Identification and validation of a novel prognosis model based on m5C-related long non-coding RNAs in colorectal cancer.

BACKGROUND: The prognosis of tumor patients can be assessed by measuring the levels of lncRNAs (long non-coding RNAs), which play a role in controlling the methylation of the RNA. Prognosis in individuals with colorectal adenocarcinoma (CRC) is strongly linked to lncRNA expression, making it imperative to find lncRNAs that are associated with RNA methylation with strong prognostic value. METHODS: In this study, by analyzing TCGA dataset, we were able to develop a risk model for lncRNAs that are associated with m5C with prognostic significance by employing LASSO regression and univariate Cox proportional analysis. There were a number of methods employed to ensure the model was accurate, including multivariate and univariate Cox regression analysis, Kaplan analysis, and receiver operating characteristic curve analysis. The principal component analysis, GSEA and GSVA analysis were used for risk model analysis. The CIBERSORT instrument and the TIMER database were used to evaluate the link between the immune cells that infiltrate tumors and the risk model. In vitro experiments were also performed to validate the predicted m5C-related significant lncRNAs. RESULTS: The m5c regulators were differentially expressed in colorectal cancer and normal tissue. Based on the screening criteria and LASSO regression, 11 m5c-related lncRNAs were identified for developing the prognostic risk model. Multivariate and univariate Cox regression analysis showed the risk score is a crucial prognostic factor in CRC patients. The 1-year, 3-year, and 5-year AUC curves showed the risk score was higher than those identified for other clinicopathological characteristics. A nomogram using the risk score as a quantitative tool was developed for predicting patients' outcomes in clinical settings. In addition, the risk profile of m5C-associated lncRNAs can discriminate between tumor immune cells' characteristics in CRC. Mutation patterns and chemotherapy were analyzed between high- and low- risk groups of CRC patients. Moreover, TNFRSF10A-AS1 was chosen for the in vitro verification of the m5C-connected lncRNA to demonstrate impressive effects on the proliferation, migration and invasion of CRC cells. CONCLUSION: A risk model including the prognostic value of 11 m5C-associated lncRNAs proves to be a useful prognostic tool for CRC and improves the care of patients suffering from CRC based on these findings.

Exploration of epithelial-mesenchymal transition-related lncRNA signature and drug sensitivity in breast cancer.

Background: Breast cancer (BRCA) has become the most diagnosed cancer worldwide for female and seriously endanger female health. The epithelial-mesenchymal transition (EMT) process is associated with metastasis and drug resistance in BRCA patients. However, the prognostic value of EMT-related lncRNA in BRCA still needs to be revealed. The aim of this study is to construct an EMT-related lncRNA (ERL) signature with accuracy predictive ability for the prognosis of BRCA patients. Methods: RNA-seq expression data and Clinical characteristics obtained from the TCGA (The Cancer Genome Atlas) were used in the study. First, we identified the EMT-related lncRNA by the Pearson correlation analysis. An EMT-related lncRNAs prognostic risk signature was constructed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was validated using Kaplan-Meier (KM) survival analysis, ROC curve and C-index. Finally, a nomogram was constructed for clinical practice in evaluating the patients with BRCA and validated by calibration curve and decision curve analysis (DCA). We also evaluated the drug sensitivity of signature lncRNA and the tumor immune cell infiltration in breast cancer. Results: We constructed a 10-lncRNA risk score signature based on the lncRNAs associated with the EMT process. We could assign BRCA patients to the high- and low-risk group according to the median risk score. The prognostic risk signature showed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of the immune cell subtype. Drug sensitivity analysis proved ERLs signature could effectively predict the sensitivity of patients to common chemotherapy drugs in BRCA and provide guidance for chemotherapy drugs for high-risk and low-risk patients. Conclusion: Our ERL signature and nomogram have excellent prognostic value and could become reliable tools for clinical guidance.

Exosome-transmitted miR-29a induces colorectal cancer metastasis by destroying the vascular endothelial barrier.

Metastasis is the leading cause of colorectal cancer treatment failure and mortality. Communication between endothelium and tumor cells in the tumor microenvironment is required for cancer metastasis. Tumor-derived exosomes have been shown to increase vascular permeability by delivering microRNA (miRNA) to vascular endothelial cells, facilitating cancer metastasis. The mechanism by which Epithelial-mesenchymal transition (EMT) tumor cell-derived exosomes influence vascular permeability remains unknown. MicroRNA-29a (miR-29a) expression is up-regulated in colorectal cancer (CRC) tissues, which is clinically significant in metastasis. Exosomal miR-29a secreted by EMT-CRC cells has been found to decrease the expression of Zonula occlusion 1 (ZO-1), Claudin-5, and Occludin via targeting Kruppel-like factor 4 (KLF4). In vitro co-culture investigations further revealed that EMT-cancer cells release exosomal miR-29a, which alters vascular endothelial permeability. Furthermore, exosomal miR-29a promoted liver metastases in CRC mice. Our findings demonstrate that EMT-CRC cells may transport exosomal miR-29a to endothelial cells in the tumor microenvironment (TME). As a result, increased vascular permeability promotes the development and metastasis of CRC. Exosomal miR-29a has the potential to be a predictive marker for tumor metastasis as well as a viable therapeutic target for CRC.

LINC00543 promotes colorectal cancer metastasis by driving EMT and inducing the M2 polarization of tumor associated macrophages.

BACKGROUND: The interaction between the tumor-microenvironment (TME) and the cancer cells has emerged as a key player in colorectal cancer (CRC) metastasis. A small proportion of CRC cells which undergo epithelial-mesenchymal transition (EMT) facilitate the reshaping of the TME by regulating various cellular ingredients. METHODS: Immunohistochemical analysis, RNA immunoprecipitation (RIP), RNA Antisense Purification (RAP), dual luciferase assays were conducted to investigate the biological function and regulation of LINC00543 in CRC. A series in vitro and in vivo experiments were used to clarify the role of LINC00543 in CRC metastasis. RESULTS: Here we found that the long non-coding RNA LINC00543, was overexpressed in colorectal cancer tissues, which correlated with advanced TNM stage and poorer prognosis of CRC patients. The overexpression of LINC00543 promoted tumorigenesis and metastasis of CRC cells by enhancing EMT and remodeling the TME. Mechanistically, LINC00543 blocked the transport of pre-miR-506-3p across the nuclear-cytoplasmic transporter XPO5, thereby reducing the production of mature miR-506-3p, resulting in the increase in the expression of FOXQ1 and induction of EMT. In addition, upregulation of FOXQ1 induced the expression of CCL2 that accelerated the recruitment of macrophages and their M2 polarization. CONCLUSIONS: Our study showed that LINC00543 enhanced EMT of CRC cells through the pre-miR-506-3p/FOXQ1 axis. This resulted in the upregulation of CCL2, leading to macrophages recruitment and M2 polarization, and ultimately stimulating the progression of CRC.

Development of the expression and prognostic significance of m5 C-related LncRNAs in breast cancer.

BACKGROUND: 5-Methylcytosine (m5C) methylation is a major epigenetic RNA modification and is closely related to tumorigenesis in various cancers. This study aimed to explore the prognostic value of m5C-related lncRNAs in breast cancer. METHODS: Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. First, we performed differentially expressed gene (DEG) analysis and constructed a PPI network for the 12 m5C regulators. Then, we identified the m5C-related LncRNAs by the "cor. test." An m5C-related lncRNA prognostic risk signature was developed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was determined using Kaplan-Meier (KM) survival analysis and ROC curves. Finally, a nomogram was constructed for clinical application in evaluating patients with BRCA. We also researched the drug sensitivity of signature lncRNAs and immune cell infiltration. Finally, we validated the expression of the signature lncRNAs through qRT-PCR in a breast cancer cell line and a breast epithelial cell line. RESULTS: Overall, we constructed an 11-lncRNA risk score signature based on the lncRNAs associated with m5C regulators. According to the median risk score, we divided BRCA patients into high- and low-risk groups. The prognostic risk signature displayed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of immune cell subtypes. Drug sensitivity proved that our prognostic risk signature potentially has therapeutic value. CONCLUSIONS: The m5C-related lncRNA signature reliably predicted the prognosis of breast cancer patients and may provide new insight into the breast cancer tumor immune microenvironment.

Identification and validation of a prognostic risk model based on caveolin family genes for breast cancer.

Background: Breast cancer (BC) is the most vicious killer of women's health and is accompanied by increased incidence and mortality rates worldwide. Many studies have demonstrated that caveolins (CAVs) were abnormally expressed in a variety of tumors and implicated in tumorigenesis and cancer progression. However, the role of CAVs in BC remains somewhat contentious. Methods: We comprehensively explored the expression and prognostic value of CAVs (CAV1-3) in BC utilizing public databases (ONCOMINE, TIMER, UALCAN, and TCGA databases). Then we constructed a prognostic model based on the expression profiles. Also, a prognostic nomogram was built to predict the overall survival (OS). We further investigated the relationship between this signature and immune cell infiltration and the mutational landscape in BC. The R package "pRRophetic" was used to predict chemotherapeutic response in BC patients. Finally, we employed loss-of-function approaches to validate the role of CAVs in BC. Results: We found that CAVs were significantly downregulated in various cancer types, especially in BC. Low CAV expression was closely related to the malignant clinicopathological characteristics and worse OS and relapse-free survival (RFS) in BC. Then we constructed a prognostic model based on the expression profiles of CAVs, which divided BC patients into two risk groups. The Kaplan-Meier analysis showed that patients in the high-risk group tend to have a poorer prognosis than those in the low-risk group. Multivariate analysis indicated that the risk score and stage were both independent prognostic factors for BC patients, suggesting a complementary value. The clinical profiles and risk module were used to construct a nomogram that could accurately predict the OS in BC. In addition, we found that patients in the low-risk group tend to have a relatively high immune status and a lower mutation event frequency compared to the high-risk group. Furthermore, this signature could predict the response to chemotherapy and immunotherapy. Finally, CAV depletion promoted the colony formation, migration, and invasion of BC cells. Conclusion: CAVs may serve as novel biomarkers and independent prognostic factors for BC patients. Also, the constructed signature based on CAVs may predict immunotherapeutic responses and provide a novel nomogram for precise outcome prediction of BC.

Single-cell and WGCNA uncover a prognostic model and potential oncogenes in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Single-cell transcriptome sequencing (scRNA-seq) can provide accurate gene expression data for individual cells. In this study, a new prognostic model was constructed by scRNA-seq and bulk transcriptome sequencing (bulk RNA-seq) data of CRC samples to develop a new understanding of CRC. METHODS: CRC scRNA-seq data were downloaded from the GSE161277 database, and CRC bulk RNA-seq data were downloaded from the TCGA and GSE17537 databases. The cells were clustered by the FindNeighbors and FindClusters functions in scRNA-seq data. CIBERSORTx was applied to detect the abundance of cell clusters in the bulk RNA-seq expression matrix. WGCNA was performed with the expression profiles to construct the gene coexpression networks of TCGA-CRC. Next, we used a tenfold cross test to construct the model and a nomogram to assess the independence of the model for clinical application. Finally, we examined the expression of the unreported model genes by qPCR and immunohistochemistry. A clone formation assay and orthotopic colorectal tumour model were applied to detect the regulatory roles of unreported model genes. RESULTS: A total of 43,851 cells were included after quality control, and 20 cell clusters were classified by the FindCluster () function. We found that the abundances of C1, C2, C4, C5, C15, C16 and C19 were high and the abundances of C7, C10, C11, C13, C14 and C17 were low in CRC tumour tissues. Meanwhile, the results of survival analysis showed that high abundances of C4, C11 and C13 and low abundances of C5 and C14 were associated with better survival. The WGCNA results showed that the red module was most related to the tumour and the C14 cluster, which contains 615 genes. Lasso Cox regression analysis revealed 8 genes (PBXIP1, MPMZ, SCARA3, INA, ILK, MPP2, L1CAM and FLNA), which were chosen to construct a risk model. In the model, the risk score features had the greatest impact on survival prediction, indicating that the 8-gene risk model can better predict prognosis. qPCR and immunohistochemistry analysis showed that the expression levels of MPZ, SCARA3, MPP2 and PBXIP1 were high in CRC tissues. The functional experiment results indicated that MPZ, SCARA3, MPP2 and PBXIP1 could promote the colony formation ability of CRC cells in vitro and tumorigenicity in vivo. CONCLUSIONS: We constructed a risk model to predict the prognosis of CRC patients based on scRNA-seq and bulk RNA-seq data, which could be used for clinical application. We also identified 4 previously unreported model genes (MPZ, SCARA3, MPP2 and PBXIP1) as novel oncogenes in CRC. These results suggest that this model could potentially be used to evaluate the prognostic risk and provide potential therapeutic targets for CRC patients.

The lncRNA BDNF-AS/WDR5/FBXW7 axis mediates ferroptosis in gastric cancer peritoneal metastasis by regulating VDAC3 ubiquitination.

Ferroptosis is a novel form of cell death that is closely associated with the formation of many tumors. Our study focused on the mechanism by which long noncoding RNAs (lncRNAs) regulate ferroptosis in gastric cancer (GC) peritoneal metastasis (PM). We utilized lncRNA sequencing and protein profiling analysis to identify ferroptosis-associated lncRNAs and proteins. qRT-PCR was used to analyze the expression of BDNF-AS and FBXW7 in GC tissues and adjacent normal tissues. Chromatin isolation by RNA purification (ChIRP), RNA immunoprecipitation (RIP), chromatin immunoprecipitation (ChIP), and coimmunoprecipitation (co-IP) assays were performed to investigate the interaction between BDNF-AS and its downstream targets. Finally, the function of BDNF-AS was validated in vivo . We demonstrated that BDNF-AS was highly expressed in GC and PM tissues. High BDNF-AS expression was positively related to GC progression and poor prognosis. Functionally, BDNF-AS overexpression protected GC cells from ferroptosis and promoted the progression of GC and PM. Mechanistically, BDNF-AS could regulate FBXW7 expression by recruiting WDR5, thus affecting FBXW7 transcription, and FBXW7 regulated the protein expression of VDAC3 through ubiquitination. Conclusively, our research demonstrated that the BDNF-AS/WDR5/FBXW7 axis regulates ferroptosis in GC by affecting VDAC3 ubiquitination. BDNF-AS might be a biomarker for the evaluation of GC prognosis and the treatment of GC.

Estradiol Ameliorates Acute Kidney Ischemia-Reperfusion Injury by Inhibiting the TGF-ßRI-SMAD Pathway.

Renal ischemia-reperfusion injury (IRI) is less extensive in females than males in both animals and humans; however, this protection diminishes after menopause, suggesting that estrogen plays a pivotal role in IRI, but the underlying mechanism remains largely unknown. Our study found that 45 min of warm ischemia was sufficient to induce significant pathological changes without causing death in model animals. Compared with male rats, female rats exhibited less extensive apoptosis, kidney injury, and fibrosis; these effects were worsened in ovariectomized (OVX) rats and ameliorated upon estradiol (E2) supplementation. Furthermore, the levels of TGF-ßRI, but not TGF-ßRII or TGF-ß1, were significantly increased in OVX rats, accompanied by phosphorylated SMAD2/3 activation. Interestingly, the alteration trend of the nuclear ERα level was opposite that of TGF-ßRI. Furthermore, dual luciferase reporter and chromatin immunoprecipitation assays showed that ERα could bind to the promoter region of TGF-ßRI and negatively regulate its mRNA expression. Moreover, an in vitro study using NRK-52E cells showed that ERα knockdown blocked E2-mediated protection, while TGF-ßRI knockdown protected cells against hypoxic insult. The findings of this study suggest that renal IRI is closely related to the TGF-ßRI-SMAD pathway in females and that E2 exert its protective effect via the ERα-mediated transcriptional inhibition of TGF-ßRI expression.

A comprehensive evaluation of early potential risk factors for disease aggravation in patients with COVID-19.

The 2019 Coronavirus Disease (COVID-19) has become an unprecedented public crisis. We retrospectively investigated the clinical data of 197 COVID-19 patients and identified 88 patients as disease aggravation cases. Compared with patients without disease aggravation, the aggravation cases had more comorbidities, including hypertension (25.9%) and diabetes (20.8%), and presented with dyspnoea (23.4%), neutrophilia (31.5%), and lymphocytopenia (46.7%). These patients were more prone to develop organ damage in liver, kidney, and heart (P < 0.05). A multivariable regression analysis showed that advanced age, comorbidities, dyspnea, lymphopenia, and elevated levels of Fbg, CTnI, IL-6, and serum ferritin were significant predictors of disease aggravation. Further, we performed a Kaplan-Meier analysis to evaluate the prognosis of COVID-19 patients, which suggested that 64.9% of the patients had not experienced ICU transfers and survival from the hospital.

TM4SF1 promotes EMT and cancer stemness via the Wnt/ß-catenin/SOX2 pathway in colorectal cancer.

BACKGROUND: Transmembrane 4 L six family member 1 (TM4SF1) is upregulated in several epithelial cancers and is closely associated with poor prognosis. However, the role of TM4SF1 and its potential mechanism in colorectal cancer (CRC) remain elusive. METHODS: We investigated the expression of TM4SF1 in the Oncomine, the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and confirmed the results by immunohistochemistry (IHC), qPCR and Western blotting (WB) of CRC tissues. The effect of TM4SF1 on the epithelial-to-mesenchymal transition (EMT) and cancer stemness of CRC cells was investigated by Transwell, wound healing and sphere formation assays. A series of in vitro and in vivo experiments were conducted to reveal the mechanisms by which TM4SF1 modulates EMT and cancer stemness in CRC. RESULTS: TM4SF1 expression was markedly higher in CRC tissues than in non-tumour tissues and was positively correlated with poor prognosis. Downregulation of TM4SF1 inhibited the migration, invasion and tumour sphere formation of SW480 and LoVo cells. Conversely, TM4SF1 overexpression significantly enhanced the migration, invasion and tumoursphere formation potential of CRC cells, Additionally, TM4SF1 silencing inhibited the EMT mediated by transforming growth factor-ß1 (TGF-ß1). Mechanistically, gene set enrichment analysis (GSEA) predicted that the Wnt signalling pathway was one of the most impaired pathways in TM4SF1-deficient CRC cells compared to controls. The results were further validated by WB, which revealed that TM4SF1 modulated SOX2 expression in a Wnt/ß-catenin activation-dependent manner. Furthermore, we found that knockdown of TM4SF1 suppressed the expression of c-Myc, leading to decreased c-Myc binding to the SOX2 gene promoter. Finally, depletion of TM4SF1 inhibited metastasis and tumour growth in a xenograft mouse model. CONCLUSION: Our study substantiates a novel mechanism by which TM4SF1 maintains cancer cell stemness and EMT via the Wnt/ß-catenin/c-Myc/SOX2 axis during the recurrence and metastasis of CRC.

Integrated Analysis Identifies a Nine-microRNA Signature Biomarker for Diagnosis and Prognosis in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most lethal and malignant type of cancer in the world. Abnormal expression of human microRNA-200a (hsa-miRNA-200a or miR-200a) has previously been characterized as a clinically noticeable biomarker in several cancers, but its role in CRC is still unclear. METHODS: Three CRC miRNA expression datasets were integratively analyzed by Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Nine candidate miRNAs were identified and validated for diagnostic and prognostic capability with the prediction model. The potential roles of the tumor suppressor miR-200a-3p in invasion, migration, and epithelial-mesenchymal transition of CRC cells were elaborated by in vitro studies. RESULTS: Nine miRNAs (miR-492, miR-200a, miR-338, miR-29c, miR-101, miR-148a, miR-92a, miR-424, and miR-210) were identified as potentially useful diagnostic biomarkers in the clinic. The overall accuracy rate of the nine miRNAs in the diagnostic model was 0.94, 0.89, and 0.978 in the testing, validation, and independent validation dataset, respectively. CRC patients in the GSE29622 cohort were separated by the prognostic model into the low-risk score group and the high-risk score group. The area under the receiver operating characteristic curve (AUC) was 0.872 and 0.783 for predicting the 1- to 10-year survival of CRC patients. The performance of the prognostic model was validated by an independent TCGA-Colon Adenocarcinoma (COAD) dataset with AUC values between 0.911 and 0.796 in predicting 1- to 10-year survival. Nomograms comprising risk scores, tumor stage, and TNM staging were generated for predicting 1-, 3-, and 5-year overall survival (OS) in the GSE29622 and TCGA-COAD datasets. Colony formation, invasion, and migration in DLD1 and SW480 cells were suppressed by overexpression of miR-200a-3p. Inhibition of miR-200a-3p function contributed to abnormal colony formation, migration, invasion, and epithelial-mesenchymal transition (EMT). miR-200a-3p binding sites were located within the 3'-untranslated region (3'-UTR) of the Forkhead box protein A1 (FOXA1) mRNA. CONCLUSION: We developed and validated a diagnostic and prognostic prediction model for CRC. miR-200a-3p was determined to be a potential diagnostic and prognostic biomarker for CRC.