Knockdown of LncRNA MAPT-AS1 inhibites proliferation and migration and sensitizes cancer cells to paclitaxel by regulating MAPT expression in ER-negative breast cancers

Long non-coding RNAs in drug resistance across the top five cancers: Update on their roles and mechanisms

Cancer drug resistance stands as a formidable obstacle in the relentless fight against the top five prevalent cancers: breast, lung, colorectal, prostate, and gastric cancers. These malignancies collectively account for a significant portion of cancer-related deaths worldwide. In recent years, long non-coding RNAs (lncRNAs) have emerged as pivotal players in the intricate landscape of cancer biology, and their roles in driving drug resistance are steadily coming to light. This comprehensive review seeks to underscore the paramount significance of lncRNAs in orchestrating resistance across a spectrum of different cancer drugs, including platinum drugs (DDP), tamoxifen, trastuzumab, 5-fluorouracil (5-FU), paclitaxel (PTX), and Androgen Deprivation Therapy (ADT) across the most prevalent types of cancer. It delves into the multifaceted mechanisms through which lncRNAs exert their influence on drug resistance, shedding light on their regulatory roles in various facets of cancer biology. A comprehensive understanding of these lncRNA-mediated mechanisms may pave the way for more effective and personalized treatment strategies, ultimately improving patient outcomes in these challenging malignancies.

Harnessing the potential of long non-coding RNAs in breast cancer: from etiology to treatment resistance and clinical applications

Breast cancer (BC) is the most common malignancy among women and a leading cause of cancer-related deaths of females worldwide. It is a complex and molecularly heterogeneous disease, with various subtypes that require different treatment strategies. Despite advances in high-resolution single-cell and multinomial technologies, distant metastasis and therapeutic resistance remain major challenges for BC treatment. Long non-coding RNAs (lncRNAs) are non-coding RNAs with more than 200 nucleotides in length. They act as competing endogenous RNAs (ceRNAs) to regulate post-transcriptional gene stability and modulate protein-protein, protein-DNA, and protein-RNA interactions to regulate various biological processes. Emerging evidence suggests that lncRNAs play essential roles in human cancers, including BC. In this review, we focus on the roles and mechanisms of lncRNAs in BC progression, metastasis, and treatment resistance, and discuss their potential value as therapeutic targets. Specifically, we summarize how lncRNAs are involved in the initiation and progression of BC, as well as their roles in metastasis and the development of therapeutic resistance. We also recapitulate the potential of lncRNAs as diagnostic biomarkers and discuss their potential use in personalized medicine. Finally, we provide lncRNA-based strategies to promote the prognosis of breast cancer patients in clinical settings, including the development of novel lncRNA-targeted therapies.

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

The prognostic value of copper homeostasis-related genes in breast cancer (BC) remains largely unexplored. We analyzed copper homeostasis-related gene profiles within The Cancer Genome Atlas Program breast cancer cohorts and performed correlation analysis to explore the relationship between copper homeostasis-related mRNAs (chrmRNA) and lncRNAs. Based on these results, we developed a gene signature-based risk assessment model to predict BC patient outcomes using Cox regression analysis and a nomogram, which was further validated in a cohort of 72 BC patients. Using the gene set enrichment analysis, we identified 139 chrmRNAs and 16 core mRNAs via the Protein-Protein Interaction network. Additionally, our copper homeostasis-related lncRNAs (chrlncRNAs) (PINK1.AS, OIP5.AS1, HID.AS1, and MAPT.AS1) were evaluated as gene signatures of the predictive model. Kaplan-Meier survival analysis revealed that patients with a high-risk gene signature had significantly poorer clinical outcomes. Receiver operating characteristic curves showed that the prognostic value of the chrlncRNAs model reached 0.795 after ten years. Principal component analysis demonstrated the capability of the model to distinguish between low- and high-risk BC patients based on the gene signature. Using the pRRophetic package, we screened out 24 anticancer drugs that exhibited a significant relationship with the predictive model. Notably, we observed higher expression levels of the four chrlncRNAs in tumor tissues than in the adjacent normal tissues. The correlation between our model and the clinical characteristics of patients with BC highlights the potential of chrlncRNAs for predicting tumor progression. This novel gene signature not only predicts the prognosis of patients with BC but also suggests that targeting copper homeostasis may be a viable treatment strategy.

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.

Landscape of NcRNAs involved in drug resistance of breast cancer

Breast cancer (BC) leads to the most amounts of deaths among women. Chemo-, endocrine-, and targeted therapies are the mainstay drug treatments for BC in the clinic. However, drug resistance is a major obstacle for BC patients, and it leads to poor prognosis. Accumulating evidences suggested that noncoding RNAs (ncRNAs) are intricately linked to a wide range of pathological processes, including drug resistance. Till date, the correlation between drug resistance and ncRNAs is not completely understood in BC. Herein, we comprehensively summarized a dysregulated ncRNAs landscape that promotes or inhibits drug resistance in chemo-, endocrine-, and targeted BC therapies. Our review will pave way for the effective management of drug resistance by targeting oncogenic ncRNAs, which, in turn will promote drug sensitivity of BC in the future.

A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO-Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients' response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.

Metformin and long non-coding RNAs in breast cancer

Breast cancer (BC) is the second most common cancer and cause of death in women. In recent years many studies investigated the association of long non-coding RNAs (lncRNAs), as novel genetic factors, on BC risk, survival, clinical and pathological features. Recent studies also investigated the roles of metformin treatment as the firstline treatment for type 2 diabetes (T2D) played in lncRNAs expression/regulation or BC incidence, outcome, mortality and survival, separately. This comprehensive study aimed to review lncRNAs associated with BC features and identify metformin-regulated lncRNAs and their mechanisms of action on BC or other types of cancers. Finally, metformin affects BC by regulating five BC-associated lncRNAs including GAS5, HOTAIR, MALAT1, and H19, by several molecular mechanisms have been described in this review. In addition, metformin action on other types of cancers by regulating ten lncRNAs including AC006160.1, Loc100506691, lncRNA-AF085935, SNHG7, HULC, UCA1, H19, MALAT1, AFAP1-AS1, AC026904.1 is described.

Tau Isoforms: Gaining Insight into MAPT Alternative Splicing

Tau microtubule-associated proteins, encoded by the MAPT gene, are mainly expressed in neurons participating in axonal transport and synaptic plasticity. Six major isoforms differentially expressed during cell development and differentiation are translated by alternative splicing of MAPT transcripts. Alterations in the expression of human Tau isoforms and their aggregation have been linked to several neurodegenerative diseases called tauopathies, including Alzheimer's disease, progressive supranuclear palsy, Pick's disease, and frontotemporal dementia with parkinsonism linked to chromosome 17. Great efforts have been dedicated in recent years to shed light on the complex regulatory mechanism of Tau splicing, with a perspective to developing new RNA-based therapies. This review summarizes the most recent contributions to the knowledge of Tau isoform expression and experimental models, highlighting the role of cis-elements and ribonucleoproteins that regulate the alternative splicing of Tau exons.

Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.

Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Genome instability is a hallmark of cancer, and the function of lncRNAs in regulating genomic stability has been gradually characterized. However, the prognostic value of lncRNAs related to genetic instability has not been found in breast cancer. Here we constructed a genetic instability-related lncRNA model including U62317.4, SEMA3B-AS1, MAPT-AS1, AC115837.2, LINC01269, AL645608.7, and GACAT2. This model can evaluate the risk and predict the survival outcomes of patients. Further analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immunity and cornified envelope formation pathways. In addition, M2 macrophages infiltrated more obviously in the high-risk group. In summary, lncRNAs related to genetic instability may influence the development of breast cancer through immune infiltration and keratinization. This study provides a wider insight into breast cancer development and treatment.

A genomic instability-related lncRNA model for predicting prognosis and immune checkpoint inhibitor efficacy in breast cancer

Breast cancer has overtaken lung cancer as the most frequently diagnosed cancer type and is the leading cause of death for women worldwide. It has been demonstrated in published studies that long non-coding RNAs (lncRNAs) involved in genomic stability are closely associated with the progression of breast cancer, and remarkably, genomic stability has been shown to predict the response to immune checkpoint inhibitors (ICIs) in cancer therapy, especially colorectal cancer. Therefore, it is of interest to explore somatic mutator-derived lncRNAs in predicting the prognosis and ICI efficacy in breast cancer patients. In this study, the lncRNA expression data and somatic mutation data of breast cancer patients from The Cancer Genome Atlas (TCGA) were downloaded and analyzed thoroughly. Univariate and multivariate Cox proportional hazards analyses were used to generate the genomic instability-related lncRNAs in a training set, which was subsequently used to analyze a testing set and combination of the two sets. The qRT-PCR was conducted in both normal mammary and breast cancer cell lines. Furthermore, the Kaplan–Meier and receiver operating characteristic (ROC) curves were applied to validate the predictive effect in the three sets. Finally, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to evaluate the association between genomic instability-related lncRNAs and immune checkpoints. As a result, a six-genomic instability-related lncRNA signature (U62317.4, MAPT-AS1, AC115837.2, EGOT, SEMA3B-AS1, and HOTAIR) was identified as the independent prognostic risk model for breast cancer patients. Compared with the normal mammary cells, the qRT-PCR showed that HOTAIR was upregulated while MAPT-AS1, EGOT, and SEMA3B-AS1 were downregulated in breast cancer cells. The areas under the ROC curves at 3 and 5 years were 0.711 and 0.723, respectively. Moreover, the patients classified in the high-risk group by the prognostic model had abundant negative immune checkpoint molecules. In summary, this study suggested that the prognostic model comprising six genomic instability-related lncRNAs may provide survival prediction. It is necessary to identify patients who are suitable for ICIs to avoid severe immune-related adverse effects, especially autoimmune diseases. This model may predict the ICI efficacy, facilitating the identification of patients who may benefit from ICIs.

The Mechanisms of lncRNA-Mediated Multidrug Resistance and the Clinical Application Prospects of lncRNAs in Breast Cancer

Simple Summary

Multidrug resistance (MDR) is a major cause of breast cancer (BC) chemotherapy failure. Long noncoding RNAs (lncRNAs) have been shown closely related to the chemoresistance of BC. In this work, the mechanisms of lncRNA-mediated MDR in BC were elaborated from eight sections, including apoptosis, autophagy, DNA repair, cell cycle, drug efflux, epithelial-mesenchymal transition, epigenetic modification and the tumor microenvironment. Additionally, we also discuss the clinical significance of lncRNAs, which may be biomarkers for diagnosis, therapy and prognosis.

Abstract

Breast cancer (BC) is a highly heterogeneous disease and presents a great threat to female health worldwide. Chemotherapy is one of the predominant strategies for the treatment of BC; however, multidrug resistance (MDR) has seriously affected or hindered the effect of chemotherapy. Recently, a growing number of studies have indicated that lncRNAs play vital and varied roles in BC chemoresistance, including apoptosis, autophagy, DNA repair, cell cycle, drug efflux, epithelial-mesenchymal transition (EMT), epigenetic modification and the tumor microenvironment (TME). Although thousands of lncRNAs have been implicated in the chemoresistance of BC, a systematic review of their regulatory mechanisms remains to be performed. In this review, we systematically summarized the mechanisms of MDR and the functions of lncRNAs mediated in the chemoresistance of BC from the latest literature. These findings significantly enhance the current understanding of lncRNAs and suggest that they may be promising prognostic biomarkers for BC patients receiving chemotherapy, as well as therapeutic targets to prevent or reverse chemoresistance.

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.

Autophagy related long non-coding RNA and breast cancer prognosis analysis and prognostic risk model establishment

Background

The role of autophagy-related long-stranded non-coding RNA (lncRNA) in breast cancer (BRCA) is unclear. We proposed to screen autophagy-related lncRNAs in BRCA and construct a prognostic risk assessment model to explore prognostic correlates.

Methods

We extracted BRCA lncRNAs from The Cancer Genome Atlas (TCGA) database and autophagy-related genes from the Human Autophagy Database (HADb), to screen for autophagy-related lncRNA pairs (ARLP) in BRCA. Single-factor Cox regression analysis and multi-factor Cox regression analysis were used to screen lncRNAs associated with BRCA prognosis, and risk models were established. We divided BRCA patients into high-risk and low-risk groups based on median risk scores. The single-sample gene set enrichment analysis (ssGSEA) algorithm was used to calculate the abundance of 28 immune cells in the TCGA-BRCA cohort and to analyze the relationship between the risk score and the level of immune cell infiltration by ARLP characteristics.

Results

Univariate Cox regression results showed that 42 ARLPs were significantly associated with overall survival (OS) in BRCA patients. Further multifactorial analysis showed that a total of 11 lncRNAs, including SEMA3B-AS1, ST7-AS1, AL136295.7, AC090912.1, LINC01871, AL136531.1, AC024361.1, OTUD6B-AS1, LINC01786, AL122010.1, and MAPT-AS1, were prognostically independent influencers of BRCA. The risk model developed was further validated as a new independent prognostic factor for BRCA patients by Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression analysis to calculate the risk score. In addition, the results of the relationship between risk score and immune infiltration showed that low risk score was associated with T-lymphocyte subpopulation.

Conclusions

Our study suggested that a risk model consisting of 11 autophagy-related lncRNAs can be used to assess the prognosis of BRCA patients.

A Three lncRNA Set: AC009975.1, POTEH-AS1 and AL390243.1 as Nodal Efficacy Biomarker of Neoadjuvant Therapy for HER-2 Positive Breast Cancer

Purpose

The study aimed to explore whether the expression of lncRNAs in primary tumors could predict nodal efficacy after neoadjuvant therapy (NAT) for HER2+ breast cancer.

Methods

Total RNA was extracted from HER2+ breast cancer tissues before NAT (n=103) and from 48 pairs of cancers and para-cancers tissues that did not receive NAT. Different lncRNAs were selected by microarray, validated by qPCR, and analyzed to illuminate their potential as nodal efficacy biomarkers after NAT.

Results

Our results demonstrated that three lncRNA sets, lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1, were up-regulated in non-apCR tissues. The AUC value was 0.789 (95%CI: 0.703-0.876). The multivariate logistic regression analysis identified the expression of lncRNA-AL390243.1 (OR 5.143; 95% CI: 1.570-16.847), tumor type (OR 0.144; 95% CI: 0.024-0.855), and nodal stage (OR 0.507; 95% CI: 0.289-0.888) as independent predictors for apCR after NAT in HER2+ patients (all p<0.05). Then the three predictors were used to create a predictive nomogram. The AUC value was 0.859 (95%CI: 0.790-0.929). The calibration curve showed a satisfactory fit between predictive and actual observation based on internal validation with a bootstrap resampling frequency of 1000. Patients with higher expression of lncRNA-AL390243.1 had worse survival. LncRNA-AL390243.1 was up-regulated more in the nodal positive subgroup than in the nodal negative subgroup (p=0.0271).

Conclusion

The lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1 were upregulated in non-apCR breast cancer tissues. These three lncRNAs might have the potential to be used as predictive biomarkers of nodal efficacy of HER2+ breast cancer. Further studies are required to illuminate the underlying molecular mechanisms further.

Tau Regulates Glioblastoma Progression, 3D Cell Organization, Growth and Migration via the PI3K-AKT Axis

Simple Summary

The Microtubule-associated protein Tau is expressed in different cancers; however, its role and prognostic value are still debated. In the present work, we evaluated the role of Tau in glioblastoma by down-regulating its expression in glioblastoma cells. We showed that Tau: (1) is required for tumor progression in nude mice; (2) is necessary for glioblastoma 3D cell organization, growth, and migration; and (3) regulates the PI3K/AKT signaling pathway.

Abstract

The Microtubule-Associated Protein Tau is expressed in several cancers, including low-grade gliomas and glioblastomas. We have previously shown that Tau is crucial for the 2D motility of several glioblastoma cell lines, including U87-MG cells. Using an RNA interference (shRNA), we tested if Tau contributed to glioblastoma in vivo tumorigenicity and analyzed its function in a 3D model of multicellular spheroids (MCS). Tau depletion significantly increased median mouse survival in an orthotopic glioblastoma xenograft model. This was accompanied by the inhibition of MCS growth and cell evasion, as well as decreased MCS compactness, implying N-cadherin mislocalization. Intracellular Signaling Array analysis revealed a defective activation of the PI3K/AKT pathway in Tau-depleted cells. Such a defect in PI3K/AKT signaling was responsible for reduced MCS growth and cell evasion, as demonstrated by the inhibition of the pathway in control MCS using LY294002 or Perifosine, which did not significantly affect Tau-depleted MCS. Finally, analysis of the glioblastoma TCGA dataset showed a positive correlation between the amount of phosphorylated Akt-Ser473 and the expression of MAPT RNA encoding Tau, underlining the relevance of our findings in glioblastoma disease. We suggest a role for Tau in glioblastoma by controlling 3D cell organization and functions via the PI3K/AKT signaling axis.

An Autophagy-related Long Non-coding RNA Signature for Breast Cancer

BACKGROUND

The most prevalent malignant tumor in women is breast cancer (BC). Autophagic therapies have been identified for their contribution in BC cell death. Therefore, the potential prognostic role of long non-coding RNA (lncRNA) related to autophagy in patients with BC was examined.

METHODS

The lncRNAs expression profiles were derived from The Cancer Genome Atlas (TCGA) database. Throughout univariate Cox regression and multivariate Cox regression test, lncRNA with BC prognosis have been differentially presented. We then defined the optimal cutoff point between high and low-risk groups. The receiver operating characteristic (ROC) curves were drawn to test this signature. In order to examine possible signaling mechanisms linked to these lncRNAs, the Gene Set Enrichment Analysis (GSEA) has been carried out.

RESULTS

Based on the lncRNA expression profiles for BC, a 9 lncRNA signature associated with autophagy was developed. The optimal cutoff value for high-risk and low-risk groups was used. The high-risk group had less survival time than the low-risk group. The result of this lncRNA signature was highly sensitive and precise. GSEA study found that the gene sets have been greatly enriched in many cancer pathways.

CONCLUSIONS

Our signature of 9 lncRNAs related to autophagy has prognostic value for BC, and these lncRNAs related to autophagy may play an important role in BC biology.

Establishment of a Novel Risk Score System of Immune Genes Associated With Prognosis in Esophageal Carcinoma

Background

Few studies have addressed the role of immune-related genes in the survival and prognosis of different esophageal cancer (EC) sub-types. We established two new prognostic model indexes by bioinformatics analysis to select patients with esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) who may benefit from immunotherapy.

Methods

Based on TCGA and ImmPort data sets, we screened immune genes differentially expressed between tumor and normal tissues in ESCC and EAC and analyzed the relationship between these genes and patient survival outcomes. We established the risk score models of immune-related genes in ESCC and EAC by multivariate COX regression analysis.

Results

We identified 12 and 11 immune-related differentially expressed genes associated with the clinical prognosis of ESCC and EAC respectively, based on which two prognostic risk score models of the two EC sub-types were constructed. It was found that the survival probability of patients with high scores was significantly lower than that of patients with low scores (p < 0.001). BMP1, EGFR, S100A12, HLA-B, TNFSF18, IL1B, MAPT and OXTR were significantly related to sex, TNM stage or survival outcomes of ESCC or EAC patients (p < 0.05). In addition, the risk score of ESCC was significantly correlated with the level of B cell infiltration in immune cells (p < 0.05).

Conclusions

The prognosis-related immune gene model indexes described herein prove to be useful prognostic biomarkers of the two EC sub-types in that they may provide a reference direction for looking for the beneficiaries of immunotherapy for EC patients.

Role of non-coding RNAs in modulating the response of cancer cells to paclitaxel treatment

Paclitaxel is a chemotherapeutic substance that is administered for treatment of an extensive spectrum of human malignancies. In spite of its potent short-term effects against tumor cells, resistance to paclitaxel occurs in a number of patients precluding its long-term application in these patients. Non-coding RNAs have been shown to influence response of cancer cells to this chemotherapeutic agent via different mechanisms. Mechanistically, these transcripts regulate expression of several genes particularly those being involved in the apoptotic processes. Lots of in vivo and in vitro assays have demonstrated the efficacy of oligonucleotide-mediated microRNAs (miRNA)/ long non-coding RNAs (lncRNA) silencing in enhancement of response of cancer cells to paclitaxel. Therefore, targeted therapies against non-coding RNAs have been suggested as applicable modalities for combatting resistance to this agent. In the present review, we provide a summary of studies which assessed the role of miRNAs and lncRNAs in conferring resistance to paclitaxel.

Mechanisms of Taxane Resistance

The taxane family of chemotherapy drugs has been used to treat a variety of mostly epithelial-derived tumors and remain the first-line treatment for some cancers. Despite the improved survival time and reduction of tumor size observed in some patients, many have no response to the drugs or develop resistance over time. Taxane resistance is multi-faceted and involves multiple pathways in proliferation, apoptosis, metabolism, and the transport of foreign substances. In this review, we dive deeper into hypothesized resistance mechanisms from research during the last decade, with a focus on the cancer types that use taxanes as first-line treatment but frequently develop resistance to them. Furthermore, we will discuss current clinical inhibitors and those yet to be approved that target key pathways or proteins and aim to reverse resistance in combination with taxanes or individually. Lastly, we will highlight taxane response biomarkers, specific genes with monitored expression and correlated with response to taxanes, mentioning those currently being used and those that should be adopted. The future directions of taxanes involve more personalized approaches to treatment by tailoring drug-inhibitor combinations or alternatives depending on levels of resistance biomarkers. We hope that this review will identify gaps in knowledge surrounding taxane resistance that future research or clinical trials can overcome.

Long non-coding RNAs lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 present as regulators of sentinel lymph node metastasis in breast cancer

Long non-coding RNAs (lncRNAs) participate in various biological processed involved in tumorigenesis, metastasis and proliferation. The aim of the present study was to identify candidate long non-coding RNAs (lncRNAs) involved in sentinel lymph node (SLN) metastasis in breast cancer. Specimens of SLNs were collected from patients with SLN metastasis via punch biopsy. Total RNA was extracted and RNA sequencing (RNA-seq) was conducted. Differential expression profiles of mRNAs and lncRNAs were obtained via bioinformatics analysis, and Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on differentially expressed mRNAs. The expression levels of lncRNAs were analyzed via reverse transcription-quantitative PCR (RT-qPCR), and the regulation network of the lncRNAs to downstream microRNAs (miRs) and mRNAs was predicted. Based on RNA-seq results, six differentially expressed candidate lncRNAs were identified in patients with and without SLN metastasis: lnc-ANGPTL1-3:3, lnc-GJA10-12:1, lnc-ACAN-2:1, lnc-ZPBP2-4:1, lnc-GATA3-16:1 and lnc-ACOX3-5:1. KEGG and GO analysis identified that the mitogen-activated protein kinase (MAPK) and PI3K/Akt signaling pathways were the most enriched pathways. After RT-qPCR analysis, lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 exhibited expression patterns that were consistent with those from RNA-seq. Moreover, receiver operating characteristic curve analysis demonstrated that lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 expression levels had high sensitivity and specificity in the diagnosis of SLN metastasis, and that their expression levels were upregulated in patients with axillary lymph node metastasis. Further analysis revealed that lnc-GJA10-12:1 and lnc-ANGPTL1-3:3 were commonly involved in regulating the miR-302 family, including miR-302d-3p and miR-302c-3p, which together targeted AKT1. Additionally, lnc-ANGPTL1-3:3 was predicted to target miR-520b to regulate MAP3K2 expression. lnc-GJA10-12:1 was also predicted to target miR-34a-5p to regulate MAP2K1 and MAP3K9 expression levels, as well as miR-449a to regulate MAP2K1 expression. The results of the present study suggested that lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 may potentially serve a role in SLN metastasis of breast cancer by regulating the PI3K/Akt and MAPK signaling pathways via targeting the miR-302 family, miR-520a-3p, miR-34a-5p and miR-449a. Thus, lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 in SLN may serve as potential markers of breast cancer metastasis.

Identification of long non‑coding RNAs expressed during the osteogenic differentiation of human bone marrow‑derived mesenchymal stem cells obtained from patients with ONFH

Long non-coding RNAs (lncRNAs) are crucial for the occurrence and development of numerous diseases. Although lncRNAs are involved in the biological activities of stem cells and play crucial roles in stem cell differentiation, the expression of specific lncRNAs during human bone marrow-derived mesenchymal stem cell (hBMSC) osteogenic differentiation in osteonecrosis of the femoral head (ONFH) and their regulatory roles have not yet been fully elucidated. To the best of our knowledge, the present study is the first to characterize lncRNA expression profiles during hBMSC osteogenic differentiation in ONFH using microarray analysis and RT-qPCR to confirm the microarray data. A total of 24 downregulated and 24 upregulated lncRNAs were identified and the results of RT-qPCR were found to be consistent with those of microarray analysis. Bioinformatics analyses, using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, were conducted to explore the possible mechanisms and identify the signaling pathways that the lncRNAs are involved in. GO analysis revealed significant changes in the intracellular organelle, Ras protein signal transduction and transferase activity. KEGG pathway analysis revealed that the lncRNAs were closely associated with fatty acid metabolism, apoptosis and the TGF-β signaling pathway. The overexpression of MAPT antisense RNA 1 (MAPT-AS1) was found to promote osteogenesis and inhibit the adipogenesis of hBMSCs at the cellular and mRNA levels. On the whole, the findings of the present study identified the lncRNAs and their roles in hBMSCs undergoing osteogenic differentiation in ONFH and provide a new perspective for the pathogenesis of ONFH.

Managing therapeutic resistance in breast cancer: from the lncRNAs perspective

Breast cancer (BC) is the most common female malignancy and the second leading cause of cancer-related death worldwide. In spite of significant advances in clinical management, the mortality of BC continues to increase due to the frequent occurrence of treatment resistance. Intensive studies have been conducted to elucidate the molecular mechanisms underlying BC therapeutic resistance, including increased drug efflux, altered drug targets, activated bypass signaling pathways, maintenance of cancer stemness, and deregulated immune response. Emerging evidence suggests that long noncoding RNAs (lncRNAs) are intimately involved in BC therapy resistance through multiple modes of action. Therefore, an in-depth understanding of the implication of lncRNAs in resistance to clinical therapies may improve the clinical outcome of BC patients. Here, we highlight the role and underlying mechanisms of lncRNAs in regulating BC treatment resistance with an emphasis on lncRNAs-mediated resistance in different clinical scenarios, and discuss the potential of lncRNAs as novel biomarkers or therapeutic targets to improve BC therapy response.

Long Non-Coding RNAs in Drug Resistance of Breast Cancer

Breast cancer (BC) is the most common cancer and the leading cause of death in women. Advances in early diagnosis and therapeutic strategies have decreased the mortality of BC and improved the prognosis of patients to some extent. However, the development of drug resistance has limited the success rate of systemic therapies. Long non-coding RNAs (lncRNAs) are involved in drug resistance in BC via various mechanisms, which contribute to a complex regulatory network. In this review, we summarize the latest findings on the mechanisms underlying drug resistance modulated by lncRNAs in BC. In addition, we discuss the potential clinical applications of lncRNAs as targeted molecular therapy against drug resistance in BC.

Long Noncoding RNA ADAMTS9-AS2 Inhibits the Proliferation, Migration, and Invasion in Bladder Tumor Cells

BACKGROUND

Bladder tumor is the fifth most prevalent tumor in men, yet its pathogenesis remains to be fully identified. Albeit a host of long noncoding RNAs (lncRNA) are emerging as new players involved in bladder tumor, the functions of many lncRNAs are still enigmatic. Reports on the deluge of studies on lncRNA ADAMTS9-AS2 have been convincingly associated with various tumors, but without mention of its roles in bladder tumor. Therefore, the roles of ADAMTS9-AS2 in bladder tumor cells were explored in our study.

MATERIALS AND METHODS

Quantitative real-time PCR assays and bioinformatic tools were applied in bladder tumor cells to identify the ADAMTS9-AS2 and ADAMTS9 expression. Western blot assays were performed to obtain the protein levels of bladder tumor related key molecules. CCK8, clonogenic assay, scratch wound healing, and transwell assays were separately applied to identify the functional roles of ADAMTS9-AS2 on proliferation, migration, and invasion in bladder tumor cells.

RESULTS

First, ADAMTS9-AS2 downregulation in bladder tumor cells was identified. Overexpression and knockdown experiments showed that ADAMTS9-AS2 expression was positively related to ADAMTS9, which is in accordance with the results from GEO database. Second, ADAMTS9-AS2 contributed to the inhibition of proliferation, migration, and invasion in bladder tumor cells. Third, ADAMTS9-AS2 was linked with PI3K/AKT/mTOR pathway related-molecules, several key autophagy, and apoptotic proteins.

CONCLUSION

Conjointly, our findings suggested that ADAMTS9-AS2 might function as a tumor suppressor to restrain the proliferation, migration, and invasion in bladder tumor cells. The potential mechanism of ADAMTS9-AS2 related to PI3K/AKT/mTOR signal pathway was further identified. Of note, we found that ADAMTS9-AS2 has a significant effect on several key autophagy and apoptotic proteins. Therefore, these observations will provide supportive evidence to ADAMTS9-AS2 as a potential biomarker in patients with bladder tumor.

The novel long non-coding RNA LATS2-AS1-001 inhibits gastric cancer progression by regulating the LATS2/YAP1 signaling pathway via binding to EZH2

Background

To explore the expression pattern and role of the novel long non-coding RNA LATS2 antisense transcript 1 (LATS2-AS1-001) in gastric cancer (GC).

Methods

qRT-PCR was applied to evaluate LATS2-AS1-001 expression and correlation with LATS2 in GC. In vitro experiments were performed to investigate the role of LATS2-AS1-001 in GC cells. RNA immunoprecipitation (RIP) was performed to assess the interaction between EZH2 and LATS2-AS1-001. LATS2/YAP1 signaling pathway proteins were detected by immunoblot. Oncomine and KMPLOT data analysis was conducted to assess the prognostic value of YAP1 in GC.

Results

Decreased expression levels of LATS2-AS1-001 and LATS2 were confirmed in 357 GC tissues compared with the normal mucosa. A strong positive correlation between LATS2-AS1-001 and LATS mRNA expression was found in Pearson Correlation analysis (r = 0.719, P < 0.001). Furthermore, ROC curve analysis revealed areas under the curves for LATS2-AS1-001 and LATS2 of 0.7274 and 0.6865, respectively (P < 0.001), which indicated that LATS2-AS1-001 and LATS could be used as diagnostic indicators in GC. Moreover, ectopic expression of LATS2-AS1-001 decreased cell viability, induced G0/G1 phase arrest, and inhibited cell migration and invasion in GC cells. Mechanistically, overexpressing LATS2-AS1-001 upregulated LATS2 and induced YAP1 phosphorylation via binding to EZH2. Oncomine and KMPLOT database analysis demonstrated YAP1 was highly expressed in human GC samples, and high YAP1 expression predicted poor patient prognosis in GC.

Conclusion

This study revealed that lncRNA LATS2-AS1-001 might serve as a potential diagnostic index in GC and act as a suppressor of GC progression.

Long non‑coding RNA SNHG1 promotes breast cancer progression by regulation of LMO4

Long non-coding RNA (lncRNA) small nucleolar RNA host gene 1 (SNHG1) was reported to be a critical regulator of tumorigenesis and is frequently deregulated in several cancer types. However, the exact mechanism by which SNHG1 contributes to breast cancer progression has not been fully elucidated. The identification of the molecular mechanism of SNHG1 is important for understanding the development of breast cancer and for improving the prognosis of the patients with this disease. In the present study, increased expression levels of SNHG1 were noted in breast cancer tumors following analysis of differentially expressed lncRNAs between 1,063 tumor and 102 normal tissues derived from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. This finding was further validated using 50 pairs of normal and tumor tissues that were collected from patients with breast cancer. Notably, SNHG1 expression was significantly correlated with estrogen receptor (ER)/progesterone receptor (PR) negative status (ER⁻/PR⁻) and advanced clinical stage in breast cancer tissues. Knockdown of SNHG1 led to cell growth arrest, cell cycle redistribution and cell migration inhibition of breast cancer cells. The miRDB database predicted that miR-573 interacts with SNHG1. RT-PCR confirmed the negative regulation of miR-573 levels by SNHG1 in breast cancer cells and the Dual-luciferase reporter assay confirmed their complementary binding. The repression of miR-573 by SNGH1 decreased LIM domain only 4 (LMO4) mRNA and protein expression levels in the breast cancer cell lines tested and induced the expression of cyclin D1 and cyclin E. In vitro experiments indicated that LMO4 overexpression could reverse siSNHG1-induced cell growth arrest, cell cycle redistribution and inhibition of cell migration in breast cancer cells. Moreover, the tumor xenograft model indicated that SNHG1 knockdown inhibited MDA-MB-231 growth in vivo and LMO4 overexpression reversed the tumor growth inhibition induced by SNHG1 knockdown. The present study demonstrated that SNHG1 acts as a novel oncogene in breast cancer via the SNHG/miR-573/LMO4 axis and that it could be a promising therapeutic target for patients with breast cancer.

Microtubule-associated protein tau (MAPT) is a promising independent prognostic marker and tumor suppressive protein in clear cell renal cell carcinoma

INTRODUCTION

Microtubule-associated protein tau (MAPT) overexpression has been linked to poor prognosis in several cancers. MAPT-AS1 is a long noncoding RNA existing at the antisense strand of the MAPT promoter region. The clinical significance of MAPT and MAPT-AS-1 in clear cell renal cell carcinoma (ccRCC) is unknown. This study aimed to assess the expression and function of MAPT and MAPT-AS1 in ccRCC.

METHODS

The expression of MAPT was determined using immunohistochemistry in ccRCC. The effects of MAPT knockdown on cell growth and invasion were evaluated and the interaction between MAPT and microtubule-associated protein tau antisense (MAPT-AS1) were analyzed. The expression of MAPT-AS1 was determined using quantitative reverse transcription polymerase chain reaction in ccRCC tissues. We investigated the effect of MAPT-AS1 knockdown on cell growth and invasion. We analyzed the regulation of MAPT and MAPT-AS1.

RESULTS

Immunohistochemistry in 135 ccRCC cases showed that 61% of the cases were positive for MAPT. Kaplan-Meier analysis showed that the low expression of MAPT was associated with poor overall survival after nephrectomy. Knockdown of MAPT enhanced cell growth and invasion. quantitative reverse transcription polymerase chain reaction revealed a positive correlation between MAPT and MAPT-AS1. The expression of MAPT-AS1 was higher in ccRCC tissue than in nonneoplastic kidney tissue. Kaplan-Meier analysis showed that the low expression of MAPT-AS1 was associated with poor overall survival after nephrectomy by in silico analysis. MAPT-AS1 knockdown promoted cell growth and invasion activity. P53 knockout suppressed the expression of MAPT and MAPT-AS1.

CONCLUSION

These results suggest that MAPT and MAPT-AS1 may be promising predictive biomarkers for survival and play a tumor-suppressive role in ccRCC.

Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent

BACKGROUND

DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk.

METHODS

Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women's Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided.

RESULTS

Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes.

CONCLUSION

Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

A novel long noncoding RNA HHIP-AS1 suppresses hepatocellular carcinoma progression through stabilizing HHIP mRNA

Aberrant expression of long non-coding RNAs (lncRNAs) has been observed in hepatocellular carcinoma (HCC) and confirmed to participate in the initiation and progression of HCC. In the present study, we identified a novel functional lncRNA, hedgehog-interacting protein antisense RNA 1 (HHIP-AS1). The expression levels of HHIP-AS1 were significantly decreased in HCC tissues. Downregulation of HHIP-AS1 expression correlated with larger tumor size, metastasis, and advanced TNM stage, and also predicted worse overall survival rate of HCC patients. Through performing overexpression and knockdown experiments, the biological function of HHIP-AS1 was identified to suppress HCC cell proliferation, migration and invasion, while promote apoptosis. Further investigation showed that HHIP-AS1 interacted with and positively regulated the stability of HHIP mRNA in a HuR-dependent manner. HHIP-AS1 exerted its suppressive effects through HHIP. Taken together, our findings demonstrate that HHIP-AS1 represses HCC progression by promoting HHIP expression, and indicate that the use of HHIP-AS1 may offer a promising treatment for HCC patients.

A prognostic 11 long noncoding RNA expression signature for breast invasive carcinoma

Breast cancer, the most common cancer in women worldwide, is associated with high mortality. The long non-coding RNAs (lncRNAs) with a little capacity of coding proteins is playing an increasingly important role in the cancer paradigm. Accumulating evidences demonstrate that lncRNAs have crucial connections with breast cancer prognosis while the studies of lncRNAs in breast cancer are still in its primary stage. In this study, we collected 1052 clinical patient samples, a comparatively large sample size, including 13 159 lncRNA expression profiles of breast invasive carcinoma (BRCA) from The Cancer Genome Atlas database to identify prognosis-related lncRNAs. We randomly separated all of these clinical patient samples into training and testing sets. In the training set, we performed univariable Cox regression analysis for primary screening and played the model for Robust likelihood-based survival for 1000 times. Then 11 lncRNAs with a frequency more than 600 were selected for prediction of the prognosis of BRCA. Using the analysis of multivariate Cox regression, we established a signature risk-score formula for 11 lncRNA to identify the relationship between lncRNA signatures and overall survival. The 11 lncRNA signature was validated both in the testing and the complete set and could effectively classify the high-/low-risk group with different OS. We also verified our results in different stages. Moreover, we analyzed the connection between the 11 lncRNAs and the genes of ESR1, PGR, and Her2, of which protein products (ESR, PGR, and HER2) were used to classify the breast cancer subtypes widely. The results indicated correlations between 11 lncRNAs and the gene of PGR and ESR1. Thus, a prognostic model for 11 lncRNA expression was developed to classify the BRAC clinical patient samples, providing new avenues in understanding the potential therapeutic methods of breast cancer.

Long non-coding RNAs are emerging targets of phytochemicals for cancer and other chronic diseases

The long non-coding RNAs (lncRNAs) are the crucial regulators of human chronic diseases. Therefore, approaches such as antisense oligonucleotides, RNAi technology, and small molecule inhibitors have been used for the therapeutic targeting of lncRNAs. During the last decade, phytochemicals and nutraceuticals have been explored for their potential against lncRNAs. The common lncRNAs known to be modulated by phytochemicals include ROR, PVT1, HOTAIR, MALAT1, H19, MEG3, PCAT29, PANDAR, NEAT1, and GAS5. The phytochemicals such as curcumin, resveratrol, sulforaphane, berberine, EGCG, and gambogic acid have been examined against lncRNAs. In some cases, formulation of phytochemicals has also been used. The disease models where phytochemicals have been demonstrated to modulate lncRNAs expression include cancer, rheumatoid arthritis, osteoarthritis, and nonalcoholic fatty liver disease. The regulation of lncRNAs by phytochemicals can affect multi-steps of tumor development. When administered in combination with the conventional drugs, phytochemicals can also produce synergistic effects on lncRNAs leading to the sensitization of cancer cells. Phytochemicals target lncRNAs either directly or indirectly by affecting a wide variety of upstream molecules. However, the potential of phytochemicals against lncRNAs has been demonstrated mostly by preclinical studies in cancer models. How the modulation of lncRNAs by phytochemicals produce therapeutic effects on cancer and other chronic diseases is discussed in this review.

Mechanisms of Antisense Transcription Initiation with Implications in Gene Expression, Genomic Integrity and Disease Pathogenesis

Non-coding antisense transcripts arise from the strand opposite the sense strand. Over 70% of the human genome generates non-coding antisense transcripts while less than 2% of the genome codes for proteins. Antisense transcripts and/or the act of antisense transcription regulate gene expression and genome integrity by interfering with sense transcription and modulating histone modifications or DNA methylation. Hence, they have significant pathological and physiological relevance. Indeed, antisense transcripts were found to be associated with various diseases including cancer, diabetes, cardiac and neurodegenerative disorders, and, thus, have promising potentials for prognostic and diagnostic markers and therapeutic development. However, it is not clearly understood how antisense transcription is initiated and epigenetically regulated. Such knowledge would provide new insights into the regulation of antisense transcription, and hence disease pathogenesis with therapeutic development. The recent studies on antisense transcription initiation and its epigenetic regulation, which are limited, are discussed here. Furthermore, we concisely describe how antisense transcription/transcripts regulate gene expression and genome integrity with implications in disease pathogenesis and therapeutic development.

Epigenetic Regulation by lncRNAs: An Overview Focused on UCA1 in Colorectal Cancer

Colorectal cancers have become the second leading cause of cancer-related deaths. In particular, acquired chemoresistance and metastatic lesions occurring in colorectal cancer are a major challenge for chemotherapy treatment. Accumulating evidence shows that long non-coding (lncRNAs) are involved in the initiation, progression, and metastasis of cancer. We here discuss the epigenetic mechanisms through which lncRNAs regulate gene expression in cancer cells. In the second part of this review, we focus on the role of lncRNA Urothelial Cancer Associated 1 (UCA1) to integrate research in different types of cancer in order to decipher its putative function and mechanism of regulation in colorectal cancer cells. UCA1 is highly expressed in cancer cells and mediates transcriptional regulation on an epigenetic level through the interaction with chromatin modifiers, by direct regulation via chromatin looping and/or by sponging the action of a diversity of miRNAs. Furthermore, we discuss the role of UCA1 in the regulation of cell cycle progression and its relation to chemoresistance in colorectal cancer cells.

Long Non-Coding RNAs as New Master Regulators of Resistance to Systemic Treatments in Breast Cancer

Predicting response to systemic treatments in breast cancer (BC) patients is an urgent, yet still unattained health aim. Easily detectable molecules such as long non-coding RNAs (lncRNAs) are the ideal biomarkers when they act as master regulators of many resistance mechanisms, or of mechanisms that are common to more than one treatment. These kinds of markers are pivotal in quasi-personalized treatment selection, and consequently, in improvement of outcome prediction. In order to provide a better approach to understanding development of disease and resistance to treatments, we reviewed current literature searching for lncRNA-associated systemic BC treatments including endocrine therapies, aromatase inhibitors, selective estrogen receptor modulators (SERMs), trastuzumab, paclitaxel, docetaxel, 5-fluorouracil (5-FU), anthracyclines, and cisplatin. We found that the engagement of lncRNAs in resistance is well described, and that lncRNAs such as urotelial carcinoma-associated 1 (UCA1) and regulator of reprogramming (ROR) are indeed involved in multiple resistance mechanisms, which offers tantalizing perspectives for wide usage of lncRNAs as treatment resistance biomarkers. Thus, we propose this work as the foundation for a wide landscape of functions and mechanisms that link more lncRNAs to resistance to current and new treatments in years of research to come.