Construction and Analysis of the Tumor-Specific mRNA-miRNA-lncRNA Network in Gastric Cancer

Uncovering the ceRNA Network Related to the Prognosis of Stomach Adenocarcinoma Among 898 Patient Samples

Stomach adenocarcinoma (STAD) patients are often associated with significantly high mortality rates and poor prognoses worldwide. Among STAD patients, competing endogenous RNAs (ceRNAs) play key roles in regulating one another at the post-transcriptional stage by competing for shared miRNAs. In this study, we aimed to elucidate the roles of lncRNAs in the ceRNA network of STAD, uncovering the molecular biomarkers for target therapy and prognosis. Specifically, a multitude of differentially expressed lncRNAs, miRNAs, and mRNAs (i.e., 898 samples in total) was collected and processed from TCGA. Cytoplasmic lncRNAs were kept for evaluating overall survival (OS) time and constructing the ceRNA network. Differentially expressed mRNAs in the ceRNA network were also investigated for functional and pathological insights. Interestingly, we identified one ceRNA network including 13 lncRNAs, 25 miRNAs, and 9 mRNAs. Among them, 13 RNAs were found related to the patient survival time; their individual risk score can be adopted for prognosis inference. Finally, we constructed a comprehensive ceRNA regulatory network for STAD and developed our own risk-scoring system that can predict the OS time of STAD patients by taking into account the above.

Acetyl-CoA metabolism as a therapeutic target for cancer

Acetyl-coenzyme A (acetyl-CoA), an essential metabolite, not only takes part in numerous intracellular metabolic processes, powers the tricarboxylic acid cycle, serves as a key hub for the biosynthesis of fatty acids and isoprenoids, but also serves as a signaling substrate for acetylation reactions in post-translational modification of proteins, which is crucial for the epigenetic inheritance of cells. Acetyl-CoA links lipid metabolism with histone acetylation to create a more intricate regulatory system that affects the growth, aggressiveness, and drug resistance of malignancies such as glioblastoma, breast cancer, and hepatocellular carcinoma. These fascinating advances in the knowledge of acetyl-CoA metabolism during carcinogenesis and normal physiology have raised interest regarding its modulation in malignancies. In this review, we provide an overview of the regulation and cancer relevance of main metabolic pathways in which acetyl-CoA participates. We also summarize the role of acetyl-CoA in the metabolic reprogramming and stress regulation of cancer cells, as well as medical application of inhibitors targeting its dysregulation in therapeutic intervention of cancers.

ZNF643/ZFP69B Exerts Oncogenic Properties and Associates with Cell Adhesion and Immune Processes

The global cancer burden remains high; thus, a better understanding of the molecular mechanisms driving carcinogenesis is needed to improve current prevention and treatment options. We previously detected the ZNF643/ZFP69B gene upregulated in multiple tumors, and we speculated it may play a role in tumor biology. To test this hypothesis, we employed TCGA-centered databases to correlate ZNF643 status with various clinicopathological parameters. We also performed RNA-seq analysis and in vitro studies assessing cancer cell phenotypes, and we searched for ZNF643-bound genomic loci. Our data indicated higher levels of ZNF643 in most analyzed tumors compared to normal samples, possibly due to copy number variations. ZNF643 mRNA correlated with diverse molecular and immune subtypes and clinicopathological features (tumor stage, grade, patient survival). RNA-seq analysis revealed that ZNF643 silencing triggers the deregulation of the genes implicated in various cancer-related processes, such as growth, adhesion, and immune system. Moreover, we observed that ZNF643 positively influences cell cycle, migration, and invasion. Finally, our ChIP-seq analysis indicated that the genes associated with ZNF643 binding are linked to adhesion and immune signaling. In conclusion, our data confirm the oncogenic properties of ZNF643 and pinpoint its impact on cell adhesion and immune processes.

MicroRNA-143 acts as a tumor suppressor through Musashi-2/DLL1/Notch1 and Musashi-2/Snail1/MMPs axes in acute myeloid leukemia

BACKGROUND

The previous studies have revealed that abnormal RNA-binding protein Musashi-2 (MSI2) expression is associated with cancer progression through post-transcriptional mechanisms, however mechanistic details of this regulation in acute myeloid leukemia (AML) still remain unclear. Our study aimed to explore the relationship between microRNA-143 (miR-143) and MSI2 and to clarify their clinical significance, biological function and mechanism.

METHODS

Abnormal expression of miR-143 and MSI2 were evaluated in bone marrow samples from AML patients by quantitative real time-PCR. Effects of miR-143 on regulating MSI2 expression were investigated using luciferase reporter assay. Functional roles of MSI2 and miR-143 on AML cell proliferation and migration were determined by CCK-8 assay, colony formation, and transwell assays in vitro and in mouse subcutaneous xenograft and orthotopic transplantation models in vivo. RNA immunoprecipitation, RNA stability measurement and Western blotting were performed to assess the effects of MSI2 on AML.

RESULTS

We found that MSI2 was significantly overexpressed in AML and exerted its role of promoting AML cell growth by targeting DLL1 and thereby activating Notch signaling pathway. Moreover, we found that MSI2 bound to Snail1 transcript and inhibited its degradation, which in turn upregulated the expression of matrix metalloproteinases. We also found that MSI2 targeting miR-143 is downregulated in AML. In the AML xenograft mouse model, overexpression of MSI2 recapitulated its leukemia-promoting effects, and overexpression of miR-143 partially attenuated tumor growth and prevented metastasis. Notably, low expression of miR-143, and high expression of MSI2 were associated with poor prognosis in AML patients.

CONCLUSIONS

Our data demonstrate that MSI2 exerts its malignant properties via DLL1/Notch1 cascade and the Snail1/MMPs axes in AML, and upregulation of miR-143 may be a potential therapeutic approach for AML.

Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer

Gastric cancer is one of the most common malignancies. Although some patients benefit from immunotherapy, the majority of patients have unsatisfactory immunotherapy outcomes, and the clinical significance of immune-related genes in gastric cancer remains unknown. We used the single-sample gene set enrichment analysis (ssGSEA) method to evaluate the immune cell content of gastric cancer patients from TCGA and clustered patients based on immune cell scores. The Weighted Correlation Network Analysis (WGCNA) algorithm was used to identify immune subtype-related genes. The patients in TCGA were randomly divided into test 1 and test 2 in a 1:1 ratio, and a machine learning integration process was used to determine the best prognostic signatures in the total cohort. The signatures were then validated in the test 1 and the test 2 cohort. Based on a literature search, we selected 93 previously published prognostic signatures for gastric cancer and compared them with our prognostic signatures. At the single-cell level, the algorithms "Seurat," "SCEVAN", "scissor", and "Cellchat" were used to demonstrate the cell communication disturbance of high-risk cells. WGCNA and univariate Cox regression analysis identified 52 prognosis-related genes, which were subjected to 98 machine-learning integration processes. A prognostic signature consisting of 24 genes was identified using the StepCox[backward] and Enet[alpha = 0.7] machine learning algorithms. This signature demonstrated the best prognostic performance in the overall, test1 and test2 cohort, and outperformed 93 previously published prognostic signatures. Interaction perturbations in cellular communication of high-risk T cells were identified at the single-cell level, which may promote disease progression in patients with gastric cancer. We developed an immune-related prognostic signature with reliable validity and high accuracy for clinical use for predicting the prognosis of patients with gastric cancer.

Translational Bioinformatics Applied to the Study of Complex Diseases

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: "How does TBI provide a scientific understanding of complex diseases?" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Ferroptosis and triple-negative breast cancer: Potential therapeutic targets

Purpose

Triple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC.

Methods

The TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC.

Results

We obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database.

Conclusion

The prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

Comprehensive Analysis of Long Non-Coding RNAs N4-Acetylcytidine in Alzheimer's Disease Mice Model Using High-Throughput Sequencing

BACKGROUND

N4-acetylcytidine (ac4C), an important posttranscriptional modification, is involved in various disease processes. Long noncoding RNAs (lncRNAs) regulate gene expression mainly through epigenetic modification, transcription, and posttranscriptional modification. Alzheimer's disease (AD) is a neurodegenerative disease characterized by amyloidosis of the brain. However, the role of lncRNA ac4C modification in AD remains unclear.

OBJECTIVE

In this study, we investigated the association between ac4C modification and AD, and the underlying mechanisms of ac4C modification in AD.

METHODS

The male 9-month-old APP/PS1 double transgenic mice, age- and sex-matched wild type (WT) mice were used in this study. Then, ac4C-RIP-seq and RNA-seq were used to comprehensively analyze lncRNA ac4C modification in AD mice. The lncRNA-miRNA-mRNA regulatory networks using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed the regulatory relationships among these three lncRNAs and AD.

RESULTS

The results showed that there were 120 significantly different ac4C peaks located on 102 lncRNAs in AD, of which 55 were hyperacetylated and 47 were hypoacetylated. Simultaneously, 231 differentially expressed lncRNAs were identified, including 138 upregulated lncRNAs and 93 downregulated lncRNAs. Moreover, 3 lncRNAs, lncRNA Gm26508, lncRNA A430046D13Rik, and lncRNA 9530059O14Rik, showed significant changes in both the ac4C and RNA levels using conjoint analysis.

CONCLUSION

The abundance of lncRNA ac4C modification is significantly different in AD and indicates that lncRNA ac4C is associated with the occurrence and development of AD, which could provide a basis for further exploration of the related regulatory mechanisms.

Identification of KIF21B as a Biomarker for Colorectal Cancer and Associated with Poor Prognosis

OBJECTIVE

This study is aimed at exploring the function of KIF21B in colorectal cancer.

METHODS

The expression of KIF21B was analyzed by the UALCAN database, GEPIA site, and TIMER site. The survival rate was analyzed by Kaplan-Meier curves, and the prognosis was analyzed by ROC. Relevant signaling pathways and biological processes were analyzed by GO-KEGG enrichment analysis. The correlation between KIF21B and cancer immune infiltrates was analyzed by TIMER. The functional state of KIF21B in various types of cancers was conducted by single-cell RNA-sequencing. Furthermore, the expression of KIF21B was verified by real-time qPCR and Western blotting. The cell proliferation was measured by CCK8 assay. The cell apoptosis was analyzed by flow cytometry. Cell migration and invasion were determined by the transwell assay.

RESULTS

Combination analysis of bioinformatics methods revealed that KIF21B is high expression in CRC, associated with poor survival. KIF21B and associated genes were significantly enriched in covalent chromatin modification. The expression of KIF21B was positively correlated with infiltrating levels of CD4+ T cells and neutrophils, cell apoptosis, and metastasis. KIF21B was upregulated expression in CRC cell lines. KIF21B deficiency reduced cell proliferation, migration, and invasion.

CONCLUSIONS

Our study suggested that KIF21B may be a biomarker in CRC.

Prognosis prediction and tumor immune microenvironment characterization based on tryptophan metabolism-related genes signature in brain glioma

Glioma is the most common malignant tumor in the central nervous system with no significant therapeutic breakthrough in recent years. Most attempts to apply immunotherapy in glioma have failed. Tryptophan and its metabolism can regulate malignant features of cancers and reshape immune microenvironment of tumors. However, the role of tryptophan metabolism in glioma remains unclear. In current study, we explored the relationships between the expression pattern of tryptophan metabolism-related genes (TrMGs) and tumor characteristics, including prognosis and tumor microenvironment of gliomas through analyzing 1,523 patients' samples from multiple public databases and our own cohort. Based on expression of TrMGs, K-means clustering analysis stratified all glioma patients into two clusters with significantly different TrMG expression patterns, clinicopathological features and immune microenvironment. Furthermore, we constructed a tryptophan metabolism-related genes signature (TrMRS) based on seven essential TrMGs to classify the patients into TrMRS low- and high-risk groups and validated the prognostic value of the TrMRS in multiple cohorts. Higher TrMRS represented for potentially more active tryptophan catabolism, which could subsequently lead to less tryptophan in tumor. The TrMRS high-risk group presented with shorter overall survival, and further analysis confirmed TrMRS as an independent prognostic factor in gliomas. The nomograms uniting TrMRS with other prognostic factors manifested with satisfactory efficacy in predicting the prognosis of glioma patients. Additionally, analyses of tumor immune landscapes demonstrated that higher TrMRS was correlated with more immune cell infiltration and "hot" immunological phenotype. TrMRS was also demonstrated to be positively correlated with the expression of multiple immunotherapy targets, including PD1 and PD-L1. Finally, the TrMRS high-risk group manifested better predicted response to immune checkpoint inhibitors. In conclusion, our study illustrated the relationships between expression pattern of TrMGs and characteristics of gliomas, and presented a novel model based on TrMRS for prognosis prediction in glioma patients. The association between TrMRS and tumor immune microenvironment of gliomas indicated an important role of tryptophan and its metabolism in reshaping immune landscape and the potential ability to guide the application of immunotherapy for gliomas.

DPP10-AS1-Mediated Downregulation of MicroRNA-324-3p Is Conducive to the Malignancy of Pancreatic Cancer by Enhancing CLDN3 Expression

OBJECTIVES

Network of long noncoding RNA-microRNA (miRNA)-mRNA is becoming increasingly pivotal roles in carcinogenesis mechanism. Herein, we aim to delineate the mechanistic understanding of dipeptidyl peptidase like 10-antisense RNA 1 (DPP10-AS1)/miRNA-324-3p/claudin 3 (CLDN3) axis in the malignancy of pancreatic cancer (PC).

METHODS

Microarray profiling and other bioinformatics methods were adopted to predict differentially expressed long noncoding RNA-miRNA-mRNA in PC, followed by verification of expression of DPP10-AS1, microRNA-324-3p (miR-324-3p), and CLDN3 in PC cells. The relationship among DPP10-AS1, miR-324-3p, and CLDN3 were further assessed. The PC cell invasion and migration were evaluated by scratch test and transwell assay. Tumor formation and lymph node metastasis were assessed in nude mice.

RESULTS

Highly expressed DPP10-AS1 and CLDN3 and poorly expressed miR-324-3p were identified in PC cells. The competitively binding between DPP10-AS1 and miR-324-3p was identified, and CLDN3 was targeted and downregulated by miR-324-3p. In addition, DPP10-AS1 was found to sequester miR-324-3p to release CLDN3 expression. DPP10-AS1 knockdown or miR-324-3p restoration diminished migration, invasion, tumor formation, microvessel density, and lymph node metastasis of PC cells, which was associated with CLDN3 downregulation.

CONCLUSIONS

Taken together, the study identified the regulatory role of DPP10-AS1/miR-324-3p/CLDN3 axis in PC, offering a mechanistic basis suggesting DPP10-AS1 ablation as a therapeutic target against PC.

A novel signature of combing cuproptosis- with ferroptosis-related genes for prediction of prognosis, immunologic therapy responses and drug sensitivity in hepatocellular carcinoma

Background

Our study aimed to construct a novel signature (CRFs) of combing cuproptosis-related genes with ferroptosis-related genes for the prediction of the prognosis, responses of immunological therapy, and drug sensitivity of hepatocellular carcinoma (HCC) patients.

Methods

The RNA sequencing and corresponding clinical data of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), GSE76427, GSE144269, GSE140580, Cancer Cell Line Encyclopedia (CCLE), and IMvigor210 cohorts. CRFs was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm. The analyses involved in the prognosis, response to immunologic therapy, efficacy of transcatheter arterial chemoembolization (TACE) therapy, and drug sensitivity were performed. Furthermore, the molecular function, somatic mutation, and stemness analyses were further performed between the low- and high-risk groups, respectively. In this study, the statistical analyses were performed by using the diverse packages of R 4.1.3 software and Cytoscape 3.8.0.

Results

CRFs included seven genes (G6PD, NRAS, RRM2, SQSTM1, SRXN1, TXNRD1, and ZFP69B). Multivariate Cox regression analyses demonstrated that CRFs were an independent risk factor for prognosis. In addition, these patients in the high-risk group presented with worse prognoses and a significant state of immunosuppression. Moreover, patients in the high-risk group might achieve greater outcomes after receiving immunologic therapy, while patients in the low-risk group are sensitive to TACE. Furthermore, we discovered that patients in the high-risk group may benefit from the administration of sunitinib. In addition, enhanced mRANsi and tumor mutation burden (TMB) yielded in the high-risk group. Additionally, the functions enriched in the low-risk group differed from those in the other group.

Conclusion

In summary, CRFs may be regarded not only as a novel biomarker of worse prognosis, but also as an excellent predictor of immunotherapy response, efficacy of TACE and drug sensitivity in HCC, which is worthy of clinical promotion.

Complement system-related genes in stomach adenocarcinoma: Prognostic signature, immune landscape, and drug resistance

Stomach adenocarcinoma (STAD) is one of the most common malignant tumors of the digestive tract, and its survival predictors are critical for precision medicine but have not been fully investigated. The complement system is a complex multistep cascade at the interface of innate and adaptive immunity, which augments the function of antibodies and phagocytes. This study aimed to construct and validate a CSRG signature based on TCGA (The Cancer Genome Atlas) STAD dataset and revalidated it in an external GEO (Gene Expression Omnibus) STAD cohort. Subsequently, we assessed the association of risk levels with the stromal and immune cell infiltration level in STAD using the ESTIMATE, single-sample Gene Set Enrichment Analysis (ssGSEA), and Microenvironment Cell Populations-counter (MCP-counter) algorithm. It was found that the CSRG signature, based on three genes (SERPINE1, PROC, and CFHR3), was significantly and independently associated with the OS in TCGA STAD patients (p < 0.001). Subsequently, we found that the high-risk STAD harbors more immune cell infiltration than the low-risk group, and the ESTIMATE results indicated that there exists a more stromal component in the tumor microenvironment of the high-risk groups. Compared to the low-risk group, the high-risk STAD patients had higher expressions of marker genes for immune checkpoint inhibitors (ICIs) and showed higher sensitivity to the chemotherapy agents (rapamycin, nilotinib, 5-fluorouracil, axitinib, DMOG, and JNK inhibitor VIII). The prognostic value of the CSRGs was further validated by nomogram plots, which revealed that it was superior to tumor TNM and pathologic stage. Finally, the three expression levels were evaluated in GES-1, HGC27, and AGS cells by qRT-PCR.

MAB21L4 Deficiency Drives Squamous Cell Carcinoma via Activation of RET

Epithelial squamous cell carcinomas (SCC) most commonly originate in the skin, where they display disruptions in the normally tightly regulated homeostatic balance between keratinocyte proliferation and terminal differentiation. We performed a transcriptome-wide screen for genes of unknown function that possess inverse expression patterns in differentiating keratinocytes compared with cutaneous SCC (cSCC), leading to the identification of MAB21L4 (C2ORF54) as an enforcer of terminal differentiation that suppresses carcinogenesis. Loss of MAB21L4 in human cSCC organoids increased expression of RET to enable malignant progression. In addition to transcriptional upregulation of RET, deletion of MAB21L4 preempted recruitment of the CacyBP-Siah1 E3 ligase complex to RET and reduced its ubiquitylation. In SCC organoids and in vivo tumor models, genetic disruption of RET or selective inhibition of RET with BLU-667 (pralsetinib) suppressed SCC growth while inducing concomitant differentiation. Overall, loss of MAB21L4 early during SCC development blocks differentiation by increasing RET expression. These results suggest that targeting RET activation is a potential therapeutic strategy for treating SCC.

SIGNIFICANCE

Downregulation of RET mediated by MAB21L4-CacyBP interaction is required to induce epidermal differentiation and suppress carcinogenesis, suggesting RET inhibition as a potential therapeutic approach in squamous cell carcinoma.

Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma

Background

Gastric cancer (GC) is the 5th most common cause of cancer in the world and the 3rd largest cause of cancer-related death. It is usually associated with a variety of cancers, of which cholangiocarcinoma (CCA) combined with GC accounts for about 1.6%. This study sought to examine the hub genes and role of lipid metabolism in the development and diagnosis of GC and CCA.

Methods

To screen potential hub genes, The Cancer Genome Atlas (TCGA) data sets, including the GC (STAD, dataset of GC) and CCA (CHOL, dataset of CCA) data sets, were used to conduct a differentially expressed gene (DEG) analysis and an enrichment analysis of the DEGs. A weighted-gene co-expression network analysis (WGCNA) was conducted to identify the significant gene module and then find the hub genes in the module. To verify the 4 hub genes, we conducted a differentiation analysis of the 4 genes in GC and CCA and found that there were differences. A survival analysis of the hub genes was performed and mutations were mapped. Additionally, tumor immune microenvironment (TIME) and immune analyses were performed to evaluate how lipid metabolism affects the development of GC with CCA.

Results

The principal component analysis showed that both GC and CCA had distinct up-regulated and down-regulated genes, which are involved in a variety of metabolic processes. Upon WGCNA, the turquoise and blue modules were meaningful, and the hub genes were identified from these 2 modules. Four hub genes were identified: amyloid beta precursor protein binding family B member 1 (APBB1), Homo sapiens armadillo repeat containing X-linked 1 (ARMCX1), DAZ interacting zinc finger protein 1 (DZIP1), and methionine sulfoxide reductase B3 (MSRB3). In survival analysis, increased expression of the 4 hub genes was associated with inferior survival outcomes, with variations in all 4 genes. Additionally, we demonstrated that genes related to lipid metabolism had an effect on immune function.

Conclusions

APBB1, ARMCX1, DZIP1, and MSRB3 affect the development of GC and CCA and can be used as biomarkers. The expression of lipid metabolism genes is related to the TIME of patients with GC and CCA.

Key Molecules of Fatty Acid Metabolism in Gastric Cancer

Fatty acid metabolism is closely linked to the progression of gastric cancer (GC), a very aggressive and life-threatening tumor. This study examines linked molecules, such as Sterol Regulatory Element-Binding Protein 1 (SREBP1), ATP Citrate Lyase (ACLY), Acetyl-CoA Synthases (ACSs), Acetyl-CoA Carboxylase (ACC), Fatty Acid Synthase (FASN), Stearoyl-CoA Desaturase 1 (SCD1), CD36, Fatty Acid Binding Proteins (FABPs), and Carnitine palmitoyltransferase 1 (CPT1), as well as their latest studies and findings in gastric cancer to unveil its core mechanism. The major enzymes of fatty acid de novo synthesis are ACLY, ACSs, ACC, FASN, and SCD1, while SREBP1 is the upstream molecule of fatty acid anabolism. Fatty acid absorption is mediated by CD36 and FABPs, and fatty acid catabolism is mediated by CPT1. If at all possible, we will discover novel links between fatty acid metabolism and a prospective gastric cancer target.

LINC00922 acts as a novel oncogene in gastric cancer

Background

Long non-coding RNAs (lncRNAs) have been discovered to participate in various cancer developments. However, the biological function of lncRNAs associated with gastric cancer (GC) has not been fully elucidated.

Methods

Quantitative RT-PCR (qRT-PCR) assay was performed to measure lncRNAs, microRNAs (miRNAs) and message RNA (mRNA) expression. Cell Counter Kit-8 (CCK-8), clone formation, wound healing, and transwell assays were performed to investigate cell proliferation, migration, invasion, and apoptosis. Fluorescence in situ hybridization (FISH) assay was used to analyze LINC00922 in either the cytoplasm or nucleus. The potential binding among lncRNA, miRNA, and mRNA was evidenced by bioinformatics, luciferase reporter assay. Mouse-xenograft experiments were used to explore the tumorigenesis in vivo.

Results

LINC00922 was upregulated in GC, and high LINC00922 expression was associated with poor prognosis. Inhibition of LINC00922 suppressed GC cell proliferation, migration, invasion, and activated cell apoptosis in vitro and inhibited tumorigenesis in vivo. Besides, LINC00922 was markedly located in the cytoplasm. The mechanistic analysis demonstrated that LINC00922 acted as a sponge of miR-204-5p, thereby inhibiting the expression of the target gene-High Mobility Group AT-hook 2 (HMGA2).

Conclusion

LINC00922 accelerated the progression of GC by miR-204-5p/HMGA2 axis. These findings support LINC00922 may be a promising option for the diagnosis and therapy of GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02569-3.

Progress in Metabolic Studies of Gastric Cancer and Therapeutic Implications

Background:

Worldwide, gastric cancer is ranked the fifth malignancy in incidence and the third malignancy in mortality. Gastric cancer causes an altered metabolism that can be therapeutically exploited.

Objective:

To provide an overview of the significant metabolic alterations caused by gastric cancer and propose a blockade.

Methods:

A comprehensive and up-to-date review of descriptive and experimental publications on the metabolic alterations caused by gastric cancer and their blockade. This is not a systematic review.

Results:

Gastric cancer causes high rates of glycolysis and glutaminolysis. There are increased rates of de novo fatty acid synthesis and cholesterol synthesis. Moreover, gastric cancer causes high rates of lipid turnover via fatty acid -oxidation. Preclinical data indicate that the individual blockade of these pathways via enzyme targeting leads to antitumor effects in vitro and in vivo. Nevertheless, there is no data on the simultaneous blockade of these five pathways, which is critical, as tumors show metabolic flexibility in response to the availability of nutrients. This means tumors may activate alternate routes when one or more are inhibited. We hypothesize there is a need to simultaneously blockade them to avoid or decrease the metabolic flexibility that may lead to treatment resistance.

Conclusions:

There is a need to explore the preclinical efficacy and feasibility of combined metabolic therapy targeting the pathways of glucose, glutamine, fatty acid synthesis, cholesterol synthesis, and fatty acid oxidation. This may have therapeutical implications because we have clinically available drugs that target these pathways in gastric cancer.

LncRNA–miRNA–mRNA Networks of Gastrointestinal Cancers Representing Common and Specific LncRNAs and mRNAs

Gastrointestinal (GI) cancers are responsible for approximately half of cancer-related deaths, highlighting the need for the identification of distinct and common features in their clinicopathological characteristics. Long ncRNA (lncRNAs), which are involved in competitive endogenous RNA (ceRNA) networks with critical roles in biological processes, constitute a substantial number of non-coding RNAs. Therefore, our study aimed to investigate the similarities and differences in the ceRNA networks of The Cancer Genome Atlas (TCGA)-GI cancers. We performed a comprehensive bioinformatics analysis of ceRNA networks for TCGA-GI cancers in terms of the deferential mRNA, lncRNA, and miRNA expression levels, ceRNA networks, overall survival analysis, correlation analysis, pathological cancer stages, and gene set enrichment analysis. Our study revealed several common and distinct mRNAs and lncRNAs with prognostic values in these networks. It was specifically noteworthy that MAGI2-AS3 lncRNA was found to be shared in almost all GI cancers. Moreover, the most common shared mRNAs between GI cancers were MEIS1, PPP1R3C, ADAMTSL3, RIPOR2, and MYLK. For each cancer ceRNA network, we found that the expression level of a number of lncRNAs and mRNAs was specific. Furthermore, our study provided compelling evidence that several genes, most notably KDELC1, can act as novel proto-oncogenes in cancers. This, in turn, can highlight their role as new prognostic and therapeutic targets. Moreover, we found cell cycle and extracellular matrix structural constituent as the top shared KEGG and molecular function, respectively, among GI cancers. Our study revealed several known lncRNAs and known and unknown mRNAs in GI cancers with diagnostic and prognostic values.

Clinical Potential of lncRNA PPP1R26-AS1 in Breast Cancer and Its Contribution to Cancer Progression

Breast cancer has become the most leading diagnosed tumor worldwide in 2020. In this study, the biomarker potential and influence on the cellular function of lncRNA PPP1R26-AS1 was investigated in breast cancer. Expression levels of lncRNA PPP1R26-AS1 in breast tissues and cells were detected by RT-qPCR. Association between lncRNA PPP1R26-AS1 level and clinical parameters was investigated by Chi-square analysis. The prognostic potential was assessed by Kaplan-Meier and multivariate Cox regression analysis. Knockdown of lncRNA PPP1R26-AS1 was subjected to study the effect on cell proliferation, invasion, and migration by CCK-8 and transwell assay. The bind between PPP1R26-AS1 and miR-1226-3p was investigated. LncRNA PPP1R26-AS1 was highly expressed in breast tissues and cell lines. This upregulation was correlated with pTNM, positive ER status, luminal B subtype, positive nodal status, and shorter overall survival in breast cancer patients. Significant decreases in proliferation, migration, and invasion activity were observed upon knockdown of lncRNA PPP1R26-AS1. lncRNA PPP1R26-AS1 could act as ceRNA to bind with miR-1226-3p in breast cancer. LncRNA PPP1R26-AS1, as oncogenic lncRNA, could provide a new perspective on the development of prognostic biomarkers and a new approach in tailoring the treatment personalized in breast cancer.

The Role of miR-4256/HOXC8 Signaling Axis in the Gastric Cancer Progression: Evidence From lncRNA-miRNA-mRNA Network Analysis

Gastric cancer is a deadly human malignancy and the molecular mechanisms underlying gastric cancer pathophysiology are very complicated. Thus, further investigations are warranted to decipher the underlying molecular mechanisms. With the development of high-throughput screening and bioinformatics, gene expression profiles with large scale have been performed in gastric cancer. In the present study, we mined The Cancer Genome Atlas (TCGA) database and analyzed the gene expression profiles between gastric cancer tissues and normal gastric tissues. A series of differentially expressed lncRNAs, miRNAs and mRNAs between gastric cancer tissues and normal gastric tissues were identified. Based on the differentially expressed genes, we constructed miRNA-mRNA network, lncRNA-mRNA network and transcriptional factors-mRNA-miRNA-lncRNA network. Furthermore, the Kaplan survival analysis showed that high expression levels of EVX1, GBX2, GCM1, HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13 were all significantly correlated with shorter overall survival of the patients with gastric cancer. On the other hand, low expression level of HOXA13 was associated with shorter overall survival of patients with gastric cancer. Among these hub genes, we performed the in vitro functional studies of HOXC8 in the gastric cancer cells. Knockdown of HOXC8 and overexpression of miR-4256 both significantly repressed the gastric cancer cell proliferation and migration, and miR-4256 repressed the expression of HOXC8 via targeting its 3' untranslated region in gastric cancer cells. Collectively, our results revealed that a complex interaction networks of differentially expressed genes in gastric cancer, and further functional studies indicated that miR-4256/HOXC8 may be an important axis in regulating gastric cancer progression.

Long non-coding RNA p53 upregulated regulator of p53 levels (PURPL) promotes the development of gastric cancer

Gastric cancer (GC), one of the most prevalent malignancies across the world, has an increasing incidence rate. Long non-coding RNA (lncRNA) PURPL (also referred to as LINC01021) has been demonstrated to influence malignant GC behaviors and partake in other cancers. Notwithstanding, reports pertaining to the underlying mechanism of PURPL in GC haven’t been rarely seen. Presently, in-vivo and ex-vivo experiments were implemented to examine the PURPL-miR-137-ZBTB7A-PI3K-AKT-NF-κB regulatory axis in GC. Our statistics revealed that PURPL presented a high expression in GC tissues and cell lines. PURPL overexpression remarkably exacerbated colony formation, migration, and invasion and repressed apoptosis in GC cells (AGS and MNK-45). In-vivo experiments also corroborated that cell growth was boosted by PURPL up-regulation. Mechanistic investigations verified that PURPL interacted with miR-137 and lowered its profile in GC cell lines. miR-137 overexpression or ZBTB7A knockdown upended the oncogenic function mediated by PURPL. PURPL initiated the PI3K/AKT/NF-κB pathway. PI3K and NF-κB inhibition impaired the promoting impact on GC cells elicited by PURPL overexpression and contributed to PURPL down-regulation. These findings disclosed that PURPL serves as an oncogene in the context of GC via miR-137-ZBTB7A-PI3K-AKT-NF-κB axis modulation.

Revealing the Role of lncRNA CCDC144NL-AS1 and LINC01614 in Gastric Cancer via Integrative Bioinformatics Analysis and Experimental Validation

Long non-coding RNAs (lncRNAs) are key regulators in the pathophysiology of gastric cancer, and lncRNAs have been regarded as potential biomarkers and therapeutic targets for gastric cancer. The present study performed the WGCNA analysis of the GSE70880 dataset and aimed to identify novel lncRNAs associated with gastric cancer progression. Based on the WGCNA, the lncRNAs and mRNA co-expression network were constructed. A total of four modules were identified and the eigengenes in different modules were involved in various key signaling pathways. Furthermore, the co-expression networks were constructed between the lncRNAs and mRNA; this leads to the identification of 6 modules, which participated in various cellular pathways. The survival analysis showed that high expression of CCDC144NL antisense RNA 1 (CCDC144NL-AS1) and LINC01614 was positively correlated with the poor prognosis of patients with gastric cancer. The in vitro validation results showed that CCDC144NL-AS1 and LINC01614 were both up-regulated in the gastric cancer cells. Silence of CCDC144NL-AS1 and LINC01614 both significantly suppressed the cell proliferation and migration of gastric cancer cells, and also promoted the chemosensitivity of gastric cancer cells to 5-fluorouracil. Collectively, our results suggested that the newly identified two lncRNAs (CCDC144NL-AS1 and LINC01614) may act as oncogenes in gastric cancer.

Expression characteristics of long noncoding RNA and messenger RNA in human traumatic brain injury

OBJECTIVES

The role of long noncoding RNAs has attracted significant attention in diseases. However, their expression characteristics in human traumatic brain injury are unclear.

METHODS

The brain contusion tissues and tissues adjacent to the brain contusion from 6 server traumatic brain injury patients were used to analyze differential expression signatures of long noncoding RNAs and mRNAs via full-length transcriptome sequencing, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis and establishment of a long noncoding RNA/mRNA coexpression network.

RESULTS

We identified 1720 long noncoding RNAs and 1632 mRNAs differential expression. Microarray analysis showed that 874 long noncoding RNAs and 1405 mRNAs were upregulated, 846 long noncoding RNAs and 227 mRNAs were downregulated. Subsequently, we used Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to reveal signaling pathways that were associated with target genes. Then, a long noncoding RNA/mRNA coexpression network was generated, which showed an absolute correlation coefficient value >0.99 for 559 long noncoding RNA-mRNA pairs. Finally, we comprehensive analyzed long noncoding RNA/mRNA coexpression network and Kyoto Encyclopedia of Genes and Genomes pathway and found the top five pairs of long noncoding RNA/ mRNA. Accordingly, we identified that long noncoding RNA tubulin beta 6 class V/nuclear factor E2-related factor 2 was most closely related to the pathological process after traumatic brain injury.

CONCLUSIONS

Our results indicated that the expression profiles of long noncoding RNAs and mRNAs were different after traumatic brain injury, providing new insight regarding long noncoding RNAs in human traumatic brain injury.

Close interactions between lncRNAs, lipid metabolism and ferroptosis in cancer

Abnormal lipid metabolism including synthesis, uptake, modification, degradation and transport has been considered a hallmark of malignant tumors and contributes to the supply of substances and energy for rapid cell growth. Meanwhile, abnormal lipid metabolism is also associated with lipid peroxidation, which plays an important role in a newly discovered type of regulated cell death termed ferroptosis. Long noncoding RNAs (lncRNAs) have been proven to be associated with the occurrence and progression of cancer. Growing evidence indicates that lncRNAs are key regulators of abnormal lipid metabolism and ferroptosis in cancer. In this review, we mainly summarized the mechanism by which lncRNAs regulate aberrant lipid metabolism in cancer, illustrated that lipid metabolism can also influence the expression of lncRNAs, and discussed the mechanism by which lncRNAs affect ferroptosis. A comprehensive understanding of the interactions between lncRNAs, lipid metabolism and ferroptosis could help us to develop novel strategies for precise cancer treatment in the future.

Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease.

Methods

The RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature.

Results

Two completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=−0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=−0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC.

Conclusions

TTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.

Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization

Gastric Cancer (GC) is a common cancer worldwide with a high morbidity and mortality rate in Asia. Many prognostic signatures from genes and non-coding RNA (ncRNA) levels have been identified by high-throughput expression profiling for GC. To date, there have been no reports on integrated optimization analysis based on the GC global lncRNA-miRNA-mRNA network and the prognostic mechanism has not been studied. In the present work, a Gastric Cancer specific lncRNA-miRNA-mRNA regulatory network (GCsLMM) was constructed based on the ceRNA hypothesis by combining miRNA-target interactions and data on the expression of GC. To mine for novel prognostic signatures associated with GC, we performed topological analysis, a random walk with restart algorithm, in the GCsLMM from three levels, miRNA-, mRNA-, and lncRNA-levels. We further obtained candidate prognostic signatures by calculating the integrated score and analyzed the robustness of these signatures by combination strategy. The biological roles of key candidate signatures were also explored. Finally, we targeted the PHF10 gene and analyzed the expression patterns of PHF10 in independent datasets. The findings of this study will improve our understanding of the competing endogenous RNA (ceRNA) regulatory mechanisms and further facilitate the discovery of novel prognostic biomarkers for GC clinical guidelines.