Drug Resistance-Related Competing Interactions of lncRNA and mRNA across 19 Cancer Types

Utilizing non-coding RNA-mediated regulation of ATP binding cassette (ABC) transporters to overcome multidrug resistance to cancer chemotherapy

Multidrug resistance (MDR) is one of the primary factors that produces treatment failure in patients receiving cancer chemotherapy. MDR is a complex multifactorial phenomenon, characterized by a decrease or abrogation of the efficacy of a wide spectrum of anticancer drugs that are structurally and mechanistically distinct. The overexpression of the ATP-binding cassette (ABC) transporters, notably ABCG2 and ABCB1, are one of the primary mediators of MDR in cancer cells, which promotes the efflux of certain chemotherapeutic drugs from cancer cells, thereby decreasing or abolishing their therapeutic efficacy. A number of studies have suggested that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), play a pivotal role in mediating the upregulation of ABC transporters in certain MDR cancer cells. This review will provide updated information about the induction of ABC transporters due to the aberrant regulation of ncRNAs in cancer cells. We will also discuss the measurement and biological profile of circulating ncRNAs in various body fluids as potential biomarkers for predicting the response of cancer patients to chemotherapy. Sequence variations, such as alternative polyadenylation of mRNA and single nucleotide polymorphism (SNPs) at miRNA target sites, which may indicate the interaction of miRNA-mediated gene regulation with genetic variations to modulate the MDR phenotype, will be reviewed. Finally, we will highlight novel strategies that could be used to modulate ncRNAs and circumvent ABC transporter-mediated MDR.

New long noncoding RNA biomarkers and ceRNA networks on miR-616-3p in colorectal cancer: Bioinformatics-based study

Background

Cancer development is aided by the role of long noncoding RNAs (lncRNAs) that act as competing endogenous RNAs (ceRNAs) absorbing microRNAs (miRNAs). We aimed to discover a novel regulatory axis in colorectal cancer (CRC) and potential biomarkers based on miR-616-3p.

Materials and Methods

The gene expression omnibus database was mined for differentially expressed lncRNAs (DELs) and mRNAs. LncRNAs and mRNAs were predicted using the RegRNA and TargetScan databases. A combination of the ciBioPortal and Ensemble databases was used to locate the mRNAs. Cytoscape 3.7.1-built CeRNA networks. A quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to confirm the expression levels of these RNA molecules. Statistical analyses were implemented by GraphPad Prism 9.

Results

qRT-PCR showed (Linc01282, lnc-MYADM-1:1, and Zinc Finger Protein 347 [ZNF347]) were overexpressed whereas, (salt-inducible kinases 1 [SIK1], and miR-616-3p) were down regulated.

Conclusion

These results identify unique, unreported lncRNAs as CRC prognostic biomarkers, as well as prospective mRNAs as new treatment targets and predictive biomarkers for CRC. In addition, our study uncovered unexplored ceRNA networks that should be studied further in CRC.

A ten long noncoding RNA-based prognostic risk model construction and mechanism study in the basal-like immune-suppressed subtype of triple-negative breast cancer

Background

According to the Fudan University Shanghai Cancer Center (FUSCC) system, triple-negative breast cancer (TNBC) is divided into four stable subtypes: (I) luminal androgen receptor, (II) immunomodulatory, (III) basal-like immune-suppressed (BLIS), and (IV) mesenchymal-like. However, the treatment outcomes of the corresponding targeted therapies are unsatisfactory, especially for the BLIS subtype. Therefore, we aimed to identify the key long noncoding RNAs (lncRNAs) to construct a prognostic model for BLIS subtype and discover potential targets to explore potential therapeutic strategies in this study.

Methods

The FUSCC cohort was used to establish a prognostic risk model via least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The Cancer Genome Atlas (TCGA) cohort was then used to evaluate and verify the model. To understand the functional aspects of the model, functional, immune landscape, mutation, and drug sensitivity analyses were performed between high- and low-risk groups.

Results

Ten prognostic-related lncRNAs identified, including C5ORF66-AS2, DIO3OS, FZD10-DT, LINC00393, LNC-ERI1-32, LNC-FOXO1-2, LNC-SPARCL1-1, HCG23, LNC-MMD-4 and LNC-TMEM106C-6, were selected for risk score system construction. The results showed that the model constructed could divide the patients with BLIS subtype into two groups of high and low risk, and patients with higher risk scores had shorter recurrence-free survival. In addition, drug sensitivity analysis identified 3 compounds, including BMS-754807, cytochalasin b, and linifanib, that could have a potential therapeutic effect on patients with the BLIS subtype.

Conclusions

The risk prognosis model showed good prognostic value for the BLIS subtype patients, and the ten lncRNAs may be potential therapeutic targets.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

Insight into the regulatory mechanism of dynamic chromatin 3D interactions during cardiomyocyte differentiation in human

Cardiogenesis is an extremely complicated process involved with DNA regulatory elements, and trans factors regulate gene expression pattern spatiotemporally. Enhancers, as the well-known DNA elements, activate target gene expression by transcription factors (TFs) occupied to organize dynamic three-dimensional (3D) interactions, which when affected or interrupted might cause heart defects or diseases. In this study, we integrated transcriptome, 3D genome, and regulatome to reorganize the global 3D genome in cardiomyogenesis, showing a gradually decreased trend of both chromatin interactions and topological associating domains (TADs) during cardiomyocyte differentiation. And almost all of the chromatin interactions occurred within the same or between adjacent TADs involved with enhancers, indicating that dynamical rewiring of enhancer-related chromatin interactions in the continuous expansive TADs is closely correlated to cardiogenesis. Moreover, we found stage-specific interactions activate stage-specific expression to be involved within corresponding biological functions, and the stage-specific combined regulations of enhancers and binding TFs form connected networks to control stage-specific expression and biological processes, which promote cardiomyocyte differentiation. Finally, we identified markers based on regulatory networks, which might drive cardiac development. This study demonstrates the power of enhancer interactome combined with active TFs to reveal insights into transcriptional regulatory networks during cardiomyogenesis.

Soft Tissue Ewing Sarcoma Cell Drug Resistance Revisited: A Systems Biology Approach

Ewing sarcoma is a rare type of cancer that develops in the bones and soft tissues. Drug therapy represents an extensively used modality for the treatment of sarcomas. However, cancer cells tend to develop resistance to antineoplastic agents, thereby posing a major barrier in treatment effectiveness. Thus, there is a need to uncover the molecular mechanisms underlying chemoresistance in sarcomas and, hence, to enhance the anticancer treatment outcome. In this study, a differential gene expression analysis was conducted on high-throughput transcriptomic data of chemoresistant versus chemoresponsive Ewing sarcoma cells. By applying functional enrichment analysis and protein-protein interactions on the differentially expressed genes and their corresponding products, we uncovered genes with a hub role in drug resistance. Granted that non-coding RNA epigenetic regulators play a pivotal role in chemotherapy by targeting genes associated with drug response, we investigated the non-coding RNA molecules that potentially regulate the expression of the detected chemoresistance genes. Of particular importance, some chemoresistance-relevant genes were associated with the autonomic nervous system, suggesting the involvement of the latter in the drug response. The findings of this study could be taken into consideration in the clinical setting for the accurate assessment of drug response in sarcoma patients and the application of tailored therapeutic strategies.

A score of DNA damage repair pathway with the predictive ability for chemotherapy and immunotherapy is strongly associated with immune signaling pathway in pan-cancer

DNA damage repair (DDR) is critical in maintaining normal cellular function and genome integrity and is associated with cancer risk, progression, and therapeutic response. However, there is still a lack of a thorough understanding of the effects of DDR genes’ expression level in cancer progression and therapeutic resistance. Therefore, we defined a tumor-related DDR score (TR-DDR score), utilizing the expression levels of 20 genes, to quantify the tumor signature of DNA damage repair pathways in tumors and explore the possible function and mechanism for the score among different cancers. The TR-DDR score has remarkably predictive power for tumor tissues. It is a more accurate indicator for the response of chemotherapy or immunotherapy combined with the tumor-infiltrating lymphocyte (TIL) and G2M checkpoint score than the pre-existing predictors (CD8 or PD-L1). This study points out that the TR-DDR score generally has positive correlations with patients of advanced-stage, genome-instability, and cell proliferation signature, while negative correlations with inflammatory response, apoptosis, and p53 pathway signature. In the context of tumor immune response, the TR-DDR score strongly positively correlates with the number of T cells (CD4+ activated memory cells, CD8+ cells, T regs, Tfh) and macrophages M1 polarization. In addition, by difference analysis and correlation analysis, COL2A1, MAGEA4, FCRL4, and ZIC1 are screened out as the potential modulating factors for the TR-DDR score. In summary, we light on a new biomarker for DNA damage repair pathways and explore its possible mechanism to guide therapeutic strategies and drug response prediction.

Clinical outcomes and potential therapies prediction of subgroups based on a ferroptosis-related long non-coding RNA signature for gastric cancer

Background: Gastric cancer (GC) is one of the most aggressive malignant tumors worldwide. Ferroptosis is a kind of iron-dependent cell death, which is proved to be closely related to tumor progression. In this study, we aim at constructing a ferroptosis-related lncRNAs signature to predict the prognosis of GC and explore potential therapies.

Methods: Ferroptosis-Related LncRNAs Signature for GC patients (FRLSG) was constructed through univariate Cox regression, the LASSO algorithm, and multivariate Cox regression. Kaplan–Meier analysis, receiver operating characteristic curves, and risk score plot were applied to verify the predictive power of FRLSG. Gene Set Enrichment Analysis (GSEA) and immune infiltration analyses were conducted to explore the potential clinical value of the FRLSG. In addition, drug sensitivity prediction was applied to identify chemotherapeutic drugs with potential therapeutic effect.

Results: Five ferroptosis-related lncRNAs (AC004816.1, AC005532.1, LINC01357, AL355574.1 and AL049840.4) were identified to construct FRLSG, whose expression level in GC were confirmed by experimental validation. Kaplan-Meier curve and ROC curve proved the reliability and effectiveness of the FRLSG in predicting the prognosis for GC patients. Several immune-related pathways were enriched in the high-FRLSG group, and further immune infiltration analyses demonstrated the high immune infiltration status of the high-FRLSG group. In addition, 19 and 24 candidate drugs with potential therapeutic effect were identified for the high- and low-FRLSG groups, respectively.

Conclusions: FRLSG was an effective tool in predicting the prognosis of GC, which might help to prioritize potential therapeutics for GC patients.

LncRNA LINC00511 promotes COL1A1-mediated proliferation and metastasis by sponging miR-126-5p/miR-218-5p in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is currently the leading cause of cancer-related death worldwide. Long noncoding RNAs (lncRNAs) play key roles in tumor occurrence and development as crucial cancer regulators. The present study aimed to explore the molecular mechanism and regulatory network of Linc00511 in LUAD and to identify new potential therapeutic targets for LUAD.

Methods

Real-time quantitative polymerase chain reaction (RT–qPCR) was performed to determine the relative Linc00511 levels in LUAD tissues and cells. The proliferation, apoptosis, migration, and invasion abilities of LUAD cells were assessed by a Cell Counting Kit-8 (CCK-8) assay, a colony formation assay, flow cytometry, and a Transwell assay. Changes in hsa_miR-126-5p, hsa_miR-218-5p, and COL1A1 expression were analyzed using western blotting and RT–qPCR. Targeted binding between miR-126-5p/miR-218-5p and Linc00511 or COL1A1 was verified with a luciferase reporter system and confirmed by an RNA pulldown assay. The participation of the PI3K/AKT signaling pathway was confirmed via western blotting. Xenograft animal experiments were performed to detect the impact of Linc00511 on LUAD tumor growth in vivo.

Results

In the present work, we observed that Linc00511 was upregulated in LUAD tissues and cells. Loss/gain-of-function experiments indicated that knockdown of Linc00511 significantly inhibited LUAD cell proliferation, migration and invasion and promoted LUAD cell apoptosis, whereas overexpression of Linc00511 showed the opposite effects. In addition, we determined that Linc00511 promoted COL1A1-mediated cell proliferation and cell motility by sponging miR-126-5p and miR-218-5p. Moreover, Linc00511 activated the PI3K/AKT signaling pathway through upregulation of COL1A1. Finally, silencing of Linc00511 inhibited LUAD tumor growth in vivo.

Conclusions

Linc00511 acts as a competing endogenous RNA to regulate COL1A1 by targeting miR-126-5p and miR-218-5p, thereby promoting the proliferation and invasion of LUAD cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02070-3.

Identification and functional analysis of N6-methyladenine (m6 A)-related lncRNA across 33 cancer types

BACKGROUND

N6-methyladenosine (m⁶ A) plays an essential role in tumorigenesis and cancer progression. Long noncoding RNAs (lncRNAs) are discovered to be important targets of m⁶ A modification, and they play fundamental roles in diverse biological processes. However, there is still a lack of knowledge with regards to the association between m⁶ A and lncRNAs in human tumors.

METHODS

The relationship between lncRNAs and 21 m⁶ A regulators was comprehensively explored, through the integration of multi-omics data from M6A2Target, m6A-Atlas, and TCGA (The Cancer Genome Atlas). In order to explore the potential roles of m6A-related lncRNAs in human tumors, three applicable methods were introduced, which include the construction of ceRNA networks, drug sensitivity estimation, and survival analysis.

RESULTS

A substantial number of positive correlation events across 33 cancer types were found. Moreover, cancer-specific lncRNAs were associated with tissue specificity, and cancer-common lncRNAs were conserved in cancer-related biological function. In particular, the m⁶ A-related lncRNA FGD5-AS1 was found to be associated with cancer treatment, through its influence on cisplatin resistance in breast cancer patients. Finally, a user-friendly interface Lnc2m6A, which is enriched with various browsing sections resource for the exhibition of relationships and putative biogenesis between lncRNAs and m⁶ A modifications, is offered in http://hainmu-biobigdata.com/Lnc2m6A.

CONCLUSIONS

In summary, the results from this paper will provide a valuable resource that guides both mechanistic and therapeutic roles of m⁶ A-related lncRNAs in human tumors.

Long non-coding RNA NORAD/miR-224-3p/MTDH axis contributes to CDDP resistance of esophageal squamous cell carcinoma by promoting nuclear accumulation of β-catenin

BACKGROUND

Cis-diamminedichloro-platinum (CDDP)-based chemotherapy regimens are the most predominant treatment strategies for patients with esophageal squamous cell carcinoma (ESCC). Dysregulated long non-coding RNAs (lncRNAs) contribute to CDDP resistance, which results in treatment failure in ESCC patients. However, the majority of lncRNAs involved in CDDP resistance in ESCC remain to be elucidated.

METHODS

The public Gene Expression Omnibus (GEO) dataset GSE45670 was analysed to reveal potential lncRNAs involved in CDDP resistance of ESCC. Candidate upregulated lncRNAs were detected in ESCC specimens by qRT-PCR to identify crucial lncRNAs. Non-coding RNA activated by DNA damage (NORAD) was selected for further study. Kaplan-Meier analysis and a COX proportional regression model were performed to analyse the potential of NORAD for predicting prognosis of ESCC patients. The role of NORAD in CDDP resistance were determined by conducting gain and loss-of-function experiments in vitro. Fluorescence in situ hybridization (FISH) was performed to determine the subcellular location of NORAD in ESCC cells. A public GEO dataset and bioinformatic algorithms were used to predict the microRNAs (miRNAs) that might be latently sponged by NORAD. qRT-PCR was conducted to verify the expression of candidate miRNAs. Luciferase reporter and Argonaute-2 (Ago2)-RNA immunoprecipitation (RIP) assays were conducted to evaluate the interaction between NORAD and candidate miRNAs. A miRNA rescue experiment was performed to authenticate the NORAD regulatory axis and its effects on CDDP resistance in ESCC cells. Western blotting was conducted to confirm the precise downstream signalling pathway of NORAD. A xenograft mouse model was established to reveal the effect of NORAD on CDDP resistance in vivo.

RESULTS

The expression of NORAD was higher in CDDP-resistant ESCC tissues and cells than in CDDP-sensitive tissues and cells. NORAD expression was negatively correlated with the postoperative prognosis of ESCC patients who underwent CDDP-based chemotherapy. NORAD knockdown partially arrested CDDP resistance of ESCC cells. FISH showed that NORAD was located in the cytoplasm in ESCC cells. Furthermore, overlapping results from bioinformatic algorithms analyses and qRT-PCR showed that NORAD could sponge miR-224-3p in ESCC cells. Ago2-RIP demonstrated that NORAD and miR-224-3p occupied the same Ago2 to form an RNA-induced silencing complex (RISC) and subsequently regulated the expression of metadherin (MTDH) in ESCC cells. The NORAD/miR-224-3p/MTDH axis promoted CDDP resistance and progression in ESCC cells by promoting nuclear accumulation of β-catenin in vitro and in vivo.

CONCLUSIONS

NORAD upregulates MTDH to promote CDDP resistance and progression in ESCC by sponging miR-224-3p. Our results highlight the potential of NORAD as a therapeutic target in ESCC patients receiving CDDP-based chemotherapy.

Omics and Computational Modeling Approaches for the Effective Treatment of Drug-Resistant Cancer Cells

Chemotherapy is a mainstream cancer treatment, but has a constant challenge of drug resistance, which consequently leads to poor prognosis in cancer treatment. For better understanding and effective treatment of drug-resistant cancer cells, omics approaches have been widely conducted in various forms. A notable use of omics data beyond routine data mining is to use them for computational modeling that allows generating useful predictions, such as drug responses and prognostic biomarkers. In particular, an increasing volume of omics data has facilitated the development of machine learning models. In this mini review, we highlight recent studies on the use of multi-omics data for studying drug-resistant cancer cells. We put a particular focus on studies that use computational models to characterize drug-resistant cancer cells, and to predict biomarkers and/or drug responses. Computational models covered in this mini review include network-based models, machine learning models and genome-scale metabolic models. We also provide perspectives on future research opportunities for combating drug-resistant cancer cells.

Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance

Chemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transition, DNA repair, and cell cycle progression. Exploring the relationships between ncRNAs and drug resistance will not only contribute to our understanding of the mechanisms of drug resistance and provide ncRNA biomarkers of chemoresistance, but will also help realize personalized anticancer treatment regimens. Due to the high cost and low efficiency of biological experimentation, many researchers have opted to use computational methods to identify ncRNA biomarkers associated with drug resistance. In this review, we summarize recent discoveries related to ncRNA-mediated drug resistance and highlight the computational methods and resources available for ncRNA biomarkers involved in chemoresistance.

LncRNA as a multifunctional regulator in cancer multi-drug resistance

BACKGROUND

Malignant tumors have become the most dangerous disease in recent years. Chemotherapy is the most effective treatment for this disease; however, the problem of drug resistance has become even more common, which leads to the poor prognosis of patients suffering from cancers. Thus, necessary measures should be taken to address these problems at the earliest. Many studies have demonstrated that drug resistance is closely related to the abnormal expressions of long non-coding RNAs (lncRNAs).

METHODS AND RESULTS

This review aimed to summarize the molecular mechanisms underlying the association of lncRNAs and the development of drug resistance and to find potential strategies for the clinical diagnosis and treatment of cancer drug resistance. Studies showed that lncRNAs can regulate the expression of genes through chromatin remodeling, transcriptional regulation, and post-transcriptional processing. Furthermore, lncRNAs have been reported to be closely related to the occurrence of malignant tumors. In summary, lncRNAs have gained attention in related fields during recent years. According to previous studies, lncRNAs have a vital role in several different types of cancers owing to their multiple mechanisms of action. Different mechanisms have different functions that could result in different consequences in the same disease.

CONCLUSIONS

LncRNAs closely participated in cancer drug resistance by regulating miRNA, signaling pathways, proteins, cancer stem cells, pro- and ant-apoptosis, and autophagy. lncRNAs can be used as biomarkers of the possible treatment target in chemotherapy, which could provide solutions to the problem of drug resistance in chemotherapy in the future.

Analysis of ceRNA networks and identification of potential drug targets for drug-resistant leukemia cell K562/ADR

Background

Drug resistance is the main obstacle in the treatment of leukemia. As a member of the competitive endogenous RNA (ceRNA) mechanism, underlying roles of lncRNA are rarely reported in drug-resistant leukemia cells.

Methods

The gene expression profiles of lncRNAs and mRNAs in doxorubicin-resistant K562/ADR and sensitive K562 cells were established by RNA sequencing (RNA-seq). Expression of differentially expressed lncRNAs (DElncRNAs) and DEmRNAs was validated by qRT-PCR. The potential biological functions of DElncRNAs targets were identified by GO and KEGG pathway enrichment analyses, and the lncRNA-miRNA-mRNA ceRNA network was further constructed. K562/ADR cells were transfected with CCDC26 and LINC01515 siRNAs to detect the mRNA levels of GLRX5 and DICER1, respectively. The cell survival rate after transfection was detected by CCK-8 assay.

Results

The ceRNA network was composed of 409 lncRNA-miRNA pairs and 306 miRNA-mRNA pairs based on 67 DElncRNAs, 58 DEmiRNAs and 192 DEmRNAs. Knockdown of CCDC26 and LINC01515 increased the sensitivity of K562/ADR cells to doxorubicin and significantly reduced the half-maximal inhibitory concentration (IC₅₀) of doxorubicin. Furthermore, knockdown of GLRX5 and DICER1 increased the sensitivity of K562/ADR cells to doxorubicin and significantly reduced the IC₅₀ of doxorubicin.

Conclusions

The ceRNA regulatory networks may play important roles in drug resistance of leukemia cells. CCDC26/miR-140-5p/GLRX5 and LINC01515/miR-425-5p/DICER1 may be potential targets for drug resistance in K562/ADR cells. This study provides a promising strategy to overcome drug resistance and deepens the understanding of the ceRNA regulatory mechanism related to drug resistance in CML cells.

Paving the way for small-molecule drug discovery

Small-molecule drugs are organic compounds affecting molecular pathways by targeting important proteins, which have a low molecular weight, making them penetrate cells easily. Small-molecule drugs can be developed from leads derived from rational drug design or isolated from natural resources. As commonly used medications, small-molecule drugs can be taken orally, which enter cells to act on intracellular targets. These characteristics make small-molecule drugs promising candidates for drug development, and they are increasingly favored in the pharmaceutical market. Despite the advancements in molecular genetics and effective new processes in drug development, the drugs currently used in clinical practice are inadequate due to their poor efficacy or severe side effects. Therefore, developing new safe and efficient drugs is a top priority for disease control and curing.

Strongly preserved modules between cancer tissue and cell line contribute to drug resistance analysis across multiple cancer types

The existence and emergence of drug resistance in tumor cells is the main burden of cancer treatment. Most cancer drug resistance analyses are based entirely on cell line data and ignore the discordance between human tumors and cell lines, leading to biased preclinical model transformation. Based on cancer tissue data in TCGA and cancer cell line data in CCLE, this study identified and excluded non-preserved module (NP module) between cancer tissue and cell lines. We used strongly preserved module (SP module) for clinically relevant drug resistance analysis and identified 2068 "cancer-drug-module" pairs of 7 cancer types and 212 drugs based on data in GDSC. Furthermore, we identified potentially ineffective combination therapy (PICT) from multiple perspectives. Finally, we found 1608 sets of predictors that can predict drug response. These results provide insights and clues for the clinical selection of effective chemotherapy drugs to overcome cancer resistance in a new perspective.

Comprehensive characterization of a drug-resistance-related ceRNA network across 15 anti-cancer drug categories

Cancer is still a major health problem around the world. The treatment failure of cancer has largely been attributed to drug resistance. Competitive endogenous RNAs (ceRNAs) are involved in various biological processes and thus influence the drug sensitivity of cancers. However, a comprehensive characterization of drug-sensitivity-related ceRNAs has not yet been performed. In the present study, we constructed 15 ceRNA networks across 15 anti-cancer drug categories, involving 217 long noncoding RNAs (lncRNAs), 158 microRNAs (miRNAs), and 1,389 protein coding genes (PCGs). We found that these ceRNAs were involved in hallmark processes such as “self-sufficiency in growth signals,” “insensitivity to antigrowth signals,” and so on. We then identified an intersection ceRNA network (ICN) across the 15 anti-cancer drug categories. We further identified interactions between genes in the ICN and clinically actionable genes (CAGs) by analyzing the co-expressions, protein-protein interactions, and transcription factor-target gene interactions. We found that certain genes in the ICN are correlated with CAGs. Finally, we found that genes in the ICN were aberrantly expressed in tumors, and some were associated with patient survival time and cancer stage.

LncRNA APCDD1L-AS1 induces icotinib resistance by inhibition of EGFR autophagic degradation via the miR-1322/miR-1972/miR-324-3p-SIRT5 axis in lung adenocarcinoma

BACKGROUND

Epidermal growth factor receptor-tyrosinase kinase inhibitor (EGFR-TKI) resistance is the major obstacle in the treatment of lung adenocarcinoma (LUAD) patients harboring EGFR-sensitive mutations. However, the long non-coding RNAs (lncRNAs) related to EGFR-TKIs resistance and their functional mechanisms are still largely unknown. This study aimed to investigate the role and regulatory mechanism of lncRNA APCDD1L-AS1 in icotinib resistance of lung cancer.

METHODS

Molecular approaches including qRT-PCR, MTT assay, colony formation, RNA interference and cell transfection, RNA immunoprecipitation (RIP), dual luciferase reporter assay, RNA fluorescence in situ hybridization, TUNEL assay, flow cytometry, immunoblotting, xenograft model and transcriptome sequencing were used to investigate the mechanism of APCDD1L-AS1 in icotinib resistance.

RESULTS

A novel lncRNA, APCDD1L-AS1 was identified as the most significantly upregulated lncRNA in icotinib-resistant LUAD cells by the transcriptome sequencing and differential lncRNA expression analysis. We found that APCDD1L-AS1 not only promoted icotinib resistance, but also upregulated the protein expression level of EGFR. Mechanistically, APCDD1L-AS1 promoted icotinib resistance and EGFR upregulation by sponging with miR-1322/miR-1972/miR-324-3p to remove the transcription inhibition of SIRT5. Furthermore, SIRT5 elevated EGFR expression and activation by inhibiting the autophagic degradation of EGFR, finally promoting icotinib resistance. Consistently, the autophagy initiator rapamycin could decrease EGFR levels and increase the sensitivity of icotinib-resistant LUAD cells to icotinib.

CONCLUSION

APCDD1L-AS1 could promote icotinib resistance by inhibiting autophagic degradation of EGFR via the miR-1322/miR-1972/miR-324-3p-SIRT5 axis. The combination of autophagy initiator and EGFR-TKIs might serve as a potential new strategy for overcoming EGFR-TKIs resistance in LUAD patients.

LINC00488 stimulates the progression of esophageal cancer by targeting microRNA-485-5p

Esophageal cancer is the eighth most prevalent malignancy in the world and China has a high incidence of esophageal cancer. Previous studies have identified that LINC00488 is an oncogene; however, its role in esophageal cancer remains unclear. The present study detected the expression and biological functions of LINC00488 in the progression of esophageal cancer. LINC00488 levels in 45 esophageal cancer and matched paracancerous tissues were detected. The association between LINC00488 level, clinical indexes and overall survival rate of patients with esophageal cancer was analyzed. Using Cell Counting Kit-8, Transwell and wound healing assays, the influence of LINC00488 on the biological functions of OE19 and OE33 cells were assessed. The target gene of LINC00488, microRNA-485-5p (miRNA-485-5p), was predicted using bioinformatics databases. In addition, the role of miRNA-485-5p in the progression of esophageal cancer was evaluated using rescue experiments. LINC00488 was upregulated in esophageal cancer tissues and cell lines. A high level of LINC00488 was associated with lymphatic and distant metastasis and poor prognosis in patients with esophageal cancer. Silencing LINC00488 attenuated the viability, migration and wound healing of OE19 and OE33 cells. miRNA-485-5p was downregulated in esophageal cancer and low expression levels predicted a poor prognosis in these patients. In addition, miRNA-485-5p level was negatively correlated with that of LINC00488. Rescue experiments showed that knockdown of miRNA-485-5p reversed the attenuated proliferation and migration of esophageal cancer cells with LINC00488-knockdown. In conclusion, LINC00488 aggravated the malignant progression of esophageal cancer by targeting miRNA-485-5p.

Inferences of individual differences in response to tripterysium glycosides across patients with Rheumatoid arthritis using a novel ceRNA regulatory axis

BACKGROUND

To identify biomarkers for guiding therapy and predicting clinical response of Tripterysium Glycosides Tablets (TGT) treatment is an urgent task due to individual differences in TGT response across rheumatoid arthritis (RA) patients. Competing endogenous RNA (ceRNA) regulatory system may influence drug response with involvement in diverse biological processes. Herein, we aimed to identify a TGT response-related ceRNA axis.

METHODS

A TGT response-related ceRNA axis was screened according to clinical cohort-based RNA expression profiling, lncRNA-mRNA coexpression, and ceRNA network analyses. Its clinical relevance was evaluated by computational modeling. Regulatory mechanisms of ceRNA axis were also experimentally investigated.

RESULTS

The ceRNA regulatory axis combined with lncRNA ENST00000494760, miR-654-5p, and C1QC was identified as a candidate biomarker for RA patients' response to TGT. Both ENST00000494760 and C1QC mRNA expression were significantly lower, while miR-654-5p expression was dramatically higher in TGT responders than nonresponders. Its clinical relevance was verified by computational modeling based on both independent clinical validation cohort and collagen-induced arthritis (CIA) mice. Mechanistically, miR-654-5p directly bound to the 3'-untranslated region of both ENST00000494760 and C1QC mRNA to inhibit their expression. Moreover, miR-654-5p suppressed C1QC mRNA expression, but ENST00000494760 bound to miR-654-5p and relieved its repression on C1QC mRNA, leading to RA aggressive progression and weak TGT response.

CONCLUSIONS

LncRNA ENST00000494760 overexpression may sponge miR-654-5p to promote C1QC expression in RA patients. This novel ceRNA axis may serve as a biomarker for screening the responsive RA patients to TGT treatment, which will allow improved personalized healthcare.

Long noncoding RNA LINC00844-mediated molecular network regulates expression of drug metabolizing enzymes and nuclear receptors in human liver cells

Noncoding RNAs, such as long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), regulate gene expression in many physiological and pathological processes, including drug metabolism. Drug metabolizing enzymes (DMEs) are critical components in drug-induced liver toxicity. In this study, we used human hepatic HepaRG cells treated with 5 or 10 mM acetaminophen (APAP) as a model system and identified LINC00844 as a toxicity-responsive lncRNA. We analyzed the expression profiles of LINC00844 in different human tissues. In addition, we examined the correlations between the levels of LINC00844 and those of key DMEs and nuclear receptors (NRs) for APAP metabolism in humans. Our results showed that lncRNA LINC00844 is enriched in the liver and its expression correlates positively with mRNA levels of CYP3A4, CYP2E1, SULT2A1, pregnane X receptor (PXR), and hepatocyte nuclear factor (HNF) 4α. We demonstrated that LINC00844 regulates the expression of these five genes in HepaRG cells using gain- and loss-of-function assays. Further, we discovered that LINC00844 is localized predominantly in the cytoplasm and acts as an hsa-miR-486-5p sponge, via direct binding, to protect SULT2A1 from miRNA-mediated gene silencing. Our data also demonstrated a functional interaction between LINC00844 and hsa-miR-486-5p in regulating DME and NR expression in HepaRG cells and primary human hepatocytes. We depicted a LINC00844-mediated regulatory network that involves miRNA and NRs and influences DME expression in response to APAP toxicity.

Identification of drug resistance associated ncRNAs based on comprehensive heterogeneous network

AIMS

Chemotherapy and molecularly targeted therapy are main strategies for treatment of cancers. However, long-term treatment makes cancer cells acquire resistance to anti-cancer drugs, which severely limits the effects of cancer treatment. NcRNAs, especially miRNAs and lncRNAs, have been reported to play key roles in drug resistance and could restore drug responses in resistant cells.

MAIN METHODS

We presented a network-based framework to systematically identify drug resistance associated miRNAs and lncRNAs. First, we constructed a comprehensive heterogeneous miRNA-lncRNA regulatory network through integrating curated miRNA regulations to lncRNA, and significantly co-expressed miRNA-miRNA, lncRNA-lncRNA and miRNA-lncRNA interactions for each cancer type. Second, random walk with restart (RWR) was utilized to identify novel drug resistance associated ncRNAs.

KEY FINDINGS

We predicted 470 associations of 34 miRNAs and 79 lncRNAs for 27 drugs in 10 cancer types. In addition, leave-one-out cross validation (LOOCV) demonstrated the effectiveness of the proposed approach. Next, we also demonstrated that the integrated heterogeneous cancer-specific network achieved better performance than the general curated miRNA-lncRNA regulatory network. What's more, we found that the drug resistance associated ncRNAs validated by high-throughput technology was also a reliable source for prediction.

SIGNIFICANCE

We proposed a new framework to identify novel and reliable drug resistance associated ncRNAs, which provides new perspectives for drug resistance mechanism and new guidance for clinical cancer treatment.

LncRNA GMDS-AS1 inhibits lung adenocarcinoma development by regulating miR-96-5p/CYLD signaling

According to the global cancer statistic, lung cancer is one of the most dangerous tumors, which poses a serious threat to human health. Exploration the mechanism of lung cancer and new targeted therapeutic measures is always the hot topic. Long noncoding RNA (lncRNA) is an important factor affecting the development of tumors. However, the research on the mechanism of lncRNA in the progress of lung cancer needs to be further expanded. In this study, we found that the expression of lncRNA GMDS-AS1 was significantly reduced in lung adenocarcinoma (LUAD) tissues and cells. Upregulated GMDS-AS1 can significantly inhibit the proliferation of LUAD cells and promote cell apoptosis in vitro and in vivo. The results indicate that GMDS-AS1 acts as a tumor suppressor gene to affect the development of LUAD. Further studies revealed that GMDS-AS1 is a target gene of miR-96-5p, and GMDS-AS1 regulates proliferation and apoptosis of LUAD cells in association with miR-96-5p. In addition, we also confirmed that CYLD lysine 63 deubiquitinase (CYLD) is also a target gene of miR-96-5p. Through various validations, we confirmed that GMDS-AS1 can act as a ceRNA to upregulate the expression of CYLD by sponging miR-96-5p. Moreover, the intervention of GMDS-AS1/miR-96-5p/CYLD network can regulate the proliferation and apoptosis of LUAD cells. In this study, we revealed that the GMDS-AS1/miR-96-5p/CYLD network based on ceRNA mechanism plays an important role in the development of LUAD and provides a new direction and theoretical basis for targeted therapy of LUAD.

Systematic identification of dysregulated lncRNAs associated with platinum-based chemotherapy response across 11 cancer types

Aberrant expression of long non-coding RNAs (lncRNAs) leads to the development of chemoresistance by regulating a series of biological processes, which is one of the major obstacles in the cancer treatment. This study aimed to identify some key lncRNAs that are associated with platinum-based chemoresistance in multiple cancers. Regulating the expression levels of these lncRNAs can enhance the sensitivity of patients to chemotherapy drugs and improve the therapeutic effect of cancer. By systematically analyzing 648 samples regarding platinum drug response from the Cancer Genome Atlas (TCGA), we have identified 32 dysregulated lncRNAs across 11 cancer types that could affect platinum-based chemotherapy response, of which 78.125% (25/32) were significantly down-regulated in drug-resistant samples. Drug response prediction model that had been constructed based on the expression pattern of these dysregulated lncRNAs could accurately predict the chemotherapy response of tumor patients, and the area under the curve (AUC) was between 0.8034 and 0.9984. In particular, all of these dysregulated lncRNAs that we identified were cancer-specific. They were significantly associated with the survival of tumor patients and could serve as cancer-specific biomarkers for prognosis. In conclusion, this study will contribute to improving the drug resistance of tumor patients during chemotherapy, and it is of real significance for selecting effective chemotherapy drugs and achieving precision medicine.