ARNTL2 promotes pancreatic ductal adenocarcinoma progression through TGF/BETA pathway and is regulated by miR-26a-5p

Advances in pancreatic cancer diagnosis: from DNA methylation to AI-assisted imaging

INTRODUCTION

Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the various innovative biomarkers for PC detection, such as DNA methylation, Noncoding RNAs, and proteomic biomarkers, and the role of AI in PC detection at early stages.

AREA COVERED

Innovative biomarkers, such as DNA methylation genes, show higher specificity and sensitivity in PC diagnosis. Additionally, various non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs, show high diagnostic accuracy and serve as diagnostic and prognostic biomarkers. Additionally, proteomic biomarkers retain higher diagnostic accuracy in different body fluids. Apart from this, the utilization of AI showed that AI surpassed the radiologist's diagnostic performance in PC detection.

EXPERT OPINION

The combination of AI and advanced biomarkers can revolutionize early PC detection. However, large-scale, prospective studies are needed to validate its clinical utility. Further. standardization of biomarker panels and AI algorithms is a vital step toward their reliable applications in early PC detection, ultimately improving patient outcomes. [Figure: see text].

Circadian immunometabolism: A future insight for targeted therapy in cancer

Circadian rhythms send messages to regulate the sleep-wake cycle in living beings, which, regulate various biological activities. It is well known that altered sleep-wake cycles affect host metabolism and significantly deregulate the host immunity. The dysregulation of circadian-related genes is critical for various malignancies. One of the hallmarks of cancer is altered metabolism, the effects of which spill into surrounding microenvironments. Here, we review the emerging literature linking the circadian immunometabolic axis to cancer. Small metabolites are the products of various metabolic pathways, that are usually perturbed in cancer. Genes that regulate circadian rhythms also regulate host metabolism and control metabolite content in the tumor microenvironment. Immune cell infiltration into the tumor site is critical to perform anticancer functions, and altered metabolite content affects their trafficking to the tumor site. A compromised immune response in the tumor microenvironment aids cancer cell proliferation and immune evasion, resulting in metastases. The role of circadian rhythms in these processes is largely overlooked and demands renewed attention in the search for targets against cancer growth and spread. The precision medicine approach requires targeting the circadian immune metabolism in cancer.

Integrative analysis of a novel signature incorporating metabolism and stemness-related genes for risk stratification and assessing clinical outcomes and therapeutic responses in lung adenocarcinoma

BACKGROUND

Metabolism and stemness-related genes (msRGs) are critical in the development and progression of lung adenocarcinoma (LUAD). Nevertheless, reliable prognostic risk signatures derived from msRGs have yet to be established.

METHODS

In this study, we downloaded and analyzed RNA-sequencing and clinical data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We employed univariate and multivariate Cox regression analyses, along with least absolute shrinkage and selection operator (LASSO) regression analysis, to identify msRGs that are linked to the prognosis of LUAD and to develop the prognostic risk signature. The prognostic value was evaluated using Kaplan-Meier analysis and log-rank tests. We generated receiver operating characteristic (ROC) curves to evaluate the predictive capability of the prognostic signature. To estimate the relative proportions of infiltrating immune cells, we utilized the CIBERSORT algorithm and the MCPCOUNTER method. The prediction of the half-maximal inhibitory concentration (IC50) for commonly used chemotherapy drugs was conducted through ridge regression employing the "pRRophetic" R package. The validation of our analytical findings was performed through both in vivo and in vitro studies.

RESULTS

A novel five-gene prognostic risk signature consisting of S100P, GPX2, PRC1, ARNTL2, and RGS20 was developed based on the msRGs. A risk score derived from this gene signature was utilized to stratify LUAD patients into high- and low-risk groups, with the former exhibiting significantly poorer overall survival (OS). A nomogram was constructed incorporating the risk score and other clinical characteristics, showcasing strong capabilities in estimating the OS rates for LUAD patients. Furthermore, we observed notable differences in the infiltration of various immune cell subtypes, as well as in responses to immunotherapy and chemotherapy, between the low-risk and high-risk groups. Results from gene set enrichment analysis (GSEA) and in vitro studies indicated that the prognostic signature gene ARNTL2 influenced the prognosis of LUAD patients, primarily through the activation of the PI3K/AKT/mTOR signaling pathway.

CONCLUSIONS

Utilizing this gene signature for risk stratification could help with clinical treatment management and improve the prognosis of LUAD patients.

ARNTL2: a key player in promoting tumor aggressiveness in papillary thyroid cancer

Background

The increasing occurrence of thyroid cancer (TC), particularly papillary thyroid cancer (PTC), highlights our need for better diagnostic indicators and new therapeutic targets. Aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) plays a crucial function in multiple tumor types. Accordingly, we investigated the oncogenic function and molecular pathways associated with ARNTL2 in PTC.

Methods

Our study utilized the The Cancer Genome Atlas (TCGA) database to examine ARNTL2 expression, which was subsequently confirmed in PTC tissues and cell lines employing quantitative real-time polymerase chain reaction (qRT-PCR) and western blot (WB) analysis. Herein, we evaluated PTC cell proliferation, cell cycle progression, apoptosis, migration, and invasion through Cell Counting Kit-8 (CCK-8), flow cytometry, wound-healing assay, and Transwell assay. Eventually, we determined the mechanism behind ARNTL2 in PTC via WB.

Results

In PTC, a significant ARNTL2 upregulation was observed, which exhibited a positive correlation with enhanced tumor aggressiveness. Additionally, knocking down ARNTL2 facilitated apoptosis, besides impeding cell cycle progression, cell proliferation, migration, and invasion, alongside epithelial-mesenchymal transition (EMT) in PTC. However, the outcomes were reversed when ARNTL2 was overexpressed. Enhanced expression of ARNTL2 led to an elevation in phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) phosphorylation within PTC cells, while the administration of alpelisib effectively mitigated the effects induced by upregulated ARNTL2 on EMT, PTC cell proliferation, apoptosis, and invasion.

Conclusions

Elevated ARNTL2 levels enhance PTC proliferation, migration, invasion, and EMT while inhibiting apoptosis through the cell cycle signaling, elucidating its potential as a diagnostic PTC biomarker.

DysRegNet: Patient-specific and confounder-aware dysregulated network inference towards precision therapeutics

BACKGROUND AND PURPOSE

Gene regulation is frequently altered in diseases in unique and patient-specific ways. Hence, personalised strategies have been proposed to infer patient-specific gene-regulatory networks. However, existing methods do not scale well because they often require recomputing the entire network per sample. Moreover, they do not account for clinically important confounding factors such as age, sex or treatment history. Finally, a user-friendly implementation for the analysis and interpretation of such networks is missing.

EXPERIMENTAL APPROACH

We present DysRegNet, a method for inferring patient-specific regulatory alterations (dysregulations) from bulk gene expression profiles. We compared DysRegNet to the well-known SSN method, considering patient clustering, promoter methylation, mutations and cancer-stage data.

KEY RESULTS

We demonstrate that both SSN and DysRegNet produce interpretable and biologically meaningful networks across various cancer types. In contrast to SSN, DysRegNet can scale to arbitrary sample numbers and highlights the importance of confounders in network inference, revealing an age-specific bias in gene regulation in breast cancer. DysRegNet is available as a Python package (https://github.com/biomedbigdata/DysRegNet_package), and analysis results for 11 TCGA cancer types are available through an interactive web interface (https://exbio.wzw.tum.de/dysregnet).

CONCLUSION AND IMPLICATIONS

DysRegNet introduces a novel bioinformatics tool enabling confounder-aware and patient-specific network analysis to unravel regulatory alteration in complex diseases.

A predicted epithelial-to-mesenchymal transition-associated mRNA/miRNA axis contributes to the progression of diabetic liver disease

Despite public health measures, type 2 diabetes (T2D) is still a significant concern worldwide, given its associated complications, including hepatic alterations. The role of epithelial-to-mesenchymal transition (EMT) in liver fibrosis is well established. However, its effects on the progression of diabetic liver diseases are not well understood. Therefore, this study aims to investigate the mRNA/miRNA axes involved in this process. Bioinformatic analysis revealed new EMT-associated genes (CDH2, ITGB1, COL4A1, COL1A1, TNC, CCN2, and JUN), which showed higher expression in obese T2D and hepatocellular carcinoma (HCC) patients. In addition, six miRNAs (miR-21-5p, miR-26a-5p, miR-34a-5p, miR-106a-5p, miR-320a-3p and miR-424-5p) have been found as potential targets. Among them, miR-26a-5p and miR-424-5p were significantly downregulated in nonalcoholic steatohepatitis (NASH) and HCC (p < 0.05), being considered potential negative regulators of the EMT process. In our hepatic mesenchymal culture model, miR-26a-5p negatively regulated cadherin 2 (also known as N-cadherin, CDH2) and promoted the cadherin 1 (also known as E-cadherin, CDH1) expression. Our results reveal potential molecules involved in liver tumor development. Moreover, we observe that miR-26a-5p impairs EMT in the initial stages of diabetic liver disease by inhibiting CDH2 and could be a valuable target in this pathology.

Identification of a Novel Signature Based on Ferritinophagy-Related Genes to Predict Prognosis in Lung Adenocarcinoma: Focus on AHNAK2

BACKGROUND

Lung adenocarcinoma (LUAD) accounts for over 40% of all non-small cell lung cancer (NSCLC) cases and continues to be difficult to treat despite advancements in diagnostics and therapies. Ferritinophagy, a newly recognized autophagy process linked to ferroptosis, has been associated with LUAD development. Recent studies have shown a dysregulation of genes related to ferritinophagy in LUAD, indicating its potential as a therapeutic target.

METHODS

We constructed a predictive model using seven genes associated with ferritinophagy. The model's accuracy was evaluated across three independent gene expression datasets. We analyzed the biological functions, immune environment, mutations, and drug sensitivities in groups with high and low risk. Utilizing a single-cell sequencing (scRNA-seq) dataset, we confirmed the expression of the model genes and identified a subtype of epithelial cells expressing AHNAK2. We further investigated the impact of the ferritinophagy-related gene AHNAK2 on LUAD cell proliferation, invasion, migration, and ferroptosis in vitro.

RESULTS

Our prediction model, comprising seven genes (AHNAK2, ARNTL2, CD27, LTB, SLC15A1, SLC2A1, and SYT1), has shown potential in predicting the prognosis of individuals diagnosed with LUAD. Notably, AHNAK2 impedes ferroptosis, promoting LUAD progression in vitro.

CONCLUSIONS

Our research suggests that ferritinophagy-associated genes are promising prognostic markers for LUAD and lay the groundwork for further exploration of ferritinophagy's role in LUAD. Furthermore, we present AHNAK2 as a novel regulator of ferroptosis, which requires further investigation to understand its mechanism.

ARNTL2 facilitates bladder cancer progression through potentiating ENO1-mediated glycolysis in a SLC31A1-independent and -dependent manner

BACKGROUND

Basic helix-loop-helix ARNT like 2 (ARNTL2) is a transcription factor that controls the circadian rhythm. Amounts of studies have demonstrated the carcinogenic function of ARNTL2 in human malignant tumors albeit the underlying mechanisms remain poorly understood. We aimed to study the significance of ARNTL2 in bladder cancer (BLCA).

METHODS

Immunohistochemical staining, immunoblotting and the database from TCGA were used to analyze the clinical relevance of ARNTL2, enolase 1 (ENO1) and solute carrier family 31 member 1 (SLC31A1) in BLCA. The function of ARNTL2 was explored by cell proliferation assay, apoptosis, colony formation and xenografted tumorigenesis. The molecular mechanisms of ARNTL2-driving BLCA development were investigated by RT-qPCR, immunoblotting and luciferase assays. Glycolysis was checked by measuring glucose consumption and lactate production. ENO1 activity was assessed by using indicated assay kit.

RESULTS

Overexpression of ARNTL2 facilitates the proliferation and tumorigenesis of BLCA cells through suppression of apoptosis and enhancement of glycolysis. Up-regulation of SLC31A1, ENO1, and enhancement of SLC31A1-mediated ENO1 activity were critical for ARNTL2-triggered glycolysis and malignant growth in BLCA cells. ARNTL2 was positively correlated with SLC31A1 and ENO1 in BLCA patients. High expression of ARNTL2, SLC31A1 or ENO1 predicted the poor prognosis of BLCA patients. Depletion of SLC31A1 and inhibition of glycolysis completely blunted the growth ability of BLCA cells.

CONCLUSION

In summary, ARNTL2 facilitates the progression of BLCA via activating ENO1-mediated glycolysis in a SLC31A1-independent and -dependent manner. Inhibiting SLC31A1 and glycolysis may be an aspirational approach for the treatment of BLCA patients with overexpression of ARNTL2.

LINC01232 promotes ARNTL2 transcriptional activation and inhibits ferroptosis of CRC cells through p300/H3K27ac

Aim: This study investigated the role of lncRNA LINC01232 in ferroptosis of colorectal cancer (CRC).Materials & methods: Real time quantitative polymerase chain reaction or western blot experiments were performed to examine relevant mRNAs and proteins expression. The kit assays evaluated malondialdehyde, iron, Fe2+ and glutathione levels. ROS levels were verified by flow cytometry. Chromatin immunoprecipitation and RNA immunoprecipitation analysis monitored the correlation among LINC01232, H3K27ac, p300 and ARNTL2.Results: LINC01232 or ARNTL2 knockdown facilitated erastin-induced ferroptosis. The interaction between LINC01232 and p300 resulted in the enhancement of H3K27ac levels at ARNTL2 promoter to promote ARNTL2 transcriptional activity. ARNTL2 overexpression reversed the promoting effect of LINC01232 knockdown on ferroptosis.Conclusion: LINC01232 inhibited the ferroptosis in CRC by epigenetically upregulating the transcriptional activity of ARNTL2.

A novel tumor-derived exosomal gene signature predicts prognosis in patients with pancreatic cancer

Background

Pancreatic cancer is a devastating disease with poor prognosis. Accumulating evidence has shown that exosomes and their cargo have the potential to mediate the progression of pancreatic cancer and are promising non-invasive biomarkers for the early detection and prognosis of this malignancy. This study aimed to construct a gene signature from tumor-derived exosomes with high prognostic capacity for pancreatic cancer using bioinformatics analysis.

Methods

Gene expression data of solid pancreatic cancer tumors and blood-derived exosome tissues were downloaded from The Cancer Genome Atlas (TCGA) and ExoRBase 2.0. Overlapping differentially expressed genes (DEGs) in the two datasets were analyzed, followed by functional enrichment analysis, protein-protein interaction networks, and weighted gene co-expression network analysis (WGCNA). Using the least absolute shrinkage and selection operator (LASSO) regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was constructed based on the TCGA dataset, which was validated by an external validation dataset, GSE62452. The prognostic power of this gene signature and its relationship with various pathways and immune cell infiltration were analyzed.

Results

A total of 166 overlapping DEGs were identified from the two datasets, which were markedly enriched in functions and pathways associated with the cell cycle. Two key modules and corresponding 70 exosomal DEGs were identified using WGCNA. Using LASSO Cox regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was built using six exosomal DEGs (ARNTL2, FHL2, KRT19, MMP1, CDCA5, and KIF11), which showed high predictive performance for prognosis in both the training and validation datasets. In addition, this prognostic signature is associated with the differential activation of several pathways, such as the cell cycle, and the infiltration of some immune cells, such as Tregs and CD8+ T cells.

Conclusions

This study established a six-exosome gene signature that can accurately predict the prognosis of pancreatic cancer.

The circadian gene ARNTL2 promotes nasopharyngeal carcinoma invasiveness and metastasis through suppressing AMOTL2-LATS-YAP pathway

Metastasis is the major culprit of treatment failure in nasopharyngeal carcinoma (NPC). Aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2), a core circadian gene, plays a crucial role in the development of various tumors. Nevertheless, the biological role and mechanism of ARNTL2 are not fully elucidated in NPC. In this study, ARNTL2 expression was significantly upregulated in NPC tissues and cells. Overexpression of ARNTL2 facilitated NPC cell migration and invasion abilities, while inhibition of ARNTL2 in similarly treated cells blunted migration and invasion abilities in vitro. Consistently, in vivo xenograft tumor models revealed that ARNTL2 silencing reduced nude mice inguinal lymph node and lung metastases, as well as tumor growth. Mechanistically, ARNTL2 negatively regulated the transcription expression of AMOTL2 by directly binding to the AMOTL2 promoter, thus reducing the recruitment and stabilization of AMOTL2 to LATS1/2 kinases, which strengthened YAP nuclear translocation by suppressing LATS-dependent YAP phosphorylation. Inhibition of AMOTL2 counteracted the effects of ARNTL2 knockdown on NPC cell migration and invasion abilities. These findings suggest that ARNTL2 may be a promising therapeutic target to combat NPC metastasis and further supports the crucial roles of circadian genes in cancer development.

Ras-dependent activation of BMAL2 regulates hypoxic metabolism in pancreatic cancer

To identify drivers of malignancy in human pancreatic ductal adenocarcinoma (PDAC), we performed regulatory network analysis on a large collection of expression profiles from laser capture microdissected samples of PDAC and benign precursors. We discovered that BMAL2 plays a role in the initiation, progression, post resection survival, and KRAS activity in PDAC. Functional analysis of BMAL2 target genes led us to hypothesize that it plays a role in regulating the response to hypoxia, a critical but poorly understood feature of PDAC physiology. Knockout of BMAL2 in multiple human PDAC cell lines revealed effects on viability and invasion, particularly under hypoxic conditions. Loss of BMAL2 also affected glycolysis and other metabolic processes. We found that BMAL2 directly regulates hypoxia-responsive target genes. We also found that BMAL2 is necessary for the stabilization of HIF1A upon exposure to hypoxia, but destabilizes HIF2A under hypoxia. These data demonstrate that BMAL2 is a master transcriptional regulator of hypoxia responses in PDAC and may serve as a long-sought molecular switch that distinguishes HIF1A- and HIF2A-dependent modes of hypoxic metabolism.

MicroRNA-26a in respiratory diseases: mechanisms and therapeutic potential

MicroRNAs (miRNAs) are short, non-coding single-stranded RNA molecules approximately 22 nucleotides in length, intricately involved in post-transcriptional gene expression regulation. Over recent years, researchers have focused keenly on miRNAs, delving into their mechanisms in various diseases such as cancers. Among these, miR-26a emerges as a pivotal player in respiratory ailments such as pneumonia, idiopathic pulmonary fibrosis, lung cancer, asthma, and chronic obstructive pulmonary disease. Studies have underscored the significance of miR-26a in the pathogenesis and progression of respiratory diseases, positioning it as a promising therapeutic target. Nevertheless, several challenges persist in devising medical strategies for clinical trials involving miR-26a. In this review, we summarize the regulatory role and significance of miR-26a in respiratory diseases, and we analyze and elucidate the challenges related to miR-26a druggability, encompassing issues such as the efficiency of miR-26a, delivery, RNA modification, off-target effects, and the envisioned therapeutic potential of miR-26a in clinical settings.

MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications

Pancreatic cancer remains a formidable malignancy characterized by high mortality rates, primarily attributable to late-stage diagnosis and a dearth of effective therapeutic interventions. The identification of reliable biomarkers holds paramount importance in enhancing early detection, prognostic evaluation, and targeted treatment modalities. Small non-coding RNAs, particularly microRNAs, have emerged as promising candidates for pancreatic cancer biomarkers in recent years. In this review, we delve into the evolving role of cellular and circulating miRNAs, including exosomal miRNAs, in the diagnosis, prognosis, and therapeutic targeting of pancreatic cancer. Drawing upon the latest research advancements in omics data-driven biomarker discovery, we also perform a case study using public datasets and address commonly identified research discrepancies, challenges, and limitations. Lastly, we discuss analytical approaches that integrate multimodal analyses incorporating clinical and molecular features, presenting new insights into identifying robust miRNA-centric biomarkers.

Activation of the PI3K/AKT signaling pathway by ARNTL2 enhances cellular glycolysis and sensitizes pancreatic adenocarcinoma to erlotinib

BACKGROUND

Pancreatic adenocarcinoma (PC) is an aggressive malignancy with limited treatment options. The poor prognosis primarily stems from late-stage diagnosis and when the disease has become therapeutically challenging. There is an urgent need to identify specific biomarkers for cancer subtyping and early detection to enhance both morbidity and mortality outcomes. The addition of the EGFR tyrosine kinase inhibitor (TKI), erlotinib, to gemcitabine chemotherapy for the first-line treatment of patients with advanced pancreatic cancer slightly improved outcomes. However, restricted clinical benefits may be linked to the absence of well-characterized criteria for stratification and dependable biomarkers for the prediction of treatment effectiveness.

METHODS AND RESULTS

We examined the levels of various cancer hallmarks and identified glycolysis as the primary risk factor for overall survival in PC. Subsequently, we developed a glycolysis-related score (GRS) model to accurately distinguish PC patients with high GRS. Through in silico screening of 4398 compounds, we discovered that erlotinib had the strongest therapeutic benefits for high-GRS PC patients. Furthermore, we identified ARNTL2 as a novel prognostic biomarker and a predictive factor for erlotinib treatment responsiveness in patients with PC. Inhibition of ARNTL2 expression reduced the therapeutic efficacy, whereas increased expression of ARNTL2 improved PC cell sensitivity to erlotinib. Validation in vivo using patient-derived xenografts (PDX-PC) with varying ARNTL2 expression levels demonstrated that erlotinib monotherapy effectively halted tumor progression in PDX-PC models with high ARNTL2 expression. In contrast, PDX-PC models lacking ARNTL2 did not respond favorably to erlotinib treatment. Mechanistically, we demonstrated that the ARNTL2/E2F1 axis-mediated cellular glycolysis sensitizes PC cells to erlotinib treatment by activating the PI3K/AKT signaling pathway.

CONCLUSIONS

Our investigations have identified ARNTL2 as a novel prognostic biomarker and predictive indicator of sensitivity. These results will help to identify erlotinib-responsive cases of PC and improve treatment outcomes. These findings contribute to the advancement of precision oncology, enabling more accurate and targeted therapeutic interventions.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Identification of Prognostic Markers and Potential Therapeutic Targets using Gene Expression Profiling and Simulation Studies in Pancreatic Cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a 5-year relative survival rate of less than 10% making it one of the most fatal cancers. A lack of early measures of prognosis, challenges in molecular targeted therapy, ineffective adjuvant chemotherapy, and strong resistance to chemotherapy cumulatively make pancreatic cancer challenging to manage.

OBJECTIVE

The present study aims to enhance understanding of the disease mechanism and its progression by identifying prognostic biomarkers, potential drug targets, and candidate drugs that can be used for therapy in pancreatic cancer.

METHODS

Gene expression profiles from the GEO database were analyzed to identify reliable prognostic markers and potential drug targets. The disease's molecular mechanism and biological pathways were studied by investigating gene ontologies, KEGG pathways, and survival analysis to understand the strong prognostic power of key DEGs. FDA-approved anti-cancer drugs were screened through cell line databases, and docking studies were performed to identify drugs with high affinity for ARNTL2 and PIK3C2A. Molecular dynamic simulations of drug targets ARNTL2 and PIK3C2A in their native state and complex with nilotinib were carried out for 100 ns to validate their therapeutic potential in PDAC.

RESULTS

Differentially expressed genes that are crucial regulators, including SUN1, PSMG3, PIK3C2A, SCRN1, and TRIAP1, were identified. Nilotinib as a candidate drug was screened using sensitivity analysis on CCLE and GDSC pancreatic cancer cell lines. Molecular dynamics simulations revealed the underlying mechanism of the binding of nilotinib with ARNTL2 and PIK3C2A and the dynamic perturbations. It validated nilotinib as a promising drug for pancreatic cancer.

CONCLUSION

This study accounts for prognostic markers, drug targets, and repurposed anti-cancer drugs to highlight their usefulness for translational research on developing novel therapies. Our results revealed potential and prospective clinical applications in drug targets ARNTL2, EGFR, and PI3KC2A for pancreatic cancer therapy.

Bioinformatics Integrative Analysis of Circadian Rhythms Effects on Atopic Dermatitis and Dendritic Cells

Background

Atopic dermatitis (AD) is an allergic inflammatory skin disease caused by aberrant and over-reactive immune response. Although circadian rhythm disruption is implicated in multiple immunoinflammatory conditions, including AD, the mechanisms at the molecular level underlying AD and circadian rhythms remain elusive.

Methods

Bulk and single-cell RNA-sequencing data of AD patients were acquired from the Gene Expression Omnibus, including GSE121212, GSE120721, and GSE153760 datasets. A single-sample gene set enrichment analysis was performed to estimate circadian rhythm gene expression levels. A differential expression analysis was utilized to identify the key candidate genes in AD. CIBERSORT was used to quantify the proportions of immune cells, and the R package "Seurat" was utilized to investigate single-cell RNA-sequencing data.

Results

Circadian rhythm gene expression levels were lower in AD skin samples than in normal skin samples. Dendritic cells were significantly upregulated and negatively correlated with circadian rhythm gene expression levels in AD patients. Compared with circadian rhythm-related genes in the control samples, ARNTL2, NOCT, and RORC were differentially expressed in AD; ARNTL2 and NOCT were significantly upregulated, whereas RORC was significantly downregulated in AD. ARNTL2, NOCT, and RORC also showed robust abilities to diagnose AD. We validated that the abundance of the dendritic cell was positively correlated with the ARNTL2 and NOCT expression levels using bulk RNA-sequencing data of the GSE121212 and single-cell RNA-sequencing data of the GSE153760. Moreover, the functional enrichment analysis showed that the IL-17 and NF-κB signaling pathways, Th1 and Th2 cell differentiations, and primary immunodeficiency, were enriched in AD patients.

Conclusion

The findings of this study suggested that the circadian rhythm is involved in the progression of AD, and RNTL2, NOCT, and RORC as well as dendritic cells are differentially expressed in AD. These findings could be used to introduce diagnostic and chronotherapeutic modalities for AD.

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis.

Methods

To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis.

Results

A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results.

Conclusions

On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.

NEK6 Promotes the Progression of Osteosarcoma Through Activating STAT3 Signaling Pathway by Down-Regulation of miR-26a-5p

Background

Osteosarcoma is a malignant tumor originating from the skeletal system. There is no effective treatment other than surgery and chemotherapy, which seriously endangers the health of children and adolescents. NEK6 is a novel discovered Serine/Threonine protein kinase that can regulate cell cycle and activate several oncogenic pathways.

Methods

NEK6 expression in pan-cancer including sarcoma was evaluated using analysis tools of TIMER, UALCNA and GEPIA with TCGA database, and its association with overall survival in patients with sarcoma was also analyzed. TargetScan, tarbase, microT-CDS and Starbase online software were used to predict NEK6-targeted miRNAs, including miR-26a-5p. Tumor tissues from patients with osteosarcoma were collected for NEK6 and miRNA detection using RT-qPCR. NEK6 down-regulated by siRNAs or miR-26a-5p in osteosarcoma cells was detected by RT-qPCR, Western blot and Immunofluorescence staining assays. Effects of NEK6 knockdown on proliferation, migration, invasion and apoptosis of osteosarcoma cells were detected by CCK-8, wound healing, transwell and flow cytometry, respectively. The expressions of STAT3, metastasis and apoptosis-related genes were detected by Western blot.

Results

High expression of NEK6 and low expression of miR-26a-5p were lowly expressed in osteosarcoma and they were negative correlation. NEK6 has been confirmed as a direct target for miR-26a-5p. In addition, NEK6 down-regulated by siRNAs or miR-26a-5p led to inhibition of cell proliferation, migration and invasion while promoting cell apoptosis. The levels of phosphorylated STAT3 and metastasis genes (MMP-2, MMP-9) were inhibited, while apoptotic gene Bax was promoted and Bcl2 was inhibited by miR-26a-5p upregulation.

Conclusion

NEK6 can promote osteosarcoma progression via activating STAT3 signaling pathway, which is inhibited by miR-26a-5p, suggesting that NEK6 is a potential oncogene and miR-26a-5p is a suppressor of osteosarcoma. The strategy of inhibiting of NEK6 by miR-26a-5p may be an effective approach for osteosarcoma therapy.

The circadian rhythm key gene ARNTL2: a novel prognostic biomarker for immunosuppressive tumor microenvironment identification and immunotherapy outcome prediction in human cancers

Background

Aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) belongs to the b HLH- PAS domain transcription factor family and is one of the key clock genes that control the circadian rhythm. ARNTL2 plays an important role in human biological functions. However, its role in various tumors, especially in the tumor immune microenvironment (TIME) and immunotherapy, remains unclear.

Methods

We integrated data from cancer patients from multiple databases, including the Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia, Genotype Tissue Expression, Human Protein Atlas, cBioPortal, TIMER, and ImmuCellAI, with data from a large clinical study, three immunotherapy cohorts, and in vitro experiments to investigate the involvement of ARNTL2 expression in cancer prognosis and immune response.

Results

ARNTL2 displayed abnormal expression within most malignant tumors, and is significantly associated with poorer survival and pathologic staging. Through gene-set enrichment analysis (GSEA) and gene-set variation analysis (GSVA), we found that ARNTL2 not only regulates cell cycle-related functions to promote cell proliferation but also regulates autoimmunity-related functions of the innate and adaptive immune systems, and other immune-related signaling pathways. In addition, ARNTL2 overexpression contributes to an immunosuppressive tumor microenvironment that plays a key role in immunosuppression-related features, such as the expression of immunosuppression-related genes and pathways and the number of immunosuppressive-infiltrating cells, including regulatory T cells (Tregs), tumor-associated macrophages (TAMs), and cancer-associated fibroblasts (CAFs). The group of patients with low ARNTL2 expression who received immune checkpoint inhibitors (ICI) therapy had better response rates and longer survival when compared to those with high ARNTL2 expression.

Conclusion

The findings of this study suggest that ARNTL2 is a potential human oncogene that plays an important role in tumorigenesis and cancer immunity. Elevated ARNTL2 expression indicates an immunosuppressive tumor microenvironment. Targeting ARNTL2 in combination with ICI therapy could bring more significant therapeutic benefits to patients with cancer. Our study sheds light on the remarkable potential of ARNTL2 in tumor immunity and provides a novel perspective for anti-tumor strategies.

Construction and validation of a novel prognostic signature for cutaneous melanoma based on ferroptosis-related genes

Ferroptosis, a recently uncovered iron-dependent, non-apoptotic cell death process, has been increasingly linked to cancer development. In this study, our objective was to develop a prognostic model centered on ferroptosis-related genes (FRGs) and assess its efficacy as an overall survival (OS) prediction biomarker. We conducted a systematic analysis of cutaneous melanoma (CM) and devised a novel ferroptosis-related prognostic signature (FRGSig) using the TCGA database. An independent dataset from GSE65904 was employed to corroborate the validity of the FRGSig. Both univariate and multivariate Cox proportional hazard regression analyses were utilized to construct a FRGSig composed of five FRGs. mRNA expression and immunohistochemistry (IHC) analysis demonstrated that the expression of FRGSig genes varied between tumor and normal tissues. According to Kaplan-Meier analysis, patients with elevated FRGsig scores faced a worse prognosis. The predictive accuracy of FRGSig was evaluated using the time-dependent receiver operating characteristic curve (ROC), with the area under the curve (AUC) values for 1, 3, and 5 OS at 0.682, 0.711, 0.735 in the TCGA cohort, and 0.662, 0.695, 0.712 in the validation dataset, respectively. Univariate and multivariate Cox regression analyses demonstrated that FRGSig served as an independent prognostic factor. Further analysis revealed a significant relationship between FRGSig and Tumor Mutational Burden (TMB) as well as immune infiltration levels. Gene set enrichment analysis (GSEA) disclosed functional disparities between high- and low-risk groups, suggesting that immune checkpoint-related pathways could be instrumental in the improved prognosis of the low-risk group. Taken together, the FRGSig has potential guidance for prognosis prediction and clinical treatment of CM.

Coronin 1C, Regulated by Multiple microRNAs, Facilitates Cancer Cell Aggressiveness in Pancreatic Ductal Adenocarcinoma

Coronin proteins are actin-related proteins containing WD repeat domains encoded by seven genes (CORO1A, CORO1B, CORO1C, CORO2A, CORO2B, CORO6, and CORO7) in the human genome. Analysis of large cohort data from The Cancer Genome Atlas revealed that expression of CORO1A, CORO1B, CORO1C, CORO2A, and CORO7 was significantly upregulated in pancreatic ductal adenocarcinoma (PDAC) tissues (p < 0.05). Moreover, high expression of CORO1C and CORO2A significantly predicted the 5 year survival rate of patients with PDAC (p = 0.0071 and p = 0.0389, respectively). In this study, we focused on CORO1C and investigated its functional significance and epigenetic regulation in PDAC cells. Knockdown assays using siRNAs targeting CORO1C were performed in PDAC cells. Aggressive cancer cell phenotypes, especially cancer cell migration and invasion, were inhibited by CORO1C knockdown. The involvement of microRNAs (miRNAs) is a molecular mechanism underlying the aberrant expression of cancer-related genes in cancer cells. Our in silico analysis revealed that five miRNAs (miR-26a-5p, miR-29c-3p, miR-130b-5p, miR-148a-5p, and miR-217) are putative candidate miRNAs regulating CORO1C expression in PDAC cells. Importantly, all five miRNAs exhibited tumor-suppressive functions and four miRNAs except miR-130b-5p negatively regulated CORO1C expression in PDAC cells. CORO1C and its downstream signaling molecules are potential therapeutic targets in PDAC.

ARNTL2 upregulation of ACOT7 promotes NSCLC cell proliferation through inhibition of apoptosis and ferroptosis

BACKGROUND

Recent studies have reported that the circadian transcription factor aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) promotes the metastatic progression of lung adenocarcinoma. However, the molecular mechanisms of ARNTL2 in non-small cell lung cancer (NSCLC) cell growth and proliferation remain to be explored.

METHODS

The expression of ARNTL2 and acyl-CoA thioesterase 7 (ACOT7) in lung cancer patients was analyzed based on TCGA database. Gain-of-function of ARNTL2 and ACOT7 was conducted by transfecting the cells with plasmids or lentivirus. Knockdown assay was carried out by siRNAs. Western blot and qRT-PCR were performed to check the protein and mRNA expression. Dual luciferase and ChIP-qPCR assay was applied to check the interaction of ARNTL2 on ACOT7's promoter sequence. Triglyceride level, MDA production, the activity of casapase 3 to caspase 7, and lipid ROS were measured by indicated assay kit. Cellular function was detected by CCK8, colony formation and flow cytometry analysis of cell death and cell cycle.

RESULTS

We demonstrated that ARNTL2 upregulation of ACOT7 was critical for NSCLC cell growth and proliferation. Firstly, overexpression of ARNTL2 conferred the poor prognosis of LUAD patients and supported the proliferation of NSCLC cells. Based on molecular experiments, we showed that ARNTL2 potentiated the transcription activity of ACOT7 gene via direct binding to ACOT7's promoter sequence. ACOT7 high expression was correlated with the worse prognosis of LUAD patients. Gain-of-function and loss-of-function experiments revealed that AOCT7 contributed to NSCLC cell growth and proliferation. ACOT7 regulated the apoptosis and ferroptosis of NSCLC cells, while exhibited no effect on cell cycle progression. ACOT7 overexpression also potentiated fatty acid synthesis and suppressed lipid peroxidation. Lastly, we showed that ARNTL2 knockdown and overexpression inhibited and promoted the cellular triglyceride production and subsequent cell proliferation, which could be reversed by ACOT7 overexpression and knockdown.

CONCLUSION

Our study illustrated the oncogenic function of ARNTL2/ACOT7 axis in the development of NSCLC. Targeting ARNTL2 or ACOT7 might be promising therapeutic strategies for NSCLC patients with highly expressed ARNTL2.

Profiling of a novel circadian clock-related prognostic signature and its role in immune function and response to molecular targeted therapy in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PADA) represents a devastating type of pancreatic cancer with high mortality. Defining a prognostic gene signature that can stratify patients with different risk will benefit cancer treatment strategies.

METHODS

Gene expression profiles of PADA patients were acquired from the Cancer Genome Atlas and Gene Expression Omnibus, including GSE62452 and GSE28735. Differential expression analysis was carried out using the package edgeR in R. Intro-tumor immune infiltrates were quantified by six different computational algorithms XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, and CIBERSORT. Biological processes were investigated based on R package "clusterProfiler".

RESULTS

13 genes (ARNTL2, BHLHE40, FBXL17, FBXL8, PPP1CB, RBM4B, ADRB1, CCAR2, CDK1, CSNK1D, KLF10, PSPC1, SIAH2) were eligible for the development of a prognostic gene signature. Performance of the prognostic gene signature was assessed in the discovery set (n = 210), validation set (n = 52), and two external data set (GSE62452, n = 65, and GSE28735, n = 84). Area under the curve (AUC) for predicting 3-year overall survival was 0.727, 0.732, 0.700, and 0.658 in the training set, the validation set, and the two test sets, respectively. KM curve revealed that the low-risk group had an improved prognosis than the high-risk group in all four datasets. PCA analysis demonstrated that the low-risk group was apparently separated from the high-risk group. CD8 T cell and B cell were significantly reduced in the high-risk group than in the low-risk group, while neutrophils were significantly augmented in the high-risk group than in the low-risk group. BMS-536924, Foretinib, Linsitinib, and Sabutoclax were more sensitive in the low-risk group, whereas Erlotinib was more effective in the high-risk group.

CONCLUSIONS

We successfully established and verified a novel circadian clock-related gene signature, which could stratify patients with different risk and be reflective of the therapeutic effect of molecular targeted therapy. Our findings could incorporate the pharmacological modulation of circadian clock into future therapeutic strategies.

Genome-wide identification of A-to-I RNA editing events provides the functional implications in PDAC

Introduction

RNA editing, a wide-acknowledged post-transcriptional mechanism, has been reported to be involved in the occurrence and development of cancer, especially the abnormal alteration of adenosine to inosine. However, fewer studies focus on pancreaticcancer. Therefore, we aimed to explore the possible linkages between altered RNA editing events and the development of PDAC.

Method

We characterized the global A-to-I RNA editing spectrum from RNA and matched whole-genome sequencing data of 41 primary PDAC and adjacent normal tissues. The following analyses were performed: different editing level and RNA expression analysis,pathway analysis, motif analysis, RNA secondary structure analysis, alternative splicing events analysis, and survival analysis.The RNA editing of single-cell RNA public sequencing data was also characterized.

Result

A large number of adaptive RNA editing events with significant differences in editing levels were identified, which are mainly regulated by ADAR1. Moreover, RNA editing in tumors has a higher editing level and more abundant editing sites in general. 140genes were screened out since they were identified with significantly different RNA editing events and were significantly different in expression level between tumor and matched normal samples. Further analysis showed a preference that in the tumor-specific group, they are mainly enriched in cancer-related signal pathways, while in the normal tissue-specific group, they are mainly enriched in pancreatic secretion. At the same time, we also found positively selected differentially edited sites in a series of cancer immune genes, including EGF, IGF1R, and PIK3CD. RNA editing might participate in pathogenisis of PDAC through regulating the alternative splicing and RNA secondary structure of important genesto further regulate gene expression and protein synthesis, including RAB27B and CERS4. Furthermore, single cell sequencing results showed that type2 ductal cells contributed the most to RNA editing events in tumors.

Conclusion

RNA editing is an epigenetic mechanism involved in the occurrence and development of pancreatic cancer, which has the potential to diagnose of PDAC and is closely related to the prognosis.

ARNTL2 is an indicator of poor prognosis, promotes epithelial-to-mesenchymal transition and inhibits ferroptosis in lung adenocarcinoma

OBJECTIVES

ARNTL2, as a circadian transcription factor, has been recently proposed to play an important role in a variety of tumors. however, the role of ARNTL2 in lung carcinogenesis and progression remains unclear. The purpose of this study was to investigate the effect of ARNTL2 on the clinical characteristics and prognosis of lung adenocarcinoma and to explore the relationship between ARNTL2 and EMT, ferroptosis in lung adenocarcinoma.

METHODS

The Cancer Genome Atlas (TCGA) database's multi-omics data were downloaded using the Xena browser. Based on the expression levels of ARNTL2, patients with lung adenocarcinoma from TCGA were divided into two groups: those with high ARNTL2 expression and those with low ARNTL2 expression. ARNTL2 was studied for its effects on lung adenocarcinoma's clinicopathological, genomic, and immunological characteristics. Furthermore, in vivo and in vitro assays were used to confirm the impact of ARNLT2 knockdown on lung adenocarcinoma cells.

RESULTS

We found ARNTL2 is highly expressed in lung adenocarcinoma and was an independent predictor of a poor prognosis in patients with lung adenocarcinoma. In addition, we demonstrated that knockdown of ARNTL2 promoted ferroptosis, inhibited EMT, cell proliferation, migration and invasion in lung adenocarcinoma. In contrast, overexpressing ARNTL2 yielded the opposite results.

CONCLUSIONS

ARNTL2 is an independent unfavorable prognostic factor for lung adenocarcinoma. It plays a facilitating role in the development of lung adenocarcinoma, especially in promoting EMT and inhibiting ferroptosis, revealing that ARNTL2 may be a potential biomarker for lung adenocarcinoma.

MiR-26a-5p regulates proliferation, apoptosis, migration and invasion via inhibiting hydroxysteroid dehydrogenase like-2 in cervical cancer cell

Background

Evidences have indicated that miR-26a-5p regulates the malignant properties of various tumor cells. However, the influences of miR-26a-5p on proliferation, apoptosis and invasion are still vague in the cervical cancer (CC) cells.

Methods

The miRNA microarray and real-time quantitative PCR (RT-qPCR) analysis were utilized to detect the expression of miR-26a-5p in the patients with CC. Kaplan–Meier plotter was performed to evaluate the overall survival (OS) of the patients with CC. The CCK-8, flow cytometry, transwell and wound healing analyses were respectively used to analyze proliferation, migration and invasion in the CC cells. RT-qPCR, western blot and IHC analysis were executed to measure the expression of hydroxysteroid dehydrogenase like-2 (HSDL2) in the patients with CC. Bioinformatics and luciferase reporter assay were carried out to verify the relationship of miR-26a-5p and HSDL2.

Results

The expression of miR-26a-5p was downregulated and low expression of miR-26a-5p indicated a poor OS in patients with CC. Overexpression of miR-26a-5p significantly inhibited proliferation, migration and invasion, accelerated apoptosis in the Hela and C33A cells. The expression of HSDL2 was upregulated, and negatively correlated with miR-26a-5p in the patients with CC. HSDL2 was directly targeted by miR-26a-5p and rescue experiments displayed that HSDL2 partially abolished proliferation, apoptosis, migration, and invasion induced by miR-26a-5p in CC cells.

Conclusions

MiR-26a-5p alleviated progression of CC by suppressing proliferation, migration and invasion, promoting apoptosis through downregulating HSDL2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09970-x.

Identification of miRNA–mRNA Pairs in the Alzheimer’s Disease Expression Profile and Explore the Effect of miR-26a-5p/PTGS2 on Amyloid-β Induced Neurotoxicity in Alzheimer’s Disease Cell Model

Alzheimer’s disease (AD) is a progressive neurodegenerative disease and the most common type of dementia. MicroRNAs (miRNAs) have been extensively studied in many diseases, including AD. To identify the AD-specific differentially expressed miRNAs and mRNAs, we used bioinformatics analysis to study candidate miRNA–mRNA pairs involved in the pathogenesis of AD. These miRNA–mRNAs may serve as promising biomarkers for early diagnosis or targeted therapy of AD patients. In this study, based on the AD mRNA and miRNA expression profile data in Gene Expression Omnibus (GEO), through differential expression analysis, functional annotation and enrichment analysis, weighted gene co-expression network analysis, miRNA–mRNA regulatory network, protein–protein interaction network, receiver operator characteristic and Least absolute shrinkage and selection operator (LASSO) regression and other analysis, we screened the key miRNA–mRNA in the progress of AD: miR-26a-5p/PTGS2. Dual-luciferase and qPCR experiments confirmed that PTGS2 is a direct target gene of miR-26a-5p. The expression of miR-26a-5p in the peripheral blood of AD patients and AD model cells (SH-SY5Y cells treated with Aβ_25–35) was up-regulated, and the expression of PTGS2 was down-regulated. Functional gain -loss experiments confirmed that PTGS2 protects AD model cells from damage by inhibiting proliferation and migration. However, the expression of miR-26a-5p promotes the proliferation of AD model cells. It is further found that PTGS2 is involved in the regulation of miR-26a-5p and can reverse the effect of miR-26a-5p on the proliferation of AD model cells. In addition, through network pharmacology, qPCR and CCK-8, we found that baicalein may affect the progression of AD by regulating the expression of PTGS2. Therefore, PTGS2 can be used as a target for AD research, and miR-26a-5p/PTGS2 can be used as an axis of action to study the pathogenesis of AD.

Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma

BACKGROUND

Acidosis in the tumor microenvironment (TME) is involved in tumor immune dysfunction and tumor progression. We attempted to develop an acidosis-related index (ARI) signature to improve the prognostic prediction of pancreatic carcinoma (PC).

METHODS

Differential gene expression analyses of two public datasets (GSE152345 and GSE62452) from the Gene Expression Omnibus database were performed to identify the acidosis-related genes. The Cancer Genome Atlas-pancreatic carcinoma (TCGA-PAAD) cohort in the TCGA database was set as the discovery dataset. Univariate Cox regression and the Kaplan-Meier method were applied to screen for prognostic genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish the optimal model. The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm.

RESULTS

We identified 133 acidosis-related genes, of which 37 were identified as prognostic genes by univariate Cox analysis in combination with the Kaplan-Meier method (p values of both methods < 0.05). An acidosis-related signature involving seven genes (ARNTL2, DKK1, CEP55, CTSV, MYEOV, DSG2, and GBP2) was developed in TCGA-PAAD and further validated in GSE62452. Patients in the acidosis-related high-risk group consistently showed poorer survival outcomes than those in the low-risk group. The 5-year AUCs (areas under the curve) for survival prediction were 0.738 for TCGA-PAAD and 0.889 for GSE62452, suggesting excellent performance. The low-risk group in TCGA-PAAD showed a higher abundance of CD8+ T cells and activated natural killer cells and was predicted to possess an elevated proportion of immunotherapeutic responders compared with the high-risk counterpart.

CONCLUSIONS

We developed a reliable acidosis-related signature that showed excellent performance in prognostic prediction and correlated with tumor immune infiltration, providing a new direction for prognostic evaluation and immunotherapy management in PC.

Prognostic Stratification Based on HIF-1 Signaling for Evaluating Hypoxic Status and Immune Infiltration in Pancreatic Ductal Adenocarcinomas

Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic and desmoplastic tumor microenvironment (TME), leading to treatment failure. We aimed to develop a prognostic classifier to evaluate hypoxia status and hypoxia-related molecular characteristics of PDAC. In this study, we classified PDAC into three clusters based on 16 known hypoxia-inducible factor 1 (HIF-1)-related genes. Nine differentially expressed genes were identified to construct an HIF-1 score system, whose predictive efficacy was evaluated. Furthermore, we investigated oncogenic pathways and immune-cell infiltration status of PDAC with different scores. The C-index of the HIF-1score system for OS prediction in the meta-PDAC cohort and the other two validation cohorts were 0.67, 0.63, and 0.65, respectively, indicating that it had a good predictive value for patient survival. Furthermore, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the HIF-1α score system for predicting 1-, 3-, and 4-year OS indicated the HIF-1α score system had an optimal discrimination of prognostic prediction for PDAC. Importantly, our model showed superior predictive ability compared to previous hypoxia signatures. We also classified PDAC into HIF-1 scores of low, medium, and high groups. Then, we found high enrichment of glycolysis, mTORC1 signaling, and MYC signaling in the HIF-1 score high group, whereas the cGMP metabolic process was activated in the low score group. Of note, analysis of public datasets and our own dataset showed a high HIF-1 score was associated with high immunosuppressive TME, evidenced by fewer infiltrated CD8⁺ T cells, B cells, and type 1 T-helper cells and reduced cytolytic activity of CD8⁺ T cells. In summary, we established a specific HIF-1 score system to discriminate PDAC with various hypoxia statuses and immune microenvironments. For highly hypoxic and immunosuppressive tumors, a combination treatment strategy should be considered in the future.

ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

BACKGROUND

Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study.

METHODS

Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells.

RESULTS

We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes.

CONCLUSION

Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

STK39 enhances the progression of Cholangiocarcinoma via PI3K/AKT pathway

Serine/threonine kinase 39 (STK39) is overexpressed in various tumor tissues and plays an essential role in tumor progression. In this study, we investigated the clinical value, as well as the potential functions and mechanisms of STK39 in cholangiocarcinoma (CCA). The results showed that STK39 was overexpressed in CCA and negatively associated with the prognosis of patients with CCA. Functionally, STK39 knockdown suppressed cell proliferation, migration, and invasion, while STK39 overexpression facilitated tumor aggressiveness. The tumor-promoting effects of STK39 in CCA were also validated by in vivo experiments. Mechanistically, RNA-seq analysis identified that STK39 enhanced the progression of CCA by activating PI3K/AKT signaling pathway. Furthermore, overexpression of STK39 could induce gemcitabine resistance in CCA cells. Moreover, the increased expression of STK39 may be mediated by the dysregulation of miR-26a-5p. In summary, STK39 could be served as a valuable prognostic candidate and a potential therapeutic target of CCA.

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STK39 was overexpressed in CCA, negatively associated with the prognosis of patients with CCA

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STK39 knockdown suppressed cell proliferation and invasion. STK39 overexpression facilitated tumor aggressiveness

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STK39 mediates oncogenic effects on CCA cells by activating the PI3K/AKT signaling pathway

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STK39 reduces CCA sensitivity to gemcitabine. Increased expression of STK39 may be mediated by dysregulation of miR-26a-5p

Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics

Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted.

A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients’ response to immunotherapy. Furthermore, taking full advantage of the complementary value of clinical and molecular features, we combined the immune prognostic signature with clinical features to construct and validate a nomogram that can predict the probability of high tumor mutational burden (>10 mutations per megabyte). This may improve the estimation of immunotherapy response in LUAD patients, and provide a new perspective for clinical screening of immunotherapy beneficiaries.