Erianin inhibits the progression of triple-negative breast cancer by suppressing SRC-mediated cholesterol metabolism.

Triple-negative breast cancer (TNBC) is highly malignant and lacks effective biotherapeutic targets. The development of efficient anticancer drugs with low toxicity and few side effects is a hotspot in TNBC treatment research. Although erianin is known to have potent antitumor activity, its regulatory mechanism and target in TNBC have not been fully elucidated, hampering further drug development. This study showed that erianin can significantly inhibit TNBC cell proliferation and migration, promote cell apoptosis, and inhibit the growth of transplanted tumors in mice. Mechanistically, through network pharmacology analysis, molecular docking and cellular thermal shift assays, we preliminarily identified SRC as the cellular target of erianin. Erianin potently inhibited the expression of SRC, which mediated the anticancer effect of erianin in TNBC. Moreover, erianin can downregulate the expression of genes related to cholesterol synthesis and uptake by targeting SRC, interfering with cholesterol levels in TNBC, thereby inhibiting the progression of TNBC in vivo and in vitro. Taken together, our results suggest that erianin may inhibit the progression of TNBC by suppressing SRC-mediated cholesterol metabolism, and erianin has the great potential to be an effective treatment for TNBC patients.

Identification of potential drug targets for allergic diseases from a genetic perspective: A mendelian randomization study.

BACKGROUND: Allergic diseases typically refer to a heterogeneous group of conditions primarily caused by the activation of mast cells or eosinophils, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma. Asthma, AR, and AD collectively affect approximately one-fifth of the global population, imposing a significant economic burden on society. Despite the availability of drugs to treat allergic diseases, they have been shown to be insufficient in controlling relapses and halting disease progression. Therefore, new drug targets are needed to prevent the onset of allergic diseases. METHOD: We employed a Mendelian randomization approach to identify potential drug targets for the treatment of allergic diseases. Leveraging 1798 genetic instruments for 1537 plasma proteins from the latest reported Genome-Wide Association Studies (GWAS), we analyzed the GWAS summary statistics of Ferreira MA et al. (nCase = 180,129, nControl = 180,709) using the Mendelian randomization method. Furthermore, we validated our findings in the GWAS data from the FinnGen and UK Biobank cohorts. Subsequently, we conducted sensitivity tests through reverse causal analysis, Bayesian colocalization analysis, and phenotype scanning. Additionally, we performed protein-protein interaction analysis to determine the interaction between causal proteins. Finally, based on the potential protein targets, we conducted molecular docking to identify potential drugs for the treatment of allergic diseases. RESULTS: At Bonferroni significance (p < 3.25 × 10-5), the Mendelian randomization analysis revealed 11 significantly associated protein-allergic disease pairs. Among these, the increased levels of TNFAIP3, ERBB3, TLR1, and IL1RL2 proteins were associated with a reduced risk of allergic diseases, with corresponding odds ratios of 0.82 (0.76-0.88), 0.74 (0.66-0.82), 0.49 (0.45-0.55), and 0.81 (0.75-0.87), respectively. Conversely, increased levels of IL6R, IL1R1, ITPKA, IL1RL1, KYNU, LAYN, and LRP11 proteins were linked to an elevated risk of allergic diseases, with corresponding odds ratios of 1.04 (1.03-1.05), 1.25 (1.18-1.34), 1.48 (1.25-1.75), 1.14 (1.11-1.18), 1.09 (1.05-1.12), 1.96 (1.56-2.47), and 1.05 (1.03-1.07), respectively. Bayesian colocalization analysis suggested that LAYN (coloc.abf-PPH4 = 0.819) and TNFAIP3 (coloc.abf-PPH4 = 0.930) share the same variant associated with allergic diseases. CONCLUSIONS: Our study demonstrates a causal association between the expression levels of TNFAIP3 and LAYN and the risk of allergic diseases, suggesting them as potential drug targets for these conditions, warranting further clinical investigation.

Mechanism of Erianin anti-triple negative breast cancer based on transcriptomics methods and network pharmacology.

Triple negative breast cancer (TNBC) is a highly aggressive illness that lacks effective targeted treatments. Although Erianin has shown potential antitumor properties, its precise mechanism of action and target in TNBC remain unclear, hampering the development of drugs. The present study investigated the underlying mechanism of action of Erianin in treating TNBC by using transcriptomics and network pharmacology approaches. We evaluated Erianin's bioactivity in TNBC cell lines and xenograft tumor models. The results showed that Erianin significantly inhibited TNBC cell proliferation and impeded tumor growth. A subsequent analysis of transcriptomic and network pharmacological data identified 51 mutual targets. Analysis of protein-protein interactions identified eight hub targets. Furthermore, molecular docking indicated that the PPARA binding energy was the lowest for Erianin among the hub targets, followed by ROCK2, PDGFRB, CCND1, MUC1, and CDK1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that the common targets were associated with multiple cancer-related signaling pathways, including focal adhesion, PI3K-Akt signaling pathway, Rap1 signaling pathway, microRNAs in cancer, and human papillomavirus infection. The results of the Western blot and immunohistochemistry experiment further showed that Erianin could suppress PI3K/Akt signaling pathway activation. After co-incubation with SC79, the cell inhibition rate of Erianin was decreased, which further confirmed that Erianin inhibits TNBC progression via the PI3K-AKT signaling pathway. In conclusion, our results indicated that Erianin has the potential to inhibit the proliferation of TNBC by downregulating the PI3K/AKT signaling pathway by transcriptomics and network pharmacology. Therefore, Erianin appears to be a promising compound for the effective treatment of TNBC.

Single-cell and bulk RNA-sequencing analysis to predict the role and clinical value of CD36 in lung squamous cell carcinoma.

The majority of patients with lung squamous cell carcinoma are diagnosed at an advanced stage, which poses a challenge to the efficacy of chemotherapy. Therefore, the search for an early biomarker needs to be addressed. CD36 is a scavenger receptor expressed in various cell types. It has been reported that it is closely related to the occurrence and development of many kinds of tumours. However, its role in lung squamous cell carcinoma has not been reported. Our research aims to reveal the role of CD36 in lung squamous cell carcinoma by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data. We used bioinformatics methods to explore the potential carcinogenicity of CD36 by analysing the data from the cancer genome map (TCGA), gene expression comprehensive map (GEO), human protein map (HPA) comparative toxicology genomics database (CTD) and other resources. Our study dissected the relationship between CD36 and prognosis and gene correlation, functional analysis, mutation of different tumours, infiltration of immune cells and exploring the interaction between CD36 and chemicals. The results showed that the expression of CD36 was heterogeneous. Compared with normal patients, the expression was low in lung squamous cell carcinoma. In addition, CD36 showed early diagnostic value in four kinds of tumours (LUSC, BLCA, BRCA and KIRC) and was positively or negatively correlated with the prognosis of different tumours. The relationship between CD36 and the tumour immune microenvironment was revealed by immunoinfiltration analysis, and many drugs that might target CD36 were identified by the comparative toxicological genomics database (CTD). In summary, through pancancer analysis, we found and verified for the first time that CD36 may play a role in the detection of lung squamous cell carcinoma. In addition, it has high specificity and sensitivity in detecting cancer. Therefore, CD36 can be used as an auxiliary index for early tumour diagnosis and a prognostic marker for lung squamous cell carcinoma.

AaABI5 transcription factor mediates light and abscisic acid signaling to promote anti-malarial drug artemisinin biosynthesis in Artemisia annua.

Artemisia annua, a member of the Asteraceae family, remains the primary source of artemisinin. However, the artemisinin content in the existing varieties of this plant is very low. In this study, we found that the environmental factors light and phytohormone abscisic acid (ABA) could synergistically promote the expression of artemisinin biosynthetic genes. Notably, the increased expression levels of those genes regulated by ABA depended on light. Gene expression analysis found that AaABI5, a transcription factor belonging to the basic leucine zipper (bZIP) family, was inducible by the light and ABA treatment. Analysis of AaABI5-overexpressing and -suppressing lines suggested that AaABI5 could enhance artemisinin biosynthesis and activate the expression of four core biosynthetic genes. In addition, the key regulator of light-induced artemisinin biosynthesis, AaHY5, could bind to the promoter of AaABI5 and activate its expression. In conclusion, our results demonstrated that AaABI5 acts as an important molecular junction for the synergistic promotion of artemisinin biosynthesis by light and ABA signals, which provides a candidate gene for developing new germplasms of high-quality A. annua.

Application of Novel Transcription Factor Machine Learning Model and Targeted Drug Combination Therapy Strategy in Triple Negative Breast Cancer.

Transcription factors (TFs) have been shown to play a key role in the occurrence and development of tumors, including triple-negative breast cancer (TNBC), with a worse prognosis. Machine learning is widely used for establishing prediction models and screening key tumor drivers. Current studies lack TF integration in TNBC, so targeted research on TF prognostic models and targeted drugs is beneficial to improve clinical translational application. The purpose of this study was to use the Least Absolute Shrinkage and Selection Operator to build a prognostic TFs model after cohort normalization based on housekeeping gene expression levels. Potential targeted drugs were then screened on the basis of molecular docking, and a multi-drug combination strategy was used for both in vivo and in vitro experimental studies. The machine learning model of TFs built by E2F8, FOXM1, and MYBL2 has broad applicability, with an AUC value of up to 0.877 at one year. As a high-risk clinical factor, its abnormal disorder may lead to upregulation of the activity of pathways related to cell proliferation. This model can also be used to predict the adverse effects of immunotherapy in patients with TNBC. Molecular docking was used to screen three drugs that target TFs: Trichostatin A (TSA), Doxorubicin (DOX), and Calcitriol. In vitro and in vivo experiments showed that TSA + DOX was able to effectively reduce DOX dosage, and TSA + DOX + Calcitriol may be able to effectively reduce the toxic side effects of DOX on the heart. In conclusion, the machine learning model based on three TFs provides new biomarkers for clinical and prognostic diagnosis of TNBC, and the combination targeted drug strategy offers a novel research perspective for TNBC treatment.

Bioactive components and molecular mechanisms of Salvia miltiorrhiza Bunge in promoting blood circulation to remove blood stasis.

ETHNOPHARMACOLOGICAL RELEVANCE: Salvia miltiorrhiza Bunge (SM) is an outstanding herbal medicine with various traditional effects, especially promoting blood circulation to remove blood stasis. It has been widely used for centuries to treat blood stasis syndrome (BSS)-related diseases. BSS is one of the basic pathological syndromes of diseases such as cardiovascular and cerebrovascular diseases in traditional East Asian medicine, which is characterized by disturbance of blood circulation. However, the bioactive components and mechanisms of SM in the treatment of BSS have not been systematically reviewed. Therefore, this article outlines the anti-BSS effects of bioactive components of SM, concentrating on the molecular mechanisms. AIM OF THE REVIEW: To summarize the bioactive components of SM against BSS and highlight its potential targets and signaling pathways, hoping to provide a modern biomedical perspective to understand the efficacy of SM on enhancing blood circulation to remove blood stasis. MATERIALS AND METHODS: A comprehensive literature search was performed to retrieve articles published in the last two decades on bioactive components of SM used for BSS treatment from the online electronic medical literature database (PubMed). RESULTS: Phenolic acids and tanshinones in SM are the main bioactive components in the treatment of BSS, including but not limited to salvianolic acid B, tanshinone IIA, salvianolic acid A, cryptotanshinone, Danshensu, dihydrotanshinone, rosmarinic acid, protocatechuic aldehyde, and caffeic acid. They protect vascular endothelial cells by alleviating oxidative stress and inflammatory damage and regulating of NO/ET-1 levels. They also enhance anticoagulant and fibrinolytic capacity, inhibit platelet activation and aggregation, and dilate blood vessels. Moreover, lowering blood lipids and improving blood rheological properties may be the underlying mechanisms of their anti-BSS. More notably, these compounds play an anti-BSS role by mediating multiple signaling pathways such as Nrf2/HO-1, TLR4/MyD88/NF-κB, PI3K/Akt/eNOS, MAPKs (p38, ERK, and JNK), and Ca2+/K+ channels. CONCLUSIONS: Both phenolic acids and tanshinones in SM may act synergistically to target different signaling pathways to achieve the effect of promoting blood circulation.

Comprehensive analysis of OpHD-ZIP transcription factors related to the regulation of camptothecin biosynthesis in Ophiorrhiza pumila.

Ophiorrhiza pumila, as a folk herb belonging to the Rubiaceae family, has become a potential source of camptothecin (CPT), which is a monoterpenoid indole alkaloid with good antitumor property. However, the camptothecin content in this herb is low, and is far from meeting the increasing clinical demand. Understanding the transcriptional regulation of camptothecin biosynthesis provides an effective strategy for improvement of camptothecin yield. Previous studies have demonstrated several transcription factors that are related to camptothecin biosynthesis, while the functions of HD-ZIP members in O. pumila have not been investigated yet. In this study, 32 OpHD-ZIP transcription factor members were genome-wide identified. Phylogenetic tree showed that these OpHD-ZIP proteins are divided into four subfamilies. Based on the transcriptome data, nine OpHD-ZIP genes were shown to be predominantly expressed in O. pumila roots, which were in line with the camptothecin biosynthetic genes. Co-expression analysis showed that OpHD-ZIP7 and OpHD-ZIP20 were potentially related to the modulation of camptothecin biosynthesis. Dual-luciferase reporter assays (Dual-LUC) showed that both OpHD-ZIP7 and OpHD-ZIP20 could activate the expression of camptothecin biosynthetic genes OpIO and OpTDC. In conclusion, this study offered the promising data for exploring the roles of OpHD-ZIP transcription factors in regulating camptothecin biosynthesis.

Application value of circulating LncRNA in diagnosis, treatment, and prognosis of breast cancer.

Breast cancer is the malignant tumor with the highest incidence in women worldwide. It is highly heterogeneous, has a high incidence of drug resistance, recurrence, and metastasis, and is one of the malignant tumors with the highest mortality rate. The early diagnosis, treatment monitoring, and prognosis assessment of breast cancer are the key factors affecting the survival of patients. However, due to the lack of specific biomarkers, breast cancer is still an essential factor affecting women's quality of life and physical and mental health. Long non-coding RNA can regulate various genes and different signaling pathways and plays an essential role in the occurrence and development of tumors. Recent studies have found that the abnormal expression of circulating long non-coding RNA in serum, saliva, and other biological body fluids plays a significant role in early diagnosis, pathological classification, stage, therapeutic effect monitoring, and prognosis evaluation of breast cancer. This article will review the potential application value of circulating lncRNA in breast cancer.

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most widely distributed tumor in the world, and its immunotherapy is not practical. Neutrophil is one of a tumor's most abundant immune cell groups. This research aimed to investigate the complex communication network in the immune microenvironment (TIME) of NSCLC tumors to clarify the interaction between immune cells and tumors and establish a prognostic risk model that can predict immune response and prognosis of patients by analyzing the characteristics of Neutrophil differentiation. Integrated Single-cell RNA sequencing (scRNA-seq) data from NSCLC samples and Bulk RNA-seq were used for analysis. Twenty-eight main cell clusters were identified, and their interactions were clarified. Next, four subsets of Neutrophils with different differentiation states were found, closely related to immune regulation and metabolic pathways. Based on the ratio of four housekeeping genes (ACTB, GAPDH, TFRC, TUBB), six Neutrophil differentiation-related genes (NDRGs) prognostic risk models, including MS4A7, CXCR2, CSRNP1, RETN, CD177, and LUCAT1, were constructed by Elastic Net and Multivariate Cox regression, and patients' total survival time and immunotherapy response were successfully predicted and validated in three large cohorts. Finally, the causes of the unfavorable prognosis of NSCLC caused by six prognostic genes were explored, and the small molecular compounds targeted at the anti-tumor effect of prognostic genes were screened. This study clarifies the TIME regulation network in NSCLC and emphasizes the critical role of NDRGs in predicting the prognosis of patients with NSCLC and their potential response to immunotherapy, thus providing a promising therapeutic target for NSCLC.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment.

OBJECTIVES: The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear. METHODS: Consensus clustering was applied to identify novel subgroups. ESTIMATE, TIMER, and MCPcounter algorithms were used to determine the TIME of the subgroups. The underlying mechanisms were elucidated using functional analysis. The prognostic model was established using the LASSO algorithm and multivariate Cox regression analysis. RESULTS: Three molecular subgroups with significantly different survival were identified. The subgroup with relatively low lipid metabolic expression had a lower immune score and immune cells. The differentially expressed genes (DEGs) were concentrated in immune biological processes and cell migration via GO and KEGG analyses. GSEA analysis showed that the subgroups were mainly enriched in arachidonic acid metabolism. Gastric cancer survival can be predicted using risk models based on lipid metabolism genes. CONCLUSIONS: The TIME of gastric cancer patients is related to the expression of lipid metabolism genes and could be used to predict cancer prognosis accurately.

The Value of the Stemness Index in Ovarian Cancer Prognosis.

Ovarian cancer (OC) is one of the most common gynecological malignancies. It is associated with a difficult diagnosis and poor prognosis. Our study aimed to analyze tumor stemness to determine the prognosis feature of patients with OC. At this job, we selected the gene expression and the clinical profiles of patients with OC in the TCGA database. We calculated the stemness index of each patient using the one-class logistic regression (OCLR) algorithm and performed correlation analysis with immune infiltration. We used consensus clustering methods to classify OC patients into different stemness subtypes and compared the differences in immune infiltration between them. Finally, we established a prognostic signature by Cox and LASSO regression analysis. We found a significant negative correlation between a high stemness index and immune score. Pathway analysis indicated that the differentially expressed genes (DEGs) from the low- and high-mRNAsi groups were enriched in multiple functions and pathways, such as protein digestion and absorption, the PI3K-Akt signaling pathway, and the TGF-ß signaling pathway. By consensus cluster analysis, patients with OC were split into two stemness subtypes, with subtype II having a better prognosis and higher immune infiltration. Furthermore, we identified 11 key genes to construct the prognostic signature for patients with OC. Among these genes, the expression levels of nine, including SFRP2, MFAP4, CCDC80, COL16A1, DUSP1, VSTM2L, TGFBI, PXDN, and GAS1, were increased in the high-risk group. The analysis of the KM and ROC curves indicated that this prognostic signature had a great survival prediction ability and could independently predict the prognosis for patients with OC. We established a stemness index-related risk prognostic module for OC, which has prognostic-independent capabilities and is expected to improve the diagnosis and treatment of patients with OC.

Clinical significance and mechanism of long noncoding RNA HAGLROS in triple negative breast cancer.

PURPOSE: Triple Negative Breast Cancer (TNBC) is the malignant tumor with the fastest progression rate in breast cancer. LncRNAs are widely involved in various biological characteristics of tumor. The purpose of this study was to mine LncRNAs that can be used to diagnose and evaluate the prognosis of TNBC. METHODS: Base on TCGA dataset, we used three R language packages to analyze the differentially expressed (DE) lncRNAs in TNBC. Survival analysis and ROC curve analysis were conducted to estimate the potential diagnostic and prognostic value of LncRNAs for TNBC. Furthermore, CCK-8 and Transwell assays were used to assess the effects of LncRNA on MDA-MB-231 cells proliferation and migration. Additionally, targets mRNAs of candidate LncRNA were predicted by co-expression analysis and multiple target gene prediction databases, then KEGG pathway and GO analysis were conducted using DAVID online tool. RESULTS: 6165 DERNAs and 1258 DElncRNAs were obtained. 40 LncRNAs were significantly correlated with the survival time of TNBC patients. Among them, HAGLROS has the highest HR value. ROC curve analysis also showed that HAGLROS had high sensitivity and specificity. Further in vitro experiments showed that downregulation of HAGLROS inhibited the proliferation and migration of MDA-MB-231 cells. Moreover, by conducting bioinformatics analysis, we found that these target genes of HAGLROS were involved in regulating five signaling pathways. Mechanistic investigations demonstrated that HAGLROS might regulate the expression of PAX5 through miR-330-5p, the effects of miR-330-5p in MDA-MB-231 cells were also analyzed. CONCLUSION: Our results showed that HAGLROS was significantly overexpressed in TNBC, and high HAGLROS expression predicted poor overall survival. Downregulation of HAGLROS could inhibite the proliferation and migration of MDA-MB-231 cell by regulating PAX5 expression through miR-330-5p.

ln RNA LINC01234 promotes triple-negative breast cancer progression through regulating the miR-429/SYNJ1 axis.

Emerging evidence has illustrated that long noncoding RNA 01234 (LINC01234) has played a pivotal role in the development and progression of human cancer. The regulatory role and underlying mechanisms of LINC01234 in triple-negative breast cancer (TNBC) remains unknown. In this study, we analyzed the expression level of LINC01234 in several breast cancer cell lines. CCK-8, EdU, flow cytometry analysis, wound healing assay, and transwell assay were carried out to investigate the effect of LINC01234 on tumor proliferation, apoptosis, and migration. Bioinformatic analysis and luciferase reporter assays were performed to confirm the molecular binding. We found that LINC01234 was dramatically upregulated in breast cancer cell lines, especially in TNBC. The loss and gain-of functional experiments revealed that LINC01234 significantly promoted proliferation, migration, and suppressed cell apoptosis of MDA-MB-231 cells in vitro and inhibited tumorigenesis in vivo. Mechanistic investigations demonstrated that LINC01234 might act as a competing endogenous RNA (ceRNA) for miR-429 to regulate the SYNJ1 expression. The effects of miR-429 and SYNJ1 in MDA-MB-231 cells were also analyzed. Our results revealed that the novel LINC01234/miR-429/SYNJ1 axis played a critical role in progression of TNBC cell line MDA-MB-231, and it may serve as a therapeutic target for TNBC.

Nitrile Hydratases: From Industrial Application to Acetamiprid and Thiacloprid Degradation.

The widespread application of neonicotinoid insecticides (NEOs) in agriculture causes a series of environmental and ecological problems. Microbial remediation is a popular approach to relieve these negative impacts, but the associated molecular mechanisms are rarely explored. Nitrile hydratase (NHase), an enzyme commonly used in industry for amide production, was discovered to be responsible for the degradation of acetamiprid (ACE) and thiacloprid (THI) by microbes. Since then, research into NHases in NEO degradation has attracted increasing attention. In this review, microbial degradation of ACE and THI is briefly described. We then focus on NHase evolution, gene composition, maturation mechanisms, expression, and biochemical properties with regard to application of NHases in NEO degradation for bioremediation.

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan-Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

Potential of RASSF1A promoter methylation as a biomarker for colorectal cancer: Meta-analysis and TCGA analysis.

The RAS association domain family protein 1A (RASSF1A) is a tumor suppressor in colorectal cancer (CRC), and is often inactived by hypermethylation. Therefore, we evaluated the association between RASSF1A hypermethylation and the risk and prognosis in CRC. We identified literature through searching PubMed and China National Knowledge Infrastructure databases, and then validated and supplemented the meta-analysis with TCGA analysis. Twenty-three studies involving 2886 subjects of CRC were examined. The meta-analysis showed that RASSF1A promoter methylation inferred high CRC risk (odds ratio, 6.53, 95% confidence interval 3.88-11.01, P < .001) and poor overall survival (hazard ratio 2.85, 95% CI 1.88-4.31, P < .001). The TCGA analysis suggested that effect of RASSF1A promotor methylation was affected by tumor localization (colon vs. rectum). RASSF1A promoter methylation was a predictor of high risk (OR 2.38, 95%CI 1.02-5.6, P = .046) and poor disease free survival(HR 2.25, 95%CI 1.27-3.99, P = .006)in colon adenocarcinoma, but the association was statistically insignificant in rectum adenocarcinoma(HR 1.58, 95% CI 0.69-3.59, P = .28). These results suggested RASSF1A hypermethylation is a risk and a potential prognostic biomarker in CRC.

Application of circulating tumor DNA in breast cancer.

Precision medicine has been well recognized since it was proposed, and the invention of liquid biopsy meets the needs of this era. Circulating tumor DNA (ctDNA), one of the most promising components of liquid biopsies, has quickly become the focus of research in recent years because of its unique advantages in clinical application. This article reviews the clinical application of ctDNA in breast cancer detection in recent years and its potential clinical value.

miR-148b-3p, miR-190b, and miR-429 Regulate Cell Progression and Act as Potential Biomarkers for Breast Cancer.

PURPOSE: Breast cancer is the most frequently diagnosed malignancy in women worldwide. MicroRNAs (miRNAs) are thought to serve as potential biomarkers in various cancers, including breast cancer. METHODS: We evaluated the miRNA expression profiles in 1,083 breast cancer samples and 104 normal breast tissues from The Cancer Genome Atlas database. We used the edgeR package of R software to analyze the differentially expressed miRNAs in normal and cancer tissues, and screened survival-related miRNAs by Kaplan-Meier analysis. A receiver operating characteristic curve was generated to evaluate the accuracy of these miRNAs as molecular markers for breast cancer diagnosis. Furthermore, the functional role of these miRNAs was verified using cell experiments. Targets of candidate miRNAs were predicted using 9 online databases, and Gene Ontology (GO) functional annotation and pathway analyses were conducted using Database for Annotation, Visualization and Integrated Discovery online tool. RESULTS: A total of 68 miRNAs showed significantly different expression patterns between the groups (p < 0.001), and 13 of these miRNAs were significantly associated with poor survival (p < 0.05). Three miRNAs with high specificity and sensitivity, namely, miR-148b-3p, miR-190b, and miR-429, were selected. In vitro experiments showed that the overexpression of these 3 miRNAs significantly promoted the proliferation and migration of MDA-MB-468 and T47D cells and reduced the apoptosis of T47D cells. GO and pathway enrichment analyses revealed that the targets of these dysregulated miRNAs were involved in many critical cancer-related biological processes and pathways. CONCLUSION: The miR-148b-3p, miR-190b, and miR-429 may serve as potential diagnostic and prognostic markers for breast cancer. This study demonstrated the roles of these 3 miRNAs in the initiation and progression of breast cancer.

Cucurbitacin B inhibits tumor angiogenesis by triggering the mitochondrial signaling pathway in endothelial cells.

Cucurbitacin B (CuB), the active component of a traditional Chinese herbal medicine, Pedicellus Melo, has been shown to exhibit antitumor and anti-inflammation effects, but its role in tumor angiogenesis, the key step involved in tumor growth and metastasis, and the involved molecular mechanism are unknown. Tumor angiogenesis is one of the hallmarks of the development in malignant neoplasias and metastasis. Effective targeting of tumor angiogenesis is a key area of interest for cancer therapy. Here, we demonstrated that CuB significantly inhibited human umbilical vascular endothelial cell (HUVEC) proliferation, migration, tubulogenesis in vitro, and blocked angiogenesis in chick embryo chorioallantoic membrane (CAM) assay in vivo. Furthermore, CuB induced HUVEC apoptosis and may induce apoptosis by triggering the mitochondrial apoptotic pathway. Finally, we found that CuB inhibiting angiogenesis was associated with inhibition of the activity of vascular endothelial growth factor receptor 2 (VEGFR2). Our investigations suggested that CuB was a potential drug candidate for angiogenesis related diseases.