LncRNA as a multifunctional regulator in cancer multi-drug resistance

LncRNA MAGI2-AS3-Encoded Polypeptide Restrains the Proliferation and Migration of Breast Cancer Cells

Accumulating articles have reported the coding potential of long non-coding RNAs (lncRNAs). However, only a few lncRNAs-encoded peptides have been studied. Breast cancer (BRCA) progression-related gene modules were determined by weighted gene co-expression network analysis (WGCNA). Cell viability, proliferation, and migration capacities were assessed by Cell counting kit-8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU), and transwell assays. Immunofluorescence (IF) assay was implemented to observe protein expression. Co-immunoprecipitation (Co-IP) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) were employed to analyze MAGI2 antisense RNA 3 (MAGI2-AS3)-ORF5-interacted proteins. WGCNA identified that MEpurple and MEblack modules were significantly negatively correlated with T stage in BRCA patients. MAGI2-AS3 was screened as one of the differentially expressed (DE) lncRNAs with translational potential in MEblack and MEpurple modules in BRCA. The data in The Cancer Genome Atlas (TCGA) uncovered that MAGI2-AS3 abundance was significantly decreased in invasive BRCA patients, and it had high diagnostic and prognostic values. MAGI2-AS3-ORF5 notably restrained BRCA cell viability, proliferation, and migration. Mechanically, MAGI2-AS3-ORF5 might affect the progression of BRCA cells by binding to extracellular matrix (ECM)-related proteins. MAGI2-AS3-ORF5 played an anti-tumor role by inhibiting BRCA cell viability, proliferation, and migration. MAGI2-AS3-ORF5 might modulate BRCA cell migration through ECM-associated proteins.

Evaluation of expression level of BANCR, MALAT1 and FER1L4 and their target genes in coumarin-treated AGS cell line

Because long non-coding RNAs (lncRNAs) can affect several interconnected processes, its value as a predictive marker for gastric cancer has been demonstrated. Coumarin - a natural compound known to contain some beneficial antitumor qualities - was tested for its effects on AGS gastric cancer cells. In this study, we investigated the expression level of selected cellular lncRNAs (BANCR, MALAT1 and FER1L4) and their target genes (PTEN, p-PI3K and p-AKT) in coumarin-treated AGS cell line. The expressions of the three lncRNAs: BANCR, MALAT1 and FER1L4, as well as their specified targets, PTEN, PI3K and AKT, were measured by qRT-PCR. To gauge the impact of coumarin on the AGS cells, a MTT assay was utilized. A Western blot has been employed to assess variations in PTEN, p-PI3K, and p-AKT expression. The experiment's results showed that AGS viability diminished with increasing doses of coumarin. Compared to the control cells, the cells exposed to coumarin had showed reduced levels of mRNAs which are known targets of the lncRNA BANCR. At the same time, levels of lncRNAs MALAT1 and FER1L4 within coumarin group have been higher comparing to those within control group. Additionally, the Western blot analysis revealed that the coumarin-treated cells expressed lower levels of p-PI3K, PTEN as well as p-AKT compared to control group. This information points to coumarin being a possible option in a treatment regimen for gastric cancer due to its ability to affect lncRNAs and the molecules they target.

Long Non-Coding RNA Levels Are Modulated in Schistosoma mansoni following In Vivo Praziquantel Exposure

Schistosomiasis is a disease caused by trematodes of the genus Schistosoma that affects over 200 million people worldwide. For decades, praziquantel (PZQ) has been the only available drug to treat the disease. Despite recent discoveries that identified a transient receptor ion channel as the target of PZQ, schistosome response to this drug remains incompletely understood, since effectiveness relies on other factors that may trigger a complex regulation of parasite gene expression. Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nucleotides with low or no protein-coding potential that play important roles in S. mansoni homeostasis, reproduction, and fertility. Here, we show that in vivo PZQ treatment modulates lncRNA levels in S. mansoni. We re-analyzed public RNA-Seq data from mature and immature S. mansoni worms treated in vivo with PZQ and detected hundreds of lncRNAs differentially expressed following drug exposure, many of which are shared among mature and immature worms. Through RT-qPCR, seven out of ten selected lncRNAs were validated as differentially expressed; interestingly, we show that these lncRNAs are not adult worm stage-specific and are co-expressed with PZQ-modulated protein-coding genes. By demonstrating that parasite lncRNA expression levels alter in response to PZQ, this study unravels an important step toward elucidating the complex mechanisms of S. mansoni response to PZQ.

lncRNA-microRNA axis in cancer drug resistance: particular focus on signaling pathways

Cancer drug resistance remains a formidable challenge in modern oncology, necessitating innovative therapeutic strategies. The convergence of intricate regulatory networks involving long non-coding RNAs, microRNAs, and pivotal signaling pathways has emerged as a crucial determinant of drug resistance. This review underscores the multifaceted roles of lncRNAs and miRNAs in orchestrating gene expression and cellular processes, mainly focusing on their interactions with specific signaling pathways. Dysregulation of these networks leads to the acquisition of drug resistance, dampening the efficacy of conventional treatments. The review highlights the potential therapeutic avenues unlocked by targeting these non-coding RNAs. Developing specific inhibitors or mimics for lncRNAs and miRNAs, alone or in combination with conventional chemotherapy, emerges as a promising strategy. In addition, epigenetic modulators, immunotherapies, and personalized medicine present exciting prospects in tackling drug resistance. While substantial progress has been made, challenges, including target validation and safety assessment, remain. The review emphasizes the need for continued research to overcome these hurdles and underscores the transformative potential of lncRNA-miRNA interplay in revolutionizing cancer therapy.

Long non-coding RNAs PTENP1, GNG12-AS1, MAGI2-AS3 and MEG3 as tumor suppressors in breast cancer and their associations with clinicopathological parameters

BACKGROUND

Breast cancer is the most commonly occurring cancer worldwide and is the main cause of death from cancer in women. Novel biomarkers are highly warranted for this disease.

OBJECTIVE

Evaluation of novel long non-coding RNAs biomarkers for breast cancer.

METHODS

The study comprised the analysis of the expression of 71 candidate lncRNAs via screening, six of which (four underexpressed, two overexpressed) were validated and analyzed by qPCR in tumor tissues associated with NST breast carcinomas, compared with the benign samples and with respect to their clinicopathological characteristics.

RESULTS

The results indicated the tumor suppressor roles of PTENP1, GNG12-AS1, MEG3 and MAGI2-AS3. Low levels of both PTENP1 and GNG12-AS1 were associated with worsened progression-free and overall survival rates. The reduced expression of GNG12-AS1 was linked to the advanced stage. A higher grade was associated with the lower expression of PTENP1, GNG12-AS1 and MAGI2-AS3. Reduced levels of both MEG3 and PTENP1 were linked to Ki-67 positivity. The NRSN2-AS1 and UCA1 lncRNAs were overexpressed; higher levels of UCA1 were associated with multifocality.

CONCLUSIONS

The results suggest that the investigated lncRNAs may play important roles in breast cancer and comprise a potential factor that should be further evaluated in clinical studies.

LncRNA HCG11 enhances the chemosensitivity of non-small cell lung cancer cells to Gemcitabine via miR-17-5p/p21 axis

BACKGROUND

This study investigated the inhibitory effects of lncRNA HLA Complex Group 11 (HCG11) on non-small cell lung cancer (NSCLC) and the molecular mechanisms.

RESEARCH DESIGN AND METHODS

Bioinformatics analysis was conducted to determine the downstream targeted gene miR-17-5p/p21 and predict their binding sites. qRT-PCR and Western blot were used to detect expression levels, and dual luciferase and RIP assays were adopted to verify binding relationship.

RESULTS

The lncRNA HCG11/miR-17-5p/p21 axis was found to regulate drug resistance, proliferation, apoptosis, and cell cycle of A549 and A549-Gemcitabine (GEM) cells. HCG11 acted as a ceRNA binding to miR-17-5p, which repressed p21 expression in turn. In vivo experiments demonstrated that HCG11 hindered tumor growth. Therefore, lncRNA HCG11, by targeting the miR-17-5p/p21 axis, suppressed GEM resistance and malignant progression of NSCLC cells.

CONCLUSIONS

This study provides a reference for investigating the potential value of lncRNA HCG11 in the diagnosis of NSCLC and finding potential targets against clinical chemotherapeutic resistance in NSCLC.

METTL3-mediated m6A modification of lnc KCNQ1OT1 promotes doxorubicin resistance in breast cancer by regulating miR-103a-3p/MDR1 axis

Doxorubicin (DOX) resistance in breast cancer (BC) poses a huge challenge for the therapeutic effect on BC. Lnc KCNQ1OT1 play crucial roles in chemotherapy resistance. However, the role and mechanism of lnc KCNQ1OT1 in DOX resistance BC have not been investigated, which merits further exploration. Based on MCF-7 and MDA-MB-231 cells, MCF-7/DOX and MDA-MB-231/DOX cells were established using gradient concentrations of DOX. IC50 values and cell viability were determined using MTT. Cell proliferation was investigated by colony formation. Flow cytometry was performed to examine cell apoptosis and cell cycle. Gene expression was examined using qRT-PCR and western blot. The interactions among METTL3, lnc KCNQ1OT1, miR-103a-3p, and MDR1 were validated with MeRIP-qPCR, RIP, and dual-luciferase reporter gene assays. The results showed that Lnc KCNQ1OT1 was highly expressed in DOX-resistant BC cells, and lnc KCNQ1OT1 depletion could enhance DOX sensitivity in BC cells and DOX-resistant BC cells. Besides, lnc KCNQ1OT1 was modulated by MELLT3 in the manner of m6A modification. MiR-103a-3p could interact with lnc KCNQ1OT1 and MDR1. Overexpression of MDR1 abolished the impacts of lnc KCNQ1OT1 depletion on DOX resistance in BC. In conclusion, our results unveiled that in BC cells and DOX-resistant BC cells, lnc KCNQ1OT1 could be mediated by METTL3 through m6A modification to elevate and stabilize its expression, further inhibiting miR-103a-3p/MDR1 axis to promote DOX resistance, which might provide novel thought to overcome DOX resistance in BC.

Current insights into the oncogenic roles of lncRNA LINC00355

Long noncoding RNAs (lncRNAs) are a class of nonprotein-coding transcripts that are longer than 200 nucleotides. LINC00355 is a lncRNA located on chromosome 13q21.31 and is consistently upregulated in various cancers. It regulates the expression of downstream genes at both transcriptional and posttranscriptional levels, including eight microRNAs (miR-15a-5p, miR-34b-5p, miR-424-5p, miR-1225, miR-217-5p, miR-6777-3p, miR-195, and miR-466) and three protein-coding genes (ITGA2, RAD18, and UBE3C). LINC00355 plays a role in regulating various biological processes such as cell cycle progression, proliferation, apoptosis, epithelial-mesenchymal transition, invasion, and metastasis of cancer cells. It is involved in the regulation of the Wnt/β-catenin signaling pathway and p53 signaling pathway. Upregulation of LINC00355 has been identified as a high-risk factor in cancer patients and its increased expression is associated with poorer overall survival, recurrence-free survival, and disease-free survival. LINC00355 upregulation has been linked to several unfavorable clinical characteristics, including advanced tumor node metastasis and World Health Organization stages, reduced Karnofsky Performance Scale scores, increased tumor size, greater depth of invasion, and more extensive lymph node metastasis. LINC00355 induces chemotherapy resistance in cancer cells by regulating five downstream genes, namely HMGA2, ABCB1, ITGA2, WNT10B, and CCNE1 genes. In summary, LINC00355 is a potential oncogene with great potential as a diagnostic marker and therapeutic target for cancer.

RP11-789C1.1 inhibits gastric cancer cell proliferation and accelerates apoptosis via the ATR/CHK1 signaling pathway

BACKGROUND

Long non-coding RNAs (lncRNAs) plays an important role in the progression of gastric cancer (GC). Their involvement ranges from genetic regulation to cancer progression. However, the mechanistic roles of RP11-789C1.1 in GC are not fully understood.

METHODS

We identified the expression of lncRNA RP11-789C1.1 in GC tissues and cell lines by real-time fluorescent quantitative polymerase chain reaction. A series of functional experiments revealed the effect of RP11-789C1.1 on the proliferation of GC cells. In vivo experiments verified the effect of RP11-789C1.1 on the biological behavior of a GC cell line. RNA pull-down unveiled RP11-789C1.1 interacting proteins. Western blot analysis indicated the downstream pathway changes of RP11-789C1.1, and an oxaliplatin dosing experiment disclosed the influence of RP11-789C1.1 on the drug sensitivity of oxaliplatin.

RESULTS

Our results demonstrated that RP11-789C1.1 inhibited the proliferation of GC cells and promoted the apoptosis of GC cells. Mechanistically, RP11-789C1.1 inhibited checkpoint kinase 1 (CHK1) phosphorylation by binding ataxia-telangiectasia mutated and Rad3 related (ATR), a serine/threonine-specific protein kinase, promoted GC apoptosis, and mediated oxaliplatin sensitivity.

CONCLUSION

In general, we discovered a tumor suppressor molecule RP11-789C1.1 and confirmed its mechanism of action, providing a theoretical basis for targeted GC therapy.

A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis. Cuproptosis is a novel type of cell death, which differs from previously reported types of cell death such as apoptosis, autophagy, proptosis, ferroptosis, necroptosis, etc. Long non-coding RNAs (lncRNAs) play multiple roles in HCC.

Methods

We downloaded information from The Cancer Genome Atlas (TCGA) database, and obtained cuproptosis-related genes from published studies. The cuproptosis-related lncRNAs were obtained by correlation analysis, and subsequently used to construct a prognostic cuproptosis-related lncRNA signature. Analyses of overall survival (OS), progression-free survival (PFS), receiver operating characteristic (ROC) curve with the area under the curve (AUC) values and the index of concordance (c-index) curve were used to evaluate the signature. The tumor microenvironment (TME) was analyzed by ESTIMATE algorithm. The immune cell data was downloaded from the Tumor Immune Estimation Resource (TIMER) 2.0 database. Immune-related pathways were analyzed by single-sample gene set enrichment analysis (ssGSEA) algorithm. Immunophenoscore (IPS) scores from The Cancer Immunome (TCIA) database were used to evaluate immunotherapy response. The "pRRophetic" was employed to screen drugs for high-risk patients. The candidate lncRNA expression levels were detected by Real Time Quantitative PCR.

Results

We constructed a cuproptosis-related lncRNA signature containing seven lncRNAs: AC125437.1, PCED1B-AS1, PICSAR, AP001372.2, AC027097.1, LINC00479, and SLC6A1-AS1. This signature had excellent accuracy, and was independent of the stratification of clinicopathological features. Further study showed that high-risk tumors under this signature had higher TMB, fewer TME components and higher tumor purity. The tumors with high risk were not enriched in immune cell infiltration or immune process pathways, and high-risk patients had a poor response to immunotherapy. Moreover, 29 drugs such as sorafenib, dasatinib and paclitaxel were screened for high-risk HCC patients to improve their prognosis. The expression levels of the candidate lncRNAs in HCC tissue were significantly increased (except PCED1B-AS1).

Conclusions

Our prognostic cuproptosis-related lncRNA signature was accurate and effective for predicting the prognosis of HCC. The immunotherapy was unsuitable for high-risk HCC patients with this signature.

LncRNA SNHG4 promotes prostate cancer cell survival and resistance to enzalutamide through a let-7a/RREB1 positive feedback loop and a ceRNA network

BACKGROUND

Prostate cancer threatens the health of men over sixty years old, and its incidence ranks first among all urinary tumors among men. Enzalutamide remains the first-line drug for castration-resistant prostate cancer, however, tumors inevitably become resistant to enzalutamide. Hence, it is of great importance to investigate the mechanisms that induce enzalutamide resistance in prostate cancer cells.

METHODS

Bioinformatic analyzing approaches were used to identified the over-expressed genes in prostate cancer tumor tissues from three GEO datasets. qRT-PCR, western blotting and immunochemistry/In situ hybridization staining assays were performed to assess the expression of SNHG4, RRM2, TK1, AURKA, EZH2 and RREB1. Cell cycle was measured by flow cytometry. CCK-8, plate colony formation and EdU assays were performed to assess the cell proliferation. Senescence-associated β-Gal assay was used to detect the cell senescence level. γ-H2AX staining assay was performed to assess the DNA damages of PCa cells. Luciferase reporter assay and RNA immunoprecipitation assay were performed to verify the RNA-RNA interactions. Chromatin immunoprecipitation assay was performed to assess the bindings between protein and genomic DNA.

RESULTS

We found that RRM2 and NUSAP1 are highly expressed in PCa tumors and significantly correlated with poor clinical outcomes in PCa patients. Bioinformatic analysis as well as experimental validation suggested that SNHG4 regulates RRM2 expression via a let-7 miRNA-mediated ceRNA network. In addition, SNHG4 or RRM2 knockdown significantly induced cell cycle arrest and cell senescence, and inhibited DNA damage repair and cell proliferation, and the effects can be partially reversed by let-7a knockdown or RRM2 reoverexpression. In vitro and in vivo experiments showed that SNHG4 overexpression markedly enhanced cell resistance to enzalutamide. RREB1 was demonstrated to transcriptionally regulate SNHG4, and RREB1 was also validated to be a target of let-7a and thereby regulated by the SNHG4/let-7a feedback loop.

CONCLUSION

Our study uncovered a novel molecular mechanism of lncRNA SNHG4 in driving prostate cancer progression and enzalutamide resistance, revealing the critical roles and therapeutic potential of RREB1, SNHG4, RRM2 and let-7 miRNAs in anticancer therapy.

Necroptosis-related LncRNAs in skin cutaneous melanoma: evaluating prognosis, predicting immunity, and guiding therapy

BACKGROUND

An increasing amount of research has speculated that necroptosis could be a therapeutic strategy for treating cancer. However, understanding the prognostic value of the necroptosis-related long non-coding RNAs (NRLs) in skin cutaneous melanoma (SKCM, hereafter referred to as melanoma) remains poor and needs to be developed. Our research aims to construct a model based on NRLs for the prognosis of patients with melanoma.

METHODS

We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) database and retrieved 86 necroptosis-related genes from the GeneCards database. The lncRNAs associated with necroptosis were identified via the Pearson correlation coefficient, and the prognostic model of melanoma was constructed using LASSO regression. Next, we employed multiple approaches to verify the accuracy of the model. Melanoma patients were categorized into two groups (high-risk and low-risk) according to the results of LASSO regression. The relationships between the risk score and survival status, clinicopathological correlation, functional enrichment, immune infiltration, somatic mutation, and drug sensitivity were further investigated. Finally, the functions of AL162457.2 on melanoma proliferation, invasion, and migration were validated by in vitro experiments.

RESULTS

The prognostic model consists of seven NRLs (EBLN3P, AC093010.2, LINC01871, IRF2-DT, AL162457.2, AC242842.1, HLA-DQB1-AS1) and shows high diagnostic efficiency. Overall survival in the high-risk group was significantly lower than in the low-risk group, and risk scores could be used to predict melanoma survival outcomes independently. Significant differences were evident between risk groups regarding the expression of immune checkpoint genes, immune infiltration, immunotherapeutic response and drug sensitivity analysis. A series of functional cell assays indicated that silencing AL162457.2 significantly inhibited cell proliferation, invasion, and migration in A375 cells.

CONCLUSION

Our prognostic model can independently predict the survival of melanoma patients while providing a basis for the subsequent investigation of necroptosis in melanoma and a new perspective on the clinical diagnosis and treatment of melanoma.

Identification of associations between lncRNA and drug resistance based on deep learning and attention mechanism

Introduction

Abnormal lncRNA expression can lead to the resistance of tumor cells to anticancer drugs, which is a crucial factor leading to high cancer mortality. Studying the relationship between lncRNA and drug resistance becomes necessary. Recently, deep learning has achieved promising results in predicting biomolecular associations. However, to our knowledge, deep learning-based lncRNA-drug resistance associations prediction has yet to be studied.

Methods

Here, we proposed a new computational model, DeepLDA, which used deep neural networks and graph attention mechanisms to learn lncRNA and drug embeddings for predicting potential relationships between lncRNAs and drug resistance. DeepLDA first constructed similarity networks for lncRNAs and drugs using known association information. Subsequently, deep graph neural networks were utilized to automatically extract features from multiple attributes of lncRNAs and drugs. These features were fed into graph attention networks to learn lncRNA and drug embeddings. Finally, the embeddings were used to predict potential associations between lncRNAs and drug resistance.

Results

Experimental results on the given datasets show that DeepLDA outperforms other machine learning-related prediction methods, and the deep neural network and attention mechanism can improve model performance.

Dicsussion

In summary, this study proposes a powerful deep-learning model that can effectively predict lncRNA-drug resistance associations and facilitate the development of lncRNA-targeted drugs. DeepLDA is available at https://github.com/meihonggao/DeepLDA.

Prognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model

Objective: In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. Methods: The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receiver operator characteristic curve. High-risk patients were differentiated from low-risk patients through the cut-off value, and the correlation analyses of the high-risk subgroup and low-risk subgroup were performed. Results: This research discovered that 25 pairs of lncRNAs were associated with the lipid metabolism of ccRCC, and 12 of these pairs were utilized to build the model. In combination with clinical data, the areas under the 1-, 3- and 5-year survival curves of ccRCC patients were 0.809, 0.764 and 0.792, separately. The cut-off value was used to perform subgroup analysis. The results showed that high-risk patients had poor prognosis. The results of Cox multivariate regressive analyses revealed that age and risk score were independent prediction factors of ccRCC prognosis. In addition, immune cell infiltration, the levels of gene expression at immune checkpoints, and high-risk patients more susceptible to sunitinib-targeted treatment were assessed by the risk model. Conclusion: Our team identified new prognostic markers of ccRCC and established risk models that could assess the prognosis of ccRCC patients and help determine which type of patients were more susceptible to sunitinib. These discoveries are vital for the optimization of risk stratification and personalized management.

LncRNA LOXL1-AS1 expression in cancer prognosis: A meta-analysis

BACKGROUND

Several studies showed that LncRNA LOXL1 antisense RNA 1 (LOXL1-AS1) is overexpressed in a variety of cancers and plays a role as an oncogene in cancer. The present meta-analysis aims to elucidate the relationship between LOXL1-AS1 expression and prognosis and clinicopathological features among cancer patients.

METHODS

PubMed, Web of Science, Cochrane Library, and EMBASE database were comprehensively and systematically searched. Pooled odds ratios (ORs) and hazard ratios with a 95% confidence interval (CI) were employed to assess the relationship between LOXL1-AS1 expression and clinical outcomes and clinicopathological features in cancer patients.

RESULTS

The present study finally enrolled 8 studies which included 657 cancer patients. The combined results indicated that the overexpression of LOXL1-AS1 was significantly associated with shorter overall survival (pooled hazard ratio = 1.99, 95% CI 1.49-2.65, P < .00001). Meanwhile, regarding clinicopathology of cancer patients, the upregulation of LOXL1-AS1 expression was closely related to lymph node metastasis (yes vs no OR = 4.01, 95% CI: 2.02-7.96, P < .0001) and distant metastasis (yes vs no OR = 3.04, 95% CI: 1.82-5.06, P < .0001), respectively.

CONCLUSION

High expression of LOXL1-AS1 in some cancers predicts shorter overall survival, distant metastasis, and lymph node metastasis. LOXL1-AS1 shows great promise as a prognostic biomarker in cancer patients.

miR-96-5p regulates cervical cancer cell resistance to cisplatin by inhibiting lncRNA TRIM52-AS1 and promoting IGF2BP2

MicroRNA (miRNA) and long noncoding RNA (lncRNA) are both regulators of cancer progression. This study sought to discuss the functional mechanism of miR-96-5p/lncRNA TRIM52 antisense RNA 1 (head-to-head; TRIM52-AS1) in cervical cancer (CC) cell resistance to cisplatin (DDP). DDP-resistant CC cell line was established using increasing concentrations of DDP, followed by transfection with miR-96-5p inhibitor, or si-TRIM52-AS1, or insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) overexpression vector. Expression levels of miR-96-5p, TRIM52-AS1, and IGF2BP2 were determined. Changes in IC50 value to DDP, cell proliferation, and apoptosis rate were evaluated by cell-counting kit-8 assay, colony formation, and flow cytometry. The bindings of miR-96-5p to IGF2BP2 and TRIM52-AS1 to IGF2BP2 were verified by dual-luciferase or RNA pull-down assays. These experiments revealed an up-expression of miR-96-5p and IGF2BP2 while an under-expression of TRIM52-AS1 in CC cells. After DDP treatment, miR-96-5p inhibition increased apoptosis and decreased proliferation and DDP resistance. miR-96-5p bound to TRIM52-AS1 and downregulated TRIM52-AS1 expression, and TRIM52-AS1 bound to IGF2BP2 to inhibit IGF2BP2 expression. TRIM52-AS1 inhibition or IGF2BP2 overexpression neutralized the inhibition of silencing miR-96-5p on CC cell resistance to DDP. Overall, miR-96-5p improved CC cell resistance to DDP by inhibiting TRIM52-AS1 and promoting IGF2BP2.

Non-coding RNA in cancer drug resistance: Underlying mechanisms and clinical applications

Cancer is one of the most frequently diagnosed malignant diseases worldwide, posing a serious, long-term threat to patients’ health and life. Systemic chemotherapy remains the first-line therapeutic approach for recurrent or metastatic cancer patients after surgery, with the potential to effectively extend patient survival. However, the development of drug resistance seriously limits the clinical efficiency of chemotherapy and ultimately results in treatment failure and patient death. A large number of studies have shown that non-coding RNAs (ncRNAs), particularly microRNAs, long non-coding RNAs, and circular RNAs, are widely involved in the regulation of cancer drug resistance. Their dysregulation contributes to the development of cancer drug resistance by modulating the expression of specific target genes involved in cellular apoptosis, autophagy, drug efflux, epithelial-to-mesenchymal transition (EMT), and cancer stem cells (CSCs). Moreover, some ncRNAs also possess great potential as efficient, specific biomarkers in diagnosis and prognosis as well as therapeutic targets in cancer patients. In this review, we summarize the recent findings on the emerging role and underlying mechanisms of ncRNAs involved in cancer drug resistance and focus on their clinical applications as biomarkers and therapeutic targets in cancer treatment. This information will be of great benefit to early diagnosis and prognostic assessments of cancer as well as the development of ncRNA-based therapeutic strategies for cancer patients.

Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets

Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient’s expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) originates in the squamous cell lining the mucosal surfaces of the head and neck region, including the oral cavity, nasopharynx, tonsils, oropharynx, larynx, and hypopharynx. The heterogeneity, anatomical, and functional characteristics of the patient make the HNSCC a complex and difficult-to-treat disease, leading to a poor survival rate and a decreased quality of life due to the loss of important physiologic functions and aggressive surgical injury. Alteration of driver-oncogenic and tumor-suppressing lncRNAs has recently been recently in HNSCC to obtain possible biomarkers for diagnostic, prognostic, and therapeutic approaches. This review provides current knowledge about the implication of lncRNAs in drug resistance mechanisms in HNSCC. Chemotherapy resistance is a major therapeutic challenge in HNSCC in which lncRNAs are implicated. Lately, it has been shown that lncRNAs involved in autophagy induced by chemotherapy and epithelial–mesenchymal transition (EMT) can act as mechanisms of resistance to anticancer drugs. Conversely, lncRNAs involved in mesenchymal–epithelial transition (MET) are related to chemosensitivity and inhibition of invasiveness of drug-resistant cells. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in both processes and are important for cancer detection, progression, diagnosis, therapy response, and prognostic values. As the involvement of more lncRNAs is elucidated in chemoresistance mechanisms, an improvement in diagnostic and prognostic tools could promote an advance in targeted and specific therapies in precision oncology.

Stressing the Regulatory Role of Long Non-Coding RNA in the Cellular Stress Response during Cancer Progression and Therapy

Cellular stress response is an important adaptive mechanism for regulating cell fate decision when cells confront with stress. During tumorigenesis, tumor progression and the course of treatment, cellular stress signaling can activate subsequent response to deal with stress. Therefore, cellular stress response has impacts on the fate of tumor cells and tumor responsiveness relative to therapeutic agents. In recent years, attention has been drawn to long non-coding RNAs (lncRNAs), a novel class of RNA molecules with more than 200 nucleotides in length, which has little protein-coding potential and possesses various functions in multiple biological processes. Accumulating evidence has shown that lncRNAs are also engaged in the regulation of cellular stress response, particularly in cancers. Here, we summarize lncRNAs that have been reported in the adaptive response to major types of cellular stress including genotoxic, hypoxic, oxidative, metabolic and endoplasmic reticulum stress, all of which are often encountered by cancer cells. Specifically, the molecular mechanisms of how lncRNAs regulate cellular stress response during tumor progression or the development of therapy resistance are emphasized. The potential clinical applications of stress-responsive lncRNAs as biomarkers will also be discussed.

The Role of m6A Regulator-Mediated Methylation Modification and Tumor Microenvironment Infiltration in Glioblastoma Multiforme

N6-methyladenosine (m6A) RNA methylation is an emerging epigenetic modification in recent years and epigenetic regulation of the immune response has been demonstrated, but the potential role of m6A modification in GBM tumor microenvironment (TME) cell infiltration and stemness remain unknown. The m6A modification patterns of 310 GBM samples were comprehensively evaluated based on 21 m6A regulators, and we systematically correlated these modification patterns with TME cell infiltration characteristics and stemness characteristics. Construction of m6Ascore to quantify the m6A modification patterns of individual GBM samples using a principal component analysis algorithm. We identified two distinct patterns of m6A modification. The infiltration characteristics of TME cells in these two patterns were highly consistent with the immunophenotype of the GBM, including the immune activation differentiation pattern and the immune desert dedifferentiation pattern. We also identified two modes of regulation of immunity and stemness by m6A methylation. Stromal activation and lack of effective immune infiltration were observed in the high m6Ascore subtype. Pan-cancer analysis results illustrate a significant correlation between m6AScore and tumor clinical outcome, immune infiltration, and stemness. Our work reveals that m6A modifications play an important role in the development of TME and stemness diversity and complexity. Patients with a low m6AScore showed significant therapeutic advantages and clinical benefits. Assessing the m6A modification pattern of individual tumors will help enhance our knowledge of TME infiltration and stemness characteristics, contribute to the development of immunotherapeutic strategies.

Long Non-Coding RNA in Gastric Cancer: Mechanisms and Clinical Implications for Drug Resistance

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide, with high recurrence and mortality rate. Chemotherapy, including 5-fluorouracil (5-FU), adriamycin (ADR), vincristine (VCR), paclitaxel (PTX), and platinum drugs, remains one of the fundamental methods of GC treatment and has efficiently improved patients’ prognosis. However, most patients eventually develop resistance to chemotherapeutic agents, leading to the failure of clinical treatment and patients’ death. Recent studies suggest that long non-coding RNAs (lncRNAs) are involved in the drug resistance of GC by modulating the expression of drug resistance-related genes via sponging microRNAs (miRNAs). Moreover, lncRNAs also play crucial roles in GC drug resistance via a variety of mechanisms, such as the regulation of the oncogenic signaling pathways, inhibition of apoptosis, induction of autophagy, modulation of cancer stem cells (CSCs), and promotion of the epithelial-to-mesenchymal transition (EMT) process. Some of lncRNAs exhibit great potential as diagnostic and prognostic biomarkers, as well as therapeutic targets for GC patients. Therefore, understanding the role of lncRNAs and their mechanisms in GC drug resistance may provide us with novel insights for developing strategies for individual diagnosis and therapy. In this review, we summarize the recent findings on the mechanisms underlying GC drug resistance regulated by lncRNAs. We also discuss the potential clinical applications of lncRNAs as biomarkers and therapeutic targets in GC.

Involvement of Non-Coding RNAs in Chemo- and Radioresistance of Nasopharyngeal Carcinoma

The crucial treatment for nasopharyngeal carcinoma (NPC) is radiation therapy supplemented by chemotherapy. However, long-term radiation therapy can cause some genetic and proteomic changes to produce radiation resistance, leading to tumour recurrence and poor prognosis. Therefore, the search for new markers that can overcome the resistance of tumor cells to drugs and radiotherapy and improve the sensitivity of tumor cells to drugs and radiotherapy is one of the most important goals of pharmacogenomics and cancer research, which is important for predicting treatment response and prognosis. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), may play important roles in regulating chemo- and radiation resistance in nasopharyngeal carcinoma by controlling the cell cycle, proliferation, apoptosis, and DNA damage repair, as well as other signalling pathways. Recent research has suggested that selective modulation of ncRNA activity can improve the response to chemotherapy and radiotherapy, providing an innovative antitumour approach based on ncRNA-related gene therapy. Therefore, ncRNAs can serve as biomarkers for tumour prediction and prognosis, play a role in overcoming drug resistance and radiation resistance in NPC, and can also serve as targets for developing new therapeutic strategies. In this review, we discuss the involvement of ncRNAs in chemotherapy and radiation resistance in NPC. The effects of these molecules on predicting therapeutic cancer are highlighted.