LINC01272/miR-876/ITGB2 axis facilitates the metastasis of colorectal cancer via epithelial-mesenchymal transition

ITGB2 related to immune cell infiltration as a potential therapeutic target of inflammatory bowel disease using bioinformatics and functional research

Inflammatory bowel disease (IBD) is a chronic systemic inflammatory condition regarded as a major risk factor for colitis-associated cancer. However, the underlying mechanisms of IBD remain unclear. First, five GSE data sets available in GEO were used to perform 'batch correction' and Robust Rank Aggregation (RRA) to identify differentially expressed genes (DEGs). Candidate molecules were identified using CytoHubba, and their diagnostic effectiveness was predicted. The CIBERSORT algorithm evaluated the immune cell infiltration in the intestinal epithelial tissues of patients with IBD and controls. Immune cell infiltration in the IBD and control groups was determined using the least absolute shrinkage selection operator algorithm and Cox regression analysis. Finally, a total of 51 DEGs were screened, and nine hub genes were identified using CytoHubba and Cytoscape. GSE87466 and GSE193677 were used as extra data set to validate the expression of the nine hub genes. CD4-naïve T cells, gamma-delta T cells, M1 macrophages and resting dendritic cells (DCs) are the main immune cell infiltrates in patients with IBD. Signal transducer and activator of transcription 1, CCR5 and integrin subunit beta 2 (ITGB2) were significantly upregulated in the IBD mouse model, and suppression of ITGB2 expression alleviated IBD inflammation in mice. Additionally, the expression of ITGB2 was upregulated in IBD-associated colorectal cancer (CRC). The silence of ITGB2 suppressed cell proliferation and tumour growth in vitro and in vivo. ITGB2 resting DCs may provide a therapeutic strategy for IBD, and ITGB2 may be a potential diagnostic marker for IBD-associated CRC.

The role of long non-coding RNA in Crohn's disease

Emerging evidence has illuminated the pivotal role of long noncoding RNAs (lncRNAs) in orchestrating immunological functions and autoimmune responses. In the context of Crohn's disease (CD), an array of novel lncRNAs has been identified in the plasma and intestinal tissues of afflicted individuals, suggesting a dualistic influence on the disease progression, either exacerbating or mitigating its course. Current research has demonstrated the involvement of lncRNAs in competitive endogenous RNA, the inflammation process, epithelial barrier function, gut microbiota imbalance, and epigenetic regulation. This review aims to encapsulate the current knowledge on the lncRNA contribution to CD and underscore potential avenues for future research. LncRNAs are increasingly recognized as significant biomarkers and potential therapeutic targets, holding a key position in the pathogenesis of CD. Furthermore, the unique attributes of circulating lncRNAs, such as minimal side effects, combinational therapy potential, and personalized medicine, render them as promising therapeutic tools for individual health management in CD.

A novel neutrophil extracellular traps-related lncRNA signature predicts prognosis in patients with early-stage lung adenocarcinoma

BACKGROUND

Neutrophil extracellular traps (NETs) could entrap tumour cells and promote their dissemination and metastasis. Further analysis of NETs-related molecules is expected to provide a new strategy for prognosis prediction and treatment of lung adenocarcinoma (LUAD) patients.

METHODS

The model construction was established through co-expression analysis, Lasso Cox regression, univariate and multivariate COX regression, Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway. The potential drugs and analysed drug sensitivity were screened by pRRophetic packages.

RESULTS

In this study, we constructed a 15 NETs-related long non-coding RNAs (lncRNAs) prognostic prediction model (AC091057.1, SPART-AS1, AC023796.2, AL031600.2, AC084781.1, AC032011.1, FAM66C, C026355.2, AL096870.2, AC092718.5, PELATON, AC008635.1, AL162632.3, AC087501.4 and AC123768.3) for patients with early-stage LUAD based on public databases and datasets. The signature is associated with immune cell functions, tumour mutation burden and treatment sensitivity in LUAD patients. Additionally, we found that FAM66C is highly expressed in lung cancer patients for the first time, which is associated with poor prognosis. FAM66C knockdown significantly inhibited the proliferation and migration ability of the tumour cells.

CONCLUSIONS

In conclusion, this model is a new and effective prognostic and efficacy predictive biomarker, FAM66C plays an oncogene role in the process of LUAD development. It may provide a new theoretical basis for the clinical diagnosis and treatment in LUAD patients in early stage.

Differential Gene Expression of Checkpoint Markers and Cancer Markers in Mouse Models of Spontaneous Chronic Colitis

The presence of checkpoint markers in cancer cells aids in immune escape. The identification of checkpoint markers and early cancer markers is of utmost importance to gain clarity regarding the relationship between colitis and progressive inflammation leading to cancer. Herein, the gene expression levels of checkpoint makers, cancer-related pathways, and cancer genes in colon tissues of mouse models of chronic colitis (Winnie and Winnie-Prolapse mice) using next-generation sequencing are determined. Winnie mice are a result of a Muc2 missense mutation. The identification of such genes and their subsequent expression and role at the protein level would enable novel markers for the early diagnosis of cancer in IBD patients. The differentially expressed genes in the colonic transcriptome were analysed based on the Kyoto Encyclopedia of Genes and Genomes pathway. The expression of several oncogenes is associated with the severity of IBD, with Winnie-Prolapse mice expressing a large number of key genes associated with development of cancer. This research presents a number of new targets to evaluate for the development of biomarkers and therapeutics.

Nicotine induces macrophage pyroptosis via LINC01272/miR-515/KLF6 axis

Nicotine contributes to the causation of atherosclerosis, which the prominent cellular components are macrophages. Long non-coding RNAs (lncRNAs) play an important role in regulating cell functions such as cell proliferation, differentiation and programmed death. However, the function and mechanism of lncRNAs in nicotine-induced macrophage pyroptosis has not been reported. We screened the deferentially expressed lncRNAs of human carotid artery plaque (GSE97210) and verified them in nicotine-induced pyroptosis of macrophages. Results showed only LINC01272 was up-regulated in a dose-dependent manner in macrophages. The immunofluorescence staining result confirmed that interfering LINC01272 inhibited nicotine-induced macrophage pyroptosis. Through bioinformatics analysis, dual luciferase reporter gene assay and qPCR, we identified miR-515 was significantly negatively correlated with the expression of LINC01272, and KLF6 is the target gene of miR-515. Furthermore, our results demonstrated that LINC01272/miR-515/KLF6 axis meditated nicotine-induced macrophage pyroptosis. In addition, in human peripheral blood mononuclear cells of smoking populations, the expression of GSDMD-N, NLRP3, LINC01272 and KLF6 was significantly increased, while the level of miR-515 was reduced. This study confirmed that nicotine increases the expression of LINC01272 to competitively bind with miR-515 in macrophages, reducing the inhibitory effect of miR-515 on its target gene KLF6, which ultimately induces macrophage pyroptosis.

Systemically Identifying Triple-Negative Breast Cancer Subtype-Specific Prognosis Signatures, Based on Single-Cell RNA-Seq Data

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with different molecular subtypes. Although progress has been made, the identification of TNBC subtype-associated biomarkers is still hindered by traditional RNA-seq or array technologies, since bulk data detected by them usually have some non-disease tissue samples, or they are confined to measure the averaged properties of whole tissues. To overcome these constraints and discover TNBC subtype-specific prognosis signatures (TSPSigs), we proposed a single-cell RNA-seq-based bioinformatics approach for identifying TSPSigs. Notably, the TSPSigs we developed mostly were found to be disease-related and involved in cancer development through investigating their enrichment analysis results. In addition, the prognostic power of TSPSigs was successfully confirmed in four independent validation datasets. The multivariate analysis results showed that TSPSigs in two TNBC subtypes-BL1 and LAR, were two independent prognostic factors. Further, analysis results of the TNBC cell lines revealed that the TSPSigs expressions and drug sensitivities had significant associations. Based on the preceding data, we concluded that TSPSigs could be exploited as novel candidate prognostic markers for TNBC patients and applied to individualized treatment in the future.

LncRNA PELATON, a Ferroptosis Suppressor and Prognositic Signature for GBM

PELATON is a long noncoding RNA also known as long intergenic nonprotein coding RNA 1272 (LINC01272). The known reports showed that PELATON functions as an onco-lncRNA or a suppressor lncRNA by suppressing miRNA in colorectal cancer, gastric cancer and lung cancer. In this study, we first found that PELATON, as an onco-lncRNA, alleviates the ferroptosis driven by mutant p53 and promotes mutant p53-mediated GBM proliferation. We also first confirmed that PELATON is a new ferroptosis suppressor lncRNA that functions as a ferroptosis inhibitor mainly by mutant P53 mediating the ROS ferroptosis pathway, which inhibits the production of ROS, reduces the levels of divalent iron ions, promotes the expression of SLC7A11, and inhibits the expression of ACSL4 and COX2.PELATON can inhibit the expression of p53 in p53 wild-type GBM cells and regulate the expression of BACH1 and CD44, but it has no effect on p53, BACH1 and CD44 in p53 mutant GBM cells. PELATON and p53 can form a complex through the RNA binding protein EIF4A3. Knockdown of PELATON resulted in smaller mitochondria, increased mitochondrial membrane density, and enhanced sensitivity to ferroptosis inducers to inhibit GBM cell proliferation and invasion. In addition, we established a favourite prognostic model with NCOA4 and PELATON. PELATON is a promising target for the prognosis and treatment of GBM.

Identification and Validation of Novel Biomarkers for Hepatocellular Carcinoma, Liver Fibrosis/Cirrhosis and Chronic Hepatitis B via Transcriptome Sequencing Technology

Purpose

The aim of this study was to identify and validate novel biomarkers for distinguishing among hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), liver fibrosis/liver cirrhosis (LF/LC) and chronic hepatitis B (CHB).

Patients and Methods

Transcriptomic sequencing was conducted on the liver tissues of 5 patients with HCC, 5 patients with LF/LC, 5 patients with CHB, and 4 healthy controls. The expression levels of selected mRNAs and proteins were assessed by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining, and were verified in validation set (n=200) and testing set (n=400) via enzyme-linked immunosorbent assay (ELISA).

Results

A total of 9 hub mRNAs were identified by short time-series expression miner and weighted gene co-expression network analysis. Of note, the results of qRT-PCR and IHC staining demonstrated that SHC adaptor protein 1 (SHC1), SLAM family member 8 (SLAMF8), and interleukin-32 (IL-32) exhibited gradually increasing trends in the four groups. Subsequent ELISA tests on the validation cohort indicated that the plasma levels of SHC1, SLAMF8 and IL-32 also gradually increased. Furthermore, a diagnostic model APFSSI (age, PLT, ferritin, SHC1, SLAMF8 and IL-32) was established to distinguish among CHB, LF/LC and HCC. The performance of APFSSI model for discriminating CHB from healthy subjects (AUC=0.966) was much greater compared to SHC1 (AUC=0.900), SLAMF8 (AUC=0.744) and IL-32 (AUC=0.821). When distinguishing LF/LC from CHB, APFSSI was the most outstanding diagnostic parameter (AUC=0.924), which was superior to SHC1, SLAMF8 and IL-32 (AUC=0.812, 0.684 and 0.741, respectively). Likewise, APFSSI model with the greatest AUC value displayed an excellent performance for differentiating between HCC and LF/LC than other variables (SHC1, SLAMF8 and IL-32) via ROC analysis. Finally, the results in the test set were consistent with those in the validation set.

Conclusion

SHC1, SLAMF8 and IL-32 can differentiate among patients with HCC, LF/LC, CHB and healthy controls. More importantly, the APFSSI model greatly improves the diagnostic accuracy of HBV-associated liver diseases.

Development and Validation of a Prognostic Gene Signature Correlated With M2 Macrophage Infiltration in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer and the seventh most prevalent cause of cancer-related death worldwide. Tumor microenvironment (TME) has been confirmed to play an crucial role in ESCC progression, prognosis, and the response to immunotherapy. There is a need for predictive biomarkers of TME-related processes to better prognosticate ESCC outcomes.

Aim

To identify a novel gene signature linked with the TME to predict the prognosis of ESCC.

Methods

We calculated the immune/stromal scores of 95 ESCC samples from The Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm, and identified differentially expressed genes (DEGs) between high and low immune/stromal score patients. The key prognostic genes were further analyzed by the intersection of protein–protein interaction (PPI) networks and univariate Cox regression analysis. Finally, a risk score model was constructed using multivariate Cox regression analysis. We evaluated the associations between the risk score model and immune infiltration via the CIBERSORT algorithm. Moreover, we validated the signature using the Gene Expression Omnibus (GEO) database. Within the ten gene signature, five rarely reported genes were further validated with quantitative real time polymerase chain reaction (qRT-PCR) using an ESCC tissue cDNA microarray.

Results

A total of 133 up-regulated genes were identified as DEGs. Ten prognostic genes were selected based on intersection analysis of univariate COX regression analysis and PPI, and consisted of C1QA, C1QB, C1QC, CD86, C3AR1, CSF1R, ITGB2, LCP2, SPI1, and TYROBP (HR>1, p<0.05). The expression of 9 of these genes in the tumor samples were significantly higher compared to matched adjacent normal tissue based on the GEO database (p<0.05). Next, we assessed the ability of the ten-gene signature to predict the overall survival of ESCC patients, and found that the high-risk group had significantly poorer outcomes compared to the low-risk group using univariate and multivariate analyses in the TCGA and GEO cohorts (HR=2.104, 95% confidence interval:1.343-3.295, p=0.001; HR=1.6915, 95% confidence interval:1.053-2.717, p=0.0297). Additionally, receiver operating characteristic (ROC) curve analysis demonstrated a relatively sensitive and specific profile for the signature (1-, 2-, 3-year AUC=0.672, 0.854, 0.81). To identify the basis for these differences in the TME, we performed correlation analyses and found a significant positive correlation with M1 and M2 macrophages and CD8+ T cells, as well as a strong correlation to M2 macrophage surface markers. A nomogram based on the risk score and select clinicopathologic characteristics was constructed to predict overall survival of ESCC patients. For validation, qRT-PCR of an ESCC patient cDNA microarray was performed, and demonstrated that C1QA, C3AR1, LCP2, SPI1, and TYROBP were up-regulated in tumor samples and predict poor prognosis.

Conclusion

This study established and validated a novel 10-gene signature linked with M2 macrophages and poor prognosis in ESCC patients. Importantly, we identified C1QA, C3AR1, LCP2, SPI1, and TYROBP as novel M2 macrophage-correlated survival biomarkers. These findings may identify potential targets for therapy in ESCC patients.