indicating a functional connection between DYNLL1 and PRKN, which could be attributed to the ubiquitination of DYNLL1 by PRKN. This study could help identify the role of DYNLL1 in LUAD pathogenies and develop reliable therapeutic targets for LUAD improvement.

Advances in epigenetic therapies for B-cell non-hodgkin lymphoma

B-cell non-Hodgkin lymphomas (B-NHLs) constitute a varied group of cancers originating from B lymphocytes. B-NHLs can occur at any stage of normal B-cell development, with most arising from germinal centres (e.g. diffuse large B-cell lymphoma, DLBCL and follicular lymphoma, FL). The standard initial treatment usually involves the chemoimmunotherapy regimen. Although there is a high initial response rate, 30-40% of high-risk patients often face relapsed or refractory lymphoma due to drug resistance. Recent research has uncovered a significant link between the development of B-NHLs and various epigenetic processes, such as DNA methylation, histone modification, regulation by non-coding RNAs, and chromatin remodeling. Therapies targeting these epigenetic changes have demonstrated considerable potential in clinical studies. This article examines the influence of epigenetic regulation on the onset and progression of B-NHLs. It discusses the current therapeutic targets and agents linked to these epigenetic mechanisms, with the goal of offering new perspectives and approaches for targeted therapies and combination chemotherapy in treating B-NHLs.

Matrix stiffness-related extracellular matrix signatures and the DYNLL1 protein promote hepatocellular carcinoma progression through the Wnt/β-catenin pathway

BACKGROUND

In hepatocellular carcinoma (HCC) treatment, first-line targeted therapy in combination with immune checkpoint inhibitors (ICIs) has improved patient prognosis, but the 5-year survival rate is far from satisfactory. Studies have shown that the extracellular matrix (ECM) is an essential part of the tumour microenvironment (TME) and participates in the progression of malignant tumours. ECM remodelling can enhance matrix stiffness in cirrhosis patients, induce an immunosuppressive microenvironment network, and affect the efficacy of targeted therapies and ICIs for treating HCC. However, the exact mechanism is still unclear.

METHODS

We downloaded data from public databases, selected differentially expressed ECM proteins associated with matrix stiffness, constructed and validated a prognostic model of HCC using Lasso Cox regression, and investigated the roles and mechanism of one of the ECM proteins, dynein light chain LC8-type 1 (DYNLL1), in HCC proliferation, migration, and apoptosis via in vitro experiments.

RESULTS

In this study, the risk score of the matrix stiffness-related ECM protein model effectively predicted the prognosis of HCC patients. The high- and low-risk subgroups of the model also showed differences in immune cells, immune functions, and drug sensitivity. DYNLL1 promoted HCC cell progression and migration and inhibited HCC cell apoptosis through the Wnt/β-catenin pathway in vitro.

CONCLUSION

The expression of matrix stiffness-related ECM proteins could be an independent predictor of HCC prognosis. DYNLL1, an oncogenic gene in HCC, has the potential to be a new target for HCC treatment.

Promoter Hypomethylation Upregulates ANXA2 Expression in Pancreatic Cancer and is Associated with Poor Prognosis

Pancreatic cancer (PC) is one of the world's most aggressive and deadly cancers, owing to non-specific early clinical symptoms, late-stage diagnosis, and poor survival. Therefore, it is critical to identify specific biomarkers for its early diagnosis. Annexin A2 (ANXA2) is a calcium-dependent phospholipid-binding protein that has been reported to be upregulated in several cancer types, making it an emerging biomarker and potential cancer therapeutic target. However, the mechanism underlying the regulation of ANXA2 overexpression is still unclear. It is well established that genetic and epigenetic alterations may lead to widespread dysregulation of gene expression. Hence, in this study, we focused on exploring the regulatory mechanism of ANXA2 by investigating the transcriptional profile, methylation pattern, somatic mutation, and prognostic value of ANXA2 in PC using several bioinformatics databases. Our results revealed that the expression levels of ANXA2 were remarkably increased in PC tissues comparing to normal tissues. Furthermore, the high expression of ANXA2 was significantly related to the poor prognosis of PC patients. More importantly, we demonstrated for the first time that the ANXA2 promoter is hypomethylated in PC tissues compared to normal tissues which may result in ANXA2 overexpression in PC. However, more experimental research is required to corroborate our findings.

DYNLL1 accelerates cell cycle via ILF2/CDK4 axis to promote hepatocellular carcinoma development and palbociclib sensitivity

BACKGROUND

Disorder of cell cycle represents as a major driver of hepatocarcinogenesis and constitutes an attractive therapeutic target. However, identifying key genes that respond to cell cycle-dependent treatments still facing critical challenges in hepatocellular carcinoma (HCC). Increasing evidence indicates that dynein light chain 1 (DYNLL1) is closely related to cell cycle progression and plays a critical role in tumorigenesis. In this study, we explored the role of DYNLL1 in the regulation of cell cycle progression in HCC.

METHODS

We analysed clinical specimens to assess the expression and predictive value of DYNLL1 in HCC. The oncogenic role of DYNLL1 was determined by gain or loss-of-function experiments in vitro, and xenograft tumour, liver orthotopic, and DEN/CCl4-induced mouse models in vivo. Mass spectrometry analysis, RNA sequencing, co-immunoprecipitation assays, and forward and reverse experiments were performed to clarify the mechanism by which DYNLL1 activates the interleukin-2 enhancer-binding factor 2 (ILF2)/CDK4 signalling axis. Finally, the sensitivity of HCC cells to palbociclib and sorafenib was assessed by apoptosis, cell counting kit-8, and colony formation assays in vitro, and xenograft tumour models and liver orthotopic models in vivo.

RESULTS

DYNLL1 was significantly higher in HCC tissues than that in normal liver tissues and closely related to the clinicopathological features and prognosis of patients with HCC. Importantly, DYNLL1 was identified as a novel hepatocarcinogenesis gene from both in vitro and in vivo evidence. Mechanistically, DYNLL1 could interact with ILF2 and facilitate the expression of ILF2, then ILF2 could interact with CDK4 mRNA and delay its degradation, which in turn activates downstream G1/S cell cycle target genes CDK4. Furthermore, palbociclib, a selective CDK4/6 inhibitor, represents as a promising therapeutic strategy for DYNLL1-overexpressed HCC, alone or particularly in combination with sorafenib.

CONCLUSIONS

Our work uncovers a novel function of DYNLL1 in orchestrating cell cycle to promote HCC development and suggests a potential synergy of CDK4/6 inhibitor and sorafenib for the treatment of HCC patients, especially those with increased DYNLL1.

Inhibitory Mechanism of Combined Hydroxychavicol With Epigallocatechin-3-Gallate Against Glioma Cancer Cell Lines: A Transcriptomic Analysis

Emerging reports have shown therapeutic potential of hydroxychavicol (HC) and epigallocatechin-3-gallate (EGCG) against cancer cells, however high concentrations are required to achieve the anticancer activity. We reported the synergy of low combination doses of EGCG+HC in glioma cell lines 1321N1, SW1783, and LN18 by assessing the effects of EGCG+HC through functional assays. Using high throughput RNA sequencing, the molecular mechanisms of EGCG+HC against glioma cell lines were revealed. EGCG/HC alone inhibited the proliferation of glioma cell lines, with IC50 values ranging from 82 to 302 µg/ml and 75 to 119 µg/ml, respectively. Sub-effective concentrations of combined EGCG+HC enhanced the suppression of glioma cell growth, with SW1783 showing strong synergism with a combination index (CI) of 0.55 and LN18 showing a CI of 0.51. A moderate synergistic interaction of EGCG+HC was detected in 1321N1 cells, with a CI value of 0.88. Exposure of 1321N1, SW1783, and LN18 cells to EGCG+HC for 24 h induces cell death, with caspase-3 activation rates of 52%, 57%, and 9.4%, respectively. However, the dose for SW1783 is cytotoxic to normal cells, thus this dose was excluded from other tests. EGCG+HC induced cell cycle arrest at S phase and reduced 1321N1 and LN18 cell migration and invasion. Combined EGCG+HC amplified its anticancer effect by downregulating the axon guidance process and metabolic pathways, while simultaneously interfering with endoplasmic reticulum unfolded protein response pathway. Furthermore, EGCG+HC exerted its apoptotic effect through the alteration of mitochondrial genes such as MT-CO3 and MT-RNR2 in 1321N1 and LN18 cells respectively. EGCG+HC dynamically altered DYNLL1 alternative splicing expression in 1321N1 and DLD splicing expression in LN18 cell lines. Our work indicated the pleiotropic effects of EGCG+HC treatment, as well as particular target genes that might be investigated for future glioma cancer therapeutic development.

Single-cell transcriptomic analysis reveals a novel cell state and switching genes during hepatic stellate cell activation in vitro

Background

The transformation of hepatic stellate cell (HSC) to myofibroblast is a key event during liver fibrogenesis. However, the differentiation trajectory of HSC-to-myofibroblast transition and the switching genes during this process remains not well understood.

Methods

We applied single-cell sequencing data to reconstruct a single-lineage pseudotime trajectory of HSC transdifferentiation in vitro and analyzed the gene expression patterns along the trajectory. GeneSwitches was used to identify the order of critical gene expression and functional events during HSC activation.

Results

A novel cell state during HSC activation was revealed and the HSCs belonging to this state may be an important origin of cancer-associated fibroblasts (CAFs). Combining single-cell transcriptomics with GeneSwitches analyses, we identified some distinct switching genes and the order at which these switches take place for the new state of HSC and the classic culture-activated HSC, respectively. Based on the top switching genes, we established a four-gene combination which exhibited highly diagnostic accuracy in predicting advanced liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) or hepatitis B (HBV).

Conclusion

Our study revealed a novel cell state during HSC activation which may be relevant to CAFs, and identified switching genes that may play key roles in HSC transdifferentiation and serve as predictive markers of advanced fibrosis in patients with chronic liver diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03263-4.

mRNAsi-related genes can effectively distinguish hepatocellular carcinoma into new molecular subtypes

Background

Recent studies have shown that the mRNA expression-based stemness index (mRNAsi) can accurately quantify the similarity of cancer cells to stem cells, and mRNAsi-related genes are used as biomarkers for cancer. However, mRNAsi-driven tumor heterogeneity is rarely investigated, especially whether mRNAsi can distinguish hepatocellular carcinoma (HCC) into different molecular subtypes is still largely unknown.

Methods

Using OCLR machine learning algorithm, weighted gene co-expression network analysis, consistent unsupervised clustering, survival analysis and multivariate cox regression etc. to identify biomarkers and molecular subtypes related to tumor stemness in HCC.

Results

We firstly demonstrate that the high mRNAsi is significantly associated with the poor survival and high disease grades in HCC. Secondly, we identify 212 mRNAsi-related genes that can divide HCC into three molecular subtypes: low cancer stemness cell phenotype (CSCP-L), moderate cancer stemness cell phenotype (CSCP-M) and high cancer stemness cell phenotype (CSCP-H), especially over-activated ribosomes, spliceosomes and nucleotide metabolism lead to the worst prognosis for the CSCP-H subtype patients, while activated amino acids, fatty acids and complement systems result in the best prognosis for the CSCP-L subtype. Thirdly, we find that three CSCP subtypes have different mutation characteristics, immune microenvironment and immune checkpoint expression, which may cause the differential prognosis for three subtypes. Finally, we identify 10 robust mRNAsi-related biomarkers that can effectively predict the survival of HCC patients.

Conclusions

These novel cancer stemness-related CSCP subtypes and biomarkers in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy of HCC patients.

Estrogen- and estrogen receptor (ER)-mediated cisplatin chemoresistance in cancer

Cisplatin is a platinum-based chemotherapeutic drug used in the standard treatment of various solid cancers including testicular, bladder, head and neck, cervical and ovarian cancer. Although successful clinical responses are observed in patients following initial cisplatin treatment, resistance to cisplatin ultimately develops in most patients, leading to therapeutic failure. Multiple molecular mechanisms contributing to cisplatin resistance in cancer cells have been identified to date. In this review, we discuss the effect of estrogen, estrogen receptors (ERs) and estrogen-related receptors (ERRs) on cisplatin resistance in various cancer types. We highlight that estrogen treatment or increased expression of ERs or ERRs are generally associated with higher cisplatin resistance in cancer in vitro, mostly due to decreased caspase activity, increased anti-apoptotic protein levels such as BCL-2, higher drug efflux and higher levels of antioxidant enzymes. Targeted inhibition of ERs or estrogen production in combination with cisplatin treatment thus can be a useful strategy to overcome chemoresistance in certain cancer types. Estrogen levels and ER status can also be considered to identify cancer patients with a high potential of therapy response against cisplatin. A better mechanistic understanding of the involvement of estrogen, ERs and ERRs in the development of cisplatin resistance is needed to improve the management of cancer treatment.

circRNA_PTPRA functions as a sponge of miR-582-3p to regulate hepatocellular carcinoma cell proliferation, migration, invasion and apoptosis

Hepatocellular carcinoma (HCC) is a lethal disease and one of the most common types of cancer. HCC is associated with exponentially increasing morbidity and mortality rates. Accumulating evidence has identified circular RNAs (circRNAs) to be regulators of cancer progression. However, to the best of our knowledge, the potential effect of circRNA protein tyrosine phosphatase receptor type A (circRNA_PTPRA) in HCC and its mechanism remain unknown. The present study aimed to assess the effects and underlying mechanism of circRNA_PTPRA in a HCC Huh-7 cells model. The sites of interaction between circRNA_PTPRA and microRNA (miR)-582-3p were predicted using the StarBase software and verified using dual luciferase reporter and RNA immunoprecipitation (RIP) assays in Huh-7 cells. HCC cell viability, apoptosis, migration and invasion were measured using MTT, flow cytometry and Transwell assays, respectively. The expression levels of circRNA_PTPRA, miR-582-3p, cyclin D1, MMP-9, Bcl-2 and Bax were analyzed using reverse transcription-quantitative PCR and western blotting. The results of the dual luciferase reporter and RIP assays demonstrated that miR-582-3p directly targeted circRNA_PTPRA. Compared with the human normal hepatocyte cell line, THLE-2, the expression levels of circRNA_PTPRA were upregulated, which were found to be inversely correlated with those of miR-582-3p expression in Huh-7 and HCCLM3 cells. miR-582-3p overexpression using mimics suppressed cell proliferation, migration and invasion, whilst downregulating cyclin D1 and MMP-9 expression in Huh-7 cells. In addition, transfection of HCC cells with the miR-582-3p mimic promoted apoptosis by downregulating Bcl-2 expression and upregulating Bax expression in Huh-7 cells. Knocking down circRNA_PTPRA expression using small interfering RNA (siRNA) markedly downregulated circRNA_PTPRA expression levels and upregulated miR-582-3p expression, but was reversed by co-transfection with the miR-582-3p inhibitor. Furthermore, reduced HCC cell proliferation, migration and invasion, increased levels of cell apoptosis, upregulated Bax expression and downregulated cyclin D1, MMP-9 and Bcl-2 expression were all observed after knocking down circRNA_PTPRA. All these effects aforementioned were reversed by co-transfection with the miR-582-3p inhibitor. In conclusion, findings from the present study suggested that circRNA_PTPRA may regulate HCC cell proliferation, invasion, apoptosis and migration by sponging miR-582-3p. This indicates that the circRNA_PTPRA/miR-582-3p axis may represent a potential target for HCC diagnosis and treatment.

Involvement of ATMIN-DYNLL1-MRN axis in the progression and aggressiveness of serous ovarian cancer

The loss of DYNLL1 contributes to chemoresistance in ovarian cancer. DYNLL1 binds to MRE11, a component of MRN complex (MRE11-RAD50-NBS1), and limits its function in homologous recombination (HR) repair in BRCA1-mutant cells. Decreased activity of MRE11 results in less HR-repair events and thus leads to higher sensitivity against DNA-damaging agents such as cisplatin. Therefore, a better understanding of the cellular changes in DYNLL1-MRN axis in ovarian cancer is needed. Here, we showed that DYNLL1 overexpression leads to decreased chemoresistance even in BRCA-proficient ovarian cancer cells. ATMIN, a transcriptional activator of DYNLL1, showed decreased expression; however, two components of MRN complex, MRE11 and NBS1 (NBN), showed increased expression in high grade compared to low grade serous ovarian cancer. We found that the components of MRN complex (MRE11-RAD50-NBS1) have higher protein levels in sites of omental metastasis and serous tubal intraepithelial carcinoma (STIC) compared to surrounding non-malignant stromal cells in patients with high grade serous ovarian cancer. We showed that the percentage of copy number variation (CNV) events in genes encoding ATMIN, DYNLL1, MRE11 and NBN are the highest in ovarian cancer among other cancer types. ATMIN and DYNLL1 genes are mostly characterized by copy number losses; however, CNV events in MRN complex components are mostly copy number gains. This study highlights the importance of ATMIN-DYNLL1-MRN axis in the development, progression and therapy response of ovarian cancer. MRN levels in ovarian cancer that differ from adjacent, non-malignant tissues may represent actionable therapeutic vulnerabilities.

Systematic Analysis Identifies a Specific RNA-Binding Protein-Related Gene Model for Prognostication and Risk-Adjustment in HBV-Related Hepatocellular Carcinoma

Objective

Increasing evidence shows that dysregulated RNA binding proteins (RBPs) modulate the progression of several malignancies. Nevertheless, their clinical implications of RBPs in HBV-related hepatocellular carcinoma (HCC) remain largely undefined. Here, this study systematically analyzed the associations of RBPs with HBV-related HCC prognosis.

Methods

Based on differentially expressed RBPs between HBV-related HCC and control specimens, prognosis-related RBPs were screened by univariate analyses. A LASSO model was then created. Kaplan-Meier curves, ROCs, multivariate analyses, subgroup analyses and external verification were separately applied to assess the efficacy of this model in predicting prognosis and recurrence of patients. A nomogram was created by incorporating the model and clinical indicators, which was verified by ROCs, calibration curves and decision curve analyses. By CIBERSORT algorithm, the association between the risk score and immune cell infiltrations was evaluated.

Results

Totally, 54 RBPs were distinctly correlated to prognosis of HBV-related HCC. An 11-RBP model was created, containing POLR2L, MRPS12, DYNLL1, ZFP36, PPIH, RARS, SRP14, DDX41, EIF2B4, and NOL12. This risk score sensitively and accurately predicted one-, three- and five-year overall survival, disease-free survival, and progression-free interval. Compared to other clinical parameters, this risk score had the best predictive efficacy. Also, the clinical generalizability of the model was externally verified in the GSE14520 dataset. The nomogram may predict patients' survival probabilities. Also, the risk score was related to the components in the immune microenvironment.

Conclusion

Collectively, RBPs may act as critical elements in the malignant progression of HBV-related HCC and possess potential implications on prognostication and therapy decision.

A Novel miRNA-mRNA Axis Involves in Regulating Transcriptional Disorders in Pancreatic Adenocarcinoma

Background

Currently, there is still a lack of understanding about the mechanism and therapeutic targets of pancreatic adenocarcinoma (PAAD). The potential of miRNA-mRNA networks for the identification of regulatory mechanisms involved in PAAD development remains unexplored.

Methods

We compared differentially expressed miRNAs (DEMIs) and differentially expressed genes (DEGs) in PAAD and normal tissues from the Gene Expression Omnibus (GEO) database. Transcription factors (TFs) were obtained from FunRich. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs and DEMIs were implemented using Database for Annotation, Visualization and Integrated Discovery (DAVID). Then, key miRNAs and targeted mRNAs were identified by assessment of their expression and prognosis in UALCAN and Kaplan-Meier plotters. In the last step, the candidate miRNA-mRNA selected was confirmed by real-time quantitative polymerase chain reaction (qRT-PCR).

Results

We distinguished 62 significant DEMIs, 1314 upregulated DEGs, and 1110 downregulated DEGs. The top 10 TFs were identified. In total, there were 160 hub genes obtained by intersecting the set of 2224 predicted targets with the set of significant DEGs. And we selected 8 key miRNAs. Furthermore, low expression of miR-455-3p in PAAD tissue was closely connected with poor prognosis, and only 5 target mRNAs were predicted to be increased in PAAD tissue with poor prognosis. Therefore, a novel miRNA-hub gene regulatory network in PAAD was constructed. Finally, in vitro experiments indicated that miR-455-3p expression was decreased in PAAD sample. HOXC4, DLG4, DYNLL1 and FBXO45 were validated by qRT-PCR as highly probable targets of miR-455-3p.

Conclusion

A novel miRNA-mRNA axis has been discovered that may be involved in the regulation of transcriptional disorders and affected the survival of PAAD patients, which would provide a novel strategy for the treatment of PAAD.

Identification of key genes and pathways involved in abdominal aortic aneurysm initiation and progression

OBJECTIVE

The study aimed to assess the gene expression profile of biopsies obtained from the neck of human abdominal aortic aneurysm (AAA) and the main site of AAA dilatation and to investigate the molecular mechanism underlying the development of AAA.

METHODS

The microarray profile of GSE47472 and GSE57691 were obtained from the Gene Expression Omnibus (GEO) database. The GSE47472 was a microarray dataset of tissues from the aortic neck of AAA patients versus normal controls. The GSE57691 was a microarray dataset including the tissues from main site of AAA dilatation versus normal controls. Differentially expressed genes (DEGs) were chosen using the R package and annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). The hub genes were identified in the protein-protein interaction (PPI) network.

RESULTS

342 upregulated DEGs and 949 downregulated DEGs were obtained from GSE47472. The upregulated DEGs were mainly enriched in biological regulation (ontology: BP), the membrane (ontology: CC), and protein binding (ontology: MF), and the downregulated genes were mainly enriched in biological regulation (ontology: BP), the membrane (ontology: CC), and protein blinding (ontology: MF). In the KEGG enrichment analysis, the DEGs mainly involved glycosaminoglycan degradation, vasopressin-regulated water reabsorption, and pyruvate metabolism. The hub genes in GSE47472 mainly include VAMP8, PTPRC, DYNLL1, RPL38, RPS4X, HNRNPA1, PRMT1, TGOLN2, PA2G4, and CUL2. From GSE57691, 248 upregulated DEGs and 1120 downregulated DEGs were selected. The upregulated DEGs of GSE57691 were mainly enriched in biological regulation (ontology: BP), the membrane (ontology: CC), and protein binding (ontology: MF), and the downregulated genes were mainly enriched in metabolic process (ontology: BP), the membrane (ontology: CC), and protein blinding (ontology: MF). In the KEGG enrichment analysis, the DEGs mainly involved the mitochondrial respiratory, respiratory chain complex, and respiratory chain. RPS15A, RPS5, RPL23, RPL27A, RPS24, RPL35A, RPS4X, RPL7, RPS25, and RPL21 were identified as the hub genes.

CONCLUSION

At the early stage of AAA, the current study indicated the importance of glycosaminoglycan degradation and anaerobic metabolism. We also identified several hub genes closely related to AAA (VAMP8, PTPRC, DYNLL1, etc.). At the progression of the AAA, the dysfunctional mitochondria played a critical role in AAA formation and the RPS15A, RPS5, RPL23, etc., were identified as the hub genes.

A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

Background: Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment. However, autophagy-related genes (ARGs) have rarely been analyzed in gastric cancer (GC). The purpose of this study was to analyze ARGs in GC using bioinformatic analysis and to identify new biomarkers for predicting the overall survival (OS) of patients with GC.

Methods: The gene expression profiles and clinical data of patients with GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and ARGs were obtained from two other datasets (the Human Autophagy Database and Molecular Signatures Database). Lasso, univariate, and multivariate Cox regression analyses were performed to identify the OS-related ARGs. Finally, a six-ARG model was identified as a prognostic indicator using the risk-score model, and survival and prognostic performance were analyzed based on the Kaplan-Meier test and ROC curve. Estimate calculations were used to assess the immune status of this model, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed for investigating the functions and terms associated with the model-related genes in GC.

Results: The six ARGs, DYNLL1, PGK2, HPR, PLOD2, PHYHIP, and CXCR4, were identified using Lasso and Cox regression analyses. Survival analysis revealed that the OS of GC patients in the high-risk group was significantly lower than that of the low-risk group (p < 0.05). The ROC curves revealed that the risk score model exhibited better prognostic performance with respect to OS. Multivariate Cox regression analysis indicated that the model was an independent predictor of OS and was not affected by most of the clinical traits (p < 0.05). The model-related genes were associated with immune suppression and several biological process terms, such as extracellular structure organization and matrix organization. Moreover, the genes were associated with the P13K-Akt signaling pathway, focal adhesion, and MAPK signaling pathway.

Conclusions: This study presents potential prognostic biomarkers for GC patients that would aid in determining the best patient-specific course of treatment.

Tumour Microenvironment: Roles of the Aryl Hydrocarbon Receptor, O-GlcNAcylation, Acetyl-CoA and Melatonergic Pathway in Regulating Dynamic Metabolic Interactions across Cell Types-Tumour Microenvironment and Metabolism

This article reviews the dynamic interactions of the tumour microenvironment, highlighting the roles of acetyl-CoA and melatonergic pathway regulation in determining the interactions between oxidative phosphorylation (OXPHOS) and glycolysis across the array of cells forming the tumour microenvironment. Many of the factors associated with tumour progression and immune resistance, such as yin yang (YY)1 and glycogen synthase kinase (GSK)3β, regulate acetyl-CoA and the melatonergic pathway, thereby having significant impacts on the dynamic interactions of the different types of cells present in the tumour microenvironment. The association of the aryl hydrocarbon receptor (AhR) with immune suppression in the tumour microenvironment may be mediated by the AhR-induced cytochrome P450 (CYP)1b1-driven 'backward' conversion of melatonin to its immediate precursor N-acetylserotonin (NAS). NAS within tumours and released from tumour microenvironment cells activates the brain-derived neurotrophic factor (BDNF) receptor, TrkB, thereby increasing the survival and proliferation of cancer stem-like cells. Acetyl-CoA is a crucial co-substrate for initiation of the melatonergic pathway, as well as co-ordinating the interactions of OXPHOS and glycolysis in all cells of the tumour microenvironment. This provides a model of the tumour microenvironment that emphasises the roles of acetyl-CoA and the melatonergic pathway in shaping the dynamic intercellular metabolic interactions of the various cells within the tumour microenvironment. The potentiation of YY1 and GSK3β by O-GlcNAcylation will drive changes in metabolism in tumours and tumour microenvironment cells in association with their regulation of the melatonergic pathway. The emphasis on metabolic interactions across cell types in the tumour microenvironment provides novel future research and treatment directions.