Interactions between hedgehog signaling pathway and the complex tumor microenvironment in breast cancer: current knowledge and therapeutic promises.

Breast cancer ranks as one of the most common malignancies among women, with its prognosis and therapeutic efficacy heavily influenced by factors associated with the tumor cell biology, particularly the tumor microenvironment (TME). The diverse elements of the TME are engaged in dynamic bidirectional signaling interactions with various pathways, which together dictate the growth, invasiveness, and metastatic potential of breast cancer. The Hedgehog (Hh) signaling pathway, first identified in Drosophila, has been established as playing a critical role in human development and disease. Notably, the dysregulation of the Hh pathway is recognized as a major driver in the initiation, progression, and metastasis of breast cancer. Consequently, elucidating the mechanisms by which the Hh pathway interacts with the distinct components of the breast cancer TME is essential for comprehensively evaluating the link between Hh pathway activation and breast cancer risk. This understanding is also imperative for devising novel targeted therapeutic strategies and preventive measures against breast cancer. In this review, we delineate the current understanding of the impact of Hh pathway perturbations on the breast cancer TME, including the intricate and complex network of intersecting signaling cascades. Additionally, we focus on the therapeutic promise and clinical challenges of Hh pathway inhibitors that target the TME, providing insights into their potential clinical utility and the obstacles that must be overcome to harness their full therapeutic potential.

Epigallocatechin-3-gallate at the nanoscale: a new strategy for cancer treatment.

CONTEXT: Epigallocatechin-3-gallate (EGCG), the predominant catechin in green tea, has shown the potential to combat various types of cancer cells through its ability to modulate multiple signaling pathways. However, its low bioavailability and rapid degradation hinder its clinical application. OBJECTIVE: This review explores the potential of nanoencapsulation to enhance the stability, bioavailability, and therapeutic efficacy of EGCG in cancer treatment. METHODS: We searched the PubMed database from 2019 to the present, using 'epigallocatechin gallate', 'EGCG', and 'nanoparticles' as search terms to identify pertinent literature. This review examines recent nano-engineering technology advancements that encapsulate EGCG within various nanocarriers. The focus was on evaluating the types of nanoparticles used, their synthesis methods, and the technologies applied to optimize drug delivery, diagnostic capabilities, and therapeutic outcomes. RESULTS: Nanoparticles improve the physicochemical stability and pharmacokinetics of EGCG, leading to enhanced therapeutic outcomes in cancer treatment. Nanoencapsulation allows for targeted drug delivery, controlled release, enhanced cellular uptake, and reduced premature degradation of EGCG. The studies highlighted include those where EGCG-loaded nanoparticles significantly inhibited tumor growth in various models, demonstrating enhanced penetration and efficacy through active targeting mechanisms. CONCLUSIONS: Nanoencapsulation of EGCG represents a promising approach in oncology, offering multiple therapeutic benefits over its unencapsulated form. Although the results so far are promising, further research is necessary to fully optimize the design of these nanosystems to ensure their safety, efficacy, and clinical viability.

Crosstalk and plasticity driving between cancer-associated fibroblasts and tumor microenvironment: significance of breast cancer metastasis.

Cancer-associated fibroblasts (CAFs) are the most abundant stromal cell population in breast tumors. A functionally diverse population of CAFs increases the dynamic complexity of the tumor microenvironment (TME). The intertwined network of the TME facilitates the interaction between activated CAFs and breast cancer cells, which can lead to the proliferation and invasion of breast cells. Considering the special transmission function of CAFs, the aim of this review is to summarize and highlight the crosstalk between CAFs and breast cancer cells in the TME as well as the relationship between CAFs and extracellular matrix (ECM), soluble cytokines, and other stromal cells in the metastatic state. The crosstalk between cancer-associated fibroblasts and tumor microenvironment also provides a plastic therapeutic target for breast cancer metastasis. In the course of the study, the inhibitory effects of different natural compounds on targeting CAFs and the advantages of different drug combinations were summarized. CAFs are also widely used in the diagnosis and treatment of breast cancer. The cumulative research on this phenomenon supports the establishment of a targeted immune microenvironment as a possible breakthrough in the prevention of invasive metastasis of breast cancer.

Plant-derived nanoparticles and plant virus nanoparticles: Bioactivity, health management, and delivery potential.

Natural plants have acquired an increasing attention in biomedical research. Recent studies have revealed that plant-derived nanoparticles (PDNPs), which are nano-sized membrane vesicles released by plants, are one of the important material bases for the health promotion of natural plants. A great deal of research in this field has focused on nanoparticles derived from fresh vegetables and fruits. Generally, PDNPs contain lipids, proteins, nucleic acids, and other active small molecules and exhibit unique biological regulatory activity and editability. Specifically, they have emerged as important mediators of intercellular communication, and thus, are potentially suitable for therapeutic purposes. In this review, PDNPs were extensively explored; by evaluating them systematically starting from the origin and isolation, toward their characteristics, including morphological compositions, biological functions, and delivery potentials, as well as distinguishing them from plant-derived exosomes and highlighting the limitations of the current research. Meanwhile, we elucidated the variations in PDNPs infected by pathogenic microorganisms and emphasized on the biological functions and characteristics of plant virus nanoparticles. After clarifying these problems, it is beneficial to further research on PDNPs in the future and develop their clinical application value.

Flavonoids regulate tumor-associated macrophages - From structure-activity relationship to clinical potential (Review).

In recent years, the strategy for tumor therapy has changed from focusing on the direct killing effect of different types of therapeutic agents on cancer cells to the new mainstream of multi-mode and -pathway combined interventions in the microenvironment of the developing tumor. Flavonoids, with unique tricyclic structures, have diverse and extensive immunomodulatory and anti-cancer activities in the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are the most abundant immunosuppressive cells in the TME. The regulation of macrophages to fight cancer is a promising immunotherapeutic strategy. This study covers the most comprehensive cognition of flavonoids in regulating TAMs so far. Far more than a simple list of studies, we try to dig out evidence of crosstalk at the molecular level between flavonoids and TAMs from literature, in order to discuss the most relevant chemical structure and its possible relationship with the multimodal pharmacological activity, as well as systematically build a structure-activity relationship between flavonoids and TAMs. Additionally, we point out the advantages of the macro-control of flavonoids in the TME and discuss the potential clinical implications as well as areas for future research of flavonoids in regulating TAMs. These results will provide hopeful directions for the research of antitumor drugs, while providing new ideas for the pharmaceutical industry to develop more effective forms of flavonoids.

Analysis of the expression patterns and clinical relevance of m6A regulators in 33 cancer types.

Background: The role of N6-methyladenine (m6A) RNA methylation in a variety of biological processes is gradually being revealed. Methods: Here, we systematically describe the correlation between the expression pattern of m6A RNA methylation regulatory factors and clinical phenotype, immunity, drug sensitivity, stem cells and prognosis in more than 10,000 samples of 33 types of cancer. Results: The results show that there are significant differences in the expression of 20 m6A RNA methylation regulatory factors in different cancers, and there was a significant correlation with the analysis indicators. Conclusion: In this study, the m6A RNA methylation regulatory factor was found not only to potentially assist in stratifying the prognosis but also to predict or improve the sensitivity of clinical drug therapy.

Construction of a survival prediction model for high-and low -grade UTUC after tumor resection based on "SEER database": a multicenter study.

BACKGROUND: There are differences in survival between high-and low-grade Upper Tract Urothelial Carcinoma (UTUC). Our study aimed to develop a nomogram to predict overall survival (OS) of patients with high- and low-grade UTUC after tumor resection, and to explore the difference between high- and low-grade patients. METHODS: Patients confirmed to have UTUC between 2004 and 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. The UTUCs were identified and classified as high- and low-grade, and 1-, 3- and 5-year nomograms were established. The nomogram was then validated using the Chinese multicenter dataset (patients diagnosed in Shandong, China between January 2010 and October 2020). RESULTS: In the high-grade UTUC patients, nine important factors related to survival after tumor resection were identified to construct nomogram. The C index of training dataset was 0.740 (95% confidence interval [CI]: 0.727-0.754), showing good calibration. The C index of internal validation dataset was 0.729(95% CI:0.707-0.750). On the other hand, Two independent predictors were identified to construct nomogram of low-grade UTUC. The C index was 0.714 (95% CI: 0.671-0.758) for the training set,0.731(95% CI:0.670-0.791) for the internal validation dataset. Encouragingly, the nomogram was clinically useful and had a good discriminative ability to identify patients at high risk. CONCLUSION: We constructed a nomogram and a corresponding risk classification system predicting the OS of patients with an initial diagnosis of high-and low-grade UTUC.

Research progress of phenolic compounds regulating IL-6 to exert antitumor effects.

Cytokine therapy, which activates the host immune system, has become an important and novel therapeutic approach to treat various cancers. Recent studies have shown that IL-6 is an important cytokine that regulates the homeostasis in vivo. However, excessive IL-6 plays a pathological role in a variety of acute and chronic inflammatory diseases, especially in cancer. IL-6 can transmit signals through JAK/STAT, RAS /MAPK, PI3K/ Akt, NF-κB, and other pathways to promote cancer progression. Phenolic compounds can effectively regulate the level of IL-6 in tumor cells and improve the tumor microenvironment. This article focuses on the phenolic compounds through the regulation of IL-6, participate in the prevention of cancer, inhibit the proliferation of cancer cells, reduce angiogenesis, improve therapeutic efficacy, and reduce side effects and other aspects. This will help to further advance research on cytokine therapy to reduce the burden of cancer and improve patient prognosis. However, current studies are mostly limited to animal and cellular experiments, and high-quality clinical studies are needed to further determine their antitumor efficacy in humans.

circRNA-associated ceRNA network construction reveals the circRNAs involved in the progression and prognosis of breast cancer.

Recently, increasing evidences show that circular RNAs (circRNAs) are important regulators of various diseases, especially cancer. However, the regulatory role and the potential mechanism of action of circRNAs in breast cancer remain largely unknown. In this study, weighted gene co-expression network analysis was conducted with the differentially expressed miRNAs and mRNAs in breast cancer from The Cancer Genome Atlas database to identify the key modules associated with the carcinogenesis of breast cancer. In the significant turquoise and brown modules, 22 miRNAs and 1877 mRNAs were identified, respectively. Then, We compared and predicted the target genes and performed survival analysis to identify the miRNAs and mRNAs related to the prognosis of breast cancer. A circRNA-related competitive endogenous RNA network was identified by database co-screening, and deleted in liver cancer 1 (DLC1) was identified as a key gene. Finally, to assess how genes in key modules and key genes contribute to the development of breast cancer, relevant pathway information was obtained through DAVID and Gene Set Enrichment Analysis. These data demonstrated that three circRNAs (hsa-circ-0083373, hsa-circ-0083374, and hsa-circ-0083375) that regulate DLC1 expression via hsa-mir-511 and are involved in the pathogenesis and development of breast cancer.

Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer.

The relationship between age and breast cancer is ambiguous. Here, we analyzed the differential expression pattern of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in different age groups to provide an effective association between age and breast cancer risk at the molecular level. We integrated the microarray information from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. The patients were divided into young ( < 50 years) and old ( ≥ 50 years) age groups and evaluated by differential gene expression, weighted gene correlation network analysis (WGCNA), functional enrichment analyses, and coexpression analysis. To determine their potential clinical significance, univariate Cox regression analysis and survival assessment were conducted. We identified two lncRNAs (AL139280.1 and AP000851.1) and three mRNAs (MT1M, HBB, and TFPI2) as the risk markers, and Gene set enrichment analysis (GSEA) focusing on a single gene revealed that "pyrimidine metabolism," "cell cycle," and "P53 signaling pathway" were coenriched. These data demonstrated that age may be a risk factor for breast carcinogenesis and prognosis and provide an in-depth molecular characterization based on the expression patterns of lncRNAs and mRNAs.

Development of a risk scoring system for evaluating the prognosis of patients with Her2-positive breast cancer.

BACKGROUND: As one of the many breast cancer subtypes, human epidermal growth factor receptor 2 (Her2)-positive breast cancer has higher invasiveness and poor prognosis, although the advent of anti-Her2 drugs has brought good news to patients. However, the emergence of drug resistance still limits its clinical efficacy, so there is an urgent need to explore new targets and develop a risk scoring system to improve treatments and evaluate patient prognosis. METHODS: Differentially expressed mRNAs associated with Her2-positive breast cancer were screened from a TCGA cohort. The prognostic risk scoring system was constructed according to univariate and Lasso Cox regression model analyses and combined with clinical factors (such as age and TNM) for univariate and multivariate analyses to verify the specificity and sensitivity of the risk scoring system. Finally, based on correlation and CNV mutation analyses, we explored the research value of the mRNAs involved in the system as key genes of the model. RESULTS: In this study, six mRNAs were screened and identified to construct a prognostic risk scoring system, including four up-regulated mRNA (RDH16, SPC25, SPC24, and SCUBE3) and two down-regulated mRNA (DGAT2 and CCDC69). The risk scoring system can divide Her2-positive breast cancer samples into high-risk and low-risk groups to evaluate patient prognosis. In addition, whether through the time-dependent receiver operating characteristics curve or compared with clinical factors, the risk scoring system showed high predictive sensitivity and specificity. Moreover, some CNV mutations in mRNA increase patient risk by influencing expression levels. CONCLUSION: The risk scoring system constructed in this study is helpful to improve the screening of high-risk patients with Her2-positive breast cancer and is beneficial for implementing early diagnosis and personalized treatment. It is suggested that these mRNAs may play an important role in the progression of Her2-positive breast cancer.

Cardiotoxicity of doxorubicin-based cancer treatment: What is the protective cognition that phytochemicals provide us?

Doxorubicin (DOX) continues to attract the interest of preclinical and clinical investigations despite its longer-than-50-year record of longevity. The clinical application of DOX can be regarded as a sort of double-edged sword. On one hand, anthracyclines play an indisputable key role in the treatment of tumors; on the other hand, their chronic administration leads to cardiomyopathy and congestive heart failure, which is usually refractory to common medications. Finding the ideal cardioprotective agents has always been the focus of oncologists and cardiologists. Researchers put a lot of energy into phytochemicals because they are often in line with the expected standards, that is, to improve DOX-induced cardiotoxicity without compromising the clinical efficacy or to even produce synergy. We summarized the previous efforts, briefly outlined the mechanism of DOX cardiotoxicity, and focused on exploring the protective effects and potential mechanisms of all phytochemical types that have been investigated under DOX-induced cardiotoxicity. Phytochemicals have been found to be potential cardioprotective agents with universal safety and effectiveness. As a resource repository of pharmacophores, phytochemicals deserve to be utilized as drug templates for further development and research in combating DOX-induced cardiotoxicity.

Integrated analysis of co-expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer.

Long non-coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co-expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan-Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co-expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2-AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.

Efficacy and acceptability of neoadjuvant endocrine therapy in patients with hormone receptor-positive breast cancer: A network meta-analysis.

BACKGROUND: The optimal sequence of endocrine therapy in a neoadjuvant setting for hormone receptor-positive (HR+) breast cancer is unclear. Our study evaluated the efficacy and acceptability of neoadjuvant endocrine therapy for HR+ breast cancer. METHODS: We identified studies based on titles and abstracts that were published before 22 June 2018 in the following databases: PubMed, EMBASE, and the Cochrane Library. Eligible studies were randomised controlled trials with at least one arm that evaluated the effectiveness of one or a combination of anastrozole, letrozole, palbociclib, tamoxifen, fulvestrant, abemaciclib, everolimus, gefitinib, ribociclib, taselisib, and exemestane. We pooled effect sizes using the odds ratio (OR) and corresponding 95% credibility interval (95% CrI). The primary outcomes were response rate and treatment completion. RESULTS: Our network meta-analysis included 3,306 participants and 16 eligible studies, which assessed 15 treatments. In terms of response rates, compared with letrozole combined therapy, tamoxifen was associated with a significant reduction in response rate (OR, 0.34; 95% CrI, 0.13-0.85; OR, 0.32; 95% CrI, 0.13-0.80; OR, 0.26; 95% CrI, 0.09-0.83; and OR, 0.30; 95% CrI, 0.09-0.96; for letrozole plus everolimus, letrozole plus taselisib, letrozole plus zoledronic acid, and letrozole plus lapatinib, respectively). Based on the surface under the cumulative ranking curves ranking, letrozole plus zoledronic acid was associated with the highest rate of response (87.6%), followed by letrozole plus lapatinib (85.2%), and letrozole plus taselisib (79.3%). CONCLUSIONS: Ultimately, our study established that letrozole plus zoledronic acid may be an optimal treatment based on its current rank in a neoadjuvant setting for HR+ breast cancer.

Prognostic value of aberrantly expressed methylation gene profiles in lung squamous cell carcinoma: A study based on The Cancer Genome Atlas.

Currently, research on genome-scale epigenetic modifications for studying the pathogenesis of lung cancer is lacking. Aberrant DNA methylation, as the most common and important modification in epigenetics, is an important means of regulating genomic function and can be used as a biomarker for the diagnosis and prognosis of lung squamous cell carcinoma (LUSC). In this paper, methylation information and gene expression data from patients with LUSC were extracted from the TCGA database. Univariate and multivariate COX analyses were used to screen abnormally methylated genes related to the prognosis of LUSC. The relationship between key DNA methylation sites and the transcriptional expression of LUSC-related genes was explored. A prognostic risk model constructed by four abnormally methylated genes (VAX1, CH25H, AdCyAP1, and Irx1) was used to predict the prognosis of LUSC patients. Also, the methylation levels of the key gene IRX1 are significantly correlated with the prognosis and correlated with the methylation of the site cg09232937 and cg10530883. This study is based on high-throughput data mining and provides an effective bioinformatics basis for further understanding the pathogenesis and prognosis of LUSC, which has important theoretical significance for follow-up studies on LUSC.

Four lncRNAs associated with breast cancer prognosis identified by coexpression network analysis.

Previous studies on long noncoding RNA (lncRNA) have made breakthroughs in the treatment of several tumors, and these findings have brought attention to the lncRNA signature of breast cancer. Increased understanding of genomic architecture and achievement of innovative therapeutic strategies has prompted creation of a novel oncological model for the treatment of solid cancers. In this study, we systematically analyzed the transcriptome of breast cancer tissues to gain more in-depth knowledge of tumor biology. Gene coexpression relationships were studied in 206 samples from The Cancer Genome Atlas database, and nine coexpression modules were identified. After screening and analysis, we identified four important prognosis-related lncRNAs (HOTAIR, SNHG16, HCP5, and TINCR), and constructed a prognostic model, one (HCP5) of which has not previously been identified in the context of breast cancer. Importantly, an understanding of prognosis facilitates precise disease risk assessment and advances the selection of strategies for risk-adaptive management. These findings broaden the landscape of carcinogenic lncRNAs in breast cancer, providing insights into the biological significance and clinical application of lncRNAs in breast cancer.

The effect of long noncoding RNAs HOX transcript antisense intergenic RNA single-nucleotide polymorphisms on breast cancer, cervical cancer, and ovarian cancer susceptibility: A meta-analysis.

Recent studies have shown that long noncoding RNAs (lncRNA) HOX transcript antisense intergenic RNA (HOTAIR) polymorphisms are associated with cancer susceptibility. The greatest threat to women's health among a variety of cancers is breast cancer (BC), cervical cancer (CC), and ovarian cancer (OC), and the incidence of it is increasing. We performed a meta-analysis to clarify the relationship between lncRNA HOTAIR expression and BC, CC, and OC susceptibility. We thoroughly searched PubMed, Embase, and the Cochrane Library to obtain the relevant literature. We extracted data from case groups and control groups for each single-nucleotide polymorphism (SNP) (rs4759314, rs920778, rs189663, rs12826786, rs7958904, and rs874945) and compared the relationship between alleles, codominance models, dominant and invisible models and BC, CC, and OC susceptibility. Our study included 11 studies with a total of 5322 patients. There was a significant association between the rs4759314 polymorphism of HOTAIR and susceptibility to BC, CC, and OC (codominant model: AG/AA odds ratio [OR] = 1.13 [95% confidence intervals [CI], 1.00-1.29], GG/AA OR = 1.54 [95% CI, 1.06-2.23]; dominant model: GG + AG/AA OR = 1.16 [95% CI, 1.02-1.32]; and recessive model: GG/AA + AG OR = 1.51 [95% CI, 1.05-2.19]). The association between the expression of rs920778 and BC, CC, and OC susceptibility was not clear (alleles T/C: OR = 1.28 [95% CI, 0.87-1.89]; in codominant model: CT/CC OR = 1.10, [95% CI, 0.71-1.71], TT/CC OR = 1.29 [95% CI, 0.59-2.80]; dominant model: TC + TT/CC OR = 1.16, [95% CI, 0.73-1.86]; and recessive model: TT/TC + CC OR = 1.43, [95% CI, 0.83-2.47]). HOTAIR polymorphism rs1899663 was associated with BC, CC, and OC susceptibility to a certain extent, (alleles T/G OR = 0.90 [95% CI, 0.69-1.16]; in the codominant model: GT/GG OR = 0.81 [95% CI, 0.50-1.30], TT/GG OR = 1.04 [95% CI, 0.63-1.72]; dominant model: GT + TT/GG OR = 0.82 [95% CI, 0.52-1.29]; and recessive model: TT/GT + GG OR = 1.21 [95% CI, 0.76-1.94]). The rs12826786, rs7958904, and rs874945 polymorphisms were associated with a certain degree of BC, CC, and OC susceptibility, but they were not statistically significant. HOTAIR rs4759314 increased susceptibility to BC, CC, and OC in some patients; rs029778 and rs1899663 also increased susceptibility to some extent. SNPs rs12826786, rs7958904, and rs874945 did not correlate with an effect on patient susceptibility to BC, CC, and OC.

DNA methylation-based diagnostic and prognostic biomarkers of nonsmoking lung adenocarcinoma patients.

Currently, there are few studies on patients with nonsmoking lung adenocarcinoma, and the pathogenesis is still unclear. The role of DNA methylation in the pathogenesis of cancer is gradually being recognized. The purpose of this study was to determine the abnormal methylation genes and pathways involved in nonsmoking lung adenocarcinoma patients. Gene expression microarray data (GSE10072, GSE43458) and gene methylation microarray data (GSE62948) were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes were obtained through GEO2R. Next, we analyzed the function and enrichment of the selected genes using Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction (PPI) networks were constructed using the Search Tool for the Retrieval of Interacting Genes database and visualized in Cytoscape. Finally, we performed module analysis of the PPI network using Molecular Complex Detection. And we obtained 10 hub genes by Cytoscape Centiscape. We analyzed the independent prognostic value of each hub gene in nonsmoking nonsmall cell lung cancer patients through Kaplan-Meier plotter. Seven hub genes (CXCL12, CDH1, CASP3, CREB1, COL1A1, ERBB2, and ENO2) were closely related to the overall survival time. This study provides an effective bioinformatics basis for further understanding the pathogenesis and prognosis of nonsmoking lung adenocarcinoma patients. Hub genes with prognostic value could be selected as effective biomarkers for timely diagnosis and prognostic of nonsmoking lung adenocarcinoma patients.

MicroRNAs associated with lung squamous cell carcinoma: New prognostic biomarkers and therapeutic targets.

BACKGROUND: With the development in research, the importance of microRNAs (miRNAs) in the occurrence and metastasis, and prognosis of lung squamous cell carcinoma (LUSC) have received extensive attention. This study aims to identify new biomarkers and pivotal genes associated with LUSC prognosis through bioinformatics. MATERIALS AND METHODS: We downloaded miRNA and messenger RNA samples related to LUSC from The Cancer Genome Atlas (TCGA) database. Following initial data screening and preprocessing, we utilized the R platform and a range of analysis tools (miRDB, TargetScanHuman7.2, DAVID, and Cytoscape_v3.5.1) to analyze the TCGA data and identify highly specific and sensitive biomarkers. RESULTS: We finally identified 12 miRNAs and six central genes closely related to the overall survival of patients with LUSC. We found that high expression of 7 miRNAs (miR-301b, miR-383, miR-512, miR-515, miR-525, miR-577, and miR-5682) and low expression of five miRNAs (miR-448, miR-486, miR-4732,miR-4732, miR-516, and miR-1911) can significantly improve the overall survival rate of patients with LUSC. The six central genes DLGAP5, CENPA, CHEK1, LRRK2, CALB1, and TOP2A are directly or indirectly involved in the formation and metastasis of LUSC and could, therefore, be considered as target genes for drug therapy. CONCLUSION: With the development in research, the importance of miRNAs in the occurrence and metastasis and prognosis of LUSC have received extensive attention. This study aims to identify new biomarkers and pivotal genes associated with LUSC prognosis through bioinformatics.

Identification of prognostic biomarkers for breast cancer based on miRNA and mRNA co-expression network.

PURPOSE: Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC. METHODS: Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers. RESULTS: A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis. CONCLUSION: We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.