Analysis of the expression profile of serum exosomal lncRNA in breast cancer patients

Polydatin ameliorates low-density lipoprotein cholesterol and lipid metabolism by downregulating proprotein convertase subtilisin/kexin type 9 (PCSK9) in triple-negative breast cancer with hyperlipidemia

To investigate polydatin's effects on low-density lipoprotein cholesterol (LDL-C) and lipid metabolism in mice with triple-negative breast cancer (TNBC) and hyperlipidemia, as well as the underlying mechanism of proprotein convertase subtilisin/kexin type 9 (PCSK9). In vivo, we designed two animal models, namely breast pad in situ inoculation of TNBC model and TNBC with lung metastatic were inoculated with the caudal vein model. Mice were administered a high-fat diet. Upon the completion of the experiment, plasma triglycerides (TG), total plasma cholesterol (TC), plasma LDL-C, and plasma high-density lipoprotein cholesterol (HDL-C) were measured. ELISA was employed to measure PCSK9 and the low-density lipoprotein receptor (LDLR). The morphological alterations were observed using Oil-red O staining. Immunohistochemical labeling was used to determine the expression of PCSK9 and LDLR in mouse breast cancer (BC) tissues. MTT, wound healing assay, and the transwell migration and invasion test were conducted to examine co-cultured adipocytes' effects on the growth, invasion, and migration of BC cells. In the 4T1-luc cell model injected in situ into the breast pad and 4T1-luc cell model injected into the tail vein, we observed that a high-fat diet promoted the proliferation and lung metastasis of BC cells, whereas polydatin suppressed the proliferation and lung metastasis of BC cells. Co-culture of BC cells with adipocytes enhanced the proliferation, invasion, and metastasis, while polydatin intervention inhibited the growth, invasion, and metastasis. After treatment with polydatin, serum lipid levels decreased, PCSK9 decreased, LDLR increased, and LDL-C decreased in mouse BC, liver, and lung tissues. After polydatin treatment, PCSK9 decreased, LDLR increased, and LDL-C decreased in an in vitro co-culture system of BC cells and adipocytes. After transfection of siRNA PCSK9 in the co-culture system, the LDLR increased more significantly, and the LDL-C decreased more significantly. After transfection of LV-PCSK9, PCSK9 decreased, LDLR increased, and LDL-C decreased. We concluded that polydatin inhibited breast tumor proliferation and distant lung metastasis in mice promoted by a high lipid environment. By suppressing PCSK9, polydatin alters the lipid profile of hyperlipidemic TNBC mice and prevents distant metastases. Our findings provide credence to the established practice of using polydatin in treating TNBC combined with hyperlipidemia.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

lncRNA VIM-AS1 acts as a prognostic biomarker and promotes apoptosis in lung adenocarcinoma

Background: Long non-coding RNA VIM-antisense 1 (VIM-AS1) has been reported that it is involved in the progression of several cancers. However, the aberrant expression profile, clinical significance, and biological function of VIM-AS1in lung adenocarcinoma (LUAD) have not been fully described. We tend to perform a comprehensive analysis to identify the clinical prognostic value of VIM-AS1 for LUAD patients and explore its potential molecular mechanisms in LUAD development. Methods: The expression features of VIM-AS1 in LUAD were identified based on Cancer Genome Atlas database (TCGA) and genotypic tissue expression (GTEx). The LUAD patients' lung tissues were collected to testify above expression features. Survival analysis and COX regression analysis were performed to evaluate the prognostic value of VIM-AS1 in LUAD patients. Then Correlation analysis was performed to filter VIM-AS1 co-expression genes, and their molecular functions were constructed. Furtherly, we constructed the lung carcinoma A549 cell line with VIM-AS1 overexpression to test its effect on cell function. Results: VIM-AS1 expression levels were significantly downregulated in LUAD tissues. VIM-AS1 with low expression is significantly associated with short overall survival (OS), disease-specific survival (DSS), progress free interval (PFI), late T pathological stage, and lymph node metastasis for LUAD patients. The low expression level of VIM-AS1 was an independent risk factor for poor prognosis for LUAD patients. The biological functions of co-expressed genes indicated that VIM-AS1 regulating the apoptosis process may be the potential mechanism for LUAD. Specifically, we testified VIM-AS1 can promote apoptosis in A549 cells. Conclusion: VIM-AS1 was significantly downregulated in LUAD tissues, and it can be a promising prognostic index for LUAD development. VIM-AS1 regulating apoptotic effects may play important roles in LUAD progression.

Immune-Related Long Non-Coding RNA Signatures for Tongue Squamous Cell Carcinoma

BACKGROUND

Tongue squamous cell carcinoma (TSCC) represents one of the major subsets of head and neck cancer, which is characterized by unfavorable prognosis, frequent lymph node metastasis, and high mortality rate. The molecular events regulating tongue tumorigenesis remain elusive. In this study, we aimed to identify and evaluate immune-related long non-coding RNAs (lncRNAs) as prognostic biomarkers in TSCC.

METHODS

The lncRNA expression data for TSCC were obtained from The Cancer Genome Atlas (TCGA) and the immune-related genes were downloaded from the Immunology Database and Analysis Portal (ImmPort). Pearson correlation analysis was performed to identify immune-related lncRNAs. The TCGA TSCC patient cohort was randomly divided into training and testing cohorts. In the training cohort, univariate and multivariate Cox regression analyses were used to determining key immune-related lncRNAs, which were then validated through Cox regression analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) analysis in the testing cohort.

RESULTS

Six immune-related signature lncRNAs (MIR4713HG, AC104088.1, LINC00534, NAALADL2-AS2, AC083967.1, FNDC1-IT1) were found to have prognostic value in TSCC. Multivariate and univariate cox regression analyses showed that the risk score based on our six-lncRNA model, when compared to other clinicopathological factors (age, gender, stage, N, T), was an important indicator of survival rate. In addition, Kaplan-Meier survival analysis demonstrated significantly higher overall survival in the low-risk patient group than the high-risk patient group within both training and testing cohorts. The ROC analysis indicated that the AUCs for 5-year overall survival were 0.790, 0.691, and 0.721, respectively, for training, testing, and entire cohorts. Finally, PCA analysis demonstrated that the high-risk and low-risk patient groups presented significant deviation regarding their immune status.

CONCLUSIONS

A prognostic model based on six immune-related signature lncRNAs was established. This six-lncRNA prognostic model has clinical significance and may be helpful in the development of personalized immunotherapy strategies.

Role of Exosomes and Their Potential as Biomarkers in Epstein-Barr Virus-Associated Gastric Cancer

Exosomes are a subtype of extracellular vesicles ranging from 30 to 150 nm and comprising many cellular components, including DNA, RNA, proteins, and metabolites, encapsulated in a lipid bilayer. Exosomes are secreted by many cell types and play important roles in intercellular communication in cancer. Viruses can hijack the exosomal pathway to regulate viral propagation, cellular immunity, and the microenvironment. Cells infected with Epstein-Barr virus (EBV), one of the most common oncogenic viruses, have also been found to actively secrete exosomes, and studies on their roles in EBV-related malignancies are ongoing. In this review, we focus on the role of exosomes in EBV-associated gastric cancer and their clinical applicability in diagnosis and treatment.

Blood plasma derived extracellular vesicles (BEVs): particle purification liquid chromatography (PPLC) and proteomic analysis reveals BEVs as a potential minimally invasive tool for predicting response to breast cancer treatment

PURPOSE

Circulating blood plasma derived extracellular vesicles (BEVs) containing proteins hold promise for their use as minimally invasive biomarkers for predicting response to cancer therapy. The main goal of this study was to establish the efficiency and utility of the particle purification liquid chromatography (PPLC) BEV isolation method and evaluate the role of BEVs in predicting breast cancer (BC) patient response to neoadjuvant chemotherapy (NAC).

METHODS

PPLC isolation was used to separate BEVs from non-EV contaminants and characterize BEVs from 17 BC patients scheduled to receive NAC. Using LC-MS/MS, we compared the proteome of PPLC-isolated BEVs from patients (n = 7) that achieved a pathological complete response (pCR) after NAC (responders [R]) to patients (n = 10) who did not achieve pCR (non-responders [NR]). Luminal MCF7 and basaloid MDA-MB-231 BC cells were treated with isolated BEVs and evaluated for metabolic activity by MTT assay.

RESULTS

NR had elevated BEV concentrations and negative zeta potential (ζ-potential) prior to receipt of NAC. Eight proteins were enriched in BEVs of NR. GP1BA (CD42b), PECAM-1 (CD31), CAPN1, HSPB1 (HSP27), and ANXA5 were validated using western blot. MTT assay revealed BEVs from R and NR patients increased metabolic activity of MCF7 and MDA-MB-231 BC cells and the magnitude was highest in MCF7s treated with NR BEVs.

CONCLUSION

PPLC-based EV isolation provides a preanalytical separation process for BEVs devoid of most contaminants. Our findings suggest that PPLC-isolated BEVs and the five associated proteins may be established as predictors of chemoresistance, and thus serve to identify NR to spare them the toxic effects of NAC.

Extracellular vesicle isolation, purification and evaluation in cancer diagnosis

Strategies for non-invasive biomarker discovery in early detection of cancer are an urgent need. Extracellular vesicles (EVs) have generated increasing attention from the scientific community and are under intensive investigations due to their unique biological profiles and their non-invasive nature. EVs are membrane-enclosed vesicles with variable sizes and function. Such vesicles are actively secreted from multiple cell types and are considered as key vehicles for inter-cellular communications and signalling. The stability and potential to easily cross biological barriers enable EVs for exerting durable effects on target cells. These along with easy access to such vesicles, the consistent secretion from tumour during all stages of tumorigenesis and their content providing a reservoir of molecules as well as mirroring the identity of the cell of origin are virtues that have made EVs appealing to be assessed in liquid biopsy approaches and for using as a promising resource of biomarkers in cancer diagnosis and therapy and monitoring targeted cancer therapy. Early detection of EVs will guide time-scheduled personalised therapy. Surveying reliable and sensitive methods for rapid isolation of EVs from biofluids, the purity of isolated vesicles and their molecular profiling and marker specification for clinical translation in patients with cancer are issues in the area and the hot topics of many recent studies. Here, the focus is over methods for EV isolation and stratification for digging more information about liquid biopsy-based diagnosis. Extending knowledge regarding EV-based strategies is a key to validate independent patient follow-up for cancer diagnosis at early stages and inspecting the efficacy of therapeutics.