Transcriptome Analysis of Triple-Negative Breast Cancer Reveals an Integrated mRNA-lncRNA Signature with Predictive and Prognostic Value

Breast cancer drug resistance: Decoding the roles of Hippo pathway crosstalk

The most significant factors that lead to cancer-related death in breast cancer (BC) patients include drug resistance, migration, invasion, and metastasis. Several signaling pathways are involved in the development of BC. The different types of BC are initially sensitive to chemotherapy, and drug resistance can occur through multiple molecular mechanisms. Regardless of developing targeted Therapy, due to the heterogenic nature and complexity of drug resistance, it is a major clinical challenge with the low survival rate in BC patients. The deregulation of several signaling pathways, particularly the Hippo pathway (HP), is one of the most recent findings about the molecular mechanisms of drug resistance in BC, which are summarized in this review. Given that HP is one of the recent cancer research hotspots, this review focuses on its implication in BC drug resistance. Unraveling the different molecular basis of HP through its crosstalk with other signaling pathways, and determining the effectiveness of HP inhibitors can provide new insights into possible therapeutic strategies for overcoming chemoresistance in BC.

Constructing a novel prognostic model for triple-negative breast cancer based on genes associated with vasculogenic mimicry

BACKGROUND

Research has shown a connection between vasculogenic mimicry (VM) and cancer progression. However, the functions of genes related to VM in the emergence and progression of TNBC have not been completely elucidated.

METHODS

A survival risk model was constructed by screening biomarkers using DESeq2 and WGCNA based on public TNBC transcriptome data. Furthermore, gene set enrichment analysis was performed, and tumor microenvironment and drug sensitivity were analyzed. The selected biomarkers were validated via quantitative PCR detection, immunohistochemical staining, and protein detection in breast cancer cell lines. Biomarkers related to the proliferation and migration of TNBC cells were validated via in vitro experiments.

RESULTS

The findings revealed that 235 target genes were connected to the complement and coagulation cascade pathways. The risk score was constructed using KCND2, NRP1, and VSTM4. The prognosis model using the risk score and pathological T stage yielded good validation results. The clinical risk of TNBC was associated with the angiogenesis signaling pathway, and the low-risk group exhibited better sensitivity to immunotherapy. Quantitative PCR and immunohistochemistry indicated that the expression levels of KCND2 in TNBC tissues were higher than those in adjacent nontumor tissues. In the TNBC cell line, the protein expression of KCND2 was increased. Knockdown of KCND2 and VSTM4 inhibited the proliferation and migration of TNBC cells in vitro.

CONCLUSIONS

In this study, three VM-related biomarkers were identified, including KCND2, NRP1, and VSTM4. These findings are likely to aid in deepening our understanding of the regulatory mechanism of VM in TNBC.

Actinomycin D synergizes with Doxorubicin in triple-negative breast cancer by inducing P53-dependent cell apoptosis

OBJECTIVES

There are three major subtypes of breast cancer, ER+, HER2+ and triple-negative breast cancer (TNBC), namely ER-, PR-, HER2-. TNBC is the most aggressive breast cancer with poor prognosis and no target drug up to now. Actinomycin D (ActD) is a bioactive metabolite of marine bacteria that has been reported to have antitumor activity. The aim of study is to investigate whether ActD has a synergetic effect on TNBC with Doxorubicin (Dox), the major chemotherapeutic drug for TNBC, and explore the underlying mechanism.

METHODS

TNBC cell lines HCC1937, MDA-MB-436 and nude mice were used in the study. Drug synergy determination, LDH assay, MMP assay, Hoechst 33342 staining, Flow cytometry, Flexible docking and CESTA assay were carried out. The expression of proteins associated with apoptosis was checked by Western blot and siRNA experiments were performed to investigate the role of P53 and PUMA induced by drugs.

RESULTS

There was much higher apoptosis rate of cells in the ActD + Dox group than that in ActD group or Dox group. Expression of MDM2 and BCL-2 was reduced while expression of P53, PUMA and BAX were increased in the groups treated with ActD + Dox or Dox compared to the control group. Furthermore, P53 siRNA or PUMA siRNA tremendously abrogated the cell apoptosis in the groups treated by ActD, Dox and ActD + Dox. Flexible docking and CESTA showed that ActD can bind MDM2.

CONCLUSIONS

ActD had a synergetic effect on TNBC with Dox via P53-dependent apoptosis and it may be a new choice for treatment of TNBC.

Identification and validation of an endoplasmic-reticulum-stress-related gene signature as an effective diagnostic marker of endometriosis

Background

Endometriosis is one of the most common benign gynecological diseases and is characterized by chronic pain and infertility. Endoplasmic reticulum (ER) stress is a cellular adaptive response that plays a pivotal role in many cellular processes, including malignant transformation. However, whether ER stress is involved in endometriosis remains largely unknown. Here, we aimed to explore the potential role of ER stress in endometriosis, as well as its diagnostic value.

Methods

We retrieved data from the Gene Expression Omnibus (GEO) database. Data from the GSE7305 and GSE23339 datasets were integrated into a merged dataset as the training cohort. Differentially expressed ER stress-related genes (DEG-ERs) were identified by integrating ER stress-related gene profiles downloaded from the GeneCards database with differentially expressed genes (DEGs) in the training cohort. Next, an ER stress-related gene signature was identified using LASSO regression analysis. The receiver operating characteristic curve was used to evaluate the discriminatory ability of the constructed model, which was further validated in the GSE51981 and GSE105764 datasets. Online databases were used to explore the possible regulatory mechanisms of the genes in the signature. Meanwhile, the CIBERSORT algorithm and Pearson correlation test were applied to analyze the association between the gene signature and immune infiltration. Finally, expression levels of the signature genes were further detected in clinical specimens using qRT-PCR and validated in the Turku endometriosis database.

Results

In total, 48 DEG-ERs were identified in the training cohort. Based on LASSO regression analysis, an eight-gene-based ER stress-related gene signature was constructed. This signature exhibited excellent diagnostic value in predicting endometriosis. Further analysis indicated that this signature was associated with a compromised ER stress state. In total, 12 miRNAs and 23 lncRNAs were identified that potentially regulate the expression of ESR1, PTGIS, HMOX1, and RSAD2. In addition, the ER stress-related gene signature indicated an immunosuppressive state in endometriosis. Finally, all eight genes showed consistent expression trends in both clinical samples and the Turku database compared with the training dataset.

Conclusions

Our work not only provides new insights into the impact of ER stress in endometriosis but also provides a novel biomarker with high clinical value.

CRTAM promotes antitumor immune response in triple negative breast cancer by enhancing CD8+ T cell infiltration

The immunomodulatory (IM) subtype of triple negative breast cancer (TNBC) exhibits high expression of immune cell signaling genes and is more responsive to immunotherapy. However, the specific mechanism underlying this phenomenon remains unclear. One of the potential key genes appears to be the cytotoxic and regulatory T cell molecule (CRTAM). A cohort of 360 previously untreated TNBC patients from Fudan University Shanghai Cancer Center (FUSCC) underwent RNA sequencing analysis of their primary tumor tissue. Combined with three RNA-seq datasets obtained from the GEO database, a LASSO regression analysis was conducted to identify genes specific to the IM type of TNBC. Our findings revealed elevated CRTAM expression in the IM-type TNBC, which correlated with a favorable overall survival and recurrence-free survival in TNBC patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated a strong association between CRTAM and immune responses as well as immune system processes. Notably, CRTAM overexpression induced STAT1 phosphorylation and upregulation of interferon-stimulated genes. We also found that CRTAM enhanced tumor-associated immune cell infiltration, especially CD8+ T cells, which may be related to the increased expression of MHC class I molecules caused by CRTAM overexpression. These results suggest that CRTAM may serve as a potential biomarker for predicting the efficacy of immunotherapy in TNBC.

Roles of lncRNA in the diagnosis and prognosis of triple-negative breast cancer

Breast cancer is a malignant tumor that seriously endangers women's lives. The prognosis of breast cancer patients differs among molecular types. Compared with other subtypes, triple-negative breast cancer (TNBC) has been a research hotspot in recent years because of its high degree of malignancy, strong invasiveness, rapid progression, easy of recurrence, distant metastasis, poor prognosis, and high mortality. Many studies have found that long non-coding RNA (lncRNA) plays an important role in the occurrence, proliferation, migration, recurrence, chemotherapy resistance, and other characteristics of TNBC. Some lncRNAs are expected to become biomarkers in the diagnosis and prognosis of TNBC, and even new targets for its treatment. Based on a PubMed literature search, this review summarizes the progress in research on lncRNAs in TNBC and discusses their roles in TNBC diagnosis, prognosis, and chemotherapy with the hope of providing help for future research.

Roles of Human Endogenous Retroviruses and Endogenous Virus-Like Elements in Cancer Development and Innate Immunity

Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections in the host genome. Although mutations and silencing mechanisms impair their original role in viral replication, HERVs are believed to play roles in various biological processes. Long interspersed nuclear elements (LINEs) are non-LTR retrotransposons that have a lifecycle resembling that of retroviruses. Although LINE expression is typically silenced in somatic cells, it also contributes to various biological processes. The aberrant expression of HERVs and LINEs is closely associated with the development of cancer and/or immunological diseases, suggesting that they are integrated into various pathways related to the diseases. HERVs/LINEs control gene expression depending on the context as promoter/enhancer elements. Some RNAs and proteins derived from HERVs/LINEs have oncogenic potential, whereas others stimulate innate immunity. Non-retroviral endogenous viral elements (nrEVEs) are a novel type of virus-like element in the genome. nrEVEs may also be involved in host immunity. This article provides a current understanding of how these elements impact cellular physiology in cancer development and innate immunity, and provides perspectives for future studies.

Exploiting Long Non-Coding RNAs and Circular RNAs as Pharmacological Targets in Triple-Negative Breast Cancer Treatment

Breast cancer is one of the most frequent causes of cancer death among women worldwide. In particular, triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype because it is characterized by the absence of molecular targets, thus making it an orphan type of malignancy. The discovery of new molecular druggable targets is mandatory to improve treatment success. In that context, non-coding RNAs represent an opportunity for modulation of cancer. They are RNA molecules with apparently no protein coding potential, which have been already demonstrated to play pivotal roles within cells, being involved in different processes, such as proliferation, cell cycle regulation, apoptosis, migration, and diseases, including cancer. Accordingly, they could be used as targets for future TNBC personalized therapy. Moreover, the peculiar characteristics of non-coding RNAs make them reliable biomarkers to monitor cancer treatment, thus, to monitor recurrence or chemoresistance, which are the most challenging aspects in TNBC. In the present review, we focused on the oncogenic or oncosuppressor role of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) mostly involved in TNBC, highlighting their mode of action and depicting their potential role as a biomarker and/or as targets of new non-coding RNA-based therapeutics.

Long Noncoding RNAs in Taxane Resistance of Breast Cancer

Breast cancer is a common cancer in women and a leading cause of mortality. With the early diagnosis and development of therapeutic drugs, the prognosis of breast cancer has markedly improved. Chemotherapy is one of the predominant strategies for the treatment of breast cancer. Taxanes, including paclitaxel and docetaxel, are widely used in the treatment of breast cancer and remarkably decrease the risk of death and recurrence. However, taxane resistance caused by multiple factors significantly impacts the effect of the drug and leads to poor prognosis. Long noncoding RNAs (lncRNAs) have been shown to play a significant role in critical cellular processes, and a number of studies have illustrated that lncRNAs play vital roles in taxane resistance. In this review, we systematically summarize the mechanisms of taxane resistance in breast cancer and the functions of lncRNAs in taxane resistance in breast cancer. The findings provide insight into the role of lncRNAs in taxane resistance and suggest that lncRNAs may be used to develop therapeutic targets to prevent or reverse taxane resistance in patients with breast cancer.

Regulatory miRNAs, circRNAs and lncRNAs in cell cycle progression of breast cancer

Breast cancer is a complex and heterogeneous disease that poses a significant public health concern worldwide, and it remains a major challenge despite advances in treatment options. One of the main properties of cancer cells is the increased proliferative activity that has lost regulation. Dysregulation of various positive and negative modulators in the cell cycle has been identified as one of the driving factors of breast cancer. In recent years, non-coding RNAs have garnered much attention in the regulation of cell cycle progression, with microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs) being of particular interest. MiRNAs are a class of highly conserved and regulatory small non-coding RNAs that play a crucial role in the modulation of various cellular and biological processes, including cell cycle regulation. CircRNAs are a novel form of non-coding RNAs that are highly stable and capable of modulating gene expression at posttranscriptional and transcriptional levels. LncRNAs have also attracted considerable attention because of their prominent roles in tumor development, including cell cycle progression. Emerging evidence suggests that miRNAs, circRNAs and lncRNAs play important roles in the regulation of cell cycle progression in breast cancer. Herein, we summarized the latest related literatures in breast cancer that emphasize the regulatory roles of miRNAs, circRNAs and lncRNAs in cell cycle progress of breast cancer. Further understanding of the precise roles and mechanisms of non-coding RNAs in breast cancer cell cycle regulation could lead to the development of new diagnostic and therapeutic strategies for breast cancer.

Locoregional recurrence in triple negative breast cancer: past, present, and future

INTRODUCTION

Triple negative breast cancer (TNBC) is a rare but aggressive biological subtype of breast cancer associated with higher locoregional and distant recurrence rates and lower overall survival despite advancements in diagnostic and treatment strategies.

AREAS COVERED

This review explores the evolving landscape of locoregional recurrence (LRR) in TNBC with improved surgical and radiation therapy delivery techniques including salvage breast conserving surgery (SBCS), re-irradiation, and thermo-radiation. We review current retrospective and prospective, albeit limited, clinical data highlighting the optimal management of locoregionally recurrent TNBC. We also discuss tumor genomic profiling and transcriptome analysis and review potential investigational directions.

EXPERT OPINION

Significant progress has been made in the prevention of LRR but rates remain suboptimal, particularly in the TNBC population, and outcomes following LRR are poor. Further prospective studies are needed to identify the most effective and safest systemic therapy regimens and to whom it should be offered. There has been growing interest in the role of molecular markers, genomic signatures, and tumor microenvironment in predicting outcomes and guiding LRR treatment. Transcriptome analyses and biomarker-driven investigations are currently being studied and represent a promising era of development in the management of LRR.

Construction of a pancreatic cancer prediction model for oxidative stress-related lncRNA

Long non-coding RNAs (lncRNAs) may play a role in oxidative stress by altering the tumor microenvironment, thereby affecting pancreatic cancer progression. There is currently limited information on oxidative stress-related lncRNAs as novel prognostic markers of pancreatic cancer. Gene expression and clinical data of patients with pancreatic cancer were downloaded from The Cancer Genome Atlas (TCGA-PAAD) and the International Cancer Genome Consortium (ICGC-PACA) database. A weighted gene co-expression network analysis (WGCNA) was constructed to identify genes that were differentially expressed between normal and tumor samples. Based on the TCGA-PAAD cohort, a prediction model was established using lasso regression and Cox regression. The TCGA-PAAD and ICGC-PACA cohorts were used for internal and external validation, respectively. Furthermore, a nomogram based on clinical characteristics was used to predict mortality of patients. Differences in mutational status and tumor-infiltrating immune cells between risk subgroups were also explored and model-based lncRNAs were analyzed for potential immune-related therapeutic drugs. A prediction model for 6-lncRNA was established using lasso regression and Cox regression. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves indicated that patients with lower risk scores had a better prognosis. Combined with Cox regression analysis of clinical features, risk score was an independent factor predicting overall survival of patients with pancreatic cancer in both the TCGA-PAAD and ICGC-PACA cohorts. Mutation status and immune-related analysis indicated that the high-risk group had a significantly higher gene mutation rate and a higher possibility of immune escape, respectively. Furthermore, the model genes showed a strong correlation with immune-related therapeutic drugs. A pancreatic cancer prediction model based on oxidative stress-related lncRNA was established, which may be used as a biomarker related to the prognosis of pancreatic cancer to evaluate the prognosis of pancreatic cancer patients.

FKBP11 improves the malignant property in osteosarcoma cells and acts as a prognostic factor of osteosarcoma

BACKGROUND

Osteosarcoma has become the most common bone malignancy in adolescents. Although the clinical treatment of osteosarcoma has developed very much in recent years, the 5-year survival rate for patients with osteosarcoma has not improved significantly. Currently, many studies have shown that mRNA has a unique advantage as a target for drug therapy. Therefore, this study is dedicated to finding a new prognostic factor and providing a new target for the treatment of osteosarcoma to improve the prognosis of patients with osteosarcoma.

METHODS AND RESULTS

We selected the prognostic genes which are closely associated with osteosarcoma clinical features by obtaining osteosarcoma patients' information from the GTEx and TARGET database, then developed a risk model. We detected the expression of FKBP11 in osteosarcoma by qRT-PCR, Western blotting, and immunohistochemistry, and performed CCK8, transwell, colony formation, and flow cytometry to reveal the regulatory role of FKBP11. We found that FKBP11 was highly expressed in osteosarcoma, and silencing FKBP11 expression reduced the invasion and migration ability of osteosarcoma cells and slowed down cell proliferation, while promoting apoptosis. We also found that silencing the expression of FKBP11 led to inhibiting the phosphorylation of MEK/ERK.

CONCLUSIONS

In conclusion, we validated that the prognostic factor FKBP11 is closely associated with osteosarcoma and found a novel mechanism by which FKBP11 ameliorates the malignant properties of osteosarcoma cells through the MAPK pathway and serves as a prognostic factor in osteosarcoma. It provides a new idea for the treatment of osteosarcoma.

Transcription factor E2F8 is a therapeutic target in the basal-like subtype of breast cancer

Introduction

Tumorigenesis in breast cancers usually accompanied by the dysregulation of transcription factors (TFs). Abnormal amplification of TFs leads aberrant expression of its downstream target genes. However, breast cancers are heterogeneous disease with different subtypes that have distinguished clinical behaviours, and the identification of prognostic TFs may enable to provide diagnosis and treatment of breast cancer based on subtypes, especially in Basal-like breast cancer.

Methods

The RNA-sequencing was performed to screen differential TFs in breast cancer subtypes. The GEPIA dataset analysis was used to analyze the genes expression in invasive breast carcinoma. The expression of MYBL2, HOXC13, and E2F8 was verified by qRT-PCR assay in breast cancers. The depiction analysis of co-expressed proteins was revealed using the STRING datasets. The cellular infiltration level analysis by the TISIDB and TIMER databases. The transwell assay was performed to analyze cellular migration and invasion. CCK-8 assay was used to evaluate cellular drug susceptibility for docetaxel treatment. Predicted targeted drugs in breast cancers by GSCA Lite database online.

Results

Kaplan-Meier plotter suggested that high expression of both E2F8 and MYBL2 in Basal-like subtype had a poor relapse-free survival. Functional enrichment results identified that apoptosis, cell cycle, and hormone ER pathway were represented the crucial regulation pathways by both E2F8 and MYBL2. In the meantime, database analysis indicated that high expression of E2F8 responded to chemotherapy, while those patients of high expression of MYBL2 responded to endocrinotherapy, and a positive correlation between the expression of E2F8 and PD-L1/CTLA4. Our cell line experiments confirmed the importance of E2F8 and MYBL2 in proliferation and chemotherapy sensitivity, possibly, the relationship with PD-L1. Additionally, we also observed that the up-regulation of E2F8 was accompanied with higher enrichments of CD4+ T cells and CD8+ T cells in breast cancers.

Conclusion

Taken together, our findings elucidated a prospective target in Basal-like breast cancer, providing underlying molecular biomarkers for the development of breast cancer treatment.

LncRNA TINCR impairs the efficacy of immunotherapy against breast cancer by recruiting DNMT1 and downregulating MiR-199a-5p via the STAT1-TINCR-USP20-PD-L1 axis

Although programmed death-ligand 1 (PD-L1) inhibitors have achieved some therapeutic success in breast cancer, their efficacy is limited by low therapeutic response rates, which is closely related to the immune escape of breast cancer cells. Tissue differentiation inducing non-protein coding RNA (TINCR), a long non-coding RNA, as an oncogenic gene associated with the progression of various malignant tumors, including breast cancer; however, the role of TINCR in tumor immunity, especially in breast cancer, remains unclear. We confirmed that TINCR upregulated PD-L1 expression in vivo and in vitro, and promoted the progression of breast cancer. Next, we revealed that TINCR knockdown can significantly improve the therapeutic effect of PD-L1 inhibitors in breast cancer in vivo. Mechanistically, TINCR recruits DNMT1 to promote the methylation of miR-199a-5p loci and inhibit its transcription. Furthermore, in the cytoplasm, TINCR potentially acts as a molecular sponge of miR-199a-5p and upregulates the stability of USP20 mRNA through a competing endogenous RNA (ceRNA) regulatory mechanism, thus promoting PD-L1 expression by decreasing its ubiquitination level. IFN-γ stimulation activates STAT1 by phosphorylation, which migrates into the nucleus to promote TINCR transcription. This is the first study to describe the regulatory role of TINCR in breast cancer tumor immunity, broadening the current paradigm of the functional diversity of TINCR in tumor biology. In addition, our study provides new research directions and potential therapeutic targets for PD-L1 inhibitors in breast cancer.

Subtypes analysis and prognostic model construction based on lysosome-related genes in colon adenocarcinoma

Background: Lysosomes are essential for the development and recurrence of cancer. The relationship between a single lysosome-related gene and cancer has previously been studied, but the relationship between the lysosome-related genes (LRGs) and colon adenocarcinoma (COAD) remains unknown. This research examined the role of lysosome-related genes in colon adenocarcinoma. Methods: 28 lysosome-related genes associated with prognosis (PLRGs) were found by fusing the gene set that is differently expressed between tumor and non-tumor in colon adenocarcinoma with the gene set that is related to lysosomes. Using consensus unsupervised clustering of PLRGs, the colon adenocarcinoma cohort was divided into two subtypes. Prognostic and tumor microenvironment (TME) comparisons between the two subtypes were then made. The PLRGs_score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify each patient's prognosis and provide advice for treatment. Lastly, Western Blot and immunohistochemistry (IHC) were used to identify MOGS expression at the protein level in colon adenocarcinoma tissues. Results: PLRGs had more somatic mutations and changes in genetic level, and the outcomes of the two subtypes differed significantly in terms of prognosis, tumor microenvironment, and enrichment pathways. Then, PLRGs_score was established based on two clusters of differential genes in the cancer genome atlas (TCGA) database, and external verification was performed using the gene expression omnibus (GEO) database. Then, we developed a highly accurate nomogram to enhance the clinical applicability of the PLRGs_score. Finally, a higher PLRGs_score was associated with a poorer overall survival (OS), a lower tumor mutation burden (TMB), a lower cancer stem cell (CSC) index, more microsatellite stability (MSS), and a higher clinical stage. MOGS was substantially elevated at the protein level in colon adenocarcinoma as additional confirmation. Conclusion: Overall, based on PLRGs, we identified two subtypes that varied significantly in terms of prognosis and tumor microenvironment. Then, in order to forecast patient prognosis and make treatment suggestions, we developed a diagnostic model with major significance for prognosis, clinical relevance, and immunotherapy. Moreover, we were the first to demonstrate that MOGS is highly expressed in colon adenocarcinoma.

Revealing the Potential Markers of N(4)-Acetylcytidine through acRIP-seq in Triple-Negative Breast Cancer

Understanding the causes of tumorigenesis and progression in triple-receptor negative breast cancer (TNBC) can help the design of novel and personalized therapies and prognostic assessments. Abnormal RNA modification is a recently discovered process in TNBC development. TNBC samples from The Cancer Genome Atlas database were categorized according to the expression level of NAT10, which drives acetylation of cytidine in RNA to N(4)-acetylcytidine (ac4C) and affects mRNA stability. A total of 703 differentially expressed long non-coding RNAs (lncRNAs) were found between high- and low-expressed NAT10 groups in TNBC. Twenty of these lncRNAs were significantly associated with prognosis. Two breast cancer tissues and their paired normal tissues were sequenced at the whole genome level using acetylated RNA immunoprecipitation sequencing (acRIP-seq) technology to identify acetylation features in TNBC, and 180 genes were significantly differentially ac4c acetylated in patients. We also analyzed the genome-wide lncRNA expression profile and constructed a co-expression network, containing 116 ac4C genes and 1080 lncRNAs. Three of these lncRNAs were prognostic risk lncRNAs affected by NAT10 and contained in the network. The corresponding reciprocal pairs were "LINC01614-COL3A1", "OIP5-AS1-USP8", and "RP5-908M14.9-TRIR". These results indicate that RNA ac4c acetylation involves lncRNAs and affects the tumor process and prognosis of TNBC. This will aid the prediction of drug targets and drug sensitivity.

Concomitant medication of cetirizine in advanced melanoma could enhance anti-PD-1 efficacy by promoting M1 macrophages polarization

BACKGROUND

The clinical observation showed a potential additive effect of anti-PD-1 agents and cetirizine in patients with advanced melanoma.

METHODS

Clinical outcomes of concomitant cetirizine/anti-PD-1 treatment of patients with stage IIIb-IV melanoma were retrospectively collected, and a transcriptomic analysis was performed on blood samples obtained at baseline and after 3 months of treatment.

RESULTS

Patients treated with cetirizine concomitantly with an anti-PD-1 agent had significantly longer progression-free survival (PFS; mean PFS: 28 vs 15 months, HR 0.46, 95% CI: 0.28-0.76; p = 0.0023) and OS (mean OS was 36 vs 23 months, HR 0.48, 95% CI: 0.29-0.78; p = 0.0032) in comparison with those not receiving cetirizine. The concomitant treatment was significantly associated with ORR and DCR (p < 0.05). The expression of FCGR1A/CD64, a specific marker of macrophages, was increased after the treatment in comparison with baseline in blood samples from patients receiving cetirizine, but not in those receiving only the anti-PD1, and positively correlated with the expression of genes linked to the interferon pathway such as CCL8 (rho = 0.32; p = 0.0111), IFIT1 (rho = 0.29; p = 0.0229), IFIT3 (rho = 0.57; p < 0.0001), IFI27 (rho = 0.42; p = 0.008), MX1 (rho = 0.26; p = 0.0383) and RSAD2 (rho = 0.43; p = 0.0005).

CONCLUSIONS

This retrospective study suggests that M1 macrophage polarization may be induced by cetirizine through the interferon-gamma pathway. This effect may synergize with the immunotherapy of advanced melanoma with anti-PD-1 agents.

Association of hypoxia inducible factor 1-Alpha gene polymorphisms with multiple disease risks: A comprehensive meta-analysis

HIF1A gene polymorphisms have been confirmed the association with cancer risk through the statistical meta-analysis based on single genetic association (SGA) studies. A good number SGA studies also investigated the association of HIF1A gene with several other diseases, but no researcher yet performed statistical meta-analysis to confirm this association more accurately. Therefore, in this paper, we performed a statistical meta-analysis to draw a consensus decision about the association of HIF1A gene polymorphisms with several diseases except cancers giving the weight on large sample size. This meta-analysis was performed based on 41 SGA study’s findings, where the polymorphisms rs11549465 (1772 C/T) and rs11549467 (1790 G/A) of HIF1A gene were analyzed based on 11544 and 7426 cases and 11494 and 7063 control samples, respectively. Our results showed that the 1772 C/T polymorphism is not significantly associated with overall disease risks. The 1790 G/A polymorphism was significantly associated with overall diseases under recessive model (AA vs. AG + GG), which indicates that the A allele is responsible for overall diseases though it is recessive. The subgroup analysis based on ethnicity showed the significant association of 1772 C/T polymorphism with overall disease for Caucasian population under the all genetic models, which indicates that the C allele controls overall diseases. The ethnicity subgroup showed the significant association of 1790 G/A polymorphism with overall disease for Asian population under the recessive model (AA vs. AG + GG), which indicates that the A allele is responsible for overall diseases. The subgroup analysis based on disease types showed that 1772 C/T is significantly associated with chronic obstructive pulmonary disease (COPD) under two genetic models (C vs. T and CC vs. CT + TT), skin disease under two genetic models (CC vs. TT and CC + CT vs. TT), and diabetic complications under three genetic models (C vs. T, CT vs. TT and CC + CT vs. TT), where C allele is high risk factor for skin disease and diabetic complications (since, ORs > 1), but low risk factor for COPD (since, ORs < 1). Also the 1790 G/A variant significantly associated with the subgroup of cardiovascular disease (CVD) under homozygote model, diabetic complications under allelic and homozygote models, and other disease under four genetic models, where the A is high risk factor for diabetic complications and low risk factor for CVD. Thus, this study provided more evidence that the HIF1A gene is significantly associated with COPD, CVD, skin disease and diabetic complications. These might be the severe comorbidities and risk factors for multiple cancers due to the effect of HIF1A gene and need further investigations accumulating large number of studies.

N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors

Background: 7-Methylguanosine(m7G) contributes greatly to its pathogenesis and progression in colorectal cancer. We proposed building a prognostic model of m7G-related LncRNAs. Our prognostic model was used to identify differences between hot and cold tumors.

Methods: The study included 647 colorectal cancer patients (51 cancer-free patients and 647 cancer patients) from The Cancer Genome Atlas (TCGA). We identified m7G-related prognostic lncRNAs by employing the univariate Cox regression method. Assessments were conducted using univariate Cox regression, multivariate Cox regression, receiver operating characteristics (ROC), nomogram, calibration curves, and Kaplan-Meier analysis. All of these procedures were used with the aim of confirming the validity and stability of the model. Besides these two analyses, we also conducted half-maximal inhibitory concentration (IC50), immune analysis, principal component analysis (PCA), and gene set enrichment analysis (GSEA). The entire set of m7G-related (lncRNAs) with respect to cold and hot tumors has been divided into two clusters for further discussion of immunotherapy.

Results: The risk model was constructed with 17 m7G-related lncRNAs. A good correlation was found between the calibration plots and the prognosis prediction in the model. By assessing IC50 in a significant way across risk groups, systemic treatment can be guided. By using clusters, it may be possible to distinguish hot and cold tumors effectively and to aid in specific therapeutic interventions. Cluster 1 was identified as having the highest response to immunotherapy drugs and thus was identified as the hot tumor.

Conclusion: This study shows that 17 m7G-related lncRNA can be used in clinical settings to predict prognosis and use them to determine whether a tumor is cold or hot in colorectal cancer and improve the individualization of treatment.

Construction of miRNA-lncRNA-mRNA co-expression network affecting EMT-mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

Predicting Prognosis and Distinguishing Cold and Hot Tumors in Bladder Urothelial Carcinoma Based on Necroptosis-Associated lncRNAs

Background

In reference to previous studies, necroptosis played an important role in cancer development. Our team decided to explore the potential prognostic values of long non-coding RNAs (lncRNAs) associated with necroptosis in bladder urothelial carcinoma (BLCA) and their relationship with the tumor microenvironment (TME) and the immunotherapeutic response for accurate dose.

Methods

To obtain the required data, bladder urothelial carcinoma transcriptome data were searched from Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/). We used co-expression analysis, differential expression analysis, and univariate Cox regression to screen out prognostic lncRNAs associated with necroptosis in BLCA. Then the least absolute shrinkage and selection operator (LASSO) was conducted to construct the necroptosis-associated lncRNAs model. Based on this model, we also performed the Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC) to estimate the prognostic power of risk score. Multivariate and univariate Cox regression analysis were performed to build up a nomogram. Calibration curves, and time-dependent ROC were also conducted to evaluate nomogram. Principal component analysis (PCA) revealed a difference between high- and low-risk groups. In addition, we explored immune analysis, gene set enrichment analyses (GSEA), and evaluation of the half-maximal inhibitory concentration (IC50) in constructed model. Finally, the entire samples were divided into three clusters based on model of necroptosis-associated lncRNAs to further compare immunotherapy in cold and hot tumors.

Results

A model was built up based on necroptosis-associated lncRNAs. The model revealed good consistence between calibration plots and prognostic prediction. The area of 1-, 3-, and 5-year OS under the ROC curve (AUC) were 0.707, 0.679, and 0.675. Risk groups could be helpful for systemic therapy due to the markedly diverse IC50 between risk groups. To our delight, clusters could effectively identify cold and hot tumors, which would be beneficial to accurate mediation. Clusters 2 and 3 were considered the hot tumor, which was more sensitive to immunotherapeutic drugs.

Conclusions

The outcomes of our study suggested that necroptosis-associated lncRNAs could effectively predict patients with BLCA prognosis, which may be helpful for distinguishing the cold and hot tumors and improving individual treatment of BLCA.

Noncoding RNAs and their therapeutics in paclitaxel chemotherapy: Mechanisms of initiation, progression, and drug sensitivity

The identification of agents that can reverse drug resistance in cancer chemotherapy, and enhance the overall efficacy is of great interest. Paclitaxel (PTX) belongs to taxane family that exerts an antitumor effect by stabilizing microtubules and inhibiting cell cycle progression. However, PTX resistance often develops in tumors due to the overexpression of drug transporters and tumor-promoting pathways. Noncoding RNAs (ncRNAs) are modulators of many processes in cancer cells, such as apoptosis, migration, differentiation, and angiogenesis. In the present study, we summarize the effects of ncRNAs on PTX chemotherapy. MicroRNAs (miRNAs) can have opposite effects on PTX resistance (stimulation or inhibition) via influencing YES1, SK2, MRP1, and STAT3. Moreover, miRNAs modulate the growth and migration rates of tumor cells in regulating PTX efficacy. PIWI-interacting RNAs, small interfering RNAs, and short-hairpin RNAs are other members of ncRNAs regulating PTX sensitivity of cancer cells. Long noncoding RNAs (LncRNAs) are similar to miRNAs and can modulate PTX resistance/sensitivity by their influence on miRNAs and drug efflux transport. The cytotoxicity of PTX against tumor cells can also be affected by circular RNAs (circRNAs) and limitation is that oncogenic circRNAs have been emphasized and experiments should also focus on onco-suppressor circRNAs.

Chordin-Like 1 Regulates Epithelial-to-Mesenchymal Transition and Metastasis via the MAPK Signaling Pathway in Oral Squamous Cell Carcinoma

Background

Accumulating evidence suggests that dysregulation of Chordin-like 1 (CHRDL1) is associated with malignant biological behaviors in multiple cancers. However, the exact function and molecular mechanism of CHRDL1 in oral squamous cell carcinoma (OSCC) remain unclear.

Methods

The expression levels of CHRDL1 in OSCC tissues and CAL27 cells were determined by RT-qPCR. Immunohistochemical staining was applied to detect CHRDL1 protein expression in sample tissues from OSCC patients. Gain of function and knockdown by lentivirus were further used to examine the effects of CHRDL1 on cell proliferation, migration, invasion, and adhesion in OSCC. Tail vein injection of CAL27 cells with dysregulated CHRDL1 expression was further used to examine the effect of CHRDL1 on lung colonization. RNA sequencing was performed to explore the molecular mechanisms of CHRDL1 that underlie the progression of OSCC.

Results

CHRDL1 was significantly downregulated in OSCC tissues and CAL27 cells compared to controls. CHRDL1 knockdown enhanced migration, invasion, adhesion, and EMT, but not proliferation, in CAL27 cells. Overexpression of CHRDL1 had the opposite effects. Moreover, CHRDL1 was proven to inhibit tumor metastasis in vivo. Mechanistically, MAPK signaling pathway components, including ERK1/2, p38, and JNK, were found to regulate the malignant biological behaviors of CAL27 cells.

Conclusions

Our results suggest that CHRDL1 has an inhibitory effect on OSCC metastasis via the MAPK signaling pathway, which provides a new possible potential therapeutic target against OSCC.

Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis

OBJECTIVE

Sonographic features are associated with pathological and immunohistochemical characteristics of triple-negative breast cancer (TNBC). To predict the biological property of TNBC, the performance using quantitative high-throughput sonographic feature analysis was compared with that using qualitative feature assessment.

METHODS

We retrospectively reviewed ultrasound images, clinical, pathological, and immunohistochemical (IHC) data of 252 female TNBC patients. All patients were subgrouped according to the histological grade, Ki67 expression level, and human epidermal growth factor receptor 2 (HER2) score. Qualitative sonographic feature assessment included shape, margin, posterior acoustic pattern, and calcification referring to the Breast Imaging Reporting and Data System (BI-RADS). Quantitative sonographic features were acquired based on the computer-aided radiomics analysis. Breast cancer masses were manually segmented from the surrounding breast tissues. For each ultrasound image, 1688 radiomics features of 7 feature classes were extracted. The principal component analysis (PCA), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) were used to determine the high-throughput radiomics features that were highly correlated to biological properties. The performance using both quantitative and qualitative sonographic features to predict biological properties of TNBC was represented by the area under the receiver operating characteristic curve (AUC).

RESULTS

In the qualitative assessment, regular tumor shape, no angular or spiculated margin, posterior acoustic enhancement, and no calcification were used as the independent sonographic features for TNBC. Using the combination of these four features to predict the histological grade, Ki67, HER2, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI), the AUC was 0.673, 0.680, 0.651, 0.587, and 0.566, respectively. The number of high-throughput features that closely correlated with biological properties was 34 for histological grade (AUC 0.942), 27 for Ki67 (AUC 0.732), 25 for HER2 (AUC 0.730), 34 for ALNM (AUC 0.804), and 34 for LVI (AUC 0.795).

CONCLUSION

High-throughput quantitative sonographic features are superior to traditional qualitative ultrasound features in predicting the biological behavior of TNBC.

KEY POINTS

• Sonographic appearances of TNBCs showed a great variety in accordance with its biological and clinical characteristics. • Both qualitative and quantitative sonographic features of TNBCs are associated with tumor biological characteristics. • The quantitative high-throughput feature analysis is superior to two-dimensional sonographic feature assessment in predicting tumor biological property.

A Lipid Metabolism-Based Seven-Gene Signature Correlates with the Clinical Outcome of Lung Adenocarcinoma

Background. Herein, we tried to develop a prognostic prediction model for patients with LUAD based on the expression profiles of lipid metabolism-related genes (LMRGs). Methods. Molecular subtypes were identified by non-negative matrix factorization (NMF) clustering. The overall survival (OS) predictive gene signature was developed and validated internally and externally based on online data sets. Time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier curve, nomogram, restricted mean survival time (EMST), and decision curve analysis (DCA) were used to assess the performance of the gene signature. Results. We identified three molecular subtypes in LUAD with distinct characteristics on immune cells infiltration and clinical outcomes. Moreover, we confirmed a seven-gene signature as an independent prognostic factor for patients with LUAD. Calibration and DCA analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the gene signature. In addition, the nomogram showed higher robustness and clinical usability compared with four previously reported prognostic gene signatures. Conclusions. Findings in the present study shed new light on the characteristics of lipid metabolism within LUAD, and the established seven-gene signature can be utilized as a new prognostic marker for predicting survival in patients with LUAD.

Small-molecule inhibitors that disrupt the MTDH-SND1 complex suppress breast cancer progression and metastasis

Metastatic breast cancer is a leading health burden worldwide. Previous studies have shown that metadherin (MTDH) promotes breast cancer initiation, metastasis and therapy resistance; however, the therapeutic potential of targeting MTDH remains largely unexplored. Here, we used genetically modified mice and demonstrate that genetic ablation of Mtdh inhibits breast cancer development through disrupting the interaction with staphylococcal nuclease domain-containing 1 (SND1), which is required to sustain breast cancer progression in established tumors. We performed a small-molecule compound screening to identify a class of specific inhibitors that disrupts the protein-protein interaction (PPI) between MTDH and SND1 and show that our lead candidate compounds C26-A2 and C26-A6 suppressed tumor growth and metastasis and enhanced chemotherapy sensitivity in preclinical models of triple-negative breast cancer (TNBC). Our results demonstrate a significant therapeutic potential in targeting the MTDH-SND1 complex and identify a new class of therapeutic agents for metastatic breast cancer.

Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer

OBJECTIVE

Triple-negative breast cancer (TNBC) is aggressive cancer usually diagnosed in young women with no effective prognosis prediction model to use. The present study was performed to develop a useful prognostic model for predicting overall survival (OS) for TNBC patients.

METHODS

The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used as training and validation data sets, respectively, in which the gene expression levels and clinical prognostic information of TNBC were collected. Differentially expressed genes (DEGs) between TNBC and non-TNBC (NTNBC) were identified with the thresholds of false discovery rate < 0.05 and |log2 Fold Change| > 1. DEGs in AmiGO2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were retained for further study. Univariate, multivariate Cox, and logistic regression analysis were conducted for detecting DEG signature with the threshold of log-rank P < 0.05. The prognosis models of mRNA signature, clinical factors were constructed and compared.

RESULTS

One five-DEG signature, including CHST4, COCH, CST9, SOX11, and TDGF1 was identified in DEG prognosis model. Stratified analysis showed that the patients aged over 60, with higher pathologic stage (III-IV) and recurrence induced a significantly lower survival rate than those aged below 60, lower pathologic stage and without recurrence. Compared with patients with low-risk scores, those presented high-risk scores demonstrated significantly lower survival rate in the subgroup aged over 60 [HR = 3.780 (1.801-7.933), P < 0.0001]. For patients who obtained a higher pathologic stage and recurrence, high-risk scores were correlated with a significantly lower survival rate than patients with low-risk scores. The five-mRNA signature combined with clinical model (AUC = 0.950) predicted better than single clinical model (AUC = 0.795) or five-mRNA signature model (AUC = 0.823).

CONCLUSION

Our present study identified a prognostic prediction model (combined with five-mRNA signature and clinical factors) for TNBC patients receiving immunotherapy, which will benefit future research and clinical therapies.

Necroptosis-Related lncRNAs: Predicting Prognosis and the Distinction between the Cold and Hot Tumors in Gastric Cancer

Background

In the face of poor prognosis and immunotherapy failure of gastric cancer (GC), this project tried to find new potential biomarkers for predicting prognosis and precision medication to ameliorate the situation.

Methods

To form synthetic matrices, we retrieved stomach adenocarcinoma transcriptome data from Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA). Necroptosis-related prognostic lncRNA was identified by coexpression analysis and univariate Cox regression. Then we performed the least absolute shrinkage and selection operator (LASSO) to construct the necroptosis-related lncRNA model. Next, the Kaplan–Meier analysis, time-dependent receiver operating characteristics (ROC), univariate Cox (uni-Cox) regression, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were made to verify and evaluate the model. Gene set enrichment analyses (GSEA), principal component analysis (PCA), immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) in risk groups were also analyzed. For further discussing immunotherapy between the cold and hot tumors, we divided the entire set into two clusters based on necroptosis-related lncRNAs.

Results

We constructed a model with 16 necroptosis-related lncRNAs. In the model, we found the calibration plots showed a good concordance with the prognosis prediction. The area's 1-, 2-, and 3-year OS under the ROC curve (AUC) were 0.726, 0.763, and 0.770, respectively. Risk groups could be a guide of systemic treatment because of significantly different IC50 between risk groups. Above all, clusters could help distinguish between the cold and hot tumors effectively and contribute to precise mediation. Cluster 2 was identified as the hot tumor and more susceptible to immunotherapeutic drugs.

Conclusion

The results of this project supported that necroptosis-related lncRNAs could predict prognosis and help make a distinction between the cold and hot tumors for improving individual therapy in GC.

LncRNA RNA Component of Mitochondrial RNA-Processing Endoribonuclease Promotes AKT-Dependent Breast Cancer Growth and Migration by Trapping MicroRNA-206

The RNA component of mitochondrial RNA-processing endoribonuclease (RMRP) was recently shown to play a role in cancer development. However, the function and mechanism of RMRP during cancer progression remain incompletely understood. Here, we report that RMRP is amplified and highly expressed in various malignant cancers, and the high level of RMRP is significantly associated with their poor prognosis, including breast cancer. Consistent with this, ectopic RMRP promotes proliferation and migration of TP53-mutated breast cancer cells, whereas depletion of RMRP leads to inhibition of their proliferation and migration. RNA-seq analysis reveals AKT as a downstream target of RMRP. Interestingly, RMRP indirectly elevates AKT expression by preventing AKT mRNA from miR-206-mediated targeting via a competitive sequestering mechanism. Remarkably, RMRP endorses breast cancer progression in an AKT-dependent fashion, as knockdown of AKT completely abolishes RMRP-induced cancer cell growth and migration. Altogether, our results unveil a novel role of the RMRP-miR-206-AKT axis in breast cancer development, providing a potential new target for developing an anti-breast cancer therapy.

A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer

Background

The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.

Methods

We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.

Results

A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.

Conclusions

The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.

Expression and Functional Analysis of lncRNAs Involved in Platelet-Derived Growth Factor-BB-Induced Proliferation of Human Aortic Smooth Muscle Cells

Abnormal proliferation of vascular smooth muscle cells (VSMCs) is a common feature of many vascular remodeling diseases. Because long non-coding RNAs (lncRNAs) play a critical role in cardiovascular diseases, we analyzed the key lncRNAs that regulate VSMC proliferation. Microarray analysis identified 2,643 differentially expressed lncRNAs (DELs) and 3,720 differentially expressed coding genes (DEGs) between fetal bovine serum (FBS) starvation-induced quiescent human aortic smooth muscle cells (HASMCs) and platelet-derived growth factor-BB (PDGF-BB)-stimulated proliferative HASMCs. Gene Ontology and pathway analyses of the identified DEGs and DELs demonstrated that many lncRNAs were enriched in pathways related to cell proliferation. One of the upregulated lncRNAs in proliferative HASMC was HIF1A anti-sense RNA 2 (HIF1A-AS2). HIF1A-AS2 suppression decreased HASMC proliferation via the miR-30e-5p/CCND2 mRNA axis. We have thus identified key DELs and DEGs involved in the regulation of PDGF-BB induced HASMC proliferation. Moreover, HIF1A-AS2 promotes HASMC proliferation, suggesting its potential involvement in VSMC proliferative vascular diseases.

Impact of Stilbenes as Epigenetic Modulators of Breast Cancer Risk and Associated Biomarkers

With the recent advancement of genetic screening for testing susceptibility to mammary oncogenesis in women, the relevance of the gene−environment interaction has become progressively apparent in the context of aberrant gene expressions. Fetal exposure to external stressors, hormones, and nutrients, along with the inherited genome, impact its traits, including cancer susceptibility. Currently, there is increasing interest in the role of epigenetic biomarkers such as genomic methylation signatures, plasma microRNAs, and alterations in cell-signaling pathways in the diagnosis and primary prevention of breast cancer, as well as its prognosis. Polyphenols like natural stilbenes have been shown to be effective in chemoprevention by exerting cytotoxic effects that can stall cell proliferation. Besides possessing antioxidant properties against the DNA-damaging effects of reactive oxygen species, stilbenes have also been observed to modulate cell-signaling pathways. With the increasing trend of early-life screening for hereditary breast cancer risks, the potency of different phytochemicals in harnessing the epigenetic biomarkers of breast cancer risk demand more investigation. This review will explore means of exploiting the abilities of stilbenes in altering the underlying factors that influence breast cancer risk, as well as the appearance of associated biomarkers.

lncRNA HIF1A-AS2: A potential oncogene in human cancers (Review)

Long non-coding RNAs (lncRNAs) are transcripts that are >200 nucleotides, but with no open reading frame. An increasing number of lncRNAs have been identified following the development of second-generation sequencing technologies, and they have since become a research hotspot. Functionally, they play a vital role in tumor progression, including in tumor proliferation, migration, invasion, apoptosis and acquisition of drug resistance. They regulate gene expression primarily through interaction with DNA, RNA and proteins at the epigenetic, transcriptional and post-transcriptional levels. Endogenous hypoxia-inducible factor 1α antisense RNA 2 (lncRNA HIF1A-AS2) is aberrantly expressed and involved the development/progression of various types of tumors, such as bladder cancer, glioblastoma, breast cancer and osteosarcoma. It plays a vital role in the proliferation, apoptosis, migration, invasion and epithelial-mesenchymal transformation of various tumor cells. This review summarizes the current body of knowledge on the biological functions and related molecular mechanisms of lncRNA HIF1A-AS2 in the development/progression of human tumors and other diseases.

lncRNA and breast cancer: Progress from identifying mechanisms to challenges and opportunities of clinical treatment

Breast cancer is a malignant tumor that has a high mortality rate and mostly occurs in women. Although significant progress has been made in the implementation of personalized treatment strategies for molecular subtypes in breast cancer, the therapeutic response is often not satisfactory. Studies have reported that long non-coding RNAs (lncRNAs) are abnormally expressed in breast cancer and closely related to the occurrence and development of breast cancer. In addition, the high tissue and cell-type specificity makes lncRNAs particularly attractive as diagnostic biomarkers, prognostic factors, and specific therapeutic targets. Therefore, an in-depth understanding of the regulatory mechanisms of lncRNAs in breast cancer is essential for developing new treatment strategies. In this review, we systematically elucidate the general characteristics, potential mechanisms, and targeted therapy of lncRNAs and discuss the emerging functions of lncRNAs in breast cancer. Additionally, we also highlight the advantages and challenges of using lncRNAs as biomarkers for diagnosis or therapeutic targets for drug resistance in breast cancer and present future perspectives in clinical practice.

Knockdown of lncRNA HIF1A-AS2 increases drug sensitivity of SCLC cells in association with autophagy

The aim of this study was to determine the effect of lncRNA HIF1A-AS2 on autophagy-associated drug resistance in small cell lung cancer (SCLC) cells. The expression of HIF1A-AS2 was silenced by siRNA in doxorubicin-sensitive H69 and doxorubicin-resistant H69AR cells. Then, cytotoxicity, apoptosis and autophagy analyses were carried out in the normoxic and CoCl₂-induced hypoxic environment. The effect of HIF1A-AS2 on the expression levels of genes, which are associated with drug resistance and autophagy, was determinated by qRT-PCR analysis. The levels of MRP1, HIF-1α and Beclin-1 were analyzed by western blot method. Knockdown of HIF1A-AS2 increased doxorubicin sensitivity of SCLC cells and decreased autophagy. Knockdown of HIF1A-AS2 has also affected the expression of several genes that will increase drug sensitivity and inhibit autophagy in both cell lines. The levels of HIF-1α and Beclin-1 were decreased in both cell lines by knockdown of HIF1A-AS2. MRP1 expression was decrease in H69AR cells. In addition, CoCl₂-induced hypoxic environment decreased in doxorubicin sensitivity of H69 cells, and knockdown of HIF1A-AS2 reversed this effect of hypoxia. Knockdown of HIF1A-AS2 increased drug sensitivity of SCLC cells in relation to autophagy. Therefore, hypoxia-HIF1A-AS2-autophagy interaction is thought to be determinative in drug sensitivity of these cells.

Multifaceted roles of long non-coding RNAs in triple-negative breast cancer: biology and clinical applications

Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer subtype that lacks targeted therapy due to the absence of estrogen, progesterone, and HER2 receptors. Moreover, TNBC was shown to have a poor prognosis, since it involves aggressive phenotypes that confer significant hindrance to therapeutic treatments. Recent state-of-the-art sequencing technologies have shed light on several long non-coding RNAs (lncRNAs), previously thought to have no biological function and were considered as genomic junk. LncRNAs are involved in various physiological as well as pathological conditions, and play a key role in drug resistance, gene expression, and epigenetic regulation. This review mainly focuses on exploring the multifunctional roles of candidate lncRNAs, and their strong association with TNBC development. We also summarise various emerging research findings that establish novel paradigms of lncRNAs function as oncogenes and/or tumor suppressors in TNBC development, suggesting their role as prospective therapeutic targets.

The Biological Function of TUSC7/miR-1224-3p Axis in Triple-Negative Breast Cancer

Background

Triple-negative breast cancers (TNBC), comprising about 20% of breast cancers, have a poor prognosis. Currently, there is no effective target therapy for TNBC. LncRNA TUSC7 has been identified as a tumor suppressor in osteosarcoma and colorectal cancer. In this study, we investigated the clinical significance and the biological function of TUSC7 in breast cancer.

Methods

We retrospectively evaluated the expression level and clinical significance of TUSC7 in 90 paired breast cancer tissues and normal tissues. The proliferation, migration, and invasion assays were performed to investigate the biological function of TUSC7 in breast cancer. Finally, microarray, a luciferase reporter assay, and quantitative real-time polymerase chain reaction (qPCR) were used to explore the potential underlying mechanism of tumor suppressor role of TUSC7.

Results

Low TUSC7 expression was found to be an independent prognostic factor of poor overall survival (OS) in TNBC patients. Ectopic expression of TUSC7 inhibited tumor cell growth both in vitro and in vivo. TUSC7 overexpression significantly promoted the sensitivity of MDA-MB-468 cells to paclitaxel and carboplatin. In terms of the mechanism, TUSC7 might perform its biological function through binding with miR-1224-3P and regulating its expression level. Besides, genes in cell cycle pathways, such as BUB3 (budding uninhibited by benzimidazoles 3) and TGF-ß (targeting transforming growth factor β) pathways were downregulated, and genes involved in the MAPK (mitogen-activated protein kinase) (TGFBR2, transforming growth factor-beta receptor 2), PI3K-AKT (phosphoinositide 3-kinase- AKT serine/threonine kinase 1) and NF-κB (nuclear factor-kappa B subunit) pathways were upregulated in TUSC7 knockdown MDA-MB-231 cells.

Conclusion

The low TUSC7 expression is an independent prognostic factor of poor OS of TNBC patients. TUSC7 might inhibit breast cancer cell growth and metastasis both in vitro and vivo through binding with miR-1224-3P and regulating MAPK, PI3K/AKT, and NF-κB signaling pathways.

Prognostic Biomarkers on a Competitive Endogenous RNA Network Reveals Overall Survival in Triple-Negative Breast Cancer

The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.

Long noncoding RNAs in triple-negative breast cancer: A new frontier in the regulation of tumorigenesis

In recent years, triple-negative breast cancer (TNBC) has emerged as the most aggressive subtype of breast cancer and is usually associated with increased mortality worldwide. The severity of TNBC is primarily observed in younger women, with cases ranging from approximately 12%-24% of all breast cancer cases. The existing hormonal therapies offer limited clinical solutions in completely circumventing the TNBC, with chemoresistance and tumor recurrences being the common hurdles in the path of TNBC treatment. Accumulating evidence has correlated the dysregulation of long noncoding RNAs (lncRNAs) with increased cell proliferation, invasion, migration, tumor growth, chemoresistance, and decreased apoptosis in TNBC. Various clinical studies have revealed that aberrant expression of lncRNAs in TNBC tissues is associated with poor prognosis, lower overall survival, and disease-free survival. Due to these specific characteristics, lncRNAs have emerged as novel diagnostic and prognostic biomarkers for TNBC treatment. However, the underlying mechanism through which lncRNAs perform their actions remains unclear, and extensive research is being carried out to reveal it. Therefore, understanding of mechanisms regulating the modulation of lncRNAs will be a substantial breakthrough in effective treatment therapies for TNBC. This review highlights the association of several lncRNAs in TNBC progression and treatment, along with their possible functions and mechanisms.

Comprehensive Analysis of Differentially Expressed Long Noncoding RNA-mRNA in the Adenoma-Carcinoma Sequence of DNA Mismatch Repair Proficient Colon Cancer

DNA proficient mismatch repair colon cancer (pMMR CC) is the most common subtype of sporadic CC. We aimed to investigate the role of long noncoding RNAs (lncRNAs) in pMMR CC carcinogenesis. In the present study, we conducted transcriptomic analysis of lncRNAs-mRNAs in five low-grade intraepithelial neoplasia (LGIN), five high-grade intraepithelial neoplasia (HGIN), four pMMR CC, and five normal control (NC) tissues. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway, and coexpression network analyses were performed to elucidate the functions of lncRNAs and mRNAs as well as their interactions. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate five dysregulated lncRNAs in a large set of colon tissues. Receiver-operating characteristic (ROC) curves were employed to evaluate the performance of the candidate lncRNAs. A set of 5783 differentially expressed lncRNAs and 4483 differentially expressed mRNAs were detected among the LGIN, HGIN, pMMR CC, and NC samples. These differentially expressed lncRNAs and mRNAs were assigned to 275 significant GO terms and 179 significant KEGG enriched pathways. qRT-PCR confirmed that the expression of five selected lncRNAs (ENST00000521815, ENST00000603052, ENST00000609220, NR_026543, and ENST00000545920) were consistent with the microarray data. ROC analysis showed that four lncRNAs (ENST00000521815, ENST00000603052, ENST00000609220, and NR_026543) had larger area under the ROC curve (AUC) values compared to serum carcinoembryonic antigens, thereby distinguishing NC from pMMR CC. In conclusion, several lncRNAs play various roles in the adenoma-carcinoma sequence and may serve as potential biomarkers for the early diagnosis of pMMR CC.

The Use of Zebrafish Xenotransplant Assays to Analyze the Role of lncRNAs in Breast Cancer

Breast cancer represents a great challenge since it is the first cause of death by cancer in women worldwide. LncRNAs are a newly described class of non-coding RNAs that participate in cancer progression. Their use as cancer markers and possible therapeutic targets has recently gained strength. Animal xenotransplants allows for in vivo monitoring of disease development, molecular elucidation of pathogenesis and the design of new therapeutic strategies. Nevertheless, the cost and complexities of mice husbandry makes medium to high throughput assays difficult. Zebrafishes (Danio rerio) represent a novel model for these assays, given the ease with which xenotransplantation trials can be performed and the economic and experimental advantages it offers. In this review we propose the use of xenotransplants in zebrafish to study the role of breast cancer lncRNAs using low to medium high throughput assays.

Artificial Intelligence in Breast MRI Radiogenomics: Towards Accurate Prediction of Neoadjuvant Chemotherapy Responses

Neoadjuvant Chemotherapy (NAC) in breast cancer patients has considerable prognostic and treatment potential and can be tailored to individual patients as part of precision medicine protocols. This work reviews recent advances in artificial intelligence so as to enable the use of radiogenomics for accurate NAC analysis and prediction. The work addresses a new problem in radiogenomics mining: How to combine structural radiomics information and non-structural genomics information for accurate NAC prediction. This requires the automated extraction of parameters from structural breast radiomics data, and finding non-structural feature vectors with diagnostic value, which then are combined with genomics data acquired from exocrine bodies in blood samples from a cohort of cancer patients to enable accurate NAC prediction. A self-attention-based deep learning approach, along with an effective multi-channel tumour image reconstruction algorithm of high dimensionality, is proposed. The aim was to generate non-structural feature vectors for accurate prediction of the NAC responses by combining imaging datasets with exocrine body related genomics analysis.

Alternative Animal Models of Aging Research

Most research on mechanisms of aging is being conducted in a very limited number of classical model species, i.e., laboratory mouse (Mus musculus), rat (Rattus norvegicus domestica), the common fruit fly (Drosophila melanogaster) and roundworm (Caenorhabditis elegans). The obvious advantages of using these models are access to resources such as strains with known genetic properties, high-quality genomic and transcriptomic sequencing data, versatile experimental manipulation capabilities including well-established genome editing tools, as well as extensive experience in husbandry. However, this approach may introduce interpretation biases due to the specific characteristics of the investigated species, which may lead to inappropriate, or even false, generalization. For example, it is still unclear to what extent knowledge of aging mechanisms gained in short-lived model organisms is transferable to long-lived species such as humans. In addition, other specific adaptations favoring a long and healthy life from the immense evolutionary toolbox may be entirely missed. In this review, we summarize the specific characteristics of emerging animal models that have attracted the attention of gerontologists, we provide an overview of the available data and resources related to these models, and we summarize important insights gained from them in recent years. The models presented include short-lived ones such as killifish (Nothobranchius furzeri), long-lived ones such as primates (Callithrix jacchus, Cebus imitator, Macaca mulatta), bathyergid mole-rats (Heterocephalus glaber, Fukomys spp.), bats (Myotis spp.), birds, olms (Proteus anguinus), turtles, greenland sharks, bivalves (Arctica islandica), and potentially non-aging ones such as Hydra and Planaria.

A ten N6-methyladenosine-related long non-coding RNAs signature predicts prognosis of triple-negative breast cancer

Background

Patients with triple‐negative breast cancer (TNBC) face a major challenge of the poor prognosis, and N6‐methyladenosine‐(m6A) mediated regulation in cancer has been proposed. Therefore, this study aimed to explore the prognostic roles of m6A‐related long non‐coding RNAs (LncRNAs) in TNBC.

Methods

Clinical information and expression data of TNBC samples were collected from TCGA and GEO databases. Pearson correlation, univariate, and multivariate Cox regression analysis were employed to identify independent prognostic m6A‐related LncRNAs to construct the prognostic score (PS) risk model. Receiver operating characteristic (ROC) curve was used to evaluate the performance of PS risk model. A competing endogenous RNA (ceRNA) network was established for the functional analysis on targeted mRNAs.

Results

We identified 10 independent prognostic m6A‐related LncRNAs (SAMD12‐AS1, BVES‐AS1, LINC00593, MIR205HG, LINC00571, ANKRD10‐IT1, CIRBP‐AS1, SUCLG2‐AS1, BLACAT1, and HOXB‐AS1) and established a PS risk model accordingly. Relevant results suggested that TNBC patients with lower PS had better overall survival status, and ROC curves proved that the PS model had better prognostic abilities with the AUC of 0.997 and 0.864 in TCGA and GSE76250 datasets, respectively. Recurrence and PS model status were defined as independent prognostic factors of TNBC. These ten LncRNAs were all differentially expressed in high‐risk TNBC compared with controls. The ceRNA network revealed the regulatory axes for nine key LncRNAs, and mRNAs in the network were identified to function in pathways of cell communication, signaling transduction and cancer.

Conclusion

Our findings proposed a ten‐m6A‐related LncRNAs as potential biomarkers to predict the prognostic risk of TNBC.

A novel cystathionine γ-lyase inhibitor, I194496, inhibits the growth and metastasis of human TNBC via downregulating multiple signaling pathways

Triple-negative breast cancer (TNBC) is a high-risk subtype of breast cancer with high capacity for metastasis and lacking of therapeutic targets. Our previous studies indicated that cystathionine γ-lyase (CSE) may be a new target related to the recurrence or metastasis of TNBC. Downregulation of CSE could inhibit the growth and metastasis of TNBC. The purpose of this study was to investigate the activity of the novel CSE inhibitor I194496 against TNBC in vivo and in vitro. The anticancer activity of I194496 in vitro were detected by MTS, EdU, and transwell assays. Methylene blue assay was used to determine the H₂S level. Western blot was performed to analyze the expression of related pathway proteins. Xenograft tumors in nude mice were used to analyze the anticancer activity of I194496 in vivo. I194496 exerted potent inhibitory effects than l-propargylglycine (PAG, an existing CSE inhibitor) on human TNBC cells and possessed lower toxicity in normal breast epithelial Hs578Bst cells. I194496 reduced the activity and expression of CSE protein and the release of H₂S in human TNBC cells. Meanwhile, the protein levels of PI3K, Akt, phospho (p)-Akt, Ras, Raf, p-ERK, p-Anxa2, STAT3, p-STAT3, VEGF, FAK, and Paxillin were decreased in human TNBC cells administrated with I194496. Furthermore, I194496 showed more stronger inhibitory effects on human TNBC xenograft tumors in nude mice. I194496 could inhibit the growth of human TNBC cells via the dual targeting PI3K/Akt and Ras/Raf/ERK pathway and suppress the metastasis of human TNBC cells via down-regulating Anxa2/STAT3 and VEGF/FAK/Paxillin signaling pathways. CSE inhibitor I194496 might become a novel and potential agent in the treatment of TNBC.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

A Signature of Autophagy-Related Long Non-coding RNA to Predict the Prognosis of Breast Cancer

Background: A surge in newly diagnosed breast cancer has overwhelmed the public health system worldwide. Joint effort had beed made to discover the genetic mechanism of these disease globally. Accumulated research has revealed autophagy may act as a vital part in the pathogenesis of breast cancer.

Objective: Aim to construct a prognostic model based on autophagy-related lncRNAs and investigate their potential mechanisms in breast cancer.

Methods: The transcriptome data and clinical information of patients with breast cancer were obtained from The Cancer Genome Atlas (TCGA) database. Autophagy-related genes were obtained from the Human Autophagy Database (HADb). Long non-coding RNAs (lncRNAs) related to autophagy were acquired through the Pearson correlation analysis. Univariate Cox regression analysis as well as the least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify autophagy-related lncRNAs with prognostic value. We constructed a risk scoring model to assess the prognostic significance of the autophagy-related lncRNAs signatures. The nomogram was then established based on the risk score and clinical indicators. Through the calibration curve, the concordance index (C-index) and receiver operating characteristic (ROC) curve analysis were evaluated to obtain the model's predictive performance. Subgroup analysis was performed to evaluate the differential ability of the model. Subsequently, gene set enrichment analysis was conducted to investigate the potential functions of these lncRNAs.

Results: We attained 1,164 breast cancer samples from the TCGA database and 231 autophagy-related genes from the HAD database. Through correlation analysis, 179 autophagy-related lncRNAs were finally identified. Univariate Cox regression analysis and LASSO regression analysis further screened 18 prognosis-associated lncRNAs. The risk scoring model was constructed to divide patients into high-risk and low-risk groups. It was found that the low-risk group had better overall survival (OS) than those of the high-risk group. Then, the nomogram model including age, tumor stage, TNM stage and risk score was established. The evaluation index (C-index: 0.78, 3-year OS AUC: 0.813 and 5-year OS AUC: 0.785) showed that the nomogram had excellent predictive power. Subgroup analysis showed there were difference in OS between high-risk and low-risk patients in different subgroups (stage I-II, ER positive, Her-2 negative and non-TNBC subgroups; all P < 0.05). According to the results of gene set enrichment analysis, these lncRNAs were involved in the regulation of multicellular organismal macromolecule metabolic process in multicellular organisms, nucleotide excision repair, oxidative phosphorylation, and TGF-β signaling pathway.

Conclusions: We identified 18 autophagy-related lncRNAs with prognostic value in breast cancer, which may regulate tumor growth and progression in multiple ways.

LncRNA HIF1A-AS2 accelerates malignant phenotypes of renal carcinoma by modulating miR-30a-5p/SOX4 axis as a ceRNA

OBJECTIVE

Several reports have proposed that lncRNAs, as potential biomarkers, participate in the progression and growth of malignant tumors. HIF1A-AS2 is a novel lncRNA and potential biomarker, involved in the genesis and development of carcinomas. However, the molecular mechanism of HIF1A-AS2 in renal carcinoma is unclear.

METHODS

The relative expression levels of HIF1A-AS2 and miR-30a-5p were detected using RT-qPCR in renal carcinoma tissues and cell lines. Using loss-of-function and overexpression, the biological effects of HIF1A-AS2 and miR-30a-5p in kidney carcinoma progression were characterized. Dual luciferase reporter gene analysis and Western blot were used to detect the potential mechanism of HIF1A-AS2 in renal carcinomas.

RESULTS

HIF1A-AS2 was upregulated in kidney carcinoma tissues when compared with para-carcinoma tissues (P < 0.05). In addition, tumor size, tumor node mestastasis stage and differentiation were identified as being closely associated with HIF1A-AS2 expression (P < 0.05). Knockdown or overexpression of HIF1A-AS2 either restrained or promoted the malignant phenotype and WNT/β-catenin signaling in renal carcinoma cells (P < 0.05). MiR-30a-5p was downregulated in renal cancers and partially reversed HIF1A-AS2 functions in malignant renal tumor cells. HIF1A-AS2 acted as a microRNA sponge that actively regulated the relative expression of SOX4 in sponging miR-30a-5p and subsequently increased the malignant phenotypes of renal carcinomas. HIF1A-AS2 showed a carcinogenic effect and miR-30a-5p acted as an antagonist of the anti-oncogene effects in the pathogenesis of renal carcinomas.

CONCLUSIONS

The HIF1A-AS2-miR-30a-5p-SOX4 axis was associated with the malignant progression and development of renal carcinoma. The relative expression of HIF1A-AS2 was negatively correlated with the expression of miR-30a-5p, and was closely correlated with SOX4 mRNA levels in renal cancers.

The Role of LncRNAs in Translation

Long non-coding RNAs (lncRNAs), a group of non-protein coding RNAs with lengths of more than 200 nucleotides, exert their effects by binding to DNA, mRNA, microRNA, and proteins and regulate gene expression at the transcriptional, post-transcriptional, translational, and post-translational levels. Depending on cellular location, lncRNAs are involved in a wide range of cellular functions, including chromatin modification, transcriptional activation, transcriptional interference, scaffolding and regulation of translational machinery. This review highlights recent studies on lncRNAs in the regulation of protein translation by modulating the translational factors (i.e, eIF4E, eIF4G, eIF4A, 4E-BP1, eEF5A) and signaling pathways involved in this process as wells as their potential roles as tumor suppressors or tumor promoters.