The role of long non-coding RNAs in mediating chemoresistance by modulating autophagy in cancer

Insights into the Crosstalk Between miR-200a/lncRNA H-19 and IL-6/SIRT-1 Axis in Breast Cancer

Breast cancer (BC) is a highly prevalent malignancy that poses a significant threat to women's well-being. Novel biomarker identification helps to improve clinical outcomes and provide tailored treatments. Our research aims to explore the diagnostic potential of miR-200a/lncRNA H-19 and interleukin-6 (IL-6)/SIRT-1 axis crosstalk and evaluate the impact of metastasis on gene expression, which provides valuable insights into the diagnosis and treatment of BC. In this case-control study, we collected blood samples from 54 nonmetastatic breast cancer (NMBC) patients, 46 metastatic breast cancer (MBC) patients, and 50 healthy individuals. We used real time-polymerase chain reaction to measure the expression levels of lncRNA H-19 and miR-200a, whereas enzyme linked immunosorbent assay was used to determine the IL-6 levels. In addition, we evaluated SIRT-1 expression level using a Western blot assay. The levels of lncRNA H-19, miR-200a, and IL-6 were higher in BC patients, whereas SIRT-1 levels were lower. Patients with MBC had higher levels of lncRNA H-19, miR-200a, and IL-6 than those with NMBC. In addition, the expression of lncRNA H-19 and miR-200a showed a negative correlation with SIRT-1 expression, whereas the levels of lncRNA H-19 and miR-200a showed a positive correlation with IL-6 expression level. The diagnostic potential of lncRNA H-19 and miR-200a in BC is undeniable. Moreover, the robust association of IL-6/SIRT-1 with lncRNA H-19/miR-200a expression presents a promising opportunity for clinical outcomes and tailored treatments.

Depletion of CPNE7 sensitizes colorectal cancer to 5-fluorouracil by downregulating ATG9B expression

We aimed to explore the biological function of CPNE7 and determine the impact of CPNE7 on chemotherapy resistance in colorectal cancer (CRC) patients. According to the Gene Expression Profiling Interactive Analysis database and previously published data, CPNE7 was identified as a potential oncogene in CRC. RT-qPCR and Western blotting were performed to verify the expression of CPNE7. Chi-square test was used to evaluate the associations between CPNE7 and clinical features. Cell proliferation, colony formation, cell migration and invasion, cell cycle and apoptosis were assessed to determine the effects of CPNE7. Transcriptome sequencing was used to identify potential downstream regulatory genes, and gene set enrichment analysis was performed to investigate downstream pathways. The effect of CPNE7 on 5-fluorouracil chemosensitivity was verified by half maximal inhibitory concentration (IC50). Subcutaneous tumorigenesis assay was used to examine the role of CPNE7 in sensitivity of CRC to chemotherapy in vivo. Transmission electron microscopy was used to detect autophagosomes. CPNE7 was highly expressed in CRC tissues, and its expression was correlated with T stage and tumour site. Knockdown of CPNE7 inhibited the proliferation and colony formation of CRC cells and promoted apoptosis. Knockdown of CPNE7 suppressed the expression of ATG9B and enhanced the sensitivity of CRC cells to 5-fluorouracil in vitro and in vivo. Knockdown of CPNE7 reversed the induction of the autophagy pathway by rapamycin and reduced the number of autophagosomes. Depletion of CPNE7 attenuated the malignant proliferation of CRC cells and enhanced the chemosensitivity of CRC cells to 5-fluorouracil.

Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers

Colorectal cancer (CRC) and gastric cancer (GC) are major contributors to cancer-related mortality worldwide. Despite advancements in understanding molecular mechanisms and improved drug treatments, the overall survival rate for patients remains unsatisfactory. Metastasis and drug resistance are major challenges contributing to the high mortality rate in both CRC and GC. Recent research has shed light on the role of long noncoding RNAs (lncRNAs) in the development and progression of these cancers. LncRNAs regulate gene expression through various mechanisms, including epigenetic modifications and interactions with microRNAs (miRNAs) and proteins. They can serve as miRNA precursors or pseudogenes, modulating gene expression at transcriptional and post-transcriptional levels. Additionally, circulating lncRNAs have emerged as non-invasive biomarkers for the diagnosis, prognosis, and prediction of drug therapy response in CRC and GC. This review explores the intricate relationship between lncRNAs and CRC/GC, encompassing their roles in cancer development, progression, and chemoresistance. Furthermore, it discusses the potential of lncRNAs as therapeutic targets in these malignancies. The interplay between lncRNAs, miRNAs, and tumor microenvironment is also highlighted, emphasizing their impact on the complexity of cancer biology. Understanding the regulatory landscape and molecular mechanisms governed by lncRNAs in CRC and GC is crucial for the development of effective diagnostic and prognostic biomarkers, as well as novel therapeutic strategies. This review provides a comprehensive overview of the current knowledge and paves the way for further exploration of lncRNAs as key players in the management of CRC and GC.

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.

LncRNA FTH1P3: A New Biomarker for Cancer-Related Therapeutic Development

Cancer is a persistent and urgent health problem that affects the entire world. Not long ago, regulatory biomolecules referred to as long noncoding RNAs (lncRNAs) might have value for their innate abundance and stability. These single-stranded RNAs potentially interfere with several physiological and biochemical cellular processes involved in many human pathological situations, particularly cancer diseases. Ferritin heavy chain1 pseudogene 3 (FTH1P3), a lncRNA that is ubiquitously transcribed and belongs to the ferritin heavy chain (FHC) family, represents a novel class of lncRNAs primarily found in oral squamous cell carcinoma. Further research has shown that FTH1P3 is involved in other malignancies such as uveal melanoma, glioma, esophageal squamous cell carcinoma, non-small cell lung cancer, breast cancer, laryngeal squamous cell carcinoma, and cervical cancer. Accordingly, FTH1P3 significantly enhances cancer symptoms, including cell proliferation, invasion, metastasis, chemoresistance, and inhibition of apoptosis through many specific mechanisms. Notably, the clinical data significantly demonstrated the association of FTH1P3 overexpression with poor prognosis and poor overall survival within the examined samples. Here, we summarize all the research published to date (13 articles) on FTH1P3, focusing on the biological function underlying the regulatory mechanism and its possible clinical relevance.

The development and experimental validation of hypoxia-related long noncoding RNAs prognostic signature in predicting prognosis and immunotherapy of cutaneous melanoma

Cutaneous melanoma (CM) is widely acknowledged as a highly aggressive form of malignancy that is associated with a considerable degree of morbidity and poor prognosis. Despite this recognition, the precise role of hypoxia-related long noncoding RNAs (HRLs) in the pathogenesis of CM remains an area of active research. This study sought to elucidate the contribution of HRLs in CM by conducting a thorough screening and extraction of hypoxia-related genes (HRGs). In particular, we conducted univariate and multivariate Cox regression analyses to assess the independence of the prognostic signature of HRLs. Our results demonstrated that a novel risk model could be established based on five prognostic HRLs. Remarkably, patients with low-risk scores exhibited significantly higher overall survival rates compared to their high-risk counterparts, as confirmed by Kaplan-Meier survival analysis. Furthermore, we utilized consensus clustering analysis to categorize CM patients into two distinct subtypes, which revealed marked differences in their prognosis and immune infiltration landscapes. Our nomogram results confirmed that the HRLs prognostic signature served as an independent prognostic indicator, offering an accurate evaluation of the survival probability of CM patients. Notably, our findings from ESTIMATE and ssGSEA analyses highlighted significant disparities in the immune infiltration landscape between low- and high-risk groups of CM patients. Additionally, IPS and TIDE results suggested that CM patients in different risk subtypes may exhibit favorable responses to immunotherapy. Enrichment analysis and GSVA results indicated that immune-related signaling pathways may mediate the role of HRLs in CM. Finally, our tumor mutation burden (TMB) results indicated that patients with low-risk scores had a higher TMB status. In summary, the establishment of a risk model based on HRLs in this study provided an accurate prognostic prediction and correlated with the immune infiltration landscape of CM, thereby providing novel insights for the future clinical management of this disease.

Thioredoxin Reductase and Organometallic Complexes: A Pivotal System to Tackle Multidrug Resistant Tumors?

Cancers classified as multidrug-resistant (MDR) are a family of diseases with poor prognosis despite access to increasingly sophisticated treatments. Several mechanisms explain these resistances involving both tumor cells and their microenvironment. It is now recognized that a multi-targeting approach offers a promising strategy to treat these MDR tumors. Inhibition of thioredoxin reductase (TrxR), a key enzyme in maintaining redox balance in cells, is a well-identified target for this approach. Auranofin was the first inorganic gold complex to be described as a powerful inhibitor of TrxR. In this review, we will first recall the main results obtained with this metallodrug. Then, we will focus on organometallic complexes reported as TrxR inhibitors. These include gold(I), gold(III) complexes and metallocifens, i.e., organometallic complexes of Fe and Os derived from tamoxifen. In these families of complexes, similarities and differences in the molecular mechanisms of TrxR inhibition will be highlighted. Finally, the possible relationship between TrxR inhibition and cytotoxicity will be discussed and put into perspective with their mode of action.

Accurate prognostic prediction for patients with clear cell renal cell carcinoma using a ferroptosis-related long non-coding RNA risk model

INTRODUCTION

Ferroptosis is a recently discovered type of programmed cell death that plays a crucial role in tumor occurrence and progression. However, no prognostic model has been established yet for clear cell renal cell carcinoma (ccRCC) using ferroptosis-related long non-coding RNAs (lncRNAs).

METHODS

In the present study, lncRNA expression profiles, sex, age, TMN stage, and other clinical data of ccRCC samples were extracted from The Cancer Genome Atlas database. In addition, ferroptosis-related lncRNAs were identified using co-expression analysis, and the risk model was established using Cox regression and least absolute shrinkage and selection operator regression analyses. Log-rank test and Kaplan-Meier analysis were performed to evaluate the predictive accuracy of the risk model for the overall survival (OS) of patients with ccRCC. Moreover, the functional enrichment of ferroptosis-related lncRNAs was performed and visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

RESULTS

Eight prognostic ferroptosis-related lncRNAs were identified, such as LINC01615, AC026401.3, LINC00944, AL590094.1, DLGAP1-AS2, AC016773.1, AC147651.1, and AP000439.2, making up the ferroptosis-related lncRNA risk model. The risk model effectively divided patients with ccRCC into high- and low-risk groups, and their survival time was calculated. The high-risk group showed significantly shorter OS compared to the low-risk group. The nomogram to predict the survival rate of the patients revealed that the risk score was the most critical factor affecting OS in patients with ccRCC. The ferroptosis-related lncRNA risk model was an independent predictor of prognostic risk assessment in patients with ccRCC.

CONCLUSION

The ferroptosis-related lncRNAs risk model and genomic clinicopathological nomogram have the potential to accurately predict the prognosis of patients with ccRCC and could serve as potential therapeutic targets in the future.

A prognostic risk prediction model based on ferroptosis-related long non-coding RNAs in bladder cancer: A bulk RNA-seq research and scRNA-seq validation

BACKGROUND

To construct a prognostic risk model of bladder cancer (BC) from the perspective of long non-coding RNAs (lncRNAs) and ferroptosis, in order to guide clinical prognosis and identify potential therapeutic targets.

METHODS

In-hours BC samples were collected from 4 patients diagnosed with BC, who underwent radical cystectomy. Single cell transcriptome sequencing was performed and Seurat package were used for quality control and secondary analysis. LncRNAs expression profiles of BC samples were extracted from The Cancer Genome Atlas database. And sex, age, tumor, node, metastasis stage and other clinical data was downloaded at the same time. Ferroptosis-related lncRNAs were identified by co-expression analysis. We constructed a risk model by Cox regression and least absolute shrinkage and selection operator regression analyses. The predictive strength of the risk model for overall survival (OS) of patients with BC was evaluated by the log-rank test and Kaplan-Meier method. Finally, the enrichment analysis was performed and visualized.

RESULTS

We identified and included 15 prognostic ferroptosis-related lncRNAs (AL356740.1, FOXC2AS1, ZNF528AS1, LINC02535, PSMB8AS1, AL590428.1, AP000347.2, OCIAD1-AS1, AP001347.1, AC104986.2, AC018926.2, LINC00867, AC099518.4, USP30-AS1, and ARHGAP5-AS1), to build our ferroptosis-related lncRNAs risk model. Using this risk model, BC patients were divided into high and low-risk groups, and their respective survival lengths were calculated. The results showed that the OS of the low-risk group was significantly longer than that of the high-risk group. A nomogram was utilized to predict the survival rate of BC patients. As indicated in the nomogram, risk score was the most important indicator of OS in patients with BC. The ferroptosis-related lncRNAs risk model is an independent tool for prognostic risk assessment in patients with BC. Single cell transcriptome sequencing suggests that ferroptosis-related lncRNAs express specifically in BC tumor microenvironment. AL356740.1, LINC02535 and LINC00867 were mainly expressed in tumor cells.

CONCLUSION

The risk model based on the ferroptosis-related lncRNAs and the genomic clinico-pathological nomogram could be used to accurately predict the prognosis of patients with BC. The lncRNAs used to build this model might become potential therapeutic targets in the future.

Establishment and Analysis of a Prognostic Model of Autophagy-Related lncRNAs in ESCA

Esophageal cancer (ESCA) is a malignant tumor of the upper gastrointestinal tract, with a high mortality rate and poor prognosis. Long noncoding RNAs (lncRNAs) play a role in the malignant progression of tumors by regulating autophagy. This study is aimed at establishing a prognostic model of autophagy-related lncRNAs in ESCA and provide a theoretical basis to determine potential therapeutic targets for ESCA. The transcriptome expression profiles were downloaded from The Cancer Genome Atlas (TCGA). We identified autophagy-related mRNAs and lncRNAs in ESCA using differential expression analysis and the Human Autophagy Database (HADb). Four differentially expressed autophagy-related lncRNAs with a prognostic value were identified using Cox regression and survival analyses. Furthermore, the combination of the selected lncRNAs was able to predict the prognosis of patients with ESCA more accurately than any of the four lncRNAs individually. Finally, we constructed a coexpression network of autophagy-related mRNAs and lncRNAs. This study showed that autophagy-related lncRNAs play an important role in the occurrence and development of ESCA and could become a new target for the diagnosis and treatment of this disease.

Identification of pyroptosis-related long non-coding RNAs with prognosis and therapy in lung squamous cell carcinoma

Pyroptosis is a type of programmed cell death with an intense inflammatory response. Previous studies have shown that pyroptosis plays an important role in the pathogenesis and progression of lung cancer. However, the prognostic value and drug targets of pyroptosis-related lncRNAs in lung squamous cell carcinoma (LSCC) have never been studied. In the present study, we identified 1468 pyroptosis-related lncRNAs in LSCC by performing Pearson correlation analysis between the pyroptosis-related genes and the lncRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The whole set was divided into a training and a test set with a 1:1 ratio. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to establish an 11 multilncRNA signature in the three sets. The signature divided LSCC patients into the low-risk and the high-risk groups. Kaplan–Meier analysis and receiver operating characteristic (ROC) indicated that the prognostic signature had a promising predictive capability for LSCC patients. Besides, the association of microenvironment and immunotherapy response with signature was also analyzed. Moreover, 28 potential compounds targeting signature were screened as possible drugs to treat LSCC. Finally, a nomogram model was constructed to offer the quantitative prediction and net benefit for the prognosis of LSCC patients. In conclusion, the 11 pyroptosis-related lncRNAs and their signature may be promising prognostic factors and therapeutic targets for patients with LSCC.

Multidrug Resistance in Cancer: Understanding Molecular Mechanisms, Immunoprevention and Therapeutic Approaches

Cancer is one of the leading causes of death worldwide. Several treatments are available for cancer treatment, but many treatment methods are ineffective against multidrug-resistant cancer. Multidrug resistance (MDR) represents a major obstacle to effective therapeutic interventions against cancer. This review describes the known MDR mechanisms in cancer cells and discusses ongoing laboratory approaches and novel therapeutic strategies that aim to inhibit, circumvent, or reverse MDR development in various cancer types. In this review, we discuss both intrinsic and acquired drug resistance, in addition to highlighting hypoxia- and autophagy-mediated drug resistance mechanisms. Several factors, including individual genetic differences, such as mutations, altered epigenetics, enhanced drug efflux, cell death inhibition, and various other molecular and cellular mechanisms, are responsible for the development of resistance against anticancer agents. Drug resistance can also depend on cellular autophagic and hypoxic status. The expression of drug-resistant genes and the regulatory mechanisms that determine drug resistance are also discussed. Methods to circumvent MDR, including immunoprevention, the use of microparticles and nanomedicine might result in better strategies for fighting cancer.

Biological causes of immunogenic cancer cell death (ICD) and anti-tumor therapy; Combination of Oncolytic virus-based immunotherapy and CAR T-cell therapy for ICD induction

Chimeric antigen receptor (CAR) T-cell therapy is a promising and rapidly expanding therapeutic option for a wide range of human malignancies. Despite the ongoing progress of CAR T-cell therapy in hematologic malignancies, the application of this therapeutic strategy in solid tumors has encountered several challenges due to antigen heterogeneity, suboptimal CAR T-cell trafficking, and the immunosuppressive features of the tumor microenvironment (TME). Oncolytic virotherapy is a novel cancer therapy that employs competent or genetically modified oncolytic viruses (OVs) to preferentially proliferate in tumor cells. OVs in combination with CAR T-cells are promising candidates for overcoming the current drawbacks of CAR T-cell application in tumors through triggering immunogenic cell death (ICD) in cancer cells. ICD is a type of cellular death in which danger-associated molecular patterns (DAMPs) and tumor-specific antigens are released, leading to the stimulation of potent anti-cancer immunity. In the present review, we discuss the biological causes of ICD, different types of ICD, and the synergistic combination of OVs and CAR T-cells to reach potent tumor-specific immunity.

A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

Purpose

Lung adenocarcinoma is the most common pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis and precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice.

Methods

The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from the TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate the high and low risk groups and a ROC curve and nomogram to visualize the predictive ability of the current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA.

Results

A total of 1,703 autophagy-related lncRNAs were screened and five autophagy-related lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1, and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate (HR=1.075, 95% CI=1.046–1.104) and multivariate (HR=1.088, 95% CI=1.057−1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-years, and 5-years, was 0.735, 0.672, and 0.662, respectively, indicating a reliable model. Drug sensitivity analysis revealed low risk patients were more sensitive to Gemcitabine and Gefitinib, while high risk patients had a better response to Paclitaxel and Erlotinib. Moreover, the lncRNAs included in our signature were primarily enriched in the autophagy process, metabolism, p53 pathway, and JAK/STAT pathway. Finally, a multi-omics analysis of correlated genes showed CFLAR overexpressed in the tumor sample, while GAPDH and MLST8 had a slightly higher expression in the normal sample.

Conclusion

Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients’ prognosis and the related genes might be potential biomarkers and therapeutic targets.

An Autophagy-Related Long Non-Coding RNA Prognostic Signature for Patients with Lung Squamous Carcinoma Based on Bioinformatics Analysis

Purpose

Lung cancer is the most common and deadly cancer type affecting humans. Although huge progress has been made on early diagnosis and precision treatment, the overall 5 year survival rate remains low. In this study, we constructed an autophagy-related long non-coding RNA (lncRNA) prognostic signature for guiding clinical practice.

Methods

From The Cancer Genome Atlas, we retrieved mRNA and lncRNA expression matrices of patients with lung squamous carcinoma. We then established a prognostic risk model using Lasso regression and multivariate Cox regression. The model generated a risk score to differentiate high- and low-risk groups. An ROC curve and nomogram were used to visualize the predictive ability of the current signatures. Finally, we used Gene Set Enrichment Analysis to determine gene ontology and pathway enrichment.

Results

After screening 1248 autophagy-related lncRNAs, we selected seven lncRNAs (LUCAT1, AC022150.2, AL035425.3, AC138976.2, AC106786.1, GPRC5D-AS1 and AP006545.2) for our signature. Univariate (hazard ratio [HR] = 2.147, 95% confidence interval [CI]: 1.681–2.743, P < 0.001) and multivariate (HR = 2.096, 95% CI: 1.652–2.658, P < 0.001) Cox regression analyses revealed that the risk score is an independent predictive factor for LUSC patients. Further, areas under the receiver operating characteristic curve were 0.622, 0.699, and 0.721, respectively, for the 1 year, 3 year, and 5 year risk scores—indicating a reliable model. Selected lncRNAs were primarily enriched in autophagy, metabolism, MAPK pathway, and JAK/STAT pathway. Further drug sensitivity analysis revealed that low-risk patients were more sensitive to Cisplatin, Docetaxel, Vinblastine, and Vinorelbine. Finally, a multi-omics analysis found that lncRNA-linked proteins IKBKB and SQSTM1 were expressed at low levels and significantly correlated in tumor samples, compared with normal tissue.

Conclusion

Our prognostic model successfully predicted patient prognosis in lung cancer.

Autophagy in Tumor Immunity and Viral-Based Immunotherapeutic Approaches in Cancer

Autophagy is a fundamental catabolic process essential for the maintenance of cellular and tissue homeostasis, as well as directly contributing to the control of invading pathogens. Unsurprisingly, this process becomes critical in supporting cellular dysregulation that occurs in cancer, particularly the tumor microenvironments and their immune cell infiltration, ultimately playing a role in responses to cancer therapies. Therefore, understanding "cancer autophagy" could help turn this cellular waste-management service into a powerful ally for specific therapeutics. For instance, numerous regulatory mechanisms of the autophagic machinery can contribute to the anti-tumor properties of oncolytic viruses (OVs), which comprise a diverse class of replication-competent viruses with potential as cancer immunotherapeutics. In that context, autophagy can either: promote OV anti-tumor effects by enhancing infectivity and replication, mediating oncolysis, and inducing autophagic and immunogenic cell death; or reduce OV cytotoxicity by providing survival cues to tumor cells. These properties make the catabolic process of autophagy an attractive target for therapeutic combinations looking to enhance the efficacy of OVs. In this article, we review the complicated role of autophagy in cancer initiation and development, its effect on modulating OVs and immunity, and we discuss recent progress and opportunities/challenges in targeting autophagy to enhance oncolytic viral immunotherapy.

Study of HOTAIR LncRNA in AML patients in context to FLT3-ITD and NPM1 mutations status

Background

Long non-coding RNAs (LncRNAs) have recently been considered promising biomarkers for oncogenesis due to their epigenetic regulatory effects. HOTAIR is one of the oncogenic LncRNAs that was previously studied in different non-hematological malignancies. The current study set out to detect the expression level of HOTAIR LncRNA in AML patients concerning their clinical characteristics, laboratory data, FLT3-ITD, and NPM1 mutations, as well as treatment outcome. This study included quantitative detection of HOTAIR gene expression in 47 cases of AML using quantitative reverse transcription polymerase chain reaction, as well as NPM1 and FLT3-ITD genotyping.

Results

The HOTAIR expression was significantly higher in AML patients 6.87 (0.001) than in normal controls 1.66 (0.004–6.82) (p 0.007). The HOTAIR expression level was affected by chemotherapy, and it was correlated to hemoglobin level (p 0.001), age, total leukocytic count (p 0.022), and NPM1 mutation (p 0.017). HOTAIR gene expression level showed a correlation to relapse-free survival in the study group (p 0.04).

Conclusion

HOTAIR is overexpressed in patients with acute myeloid leukemia (AML). HOTAIR pre-treatment and post-chemotherapy gene expression levels can predict chemosensitivity and relapse.

Autophagy-Related Long Non-coding RNA Is a Prognostic Indicator for Bladder Cancer

Bladder cancer (BC) is one of the most common malignant urinary system tumors, and its prognosis is poor. In recent years, autophagy has been closely linked to the development of BC. Therefore, we investigated the potential prognostic role of autophagy-related long non-coding RNA (lncRNA) in patients with BC. We obtained the lncRNA information and autophagy genes, respectively, from The Cancer Genome Atlas (TCGA) data set and the human autophagy database (HADb) and performed a co-expression analysis to identify autophagy gene-associated lncRNAs. Then, we divided the data into training group and testing group. In the training group, 15 autophagy-related lncRNAs were found to have a prognostic value (AC026369.3, USP30-as1, AC007991.2, AC104785.1, AC010503.4, AC037198.1, AC010331.1, AF131215.6, AC084357.2, THUMPD3-AS1, U62317.4, MAN1B1-DTt, AC024060.1, AL662844.4, and AC005229.4). The patients were divided into low-risk group and high-risk group based on the prognostic lncRNAs. The overall survival (OS) time for the high-risk group was shorter than that for the low-risk group [risk ratio (hazard ratio, HR) = 1.08, 95% CI: 1.06-1.10; p < 0.0001]. Using our model, the defined risk value can predict the prognosis of a patient. Next, the model was assessed in the TCGA testing group to further validate these results. A total of 203 patients with BC were recruited to verify the lncRNA characteristics. We divided these patients into high-risk group and low-risk group. The results of testing data set show that the survival time of high-risk patients is shorter than that of low-risk patients. In the training group, the area under the curve (AUC) was more than 0.7, indicating a high level of accuracy. The AUC for a risk model was greater than that for each clinical feature alone, indicating that the risk value of a model was the best indicator for predicting the prognosis. Further training data analysis showed that the gene set was significantly enriched in cancer-related pathways, including actin cytoskeleton regulation and gap junctions. In conclusion, our 15 autophagy-related lncRNAs have a prognostic potential for BC, and may play key roles in the biology of BC.

Long Noncoding RNA MIR210HG Promotes the Warburg Effect and Tumor Growth by Enhancing HIF-1α Translation in Triple-Negative Breast Cancer

Background

Hypoxia is an important environmental factor and has been correlated with tumor progression, treatment resistance and poor prognosis in many solid tumors, including triple-negative breast cancer (TNBC). Emerging evidence suggests that long noncoding RNA (lncRNA) functions as a critical regulator in tumor biology. However, little is known about the link between hypoxia and lncRNAs in TNBC.

Methods

TNBC molecular profiles from The Cancer Genome Atlas (TCGA) were leveraged to identify hypoxia-related molecular alterations. Loss-of-function studies were performed to determine the regulatory role of MIR210HG in tumor glycolysis. The potential functions and mechanisms of hypoxia-MIR210HG axis were explored using qPCR, Western blotting, luciferase reporter assay, and polysome profiling.

Results

We found that MIR210HG is a hypoxia-induced lncRNA in TNBC. Loss-of-function studies revealed that MIR210HG promoted the Warburg effect as demonstrated by glucose uptake, lactate production and expression of glycolytic components. Mechanistically, MIR210HG potentiated the metabolic transcription factor hypoxia-inducible factor 1α (HIF-1α) translation via directly binding to the 5'-UTR of HIF-1α mRNA, leading to increased HIF-1a protein level, thereby upregulating expression of glycolytic enzymes. MIR210HG knockdown in TNBC cells reduced their glycolytic metabolism and abolished their tumorigenic potential, indicating the glycolysis-dependent oncogenic activity of MIR210HG in TNBC. Moreover, MIR210HG was highly expressed in breast cancer and predicted poor clinical outcome.

Conclusion

Our results decipher a positive feedback loop between hypoxia and MIR210HG that drive the Warburg effect and suggest that MIR210HG may be a good prognostic marker and therapeutic target for TNBC patients.

Progress in Natural Compounds/siRNA Co-delivery Employing Nanovehicles for Cancer Therapy

Chemotherapy using natural compounds, such as resveratrol, curcumin, paclitaxel, docetaxel, etoposide, doxorubicin, and camptothecin, is of importance in cancer therapy because of the outstanding therapeutic activity and multitargeting capability of these compounds. However, poor solubility and bioavailability of natural compounds have limited their efficacy in cancer therapy. To circumvent this hurdle, nanocarriers have been designed to improve the antitumor activity of the aforementioned compounds. Nevertheless, cancer treatment is still a challenge, demanding novel strategies. It is well-known that a combination of natural products and gene therapy is advantageous over monotherapy. Delivery of multiple therapeutic agents/small interfering RNA (siRNA) as a potent gene-editing tool in cancer therapy can maximize the synergistic effects against tumor cells. In the present review, co-delivery of natural compounds/siRNA using nanovehicles are highlighted to provide a backdrop for future research.

Knockdown of lncRNA ABHD11-AS1 Suppresses the Tumorigenesis of Pancreatic Cancer via Sponging miR-1231

Background

Pancreatic cancer ranks first among the most aggressive malignancies. Long non-coding RNA (LncRNA) ABHD11-AS1 is known to be upregulated in pancreatic cancer. However, the mechanism by which ABHD11-AS1 mediates the tumorigenesis of pancreatic cancer remains unclear.

Methods

Gene and protein expressions in pancreatic cancer cells were detected by qRT-PCR and Western blot, respectively. Cell viability was measured by CCK-8 assay. Cell apoptosis and cycle were tested by flow cytometry. In addition, cell migration and invasion were tested by wound healing and transwell assay, respectively. The correlation between ABHD11-AS1, miR-1231 and cyclin E1 was confirmed by dual-luciferase report and RNA pull-down. Finally, xenograft mice model was established to investigate the role of ABDH-AS1 in pancreatic cancer in vivo.

Results

ABHD11-AS1 was found to be negatively correlated with the survival rate of patients with pancreatic cancer. ABHD11-AS1 silencing significantly inhibited the proliferation and induced the apoptosis of pancreatic cancer cells. Additionally, knockdown of ABHD11-AS1 greatly inhibited the migration and invasion of pancreatic cancer cells. Meanwhile, ABHD11-AS1 bound to miR-1231 and cyclin E1 was found to be the target of miR-1231. Moreover, ABHD11-AS1 knockdown-induced G1 arrest in pancreatic cancer cells was reversed by miR-1231 antagomir. Finally, knockdown of ABHD11-AS1 obviously inhibited the tumor growth of pancreatic cancer in vivo.

Conclusion

ABHD11-AS1 silencing significantly inhibited the tumorigenesis of pancreatic cancer in vitro and in vivo. Thus, ABHD11-AS1 may serve as a potential target for the treatment of pancreatic cancer.

The effect of miRNA and autophagy on colorectal cancer

Colorectal cancer (CRC) has become a concern because of its high recurrence rate and metastasis rate, low early diagnosis rate and poor therapeutic effect. At present, various studies have shown that autophagy is closely connected with the occurrence and progression of CRC. Autophagy is a highly cytosolic catabolic process involved in lysosomes in biological evolution. Cells degrade proteins and damaged organelles by autophagy to achieve material circulation and maintain cell homeostasis. Moreover, microRNAs are key regulators of autophagy, and their mediated regulation of transcriptional and post‐transcriptional levels plays an important role in autophagy in CRC cells. This review focuses on the recent research advances of how autophagy and related microRNAs are involved in affecting occurrence and progression of CRC and provides a new perspective for the study of CRC treatment strategies.

Development of Prognostic Indicator Based on Autophagy-Related lncRNA Analysis in Colon Adenocarcinoma

There were no systematic researches about autophagy-related long noncoding RNA (lncRNA) signatures to predict the survival of patients with colon adenocarcinoma. It was necessary to set up corresponding autophagy-related lncRNA signatures. The expression profiles of lncRNAs which contained 480 colon adenocarcinoma samples were obtained from The Cancer Genome Atlas (TCGA) database. The coexpression network of lncRNAs and autophagy-related genes was utilized to select autophagy-related lncRNAs. The lncRNAs were further screened using univariate Cox regression. In addition, Lasso regression and multivariate Cox regression were used to develop an autophagy-related lncRNA signature. A risk score based on the signature was established, and Cox regression was used to test whether it was an independent prognostic factor. The functional enrichment of autophagy-related lncRNAs was visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Ten prognostic autophagy-related lncRNAs (AC027307.2, AC068580.3, AL138756.1, CD27-AS1, EIF3J-DT, LINC01011, LINC01063, LINC02381, AC073896.3, and SNHG16) were identified to be significantly different, which made up an autophagy-related lncRNA signature. The signature divided patients with colon adenocarcinoma into the low-risk group and the high-risk group. A risk score based on the signature was a significantly independent factor for the patients with colon adenocarcinoma (HR = 1.088, 95%CI = 1.057 - 1.120; P < 0.001). Additionally, the ten lncRNAs were significantly enriched in autophagy process, metabolism, and tumor classical pathways. In conclusion, the ten autophagy-related lncRNAs and their signature might be molecular biomarkers and therapeutic targets for the patients with colon adenocarcinoma.

The crosstalk between lncRNAs and the Hippo signalling pathway in cancer progression

LncRNAs play a pivotal role in the regulation of epigenetic modification, cell cycle, differentiation, proliferation, migration and other physiological activities. In particular, considerable studies have shown that the aberrant expression and dysregulation of lncRNAs are widely implicated in cancer initiation and progression by acting as tumour promoters or suppressors. Hippo signalling pathway has attracted researchers’ attention as one of the critical cancer‐related pathways in recent years. Increasing evidences have demonstrated that lncRNAs could interact with Hippo cascade and thereby contribute to acquisition of multiple malignant hallmarks, including proliferation, metastasis, relapse and resistance to anti‐cancer treatment. Specifically, Hippo signalling pathway is reported to modulate or be regulated by widespread lncRNAs. Intriguingly, certain lncRNAs could form a reciprocal feedback loop with Hippo signalling. More speculatively, lncRNAs related to Hippo pathway have been poised to become important putative biomarkers and therapeutic targets in human cancers. Herein, this review focuses on the crosstalk between lncRNAs and Hippo pathway in carcinogenesis, summarizes the comprehensive role of Hippo‐related lncRNAs in tumour progression and depicts their clinical diagnostic, prognostic or therapeutic potentials in tumours.