Sensory Ion Channel Candidates Inform on the Clinical Course of Pancreatic Cancer and Present Potential Targets for Repurposing of FDA-Approved Agents

Unlocking Clinical Insights: Lymphocyte-Specific Protein Tyrosine Kinase Candidates as Promising Therapeutic Targets for Pancreatic Cancer Risk Stratification

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer. Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined. Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis. Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Potential pharmacological mechanisms of tanshinone IIA in the treatment of human neuroblastoma based on network pharmacological and molecular docking Technology

Tanshinone IIA (Tan-IIA) is the main bioactive component of Chinese herbal medicine salvia miltiorrhiza (Danshen). Sodium sulfonate of Tan-IIA is widely used in the treatment of cardiovascular and cerebrovascular diseases. Tan-IIA also has inhibitory effects on tumor cells such as gastric cancer, but its therapeutic effect and mechanism on human neuroblastoma have not been evaluated, so its pharmacological mechanism is systematically evaluated by the combined method of network pharmacology and molecular docking. PharmMapper and SwissTargetPrediction predicted 331 potential Tan-IIA-related targets, and 1,152 potential neuroblastoma-related targets were obtained from GeneCards, DisGeNET, DrugBank, OMIM and Therapeutic Target databases (TTD), 107 common targets for Tan-IIA and neuroblastoma. Through gene ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomesa (KEGG) pathway enrichment, protein-protein interaction (PPI) network and cytoHubba plug-in, 10 related signal pathways (Pathways in cancer, PI3K-Akt signaling pathway, Prostate cancer, etc.) and 10 hub genes were identified. The results of molecular docking showed that Tan-IIA could interact with 10 targets: GRB2, SRC, EGFR, PTPN1, ESR1, IGF1, MAPK1, PIK3R1, AKT1 and IGF1R. This study analyzed the related pathways and targets of Tan-IIA in the treatment of human neuroblastoma, as well as the potential anticancer and anti-tumor targets and related signaling pathways of Tan-IIA, which provides a reference for us to find and explore effective drugs for the treatment of human neuroblastoma.

Revisiting of Properties and Modified Polyethylenimine-Based Cancer Gene Delivery Systems

A new era of medical technology in cancer treatment is a directly specific modification of gene expression in tumor cells by nucleic acid delivery. Currently, the main challenge to achieving this goal is to find a non-toxic, safe, and effective strategy for gene transfer to cancer cells. Synthetic composites based on cationic polymers have historically been favored in bioengineering due to their ability to mimic bimolecular structures. Among them, polyethylenimines (PEIs) with superior properties such as a wide range of molecular weight and a flexible structure may propel the development of functional combinations in the biomedical and biomaterial fields. Here, in this review, we will focus on the recent progressions in the formulation optimization of PEI-based polyplex in gene delivery to treat cancer. Also, the effect of PEI's intrinsic characteristics such as structure, molecular weight, and positive charges which influence the gene delivery efficiency will be discussed.

LncRNAs-Regulated High Expression of LAMC2 Reveals a Prognostic and Immunological Value in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is one of the most hazardous cancers in digestive system, and the prognosis is notoriously bad. Increasing evidences indicate that Laminin Subunit Gamma 2 (LAMC2) is critical for the initiation and the growth of various sorts of human cancers. However, the involved molecular pathways of LAMC2 in PAAD are still poorly understood. In this study, prediction programs and databases were employed to conduct pan-cancer analysis. Multiple variations of human malignancies showed increased LAMC2 expression, which was positively correlated to a poor prognosis in PAAD. Moreover, LAMC2 was positively correlated with the biomarkers of immune cells including CD19, CD163, and NOS2 in PAAD. The lncRNA C5orf66 /PTPRG-AS1- miR-128-3p -LAMC2 axis was identified to be a potential upstream regulatory pathway of LAMC2 in PAAD. Furthermore, LAMC2 upregulation in PAAD was associated with PD-L1 expression, indicating promoting carcinoma immune cell infiltration. Our study elucidated prognostic and immunological values of LAMC2 in PAAD, providing a promise target for PAAD treatment.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

Research Progress on TRPA1 in Diseases

For a long time, the physiological activity of TRP ion channels and the response to various stimuli have been the focus of attention, and the physiological functions mediated by ion channels have subtle links with the occurrence of various diseases. Our group has been engaged in the study of ion channels. In recent years, the report rate of TRPA1, the only member of the TRPA subfamily in the newly described TRP channel, has been very high. TRPA1 channels are not only abundantly expressed in peptidergic nociceptors but are also found in many nonneuronal cell types and tissues, and through the regulation of Ca2+ influx, various neuropeptides and signaling pathways are involved in the regulation of nerves, respiration, circulation, and various diseases and inflammation throughout the body. In this review, we mainly summarize the effects of TRPA1 on various systems in the body, which not only allows us to have a more systematic and comprehensive understanding of TRPA1 but also facilitates more in-depth research on it in the future.

Transient receptor potential channels as predictive marker and potential indicator of chemoresistance in colon cancer

Transient receptor potential (TRP) channels are strongly associated with colon cancer development and progression. This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature, with further validation of signature in real world samples from our hospital treated patient samples. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed to evaluate this gene signature's predictive accuracy and robustness in both training and testing cohorts, respectively. Additionally, the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature's immune infiltration landscape and underlying functional implications. The support vector machine algorithm was applied to evaluate the signature's potential in predicting chemotherapy outcomes. The findings unveiled a novel three TRP channels-related gene signature (MCOLN1, TRPM5, and TRPV4) in colon adenocarcinoma (COAD). The ROC and K-M survival curves in the training dataset (AUC = 0.761; p = 1.58e-05) and testing dataset (AUC = 0.699; p = 0.004) showed the signature's robust predictive capability for the overall survival of COAD patients. Analysis of the immune infiltration landscape associated with the signature revealed higher immune infiltration, especially an increased presence of M2 macrophages, in high-risk group patients compared to their low-risk counterparts. High-risk score patients also exhibited potential responsiveness to immune checkpoint inhibitor therapy, evident through increased CD86 and PD-1 expression profiles. Moreover, the TRPM5 gene within the signature was highly expressed in the chemoresistance group (p = 0.00095) and associated with poor prognosis (p = 0.036) in COAD patients, highlighting its role as a hub gene of chemoresistance. Ultimately, this signature emerged as an independent prognosis factor for COAD patients (p = 6.48e-06) and expression of model gene are validated by public data and real-world patients. Overall, this bioinformatics study provides valuable insights into the prognostic implications and potential chemotherapy resistance mechanisms associated with TRPs-related genes in colon cancer.

Long noncoding RNA BBOX1-AS1 increased radiotherapy sensitivity in colorectal cancer by stabilizing and activating PFK1

PURPOSE

Our study explored the effect of long noncoding RNA BBOX1-AS1 on colorectal cancer (CRC) radiosensitivity in vivo and in vitro.

METHODS

Differentially expressed lncRNAs in CRC were screened using a bioinformatics database and an online prediction website. The expression of BBOX1-AS1 in tissue samples was analyzed via real-time quantitative PCR (RT-qPCR). Subcellular localization of BBOX1-AS1 in CRC cells was analyzed using fluorescence in situ hybridization (FISH). The correlation between BBOX1-AS1 and PFK1 expression levels in CRC tissues was analyzed via Pearson's correlation coefficient. The effect of BBOX1-AS1 on PFK1 stability was investigated using RNA and protein stability testing. RNA Binding Protein Immunoprecipitation (RIP) and RNA pull-down assays were used to confirm the binding of BBOX1-AS1 to PFK1.

RESULTS

BBOX1-AS1 was highly expressed in CRC and associated with poor prognosis. Similarly, it was highly expressed in CRC tissues and CRC cell lines. In addition, BBOX1-AS1 promoted the proliferation, invasion, migration, and glycolysis of CRC cells and inhibited apoptosis. RIP and RNA pull-down experiments confirmed that BBOX1-AS1 bound to PFK1. RNA stability and protein stability experiments showed that BBOX1-AS1 affected the stability of PFK1 mRNA and protein. Furthermore, we confirmed that BBOX1-AS1 increased radiation resistance through the regulation of PFK1 expression.

CONCLUSIONS

BBOX1-AS1 promoted the proliferation, invasion, migration, and glycolysis of CRC cells through stabilization of the expression of PFK1. BBOX1-AS1 also inhibited CRC cell apoptosis and increased radiotherapy resistance in CRC cells.

Characteristics of alpha-fetoprotein-positive gastric cancer revealed by analysis of cancer databases and transcriptome sequencing data

Gastric cancer is one of the most common malignant tumors in the world. Alpha fetoprotein (AFP)-positive gastric cancer (AFPP-GC) is considered a special entity among gastric cancers. There is still controversy regarding the clinicopathological characteristics and prognosis of AFPP-GC, and the potential mechanism underlying its high malignant potential is still unclear. A comprehensive description of AFPP-GC genomic characteristics and regulatory mechanisms is lacking. This study analyzed the pathological characteristics and prognosis of AFPP-GC by utilizing clinical samples. The results showed that AFPP-GC has a poor prognosis and a high of risk liver metastasis. Tissue transcriptome sequencing showed that genes with high expression in AFPP-GC were involved in the activation of various cancer pathways, and genes with low expression were involved in the immune response. Single-sample gene set enrichment analysis showed that overexpression of AFP in AFPP-GC significantly inhibited the infiltration of CD8+ T cells. To further explore the genomic characteristics of AFPP-GC, the signaling pathway by which AFP regulates the invasion and metastasis of AFPP-GC cells was discussed. The results showed that AFPP-GC may promote cell invasion by regulating the PTEN/AKT1/SOX5/CES1 signaling axis. This study reveals the molecular mechanism underlying the increased malignant potential of AFPP-GC vs. AFP-negative gastric cancer (AFPN-GC). This provides important information for individualized treatment of AFPP-GC.

Integrated network pharmacology analysis and in vitro validation revealed the underlying mechanism of Xiyanping injection in treating coronavirus disease 2019

BACKGROUND

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, leading to a pandemic. In China, Xiyanping injection (XYP) has been recommended as a drug for COVID-19 treatment in the Guideline on Diagnosis and Treatment of COVID-19 by the National Health Commission of the People Republic of China and National Administration of Traditional Chinese Medicine (Trial eighth Edition). However, the relevant mechanisms at the molecular-level need to be further elucidated.

METHODS

In this study, XYP related active ingredients, potential targets and COVID-19 related genes were searched in public databases. Protein-protein interaction network and module analyzes were used to screen for key targets. gene ontology and Kyoto encyclopedia of genes and genomes were performed to investigate the potentially relevant signaling pathways. Molecular docking was performed using Autodock Tools and Vina. For the validation of potential mechanism, PolyI:C was used to induce human lung epithelial cells for an inflammation model. Subsequently, CCK-8 assays, enzyme-linked immunosorbent assay, reverse transcription quantitative polymerase chain reaction and western blot were employed to determine the effect of XYP on the expression of key genes.

RESULTS

Seven effective active ingredients in XYP were searched for 123 targets in the relevant databases. Furthermore, 6446 COVID-19 disease targets were identified. Sodium 9-dehydro-17-hydro-andrographolide-19-yl sulfate was identified as the vital active compounds, and IL-6, TNF, IL-1β, CXCL8, STAT3, MAPK1, MAPK14, and MAPK8 were considered as the key targets. In addition, molecular docking revealed that the active compound and the targets showed good binding affinities. The enrichment analysis predicted that the XYP could regulate the IL-17, Toll-like receptor, PI3K-Akt and JAK-STAT signaling pathways. Consistently, further in vitro experiments demonstrated that XYP could slow down the cytokine storm in the lung tissue of COVID-19 patients by down-regulating IL-6, TNF-α, IL-1β, CXCL8, and p-STAT3.

CONCLUSION

Through effective network pharmacology analysis and molecular docking, this study suggests that XYP contains many effective compounds that may target COVID-19 related signaling pathways. Moreover, the in vitro experiment confirmed that XYP could inhibit the cytokine storm by regulating genes or proteins related to immune and inflammatory responses.

Network pharmacology combined with molecular docking and experimental validation to reveal the pharmacological mechanism of naringin against renal fibrosis

To explore the pharmacological mechanism of naringin (NRG) in renal fibrosis (RF) based on network pharmacology combined with molecular docking and experimental validation. We used databases to screen for the targets of NRG and RF. The "drug-disease network" was established using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of targets were performed using Metascape, and molecular docking was performed using Schrödinger. We established an RF model in both mice and cells to validate the results of network pharmacology. After screening the database, we identified 222 common targets of NRG and RF and established a target network. Molecular docking showed that the target AKT had a good interaction with NRG. We found that the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway was enriched by multiple targets and served as a target for experimental validation through GO and KEGG. The results revealed that NRG ameliorated renal dysfunction, reduced the release of inflammatory cytokines, decreased the expression of α-SMA, collagen I, and Fn, and recovered the expression of E-cad by inhibiting the PI3K/AKT signaling pathway. Our study used pharmacological analysis to predict the targets and mechanisms of NRG against RF. Furthermore, experiments proved that NRG inhibited RF effectively by targeting the PI3K/AKT signaling pathway.

An extensive pharmacological evaluation of novel anti-nociceptive and IL-6 targeted anti-inflammatory guaiane-type sesquiterpenoids from Cinnamomum migao H. W. Li through in-depth in-vitro, ADMET, and molecular docking studies

Guaiane-type sesquiterpenoids are most prevalent in the genus Cinnamomum. Hence this study investigates the structures, anti-nociceptive and IL-6 targeted anti-inflammatory potential of three novels C-14 guaiane-type sesquiterpenoids and two new monoterpenoids, isolated from Cinnamomum migao. The structures were precisely confirmed and characterized through the modern chromatographic and spectroscopic techniques of HRESIMS, ¹D NMR, ²D NMR, experimental circular dichroism (ECD), and calculated (ECD). Novel sesquiterpenoids 1 and 2 exhibited significant anti-inflammatory activities against the NO production and pro-inflammatory cytokines. Their IC₅₀ values were determined as 9.52 and 13.42 μΜ against IL-6 mRNA, respectively. Similarly, subcutaneous injection of n-BuT and EA extracts showed a dose-dependent suppression of formalin-induced tonic biting/licking responses during the tonic antinociceptive phase. Furthermore, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of guaiane-type sesquiterpenoids 1 and 2 displayed that both compounds have a high level of GIT absorption, with a high zone of safety for cardiac and hepatotoxicity and no inhibition of cytochromes. In addition, molecular docking and simulation studies strengthen the anti-inflammatory potential of sesquiterpene 2 which showed a good binding affinity with IL-6 protein. Overall the inclusive results showed that the extracts and newly isolated guaiane-type sesquiterpenoids from C. migao will provide new evidence for the traditional use of this species to treat inflammation and nociception.

Integration of network pharmacology, transcriptomics and molecular docking reveals two novel hypoglycemic components in snow chrysanthemum

Our previous studies uncovered the glucose-lowering properties of snow chrysanthemum tea, however, the active ingredients and underlying mechanisms were yet to be uncovered. Flavonoids are the most active and abundant components in snow chrysanthemum tea. In this study, we treated leptin-deficient diabetic ob/ob or high-fat diet (HFD)-induced C57BL/6 J obese mice with or without total flavonoids of snow chrysanthemum (TFSC) for 14 weeks. Results indicated that TFSC ameliorated dyslipidemia and fatty liver, thereby reducing hyperlipidemia. Further mechanism experiments, including RNA-seq and experimental validation, revealed TFSC improved glycolipid metabolism primarily by activating the AMPK/Sirt1/PPARγ pathway. Additionally, by integrating UPLC, network pharmacology, transcriptomics, and experimental validation, we identified two novel hypoglycemic compounds, sulfuretin and leptosidin, in TFSC. Treatment with 12.5 μmol/L sulfuretin obviously stimulated cellular glucose consumption, and sulfuretin (3.125, 6.25 and 12.5 μmol/L) significantly mitigated glucose uptake damage and reliably facilitated glucose consumption in insulin-resistant HepG2 cells. Remarkably, sulfuretin interacted with the ligand-binding pocket of PPARγ via three hydrogen bond interactions with the residues LYS-367, GLN-286 and TYR-477. Furthermore, a concentration of 12.5 μmol/L sulfuretin effectively upregulated the expression of PPARγ, exhibiting a comparable potency to a renowned PPARγ agonist at 20 μmol/L. Taken together, our findings have identified two new hypoglycemic compounds and revealed their mechanisms, which significantly expands people's understanding of the active components in snow chrysanthemum that have hypoglycemic effects.

Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation

Background

Gastric cancer (GC) represents a malignancy with a multi-factorial combination of genetic, environmental, and microbial factors. Targeting lysosomes presents significant potential in the treatment of numerous diseases, while lysosome-related genetic markers for early GC detection have not yet been established, despite implementing this process by assembling artificial intelligence algorithms would greatly break through its value in translational medicine, particularly for immunotherapy.

Methods

To this end, this study, by utilizing the transcriptomic as well as single cell data and integrating 20 mainstream machine-learning (ML) algorithms. We optimized an AI-based predictor for GC diagnosis. Then, the reliability of the model was initially confirmed by the results of enrichment analyses currently in use. And the immunological implications of the genes comprising the predictor was explored and response of GC patients were evaluated to immunotherapy and chemotherapy. Further, we performed systematic laboratory work to evaluate the build-up of the central genes, both at the expression stage and at the functional aspect, by which we could also demonstrate the reliability of the model to guide cancer immunotherapy.

Results

Eight lysosomal-related genes were selected for predictive model construction based on the inclusion of RMSE as a reference standard and RF algorithm for ranking, namely ADRB2, KCNE2, MYO7A, IFI30, LAMP3, TPP1, HPS4, and NEU4. Taking into account accuracy, precision, recall, and F1 measurements, a preliminary determination of our study was carried out by means of applying the extra tree and random forest algorithms, incorporating the ROC-AUC value as a consideration, the Extra Tree model seems to be the optimal option with the AUC value of 0.92. The superiority of diagnostic signature is also reflected in the analysis of immune features.

Conclusion

In summary, this study is the first to integrate around 20 mainstream ML algorithms to construct an AI-based diagnostic predictor for gastric cancer based on lysosomal-related genes. This model will facilitate the accurate prediction of early gastric cancer incidence and the subsequent risk assessment or precise individualized immunotherapy, thus improving the survival prognosis of GC patients.

LncRNA model predicts liver cancer drug resistance and validate in vitro experiments

Introduction: Hepatocellular carcinoma (HCC) patients may benefit from chemotherapy, but drug resistance is an important obstacle to favorable prognoses. Overcoming drug resistance is an urgent problem to be solved.

Methods: Differential expression analysis was used to identify long non-coding RNAs (LncRNAs) that differed in chemotherapy-sensitive and chemotherapy-resistant patients. Machine learning algorithms including random forest (RF), lasso regression (LR), and support vector machines (SVMs) were used to identify important chemotherapy-related LncRNAs. A back propagation (BP) network was then used to validate the predictive capacity of important LncRNAs. The molecular functions of hub LncRNAs were investigated via qRT-PCR and cell proliferation assay. Molecular-docking technique was used to explore candidate drug of targets of hub LncRNA in the model.

Results: A total of 125 differentially expressed LncRNAs between sensitive and resistant patients. Seventeen important LncRNAs were identified via RF, and seven factors were identified via LR. With respect to SVM, the top 15 LncRNAs of AvgRank were selected. Five merge chemotherapy-related LncRNAs were used to predict chemotherapy resistance with high accuracy. CAHM was a hub LncRNA of model and expression high in sorafenib resistance cell lines. In addition, the results of CCK8 showed that the sensitivity of HepG2-sorafenib cells to sorafenib was significantly lower than that of HepG2; and the sensitivity of HepG2-sorafenib cells transfected with sh-CAHM was significantly higher than that of Sorafenib. In the non-transfection group, the results of clone formation experiments showed that the number of clones formed by HepG2-sorafenib cells treated with sorafenib was significantly more than that of HepG2; after HepG2-sorafenib cells were transfected with sh-CAHM, the number of clones formed by Sorafenib treatment was significantly higher than that of HepG2 cells. The number was significantly less than that of HepG2-s + sh-NC group. Molecular Docking results indicate that Moschus was candidate drug for target protein of CAHM.

Conclusion: Five chemotherapy-related LncRNAs could predict drug resistance in HCC with high accuracy, and the hub LncRNA CAHM has potential as a new biomarker for HCC chemotherapy resistance.

COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation

Machine learning (ML) algorithms were used to identify a novel biological target for breast cancer and explored its relationship with the tumor microenvironment (TME) and patient prognosis. The edgR package identified hub genes associated with overall survival (OS) and prognosis, which were validated using public datasets. Of 149 up-regulated genes identified in tumor tissues, three ML algorithms identified COL11A1 as a hub gene. COL11A1was highly expressed in breast cancer samples and associated with a poor prognosis, and positively correlated with a stromal score (r=0.49, p<0.001) and the ESTIMATE score (r=0.29, p<0.001) in the TME. Furthermore, COL11A1 negatively correlated with B cells, CD4 and CD8 cells, but positively associated with cancer-associated fibroblasts. Forty-three related immune-regulation genes associated with COL11A1 were identified, and a five-gene immune regulation signature was built. Compared with clinical factors, this gene signature was an independent risk factor for prognosis (HR=2.591, 95%CI 1.831–3.668, p=7.7e-08). A nomogram combining the gene signature with clinical variables, showed better predictive performance (C-index=0.776). The model correction prediction curve showed little bias from the ideal curve. COL11A1 is a potential therapeutic target in breast cancer and may be involved in the tumor immune infiltration; its high expression is strongly associated with poor prognosis.

Prognostic Assessment of Oxidative Stress-Related Genes in Colorectal Cancer and New Insights into Tumor Immunity

Oxidative stress is crucial to the biology of tumors. Oxidative stress' potential predictive significance in colorectal cancer (CRC) has not been studied; nevertheless here, we developed a forecasting model based on oxidative stress to forecast the result of CRC survival and enhance clinical judgment. The training set was chosen from the transcriptomes of 177 CRC patients in GSE17536. For validation, 65 samples of colon cancer from GSE29621 were utilized. For the purpose of choosing prognostic genes, the expression of oxidative stress-related genes (OXEGs) was found. Prognostic risk models were built using multivariate Cox regression analysis, univariate Cox regression analysis, and LASSO regression analysis. The outcomes of the western blot and transcriptome sequencing tests were finally confirmed. ATF4, CARS2, CRP, GPX1, IL1B, MAPK8, MRPL44, MTFMT, NOS1, OSGIN2, SOD2, AARS2, and FOXO3 were among the 14 OXEGs used to build prognostic characteristics. Patients with CRC were categorized into low-risk and high-risk groups according on their median risk scores. Cox regression analysis using single and multiple variables revealed that OXEG-related signals were independent risk factors for CRC. Additionally, the validation outcomes from western blotting and transcriptome sequencing demonstrated that OXEGs were differently expressed. Using 14 OXEGs, our work creates a predictive signature that may be applied to the creation of new prognostic models and the identification of possible medication candidates for the treatment of CRC.

Downregulation of miR-146a-5p Promotes Acute Pancreatitis through Activating the TLR9/NLRP3 Signaling Pathway by Targeting TRAF6 In Vitro Rat Model

Acute pancreatitis (AP) is mainly caused by acinar cells releasing various inflammatory factors, causing inflammatory storms and leading to severe pancreatitis. Detection methods and treatment targets for pancreatitis are lacking, raising the urgency of identifying diagnostic markers and therapeutic targets for AP. MicroRNAs (miRNAs) have recently been identified as molecular markers for various biological processes such as tumors, immunity, and metabolism, and the involvement of miRNAs in inflammatory responses has been increasingly studied. To explore the role of miRNAs in AP is the primary objective of this study. By using qPCR on our cerulein-induced pancreatitis cell model, it is worth noting that the change of miR-146a-5p expression in inflammation-related miRNAs in AP was predominant. Next, ELISA, CCK8, and flow cytometry were used to inspect the impact of miR-146a-5p on pancreatitis. BiBiServ bioinformatics anticipated binding ability of miR-146a-5p and 3′-untranslated region (3′UTR) of TNF receptor-associated factor 6 (TRAF6), and the dual-luciferase assay verified the combination of the two. TRAF6 knockdown verified the effect of TRAF6 on the progression of pancreatitis. Finally, rescue experiments verified the capability of miR-146a-5p and TRAF6 interaction on the Toll-like receptor 9 (TLR9)/NOD-like receptor protein 3 (NLRP3) signaling pathway and cell function. The expression of miR-146a-5p decreased in cerulein-induced AR42J pancreatic acinar cells. Functional experiments verified that miR-146a-5p facilitated the proliferation of AR42J pancreatic acinar cells and inhibited their apoptosis. Bioinformatic predictions and dual-luciferase experiments verified the actual binding efficiency between miR-146a-5p and 3′UTR of TRAF6. Our study confirmed that knockdown of TRAF6 restrained the progression of pancreatitis, and knockdown of TRAF6 rescued pancreatitis caused by miR-146a-5p downregulation by the TLR9/NLRP3 signaling pathway. Therefore, downregulation of miR-146a-5p in the induced pancreatitis cell model promotes the progression of pancreatitis via the TLR9/TRAF6/NLRP3 signaling pathway. There is potential for miR-146a-5p to serve as a diagnostic marker and therapeutic nucleic acid drug for AP.

COL10A1 allows stratification of invasiveness of colon cancer and associates to extracellular matrix and immune cell enrichment in the tumor parenchyma

Background

Treatment options for metastatic colorectal cancer (CRC) are mostly ineffective. We present new evidence that tumor tissue collagen type X alpha 1 (COL10A1) is a relevant candidate biomarker to improve this dilemma.

Methods

Several public databases had been screened to observe COL10A1 expression in transcriptome levels with cell lines and tissues. Protein interactions and alignment to changes in clinical parameters and immune cell invasion were performed, too. We also used algorithms to build a novel COL10A1-related immunomodulator signature. Various wet-lab experiments were conducted to quantify COL10A1 protein and transcript expression levels in disease and control cell models.

Results

COL10A1 mRNA levels in tumor material is clinical and molecular prognostic, featuring upregulation compared to non-cancer tissue, increase with histomorphological malignancy grading of the tumor, elevation in tumors that invade perineural areas, or lymph node invasion. Transcriptomic alignment noted a strong positive correlation of COL10A1 with transcriptomic signature of cancer-associated fibroblasts (CAFs) and populations of the immune compartment, namely, B cells and macrophages. We verified those findings in functional assays showing that COL10A1 are decreased in CRC cells compared to fibroblasts, with strongest signal in the cell supernatant of the cells.

Conclusion

COL10A1 abundance in CRC tissue predicts metastatic and immunogenic properties of the disease. COL10A1 transcription may mediate tumor cell interaction with its stromal microenvironment.

The Association between TRP Channels Expression and Clinicopathological Characteristics of Patients with Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PDAC) has low survival rates worldwide due to its tendency to be detected late and its characteristic desmoplastic reaction, which slows the use of targeted therapies. As such, the discovery of new connections between genes and the clinicopathological parameters contribute to the search for new biomarkers or targets for therapy. Transient receptor potential (TRP) channels are promising tools for cancer therapy or markers for PDAC. Therefore, in this study, we selected several genes encoding TRP proteins previously reported in cellular models, namely, Transient Receptor Potential Cation Channel Subfamily V Member 6 (TRPV6), Transient receptor potential ankyrin 1 (TRPA1), and Transient receptor potential cation channel subfamily M (melastatin) member 8 (TRPM8), as well as the TRPM8 Channel Associated Factor 1 (TCAF1) and TRPM8 Channel Associated Factor 2 (TCAF2) proteins, as regulatory factors. We analyzed the expression levels of tumors from patients enrolled in public datasets and confirmed the results with a validation cohort of PDAC patients enrolled in the Clinical Institute Fundeni, Romania. We found significantly higher expression levels of TRPA1, TRPM8, and TCAF1/F2 in tumoral tissues compared to normal tissues, but lower expression levels of TRPV6, suggesting that TRP channels have either tumor-suppressive or oncogenic roles. The expression levels were correlated with the tumoral stages and are related to the genes involved in calcium homeostasis (Calbindin 1 or S100A4) or to proteins participating in metastasis (PTPN1). We conclude that the selected TRP proteins provide new insights in the search for targets and biomarkers needed for therapeutic strategies for PDAC treatment.

Overexpression of OAS1 Is Correlated With Poor Prognosis in Pancreatic Cancer

Background

OAS1 expression in pancreatic cancer has been confirmed by many studies. However, the prognostic value and mechanism of OAS1 in pancreatic cancer have not been analyzed.

Methods

The RNA-seq in pancreatic cancer were obtained by UCSC XENA and GEO database. In addition, immunohistochemical validation and analysis were performed using samples from the 900th hospital. The prognosis of OAS1 was evaluated by timeROC package, Cox regression analysis, and Kaplan-Meier survival curves. Then, the main functional and biological signaling pathways enrichment and its relationship with the abundance of immune cells were analyzed by bioinformatics.

Results

OAS1 was highly expressed in pancreatic cancer compared with normal pancreatic tissue. High OAS1 expression was associated with poor overall survival (p<0.05). The OAS1 was significantly correlated to TNM staging (p=0.014). The timeROC analysis showed that the AUC of OAS1 was 0.734 for 3-year OS. In addition, the expression of OAS1 was significantly correlated with the abundance of a variety of immune markers. GSEA showed that enhanced signaling pathways associated with OAS1 include Apoptosis, Notch signaling pathway, and P53 signaling pathway.

Conclusions

OAS1 is a valuable prognostic factor in pancreatic cancer. Moreover, it may be a potential immunotherapeutic target.