The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes

Emerging roles of long noncoding RNAs in enzymes related intracellular metabolic pathways in cancer biology

Metabolic reprogramming plays critical roles in the development and progression of tumor by providing cancer cells with a sufficient supply of nutrients and other factors needed for fast-proliferating. Emerging evidence indicates that long noncoding RNAs (lncRNAs) are involved in the initiation of metastasis via regulating the metabolic reprogramming in various cancers. In this paper, we aim to summarize that lncRNAs could participate in intracellular nutrient metabolism including glucose, amino acid, lipid, and nucleotide, regardless of whether lncRNAs have tumor-promoting or tumor-suppressor function. Meanwhile, modulation of lncRNAs in glucose metabolic enzymes in glycolysis, pentose phosphate pathway and tricarboxylic acid cycle (TCA) in cancer is reviewed. We also discuss therapeutic strategies targeted at interfering with enzyme activity to decrease the utilization of glucoses, amino acid, nucleotide acid and lipid in tumor cells. This review focuses on our current understanding of lncRNAs participating in cancer cell metabolic reprogramming, paving the way for further investigation into the combination of such approaches with existing anti-cancer therapies.

Predictive significance of glycolysis-associated lncRNA profiles in colorectal cancer progression

BACKGROUND

The Warburg effect is a hallmark characteristic of colorectal cancer (CRC). Despite extensive research, the role of long non-coding RNAs (lncRNAs) in influencing the Warburg effect remains incompletely understood. Our study aims to identify lncRNAs that may modulate the Warburg effect by functioning as competing endogenous RNAs (ceRNAs).

METHODS

Utilizing bioinformatics approaches, we extracted glycolysis-associated gene data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and identified 101 glycolysis-related lncRNAs in CRC. We employed Univariable Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, and Multivariable Cox regression to develop a prognostic model comprising four glycolysis-linked lncRNAs. We then constructed a prognostic nomogram integrating this lncRNA model with other relevant clinical parameters.

RESULTS

The prognostic efficacy of our four-lncRNA signature and its associated nomogram was validated in both training and validation cohorts. Functional assays demonstrated significant glycolysis and hexokinase II (HK2) inhibition following the silencing of RUNDC3A - AS1, a key lncRNA in our prognostic signature, highlighting its regulatory importance in the Warburg effect.

CONCLUSIONS

Our research illuminates the critical role of glycolysis-centric lncRNAs in CRC. The developed prognostic model and nomogram underscore the pivotal prognostic and regulatory significance of the lncRNA RUNDC3A - AS1 in the Warburg effect in colorectal cancer.

CircRNA-regulated glucose metabolism in ovarian cancer: an emerging landscape for therapeutic intervention

Ovarian cancer (OC) has the highest mortality rate among female reproductive system tumours, with limited efficacy of traditional treatments and 5-year survival rates that rarely exceed 40%. Circular RNA (circRNA) is a stable endogenous circular RNA that typically regulates protein expression by binding to downstream miRNA. It has been demonstrated that circRNAs play an important role in the proliferation, migration, and glucose metabolism (such as the Warburg effect) of OC and can regulate the expression of glucose metabolism-related proteins such as GLUT1 and HK2, promoting anaerobic glycolysis of cancer cells, increasing glucose uptake and ATP production, and affecting energy supply and biosynthetic substances to support tumour growth and invasion. This review summarises the formation and characteristics of circRNAs and focuses on their role in regulating glucose metabolism in OC cells and their potential therapeutic value, providing insights for identifying new therapeutic targets.

Ascites exosomal lncRNA PLADE enhances platinum sensitivity by inducing R-loops in ovarian cancer

Cisplatin resistance is a major cause of therapeutic failure in patients with high-grade serous ovarian cancer (HGSOC). Long noncoding RNAs (lncRNAs) have emerged as key regulators of human cancers; however, their modes of action in HGSOC remain largely unknown. Here, we provide evidence to demonstrate that lncRNA Platinum sensitivity-related LncRNA from Ascites-Derived Exosomes (PLADE) transmitted by ascites exosomes enhance platinum sensitivity in HGSOC. PLADE exhibited significantly decreased expression in ascites exosomes and tumor tissues, as well as in the corresponding metastatic tumors from patients with HGSOC cisplatin-resistance. Moreover, HGSOC patients with higher PLADE expression levels exhibited longer progression-free survival. Gain- and loss-of-function studies have revealed that PLADE promotes cisplatin sensitivity by suppressing cell proliferation, migration and invasion, and enhancing apoptosis in vitro and in vivo. Furthermore, the functions of PLADE in increasing cisplatin sensitivity were proven to be transferred by exosomes to the cultured recipient cells and to the adjacent tumor tissues in mouse models. Mechanistically, PLADE binds to and downregulates heterogeneous nuclear ribonucleoprotein D (HNRNPD) by VHL-mediated ubiquitination, thus inducing an increased amount of RNA: DNA hybrids (R-loop) and DNA damage, consequently promoting cisplatin sensitivity in HGSOC. Collectively, these results shed light on the understanding of the vital roles of long noncoding RNAs in cancers.

Analysis of the potential biological value of pyruvate dehydrogenase E1 subunit β in human cancer

BACKGROUND

The pyruvate dehydrogenase E1 subunit β (PDHB) gene which regulates energy metabolism is located in mitochondria. However, few studies have elucidated the role and mechanism of PDHB in different cancers.

AIM

To comprehensive pan-cancer analysis of PDHB was performed based on bioinformatics approaches to explore its tumor diagnostic and prognostic value and tumor immune relevance in cancer. In vitro experiments were performed to examine the biological regulation of PDHB in liver cancer.

METHODS

Pan-cancer data related to PDHB were obtained from the Cancer Genome Atlas (TCGA) database. Analysis of the gene expression profiles of PDHB was based on TCGA and Genotype Tissue Expression Dataset databases. Cox regression analysis and Kaplan-Meier methods were used to assess the correlation between PDHB expression and survival prognosis in cancer patients. The correlation between PDHB and receiver operating characteristic diagnostic curve, clinicopathological staging, somatic mutation, tumor mutation burden (TMB), microsatellite instability (MSI), DNA methylation, and drug susceptibility in pan-cancer was also analyzed. Various algorithms were used to analyze the correlation between PDHB and immune cell infiltration and tumor chemotaxis environment, as well as the co-expression analysis of PDHB and immune checkpoint (ICP) genes. The expression and functional phenotype of PDHB in single tumor cells were studied by single-cell sequencing, and the functional enrichment analysis of PDHB-related genes was performed. The study also validated the level of mRNA or protein expression of PDHB in several cancers. Finally, in vitro experiments verified the regulatory effect of PDHB on the proliferation, migration, and invasion of liver cancer.

RESULTS

PDHB was significantly and differently expressed in most cancers. PDHB was significantly associated with prognosis in patients with a wide range of cancers, including kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, breast invasive carcinoma, and brain lower grade glioma. In some cancers, PDHB expression was clearly associated with gene mutations, clinicopathological stages, and expression of TMB, MSI, and ICP genes. The expression of PDHB was closely related to the infiltration of multiple immune cells in the immune microenvironment and the regulation of tumor chemotaxis environment. In addition, single-cell sequencing results showed that PDHB correlated with different biological phenotypes of multiple cancer single cells. This study further demonstrated that down-regulation of PDHB expression inhibited the proliferation, migration, and invasion functions of hepatoma cells.

CONCLUSION

As a member of pan-cancer, PDHB may be a novel cancer marker with potential value in diagnosing cancer, predicting prognosis, and in targeted therapy.

Insights into the tumor-stromal-immune cell metabolism cross talk in ovarian cancer

The ovarian cancer tumor microenvironment (TME) consists of a constellation of abundant cellular components, extracellular matrix, and soluble factors. Soluble factors, such as cytokines, chemokines, structural proteins, extracellular vesicles, and metabolites, are critical means of noncontact cellular communication acting as messengers to convey pro- or antitumorigenic signals. Vast advancements have been made in our understanding of how cancer cells adapt their metabolism to meet environmental demands and utilize these adaptations to promote survival, metastasis, and therapeutic resistance. The stromal TME contribution to this metabolic rewiring has been relatively underexplored, particularly in ovarian cancer. Thus, metabolic activity alterations in the TME hold promise for further study and potential therapeutic exploitation. In this review, we focus on the cellular components of the TME with emphasis on 1) metabolic signatures of ovarian cancer; 2) understanding the stromal cell network and their metabolic cross talk with tumor cells; and 3) how stromal and tumor cell metabolites alter intratumoral immune cell metabolism and function. Together, these elements provide insight into the metabolic influence of the TME and emphasize the importance of understanding how metabolic performance drives cancer progression.

Mitochondrial heterogeneity in diseases

As key organelles involved in cellular metabolism, mitochondria frequently undergo adaptive changes in morphology, components and functions in response to various environmental stresses and cellular demands. Previous studies of mitochondria research have gradually evolved, from focusing on morphological change analysis to systematic multiomics, thereby revealing the mitochondrial variation between cells or within the mitochondrial population within a single cell. The phenomenon of mitochondrial variation features is defined as mitochondrial heterogeneity. Moreover, mitochondrial heterogeneity has been reported to influence a variety of physiological processes, including tissue homeostasis, tissue repair, immunoregulation, and tumor progression. Here, we comprehensively review the mitochondrial heterogeneity in different tissues under pathological states, involving variant features of mitochondrial DNA, RNA, protein and lipid components. Then, the mechanisms that contribute to mitochondrial heterogeneity are also summarized, such as the mutation of the mitochondrial genome and the import of mitochondrial proteins that result in the heterogeneity of mitochondrial DNA and protein components. Additionally, multiple perspectives are investigated to better comprehend the mysteries of mitochondrial heterogeneity between cells. Finally, we summarize the prospective mitochondrial heterogeneity-targeting therapies in terms of alleviating mitochondrial oxidative damage, reducing mitochondrial carbon stress and enhancing mitochondrial biogenesis to relieve various pathological conditions. The possibility of recent technological advances in targeted mitochondrial gene editing is also discussed.

Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological cancers worldwide, mainly because of its initially asymptomatic nature and consequently late diagnosis. Long non-coding RNAs (lncRNA) are non-coding transcripts of more than 200 nucleotides, whose deregulation is involved in pathologies such as EOC, and are therefore envisaged as future biomarkers. We present a meta-analysis of available gene expression profiling (microarray and RNA sequencing) studies from EOC patients to identify lncRNA genes with diagnostic and prognostic value. In this meta-analysis, we include 46 independent cohorts, along with available expression profiling data from EOC cell lines. Differential expression analyses were conducted to identify those lncRNAs that are deregulated in (i) EOC versus healthy ovary tissue, (ii) unfavorable versus more favorable prognosis, (iii) metastatic versus primary tumors, (iv) chemoresistant versus chemosensitive EOC, and (v) correlation to specific histological subtypes of EOC. From the results of this meta-analysis, we established a panel of lncRNAs that are highly correlated with EOC. The panel includes several lncRNAs that are already known and even functionally characterized in EOC, but also lncRNAs that have not been previously correlated with this cancer, and which are discussed in relation to their putative role in EOC and their potential use as clinically relevant tools.

The Role of Genetic Mutations in Mitochondrial-Driven Cancer Growth in Selected Tumors: Breast and Gynecological Malignancies

There is an increasing understanding of the molecular and cytogenetic background of various tumors that helps us better conceptualize the pathogenesis of specific diseases. Additionally, in many cases, these molecular and cytogenetic alterations have diagnostic, prognostic, and/or therapeutic applications that are heavily used in clinical practice. Given that there is always room for improvement in cancer treatments and in cancer patient management, it is important to discover new therapeutic targets for affected individuals. In this review, we discuss mitochondrial changes in breast and gynecological (endometrial and ovarian) cancers. In addition, we review how the frequently altered genes in these diseases (BRCA1/2, HER2, PTEN, PIK3CA, CTNNB1, RAS, CTNNB1, FGFR, TP53, ARID1A, and TERT) affect the mitochondria, highlighting the possible associated individual therapeutic targets. With this approach, drugs targeting mitochondrial glucose or fatty acid metabolism, reactive oxygen species production, mitochondrial biogenesis, mtDNA transcription, mitophagy, or cell death pathways could provide further tailored treatment.

Diagnostic value of non-coding RNAs in ovarian cancer

The type of primary tumour of the ovary ranks first among all organs in the body. Although the incidence of malignant ovarian tumour ranks third among gynaecological malignancies, it is the most fatal type. A lack of effective diagnostic methods for early ovarian cancer remains, and the efficacy of advanced ovarian cancer is often unsatisfactory; the five-year survival rate of stage III-IV is less than 30%. Non-coding RNA is RNA that does not have protein-coding potential and was once considered as 'junk DNA'. However, increasing number of studies have shown that the disorder of non-coding RNA is related to a variety of diseases, including the occurrence and development of tumours. We summarised the dysregulated non-coding RNAs (miRNAs, circRNAs, and lncRNAs) reported currently in ovarian cancer and their functional mechanisms, and the clinical value of different types of ncRNAs as diagnostic or predictive markers for ovarian cancer, providing further evidence for non-coding RNAs to be considered as biomarkers of ovarian cancer.

Recent advances in understanding the metabolic plasticity of ovarian cancer: A systematic review

Epithelial ovarian cancer (EOC) is a gynecologic malignancy with a poor prognosis due to resistance to first-line chemotherapeutic agents. Some cancer cells are primarily dependent on glycolysis, but others favor mitochondrial oxidative phosphorylation (OXPHOS) over glycolysis. Changes in metabolic reprogramming have been reported to be involved in cancer cell survival. In this review, we summarize the metabolic profiles (e.g., metabolic heterogeneity, plasticity, and reprogramming) and adaptation to the dynamic tumor microenvironment and discuss potential novel therapeutic strategies. A literature search was performed between January 2000 and March 2022 in the PubMed and Google Scholar databases using a combination of specific terms. Ovarian cancer cells, including cancer stem cells, depend on glycolysis, OXPHOS, or both for survival. Several environmental stresses, such as nutrient starvation or glucose deprivation, hypoxic stress, acidification, and excessive reactive oxygen species (ROS) generation, reprogram the metabolic pathways to adapt. The interaction between tumors and adjacent stromal cells allows cancer cells to enhance mitochondrial energy metabolism. The metabolic reprogramming varies depending on genomic and epigenetic alterations of metabolism-related genes and the metabolic environment. Developing accurate and non-invasive methods for early identification of metabolic alterations could facilitate optimal cancer diagnosis and treatment. Cancer metabolism research has entered an exciting era where novel strategies targeting metabolic profiling will become more innovative.

Small nucleolar RNA host gene 3 functions as a novel biomarker in liver cancer and other tumour progression

Cancer has become the most life-threatening disease in the world. Mutations in and aberrant expression of genes encoding proteins and mutations in noncoding RNAs, especially long noncoding RNAs (lncRNAs), have significant effects in human cancers. LncRNAs have no protein-coding ability but function extensively in numerous physiological and pathological processes. Small nucleolar RNA host gene 3 (SNHG3) is a novel lncRNA and has been reported to be differentially expressed in various tumors, such as liver cancer, gastric cancer, and glioma. However, the interaction mechanisms for the regulation between SNHG3 and tumor progression are poorly understood. In this review, we summarize the results of SNHG3 studies in humans, animal models, and cells to underline the expression and role of SNHG3 in cancer. SNHG3 expression is upregulated in most tumors and is detrimental to patient prognosis. SNHG3 expression in lung adenocarcinoma remains controversial. Concurrently, SNHG3 affects oncogenes and tumor suppressor genes through various mechanisms, including competing endogenous RNA effects. A deeper understanding of the contribution of SNHG3 in clinical applications and tumor development may provide a new target for cancer diagnosis and treatment.

Mitochondrial Dysfunction Pathway Alterations Offer Potential Biomarkers and Therapeutic Targets for Ovarian Cancer

The mitochondrion is a very versatile organelle that participates in some important cancer-associated biological processes, including energy metabolism, oxidative stress, mitochondrial DNA (mtDNA) mutation, cell apoptosis, mitochondria-nuclear communication, dynamics, autophagy, calcium overload, immunity, and drug resistance in ovarian cancer. Multiomics studies have found that mitochondrial dysfunction, oxidative stress, and apoptosis signaling pathways act in human ovarian cancer, which demonstrates that mitochondria play critical roles in ovarian cancer. Many molecular targeted drugs have been developed against mitochondrial dysfunction pathways in ovarian cancer, including olive leaf extract, nilotinib, salinomycin, Sambucus nigra agglutinin, tigecycline, and eupatilin. This review article focuses on the underlying biological roles of mitochondrial dysfunction in ovarian cancer progression based on omics data, potential molecular relationship between mitochondrial dysfunction and oxidative stress, and future perspectives of promising biomarkers and therapeutic targets based on the mitochondrial dysfunction pathway for ovarian cancer.

Noncoding RNAs in the Glycolysis of Ovarian Cancer

Energy metabolism reprogramming is the characteristic feature of tumors. The tumorigenesis, metastasis, and drug resistance of ovarian cancer (OC) is dependent on energy metabolism. Even under adequate oxygen conditions, OC cells tend to convert glucose to lactate, and glycolysis can rapidly produce ATP to meet their metabolic energy needs. Non-coding RNAs (ncRNAs) interact directly with DNA, RNA, and proteins to function as an essential regulatory in gene expression and tumor pathology. Studies have shown that ncRNAs regulate the process of glycolysis by interacting with the predominant glycolysis enzyme and cellular signaling pathway, participating in tumorigenesis and progression. This review summarizes the mechanism of ncRNAs regulation in glycolysis in OC and investigates potential therapeutic targets.

Role of Mitochondria in Interplay between NGF/TRKA, miR-145 and Possible Therapeutic Strategies for Epithelial Ovarian Cancer

Ovarian cancer is the most lethal gynecological neoplasm, and epithelial ovarian cancer (EOC) accounts for 90% of ovarian malignancies. The 5-year survival is less than 45%, and, unlike other types of cancer, the proportion of women who die from this disease has not improved in recent decades. Nerve growth factor (NGF) and tropomyosin kinase A (TRKA), its high-affinity receptor, play a crucial role in pathogenesis through cell proliferation, angiogenesis, invasion, and migration. NGF/TRKA increase their expression during the progression of EOC by upregulation of oncogenic proteins as vascular endothelial growth factor (VEGF) and c-Myc. Otherwise, the expression of most oncoproteins is regulated by microRNAs (miRs). Our laboratory group reported that the tumoral effect of NGF/TRKA depends on the regulation of miR-145 levels in EOC. Currently, mitochondria have been proposed as new therapeutic targets to activate the apoptotic pathway in the cancer cell. The mitochondria are involved in a myriad of functions as energy production, redox control, homeostasis of Ca⁺², and cell death. We demonstrated that NGF stimulation produces an augment in the Bcl-2/BAX ratio, which supports the anti-apoptotic effects of NGF in EOC cells. The review aimed to discuss the role of mitochondria in the interplay between NGF/TRKA and miR-145 and possible therapeutic strategies that may decrease mortality due to EOC.

LncRNA SNHG3 promotes gastric cancer cell proliferation and metastasis by regulating the miR-139-5p/MYB axis

The long non-coding RNA (lncRNA) SNHG3 has been shown to play oncogenic roles in several cancer types, but the mechanisms underlying its activity are poorly understood. In this study, we aimed to explore the clinical relevance and mechanistic role of SNHG3 in gastric cancer (GC). We found that SNHG3 expression in GC cell lines and tissues was significantly increased, and the upregulation of this lncRNA was correlated with tumor clinical stage and decreased patient survival. Knocking down SNHG3 in GC cells impaired the proliferative, migratory, and invasive activity in vitro and constrained in vivo GC xenograft tumor growth. Mechanistically, SNHG3 was found to bind and sequester miR-139-5p, thereby indirectly promoting the upregulation of the miR-139-5p target gene MYB. These data demonstrated that SNHG3 functions in an oncogenic manner to drive GC proliferation, migration, and invasion by regulating the miR-139-5p/MYB axis.

A novel lncRNA-protein interaction prediction method based on deep forest with cascade forest structure

Long noncoding RNAs (lncRNAs) regulate many biological processes by interacting with corresponding RNA-binding proteins. The identification of lncRNA-protein Interactions (LPIs) is significantly important to well characterize the biological functions and mechanisms of lncRNAs. Existing computational methods have been effectively applied to LPI prediction. However, the majority of them were evaluated only on one LPI dataset, thereby resulting in prediction bias. More importantly, part of models did not discover possible LPIs for new lncRNAs (or proteins). In addition, the prediction performance remains limited. To solve with the above problems, in this study, we develop a Deep Forest-based LPI prediction method (LPIDF). First, five LPI datasets are obtained and the corresponding sequence information of lncRNAs and proteins are collected. Second, features of lncRNAs and proteins are constructed based on four-nucleotide composition and BioSeq2vec with encoder-decoder structure, respectively. Finally, a deep forest model with cascade forest structure is developed to find new LPIs. We compare LPIDF with four classical association prediction models based on three fivefold cross validations on lncRNAs, proteins, and LPIs. LPIDF obtains better average AUCs of 0.9012, 0.6937 and 0.9457, and the best average AUPRs of 0.9022, 0.6860, and 0.9382, respectively, for the three CVs, significantly outperforming other methods. The results show that the lncRNA FTX may interact with the protein P35637 and needs further validation.

LncRNA RP11-499E18.1 Inhibits Proliferation, Migration, and Epithelial-Mesenchymal Transition Process of Ovarian Cancer Cells by Dissociating PAK2-SOX2 Interaction

Background: Ovarian cancer (OC)is a deadly gynecological malignancy worldwide. It is urgent to identify diagnostic biomarkers of OC to disclose the underlying mechanism. Methods and Materials: Bioinformatics analysis was used to identify target genes. Gene expression was detected and altered by qRT-PCR and cell transfection, respectively. The interaction between RP11-499E18.1 and PAK2, as well as that between PAK2 and SOX2, was determined using RNA pulldown, RNA immunoprecipitation (RIP), and co-immunoprecipitation (co-IP) assay, respectively. Localizations of RP11-499E18.1, PAK2, and SOX2 were respectively determined employing immunohistochemical (IHC), IF, and FISH. The regulatory effects of RP11-499E18.1, PAK2, and SOX2 on OC cell proliferation, migration, colony formation, epithelial-mesenchymal transition (EMT)-related factor expression, and SOX2 nuclear translocation were determined. Finally, the effects of RP11-499E18.1 and PAK2 expression on the tumor growth in nude mice were determined. Results: RP11-499E18.1, PAK2, and SOX2 were selected in our study. RP11-499E18.1 was downregulated, while PAK2 and SOX2 was upregulated in OC tissues and cells. RP11-499E18.1 coexists in the nucleus and cytoplasm of OC cells. There is an interaction between RP11-499E18.1 and PAK2, as well as PAK2 and SOX2 in OC cells. Alteration of RP11-499E18.1 and PAK2 expression both had no influence on PAK2 and SOX2 levels, but PAK2 upregulation notably augmented p-SOX2 level. RP11-499E18.1 overexpression suppressed OC cell proliferation, migration, and colony formation, as well as SOX2 nuclear translocation. Besides, it inhibited tumor growth in nude mice. However, these effects were notably reversed by PAK2 upregulation and eventually offset by SOX2 knockdown. Additionally, RP11-499E18.1 overexpression reduced PAK2-SOX2 interaction and SOX phosphorylation, and increased the binding of RP11-499E18.1 by PAK2. Conclusion: These lines of evidence demonstrated that RP11-499E18.1 might play its tumor suppressor roles in OC via regulation of the RP11-499E18.1-PAK2-SOX2 axis. This research indicated that RP11-499E18.1 might be used as a diagnostic biomarker for OC in the future.

Eukaryotic Initiation Factor 4A-3: A Review of Its Physiological Role and Involvement in Oncogenesis

EIF4A3, a member of the DEAD-box protein family, is a nuclear matrix protein and a core component of the exon junction complex (EJC). Under physiological conditions, EIF4A3 participates in post-transcriptional gene regulation by promoting EJC control of precursor mRNA splicing, thus influencing nonsense-mediated mRNA decay. In addition, EIF4A3 maintains the expression of significant selenoproteins, including phospholipid hydroperoxide glutathione peroxidase and thioredoxin reductase 1. Several recent studies have shown that EIF4A3 promotes tumor growth in multiple human cancers such as glioblastoma, hepatocellular carcinoma, pancreatic cancer, and ovarian cancer. Molecular biology studies also showed that EIF4A3 is recruited by long non-coding RNAs to regulate the expression of certain proteins in tumors. However, its tumor-related functions and underlying mechanisms are not well understood. Here, we review the physiological role of EIF4A3 and the potential association between EIF4A3 overexpression and tumorigenesis. We also evaluate the protein's potential utility as a diagnosis biomarker, therapeutic target, and prognosis indicator, hoping to provide new ideas for future research.

Identification of Glycolysis-Related lncRNAs and the Novel lncRNA WAC-AS1 Promotes Glycolysis and Tumor Progression in Hepatocellular Carcinoma

BACKGROUND

High glycolysis efficiency in tumor cells can promote tumor growth. lncRNAs play an important role in the proliferation, metabolism and migration of cancer cells, but their regulation of tumor glycolysis is currently not well researched.

METHODS

We analyzed the co-expression of glycolysis-related genes and lncRNAs in The Cancer Genome Atlas (TCGA) database to screen glycolysis-related lncRNAs. Further prognostic analysis and differential expression analysis were performed. We further analyzed the relationship between lncRNAs and tumor immune infiltration. Since WAC antisense RNA 1 (WAC-AS1) had the greatest effect on the prognosis among all screened lncRNAs and had a larger coefficient in the prognostic model, we chose WAC-AS1 for further verification experiments and investigated the function and mechanism of action of WAC-AS1 in hepatocellular carcinoma.

RESULTS

We screened 502 lncRNAs that have co-expression relationships with glycolytic genes based on co-expression analysis. Among them, 112 lncRNAs were abnormally expressed in liver cancer, and 40 lncRNAs were related to the prognosis of patients. Eight lncRNAs (WAC-AS1, SNHG3, SNHG12, MSC-AS1, MIR210HG, PTOV1-AS1, AC145207.5 and AL031985.3) were used to established a prognostic model. Independent prognostic analysis (P<0.001), survival analysis (P<0.001), receiver operating characteristic (ROC) curve analysis (AUC=0.779) and clinical correlation analysis (P<0.001) all indicated that the prognostic model has good predictive power and that the risk score can be used as an independent prognostic factor (P<0.001). The risk score and lncRNAs in the model were found to be related to a variety of immune cell infiltration and immune functions. WAC-AS1 was found to affect glycolysis and promote tumor proliferation (P<0.01). WAC-AS1 affected the expression of several glycolysis-related genes (cAMP regulated phosphoprotein 19 (ARPP19), CHST12, MED24 and KIF2A) (P<0.01). Under hypoxic conditions, WAC-AS1 regulated ARPP19 by sponging miR-320d to promote glucose uptake and lactate production (P<0.01).

CONCLUSION

We constructed a model based on glycolysis-related lncRNAs to evaluate the prognostic risk of patients. The risk score and lncRNAs in the model were related to immune cell infiltration. WAC-AS1 can regulate ARPP19 to promote glycolysis and proliferation by sponging miR-320d.

LncRNA SNHG20 promotes cell proliferation and invasion by suppressing miR-217 in ovarian cancer

Background

Ovarian cancer is the most common female gynecological malignancy. SNHG20, as a long non-coding RNA, has been proven to be an important regulator in the occurrence and development of various tumors. However, the potential mechanism of SNHG20 in ovarian cancer is unclear.

Objective

The present study was aimed to investigate the functions and mechanisms of SNHG20 in ovarian cancer.

Methods

The expression of SNHG20 and miR-217 in ovarian cancer tissues and cell lines was detected by qRT-PCR. CCK-8 assay was used to measure cell proliferation in transfected cells. The transwell assay was used to detect the relative invasion rate of transfected cells. The putative binding sites between SNHG20 and miR-217 were predicted by software LncBase v.2, and the interaction between SNHG20 and miR-217 was confirmed by dual-luciferase reporter assays and RIP assay. The rescue experiments were used to illustrate potential mechanisms.

Results

SNHG20 was upregulated in ovarian cancer tissues and cell lines. Overexpression of SNHG20 promoted ovarian cancer cell proliferation and invasion. MiR-217 was downregulated in ovarian cancer tissues and cells, and was negatively regulated by SNHG20. Moreover, miR-217 overexpression inhibited ovarian cancer cell proliferation and invasion. Furthermore, miR-217 mimic reversed the inhibitory effect of SNHG20 overexpression on the biological behavior of ovarian cancer cells.

Conclusions

SNHG20 promoted cell proliferation and invasion by sponging miR-217 in ovarian cancer. These results suggested that SNHG20 and miR-217 might provide new targets for therapeutic application in ovarian cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13258-021-01138-4.

LncRNA SNHG3 Promotes Gastric Cancer Cells Proliferation, Migration, and Invasion by Targeting miR-326

The function and possible mechanism of lncRNA Small Nucleolar RNA Host Gene 3 (SNHG3) in GC have not been fully studied. The aim of our study was to investigate the role of SNHG3 in the proliferation, migration, and invasion of GC cell lines. The expressions of SNHG3, miR-326, and TWIST in GC9811-P GC cell lines were detected by RT-qPCR. Western blotting was performed to detect the protein levels of TWIST and EMT-related genes. Luciferase reporter gene analysis and RNA immunoprecipitation (RIP) analysis confirmed the interaction between lncRNA SNHG3, miR-326, and TWIST. CCK-8 and Transwell assays were performed to detect cell proliferation, invasion, and migration abilities. The results showed that lncRNA SNHG3 and TWIST were highly expressed in GC cell lines, while miR-326 was expressed to a low degree. Moreover, lncRNA SNHG3 knockdown or miR-326 overexpression significantly inhibited cell proliferation, migration, and invasion of GC cell lines. In addition, TWIST overexpression can reverse the inhibition of lncRNA SNHG3 knockdown or miR-326 overexpression on cell proliferation, migration, and invasion. In conclusion, lncRNA SNHG3 may promote GC progression through the miR-326/TWIST axis, which may provide a new diagnostic and prognostic biomarker for GC.

Long non-coding RNAs: A view to kill ovarian cancer

An emerging role of long non-coding RNAs (lncRNAs) in tumor progression has been revealed in the last decade. Through interactions with nucleic acids and proteins, lncRNAs could act as enhancers, scaffolds or decoys for a number of oncoproteins and tumor suppressors. The aberrant lncRNA expression or mutations are often associated with changes in a variety of cellular processes, including proliferation, stress response and cell death. Here, we will focus on the tumor-associated lncRNAs in ovarian cancer according to their contribution to cancer hallmarks, such as intense proliferation, cell death resistance, altered energy metabolism, invasion and metastasis, and immune evasion. Moreover, the potential clinical implications of lncRNAs and their significance for the diagnosis, prognosis and therapy of ovarian cancer will be discussed.

Long non‑coding RNA SNHG3 promotes the development of non‑small cell lung cancer via the miR‑1343‑3p/NFIX pathway

The aim of the present study was to identify the function of long non‑coding RNA (lncRNA) small nucleolar RNA host gene 3 (SNHG3) and examine its effects on non‑small cell lung cancer (NSCLC). A series of in vitro experiments were employed to evaluate the effects of SNHG3 on the progression of NSCLC, including Cell Counting Kit‑8, 5‑Ethynyl‑2'‑deoxyuridine, flow cytometry, wound healing, Transwell, western blotting and reverse transcription‑quantitative PCR assays. Bioinformatics analyses and a luciferase reporter assay were performed to identify the target gene of SNHG3 and microRNA (miR)‑1343‑3p. Finally, recuse experiments were conducted to verify the effect of SNHG3 and its target gene on proliferation, apoptosis, migration and invasion. The findings indicated that lncRNA SNHG3 was highly expressed in NSCLC tissues and cell lines. Knockdown of lncRNA SNHG3 inhibited cell proliferation, migration and invasion, and accelerated cell apoptosis in NSCLC cell lines. The results of the bioinformatics analysis and the luciferase reporter assay indicated that lncRNA SNHG3 directly bound to miR‑1343‑3p and that it could downregulate the expression levels of miR‑1343‑3p to promote the progression of NSCLC. Rescue experiments indicated that lncRNA SNHG3 increased nuclear factor IX (NFIX) expression by sequestering miR‑1343‑3p in NSCLC. These results suggested that the SNHG3/miR‑1343‑3p/NFIX axis may serve as a novel prognostic biomarker and therapeutic target for NSCLC.

A four-lncRNA signature for predicting prognosis of recurrence patients with gastric cancer

Purpose

This study aimed to develop a multi-long noncoding RNA (lncRNA) signature for the prediction of gastric cancer (GC) based on differential gene expression between recurrence and nonrecurrence patients.

Methods

By repurposing microarray expression profiles of RNAs from The Cancer Genome Atlas (TCGA), we performed differential expression analysis between recurrence and nonrecurrence patients. A prognostic risk prediction model was constructed based on data from TCGA database, and its reliability was validated using data from Gene Expression Omnibus database. Furthermore, the lncRNA-associated competing endogenous RNA (ceRNA) network was constructed, namely, DIANA-LncBasev2 and starBase database.

Results

We identified 363 differentially expressed RNAs (317 mRNAs, 18 lncRNAs, and 28 microRNAs [miRNAs]). Principal component analysis showed that the seven-feature lncRNAs screened by support vector machine-recursive feature elimination algorithm was more informative for predicting recurrence of GC in comparison with the eight-feature lncRNAs screened by random forest-out-of-bag algorithm. Four of the seven-feature lncRNAs including LINC00843, SNHG3, C21orf62-AS1, and MIR99AHG were chosen to develop a four-lncRNA risk score model. This risk score model was able to distinguish patients with high and low risk of recurrence, and was tested in two independent validation sets. The ceRNA network of this four-lncRNA signature included 10 miRNAs and 178 mRNAs. The mRNAs significantly related to the Wnt-signaling pathway and relevant biological processes.

Conclusion

A useful four-lncRNA signature recurrence was established to distinguish GC patients with high and low risk of recurrence. Regulating the relevant miRNAs and Wnt pathway might partly affect GC metastasisby.

Knockdown of Long Non-coding RNA SNGH3 by CRISPR-dCas9 Inhibits the Progression of Bladder Cancer

Recent research evidence documents that lncRNAs (long non-coding RNAs lncRNAs) play a pivotal role in the tumorigenesis and development of tumors. LncRNA SNGH3 (small nucleolar RNA host gene 3) is highly expressed in numerous forms of cancer, serving as an oncogene in cancer progression. Nonetheless, the clinical relationship, along with the mechanism of SNGH3 in bladder cancer, have not been studied. Herein, the findings exhibited upregulation of SNGH3 in bladder cancer tissues, along with the cell lines. Furthermore, overexpressed SNGH3 was positively linked to the TNM stage, as well as the histological grade of bladder cancer. Moreover, the silencing of SNGH3, using CRISPR-dCas9, suppressed cell growth along with migration, but elevated bladder cancer cell apoptosis. In summary, we established that SNGH3 serves as a bladder cancer oncogene and could be employed as a prospective diagnostic marker for clinical use, and is also a therapeutic target for CRISPR-mediated gene therapy.

Long non‑coding RNA OIP5‑AS1 facilitates the progression of ovarian cancer via the miR‑128‑3p/CCNG1 axis

Long non‑coding RNA (LncRNA) o‑phthalaldehyde-interacting protein 5 antisense transcript 1 (OIP5‑AS1) serves major roles in the progression of various types of cancer. The present study investigated its biological function in ovarian cancer (OC) and its mechanisms. The levels of OIP5‑AS1, microRNA‑128‑3p (miR‑128‑3p) and cyclin G1 (CCNG1) were examined by reverse transcription‑quantitative PCR. Cell viability, apoptosis, migration and invasion were detected to analyze cellular progression. Glycolytic metabolism was assessed by detecting the levels of glucose consumption and lactate production. CCNG1 and hexokinase 2 protein levels were measured by western blotting. Dual‑luciferase reporter assay, RNA immunoprecipitation and RNA pull‑down assays were performed to affirm the interaction between two molecules. OIP5‑AS1 was found to be upregulated in OC tissues and cells. Knockdown of OIP5‑AS1 suppressed cell viability, migration, invasion and glycolysis while promoting apoptosis in OC cells. OIP5‑AS1 interacted with miR‑128‑3p and functioned as an oncogene by sequestering miR‑128‑3p. In addition, CCNG1 was a target gene for miR‑128‑3p and miR‑128‑3p regulated the CCNG1‑induced effects on OC cells by downregulating CCNG1. OIP5‑AS1 upregulated the expression of CCNG1 via targeting miR‑128‑3p. OIP5‑AS1 knockdown also inhibited tumor growth of OC in vivo by modulating the expression of miR‑128‑3p and CCNG1. Collectively, these data illustrated that the oncogenic role of OIP5‑AS1 in OC was associated with the miR‑128‑3p/CCNG1 axis at least in part. OIP5‑AS1 might be a probable diagnostic and therapeutic biomarker for the treatment of OC patients.

Prognostic Signatures of Metabolic Genes and Metabolism-Related Long Non-coding RNAs Accurately Predict Overall Survival for Osteosarcoma Patients

In this study, we identified eight survival-related metabolic genes in differentially expressed metabolic genes by univariate Cox regression analysis based on the therapeutically applicable research to generate effective treatments (n = 84) data set and genotype tissue expression data set (n = 396). We also constructed a six metabolic gene signature to predict the overall survival of osteosarcoma (OS) patients using least absolute shrinkage and selection operator (Lasso) Cox regression analysis. Our results show that the six metabolic gene signature showed good performance in predicting survival of OS patients and was also an independent prognostic factor. Stratified correlation analysis showed that the metabolic gene signature accurately predicted survival outcomes in high-risk and low-risk OS patients. The six metabolic gene signature was also verified to perform well in predicting survival of OS patients in an independent cohort (GSE21257). Then, using univariate Cox regression and Lasso Cox regression analyses, we identified an eight metabolism-related long noncoding RNA (lncRNA) signature that accurately predicts overall survival of OS patients. Gene set variation analysis showed that the apical surface and bile acid metabolism, epithelial mesenchymal transition, and P53 pathway were activated in the high-risk group based on the eight metabolism-related lncRNA signature. Furthermore, we constructed a competing endogenous RNA (ceRNA) network and conducted immunization score analysis based on the eight metabolism-related lncRNA signature. These results showed that the six metabolic gene signature and eight metabolism-related lncRNA signature have good performance in predicting the survival outcomes of OS patients.

SILAC quantitative proteomics analysis of ivermectin-related proteomic profiling and molecular network alterations in human ovarian cancer cells

The antiparasitic agent ivermectin offers more promises to treat a diverse range of diseases. However, a comprehensive proteomic analysis of ivermectin-treated ovarian cancer (OC) cells has not been performed. This study sought to identify ivermectin-related proteomic profiling and molecular network alterations in human OC cells. Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to study the human OC TOV-21G cells. After TOV-21G cells underwent 10 passages in SILAC-labeled growth media, TOV-21G cells were treated with 10 ml of 20 μmol/L ivermectin in cell growing medium for 24 h. The SILAC-labeled proteins were digested with trypsin; tryptic peptides were identified with mass spectrometry (MS). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to mine signaling pathway alterations with ivermectin-related proteins in TOV-21G cells. Gene ontology (GO) analysis was used to explore biological functions of ivermectin-related proteins, including biological processes (BPs), cellular components (CCs), and molecular functions (MFs). The protein-protein interaction network was analyzed with molecular complex detection (MCODE) to identify hub modules. In total, 4,447 proteins were identified in ivermectin-treated TOV-21G cells. KEGG analysis revealed 89 statistically significant signaling pathways. Interestingly, the clustering analysis of these pathways showed that ivermectin was involved in various cancer pathogenesis processes, including modulation of replication, RNA metabolism, and translational machinery. GO analysis revealed 69 statistically significant CCs, 87 MFs, and 62 BPs. Furthermore, MCODE analysis identified five hub modules, including 147 hub molecules. Those hub modules involved ribosomal proteins, RNA-binding proteins, cell-cycle progression-related proteins, proteasome subunits, and minichromosome maintenance proteins. These findings demonstrate that SILAC quantitative proteomics is an effective method to analyze ivermectin-treated cells, provide the first ivermectin-related proteomic profiling and molecular network alterations in human OC cells, and provide deeper insights into molecular mechanisms and functions of ivermectin to inhibit OC cells.

The Mitochondrial Proteome of Tumor Cells: A SnapShot on Methodological Approaches and New Biomarkers

Simple Summary

Mitochondria are central hubs of cellular signaling, energy metabolism, and redox balance. The plasticity of these cellular organelles is an essential requisite for the cells to cope with different stimuli and stress conditions. Cancer cells are characterized by changes in energy metabolism, mitochondrial signaling, and dynamics. These changes are driven by alterations in the mitochondrial proteome. For this reason, in the last years a focus of basic and cancer research has been the implementation and optimization of technologies to investigate changes in the mitochondrial proteome during cancer initiation and progression. This review presents an overview of the most used technologies to investigate the mitochondrial proteome and recent evidence on changes in the expression levels and delocalization of certain proteins in and out the mitochondria for shaping the functional properties of tumor cells.

Abstract

Mitochondria are highly dynamic and regulated organelles implicated in a variety of important functions in the cell, including energy production, fatty acid metabolism, iron homeostasis, programmed cell death, and cell signaling. Changes in mitochondrial metabolism, signaling and dynamics are hallmarks of cancer. Understanding whether these modifications are associated with alterations of the mitochondrial proteome is particularly relevant from a translational point of view because it may contribute to better understanding the molecular bases of cancer development and progression and may provide new potential prognostic and diagnostic biomarkers as well as novel molecular targets for anti-cancer treatment. Making an inventory of the mitochondrial proteins has been particularly challenging given that there is no unique consensus targeting sequence that directs protein import into mitochondria, some proteins are present at very low levels, while other proteins are expressed only in some cell types, in a particular developmental stage or under specific stress conditions. This review aims at providing the state-of-the-art on methodologies used to characterize the mitochondrial proteome in tumors and highlighting the biological relevance of changes in expression and delocalization of proteins in and out the mitochondria in cancer biology.

lncRNA SNHG3 acts as oncogene in ovarian cancer through miR-139-5p and Notch1

Ovarian cancer (OC) is a common malignant tumor of the female reproductive system. Long non-coding RNAs (lncRNAs) play an important role in OC occurrence and development. Thus, the function and potential mechanism of lncRNA small nucleolar RNA host gene 3 (SNHG3) was explored in the development of OC. The expression of SNHG3, microRNA (miR)-139-5p and Notch homolog 1, translocation-associated (Drosophila) (Notch1) in OC were detected by RT-qPCR or western blot assay. In addition, CCK-8 and wound-healing assays were used to detect OVCAR3 proliferation and migration ability. The targeting relationship of miR-139-5p with SNHG3 or Notch1 was verified through luciferase reporter assay. Rescue experiments were performed to confirm whether SNHG3 could mediate OVCAR3 proliferation and migration through miR-139-5p and Notch1. In OC tissues and cell lines, the expression of SNHG3 and Notch1 were significantly increased, and the expression of miR-139-5p was significantly decreased. SNHG3 inhibition suppressed the proliferation and migration of OVCAR3 cells. Luciferase reporter experiment confirmed that miR-139-5p could target SNHG3 and Notch1. Transfection of miR-139-5p inhibitor significantly reversed the inhibitory effect of SNHG3 knockdown on OVCAR3 proliferation and migration. Moreover, SNHG3 inhibition or miR-139-5p mimic abolished the promotion of Notch1 overexpression on OVCAR3 proliferation and migration. In conclusion, SNHG3 could accelerate the proliferation and migration of OC cells by regulating miR-139-5p and Notch1.

Novel long noncoding RNA LINC02323 promotes cell growth and migration of ovarian cancer via TGF-β receptor 1 by miR-1343-3p

BACKGROUND

This study was aimed at investigating the effects of long noncoding RNA (lncRNA) LINC02323 in ovarian cancer and its possible mechanism.

METHODS

Microarray analysis and QPCR were utilized to identify lncRNA LINC02323 expression in patients with ovarian cancer. MTT assay was used for analysis of ovarian cancer cell proliferation. Western blot was utilized to investigate its possible mechanism.

RESULTS

In patients with ovarian cancer, lncRNA LINC02323 expression was up-regulated and miR-1343-3p expression was down-regulated. Over-expression of lncRNA LINC02323 promoted cell growth and reduced LDH activity levels in vitro model by suppression of miR-1343-3p expression. Down-regulation of lncRNA LINC02323 reduced cell growth and increased LDH activity levels in vitro model by induction of miR-1343-3p expression. Over-expression of miR-1343-3p reduced cell growth and reduced LDH activity levels in vitro model by suppression of TGF-β receptor. Down-regulation of miR-1343-3p promoted cell growth and reduced LDH activity levels in vitro model by induced of TGF-β receptor.

CONCLUSION

Our findings show that Novel long noncoding RNA LINC02323 promotes cell growth of ovarian cancer via TGF-β receptor 1 by miR-1343-3p.

Quantitative proteomics revealed energy metabolism pathway alterations in human epithelial ovarian carcinoma and their regulation by the antiparasite drug ivermectin: data interpretation in the context of 3P medicine

Objective

Energy metabolism abnormality is the hallmark in epithelial ovarian carcinoma (EOC). This study aimed to investigate energy metabolism pathway alterations and their regulation by the antiparasite drug ivermectin in EOC for the discovery of energy metabolism pathway-based molecular biomarker pattern and therapeutic targets in the context of predictive, preventive, and personalized medicine (PPPM) in EOC.

Methods

iTRAQ-based quantitative proteomics was used to identify mitochondrial differentially expressed proteins (mtDEPs) between human EOC and control mitochondrial samples isolated from 8 EOC and 11 control ovary tissues from gynecologic surgery of Chinese patients, respectively. Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of energy metabolic pathways in EOC cells treated with and without ivermectin. Cell proliferation, cell cycle, apoptosis, and important molecules in energy metabolism pathway were examined before and after ivermectin treatment of different EOC cells.

Results

In total, 1198 mtDEPs were identified, and various mtDEPs were related to energy metabolism changes in EOC, with an interesting result that EOC tissues had enhanced abilities in oxidative phosphorylation (OXPHOS), Kreb's cycle, and aerobic glycolysis, for ATP generation, with experiment-confirmed upregulations of UQCRH in OXPHOS; IDH2, CS, and OGDHL in Kreb's cycle; and PKM2 in glycolysis pathways. Importantly, PDHB that links glycolysis with Kreb's cycle was upregulated in EOC. SILAC-based quantitative proteomics found that the protein expression levels of energy metabolic pathways were regulated by ivermectin in EOC cells. Furthermore, ivermectin demonstrated its strong abilities to inhibit proliferation and cell cycle and promote apoptosis in EOC cells, through molecular networks to target PFKP in glycolysis; IDH2 and IDH3B in Kreb's cycle; ND2, ND5, CYTB, and UQCRH in OXPHOS; and MCT1 and MCT4 in lactate shuttle to inhibit EOC growth.

Conclusions

Our findings revealed that the Warburg and reverse Warburg effects coexisted in human ovarian cancer tissues, provided the first multiomics-based molecular alteration spectrum of ovarian cancer energy metabolism pathways (aerobic glycolysis, Kreb's cycle, oxidative phosphorylation, and lactate shuttle), and demonstrated that the antiparasite drug ivermectin effectively regulated these changed molecules in energy metabolism pathways and had strong capability to inhibit cell proliferation and cell cycle progression and promote cell apoptosis in ovarian cancer cells. The observed molecular changes in energy metabolism pathways bring benefits for an in-depth understanding of the molecular mechanisms of energy metabolism heterogeneity and the discovery of effective biomarkers for individualized patient stratification and predictive/prognostic assessment and therapeutic targets/drugs for personalized therapy of ovarian cancer patients.

LncRNA SNHG3, a potential oncogene in human cancers

Long noncoding RNAs (lncRNAs) are composed of > 200 nucleotides; they lack the ability to encode proteins but play important roles in a variety of human tumors. A large number of studies have shown that dysregulated expression of lncRNAs is related to tumor oncogenesis and progression. Emerging evidence shows that SNHG3 is a novel oncogenic lncRNA that is abnormally expressed in various tumors, including osteosarcoma, liver cancer, lung cancer, etc. SNHG3 primarily competes as a competitive endogenous RNA (ceRNA) that targets tumor suppressor microRNAs (miRNAs) and ceRNA mechanisms that regulate biological processes of tumors. In addition, abnormal expression of SNHG3 is significantly correlated with patient clinical features. Upregulation of SNHG3 contributes to biological functions, including tumor cell proliferation, migration, invasion and EMT. Therefore, SNHG3 may represent a potential diagnostic and prognostic biomarker, as well as a novel therapeutic target.

The Role of Long Non-coding RNAs in Cancer Metabolism: A Concise Review

Dysregulation of metabolic pathways in cancer cells is regarded as a hallmark of cancer. Identification of these abnormalities in cancer cells dates back to more than six decades, far before discovery of oncogenes and tumor suppressor genes. Based on the importance of these pathways, several researchers have aimed at modulation of these functions to intervene with the pathogenic course of cancer. Numerous genes have been shown to participate in the regulation of metabolic pathways, thus aberrant expression of these genes can be involved in the pathogenesis of cancer. The recent decade has experienced a significant attention toward the role of long non-coding RNAs (lncRNAs) in the biological functions. These transcripts regulate expression of genes at several levels, therefore influencing the activity of cancer-related pathways. Among the most affected pathways are those modulating glucose homeostasis, as well as amino acid and lipid metabolism. Moreover, critical roles of lncRNAs in regulation of mitochondrial function potentiate these transcripts as novel targets for cancer treatment. In the current review, we summarize the most recent literature regarding the role of lncRNAs in the cancer metabolism and their significance in the design of therapeutic modalities.

Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis

Background

Long-chain non-coding RNA (lncRNA) small nucleolar RNA host gene 3 (SNHG3) is reportedly overexpressed in malignant tumors, but its regulatory role in human ovarian cancer (OC) is not fully understood.

Methods

A qRT-PCR assay was carried out to detect the level of SNHG3 in OC tissues, serum and cells, a CCK-8 assay to measure the proliferation of OC cells, a transwell assay to measure the invasion and migration of OC cells, and a flow cytometry to detect the cell cycle distribution and apoptosis rate of OC cells. In addition, in vivo experiment was also conducted to determine the effect of SNHG3 on the growth of OC cells.

Results

SNHG3 was overexpressed in OC tissues, serum, and cells, and the overexpression in serum indicated a poor prognosis of patients. It was also found that knockdown of SNHG3 could inhibit the malignant phenotypes of OC cells, cause G1/G0 cell cycle arrest, and intensify apoptosis. Furthermore, in in vitro experiments, the growth ability of OC cells was inhibited under knockdown of SNHG3. Assays for relationship verification showed that SNHG3 regulated the expression of miR-339-5p and the canonical transient receptor potential 3 (TRPC3), and the rescue experiment revealed that co-transfection of si-SNHG3+miR-339-5p-inhibitor or si-SNHG3+pcDNA3.1-TRPC3 could reverse the effects of knockdown of SNHG3 on the biological behavior of OC cells.

Conclusion

SNHG3 can be adopted as a marker for diagnosis and prognosis evaluation of OC and it plays a role in the progression of OC by enabling the miR-339-5p sponge to regulate TRPC3 expression.

A Novel Three-lncRNA Signature Predicts the Overall Survival of HNSCC Patients

BACKGROUND

A number of long non-coding RNAs (lncRNAs) have been found to be involved in tumor progression and associated with disease prognoses in various types of cancer. Our study identified a novel three-lncRNA signature to predict survival of head and neck squamous cell caner (HNSCC) patients.

METHODS

We utilized The Cancer Genome Atlas (TCGA) cohort to screen out overall survival (OS)-associated lncRNAs in HNSCC and further developed a model to identify a lncRNA signature for evaluating disease status and prognosis. The lncRNA signature was then validated in HNSCC patients from our Fudan University Shanghai Cancer Center (FUSCC) cohort.

RESULTS

LINC02434, AL139327.2, and AC126175.1 were identified by multivariable Cox regression analyses of independent risk factors for deceased status. We built a risk score model based on the three-lncRNA signature using coefficient of multivariable Cox regression and expression value of the three lncRNAs. The high-risk signature score was significantly associated with decreased OS in both the TCGA cohort and the FUSCC cohort. The high-risk group had worse overall survival than the low-risk group in TCGA cohort. To further validate the robustness of three-lncRNA signature risk score model developed in the TCGA dataset, the performance of risk score also evaluated in our institute FUSCC cohort. Additionally, the signature score showed a positive correlation with aggressive outcomes of HNSCC, such as III/IV stage, TP53 mutation, and PI3KCA mutation. The gene set enrichment analysis indicates that the risk score is associated with cancer metastasis-related pathways. Several cancer-related pathways, such as epithelial mesenchymal transition, TNFα signaling via NF-κB, MYC targets, and angiogenesis.

CONCLUSIONS

The three-lncRNA signature could provide a novel prediction insight into the prognosis of HNSCC patients. The three-lncRNA signature was identified as a predictor of poor prognoses in HNSCC, which may serve as a potential therapeutic target.

Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis

Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa.

Long non‑coding RNA PCAT6 promotes the development of osteosarcoma by increasing MDM2 expression

Osteosarcoma is a severe malignant tumor. Several studies indicated that lncRNA prostate cancer-associated transcript 6 (PCAT6) promoted the development of multiple types of cancers. Studies have also revealed that MDM2 could aggravate tumor symptoms inhibiting P53 expression. However, whether lncRNA PCAT6 could affect the proliferation and metastasis of osteosarcoma cells by regulating P53 expression is unclear. The present study established lncRNA PCAT6-overexpressing osteosarcoma cells. Cell Counting Kit-8, wound healing and Transwell assays were performed to detect the change in proliferation, migration and invasion of these cells, respectively. Subsequently, E3 ubiquitin-protein ligase Mdm2 (MDM2), P53 and P21 expression were determined using western blotting. Finally, MDM2 expression was inhibited and the proliferation, migration and invasion of these cells was determined again. The present study found that the proliferation, migration and invasion of osteosarcoma cells increased following overexpression of lncRNA PCAT6. MDM2 expression was upregulated while the levels of P53 and P21 decreased following overexpression of lncRNA PCAT6. However, the proliferation, migration and invasion of osteosarcoma cells were inhibited following MDM2 knockdown. Additionally, P53 and P21 was rescued following MDM2 knockdown. To conclude, lncRNA PCAT6 promoted the proliferation, migration and invasion of osteosarcoma cells by promoting the expression of MDM2 and suppressing the expression of P53 and P21.

LncRNA GAS8-AS1 Inhibits Ovarian Cancer Progression Through Activating Beclin1-Mediated Autophagy

Background

Early detection and diagnosis of ovarian cancer (OC) is complicated due to the concealment of the ovarian anatomical position and the lack of clinical manifestations and specific indicators of early OC. Therefore, it is urgent to study the pathogenesis of OC, especially the molecular mechanism.

Results

LncRNA GAS8-AS1 was decreased in OC tissues and cell lines, and high expression of GAS8-AS1 indicated a higher 5-year survival rate of OC patients. Overexpression of GAS8-AS1 suppressed growth of OC cells, while deletion of GAS8-AS1 promoted the progression of OC cells. Further data indicated GAS8-AS1 activated autophagy in OC cells. Functional experiments showed that 3-MA removed the inhibitory effect of GAS8-AS1 in OC cells. On the contrary, Rapamycin reversed the promoting effect of GAS8-AS1 in OC cells. Furthermore, GAS8-AS1 bound with Beclin1 and promoted its expression, and silencing of Beclin1 reversed the inhibitory role of GAS8-AS1 in OC progression. In vivo tumorigenesis assay showed GAS8-AS1 suppressed OC progression and activated Beclin1 mediated autophagy.

Conclusion

Our study suggested GAS8-AS1 inhibited OC progression by activating autophagy via binding with Beclin1, and GAS8-AS1 might be a potential therapeutic target for OC clinical treatment.

Long Non-coding RNAs Involved in Metabolic Alterations in Breast and Prostate Cancers

Breast and prostate cancers are the most prevalent cancers in females and males, respectively. These cancers exhibit sex hormone dependence and thus, hormonal therapies are used to treat these cancers. However, acquired resistance to hormone therapies is a major clinical problem. In addition, certain portions of these cancers initially exhibit hormone-independence due to the absence of sex hormone receptors. Therefore, precise and profound understanding of the cancer pathophysiology is required to develop novel clinical strategies against breast and prostate cancers. Metabolic reprogramming is currently recognized as one of the hallmarks of cancer, as exemplified by the alteration of glucose metabolism, oxidative phosphorylation, and lipid metabolism. Dysregulation of metabolic enzymes and their regulators such as kinases, transcription factors, and other signaling molecules contributes to metabolic alteration in cancer. Moreover, accumulating lines of evidence reveal that long non-coding RNAs (lncRNAs) regulate cancer development and progression by modulating metabolism. Understanding the mechanism and function of lncRNAs associated with cancer-specific metabolic alteration will therefore provide new knowledge for cancer diagnosis and treatment. This review provides an overview of recent studies regarding the role of lncRNAs in metabolism in breast and prostate cancers, with a focus on both sex hormone-dependent and -independent pathways.

Long non-coding RNA SNHG3, induced by IL-6/STAT3 transactivation, promotes stem cell-like properties of gastric cancer cells by regulating the miR-3619-5p/ARL2 axis

BACKGROUND

Chemotherapy is, next to surgery and radiotherapy, the mainstay regimen for the clinical management of gastric cancer. This therapy is, however, heavily compromised by the acquisition of resistance. Here, we aimed to clarify the potential involvement of long non-coding RNA SNGH3 in the acquisition of cisplatin resistance and stemness in gastric cancer.

METHODS

Cell viability and proliferation were measured using Cell Counting Kit-8 and colony formation assays, respectively. Stem cell-like cell growth was evaluated using a mammosphere formation assay. RNA levels of SNHG2, OCT-4, SOX-2, CD44, miR-3619-5p and ARL2 were determined using qRT-PCR, whereas protein levels of OCT-4, SOX-2, CD44, ARL2, STAT3 and pSTAT3 were determined using Western blotting. Dual luciferase reporter assays were employed to interrogate regulatory interactions between STAT3, SNHG3, miR-3619-5p and ARL2, respectively. Direct binding of STAT3 to the SNHG3 promoter was investigated using a chromatin immunoprecipitation assay.

RESULTS

We found that IL-6 triggered stem cell-like properties in cisplatin-treated gastric cancer cells and activated STAT3, which in turn transcriptionally regulated SNHG3 expression. SNHG3 expression up-regulation positively correlated with cisplatin resistance and stemness of gastric cancer cells, while SNHG3 down-regulation inhibited stem cell-like properties. In addition, we found that SNHG3 up-regulated ARL2 expression through sponging miR-3619-5p, which predominantly mediated the oncogenic properties of SNHG3 in this disease.

CONCLUSIONS

Our data indicate an involvement of aberrant SNHG3 over-expression in the acquisition of both cisplatin resistance and stemness of gastric cancer cells, and of the IL-6/STAT3/SNHG3/miR-3619-5p/ARL2 signaling cascade in the oncogenic properties of SNHG3.

Long non-coding RNA SNHG3 accelerates progression in glioma by modulating miR-384/HDGF axis

Glioma is a malignant primary brain tumor that occurs in the central nervous system and has threatened the well-being of millions of patients. It is well acknowledged that long non-coding RNA (lncRNA) SNHG3 participates in the regulation of proliferation, inflation, differentiation, and metastasis in many cancers. However, the regulatory effect of SNHG3 on glioma progression is still controversial. The expression of SNHG3 and HDGF was upregulated, whereas miR-384 was downregulated in glioma tissues, compared with the normal tissues. Interestingly, high SNHG3 contributed to low survival rate while low SNHG3 showed the opposite result. Moreover, SNHG3 or HDGF knockdown significantly suppressed proliferation, migration, and invasion and induced apoptosis in glioma. Meanwhile, restoration of HDGF abrogated the inhibition of SNHG3 silencing on glioma cell progression. Besides, miR-384 inhibitor attenuated SNHG3 silencing induced inhibition on HDGF mRNA and protein expression in A172 and SHG44 cells. LncRNA SNHG3 promotes cell proliferation, migration, and invasion in glioma by enhancing HDGF expression via miR-384 sponging, representing the promising targets for the development of novel therapeutic strategies.

MASS SPECTROMETRY-BASED MITOCHONDRIAL PROTEOMICS IN HUMAN OVARIAN CANCERS

The prominent characteristics of mitochondria are highly dynamic and regulatory, which have crucial roles in cell metabolism, biosynthetic, senescence, apoptosis, and signaling pathways. Mitochondrial dysfunction might lead to multiple serious diseases, including cancer. Therefore, identification of mitochondrial proteins in cancer could provide a global view of tumorigenesis and progression. Mass spectrometry-based quantitative mitochondrial proteomics fulfils this task by enabling systems-wide, accurate, and quantitative analysis of mitochondrial protein abundance, and mitochondrial protein posttranslational modifications (PTMs). Multiple quantitative proteomics techniques, including isotope-coded affinity tag, stable isotope labeling with amino acids in cell culture, isobaric tags for relative and absolute quantification, tandem mass tags, and label-free quantification, in combination with different PTM-peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM-peptides, increase flexibility for researchers to study mitochondrial proteomes. This article reviews isolation and purification of mitochondria, quantitative mitochondrial proteomics, quantitative mitochondrial phosphoproteomics, mitochondrial protein-involved signaling pathway networks, mitochondrial phosphoprotein-involved signaling pathway networks, integration of mitochondrial proteomic and phosphoproteomic data with whole tissue proteomic and transcriptomic data and clinical information in ovarian cancers (OC) to in-depth understand its molecular mechanisms, and discover effective mitochondrial biomarkers and therapeutic targets for predictive, preventive, and personalized treatment of OC. This proof-of-principle model about OC mitochondrial proteomics is easily implementable to other cancer types. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Long Non-coding RNAs (lncRNAs), A New Target in Stroke

Stroke has become the most disabling and the second most fatal disease in the world. It has been a top priority to reveal the pathophysiology of stroke at cellular and molecular levels. A large number of long non-coding RNAs (lncRNAs) are identified to be abnormally expressed after stroke. Here, we summarize 35 lncRNAs associated with stroke, and clarify their functions on the prognosis through signal transduction and predictive values as biomarkers. Changes in the expression of these lncRNAs mediate a wide range of pathological processes in stroke, including apoptosis, inflammation, angiogenesis, and autophagy. Based on the exploration of the functions and mechanisms of lncRNAs in stroke, more timely, accurate predictions and more effective, safer treatments for stroke could be developed.

Long Non-Coding Small Nucleolar RNA Host Genes (SNHGs) in Endocrine-Related Cancers

Long non-coding RNAs (lncRNAs) are emerging regulators of a diverse range of biological processes through various mechanisms. Genome-wide association studies of tumor samples have identified several lncRNAs, which act as either oncogenes or tumor suppressors in various types of cancers. Small nucleolar RNAs (snoRNAs) are predominantly found in the nucleolus and function as guide RNAs for the processing of transcription. As the host genes of snoRNAs, lncRNA small nucleolar RNA host genes (SNHGs) have been shown to be abnormally expressed in multiple cancers and can participate in cell proliferation, tumor progression, metastasis, and chemoresistance. Here, we review the biological functions and emerging mechanisms of SNHGs involved in the development and progression of endocrine-related cancers including thyroid cancer, breast cancer, pancreatic cancer, ovarian cancer and prostate cancer.

SNHG3 Functions as miRNA Sponge to Promote Breast Cancer Cells Growth Through the Metabolic Reprogramming

Cancer-associated fibroblasts (CAFs) are important ingredient in tumor microenvironment. The dynamic interplay between CAFs and cancer cells plays essential roles during tumor development and progression. However, the mechanisms of intercellular communication between CAFs and cancer cells remain largely unknown. We characterized exosomes secreted from breast cancer patient-derived CAFs by transmission electron microscopy. The expression of SNHG3, miR-330-5p, and PKM (Pyruvate Kinase M1/M2) was examined by real-time QPCR and immunoblot. The function of SNHG3 on the growth and metabolism of tumor cells was used by CCK8 and mitochondrial oxygen consumption assays. The binding between SNHG3, miR-330-5p, and PKM was examined by dual luciferase reporter assays. Orthotopical xenograft of breast tumor experiments was performed to determine the function of SNHG3 in vivo. We demonstrated that exosomes secreted from CAFs reprogram the metabolic pathways after tumor cells uptake the exosomes. CAF-secreted exosomal lncRNA SNHG3 served as a molecular sponge for miR-330-5p in breast cancer cells. Moreover, PKM could be targeted by miR-330-5p and was controlled by SNHG3 in breast cancer cells. Mechanistically, SNHG3 knockdown in CAF-secreted exosomes suppressed glycolysis metabolism and cell proliferation by the increase of miR-330-5p and decrease of PKM expression in tumor cells. SNHG3 functions as a miR-330-5p sponge to positively regulate PKM expression, inhibit mitochondrial oxidative phosphorylation, increase glycolysis carboxylation, and enhance breast tumor cell proliferation. Overall, SNHG3 could play a major role in the development and progression of breast cancer and support the therapeutic potential of targeting communication between cancer cells and tumor microenvironment.

LncRNA SNHG3 promotes bladder cancer proliferation and metastasis through miR-515-5p/GINS2 axis

Growing evidence suggests that long non‐coding RNAs (lncRNAs) are associated with carcinogenesis. LncRNA small nucleolar RNA host gene 3 (SNHG3) is up‐regulated in various cancers and positively associated with poor prognosis of these cancers. However, the precise role of lncRNA SNHG3 in bladder cancer (Bca) remains unclear. In our research, we first reported that lncRNA SNHG3 was up‐regulated in bladder cancer tissues and positively related to poor clinical prognosis. Moreover, knockdown of lncRNA SNHG3 significantly suppressed the proliferation, migration, invasion and EMT process of Bca cells in vitro and vivo. Mechanistically, we revealed that suppression of SNHG3 evidently enhanced miR‐515‐5p expression and decreased GINS2 expression at posttranscriptional levels. Moreover, SNHG3 positively regulated GINS2 expression by sponging miR‐515‐5p under a competing endogenous RNA (ceRNA) mechanism. To sum up, our study suggested lncRNA SNHG3 acted as a microRNA sponge and an oncogenic role in the progression of bladder cancer.

Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes

RELEVANCE

Ivermectin, as an old anti-parasite drug, can suppress almost completely the growth of various human cancers, including ovarian cancer (OC). However, its anticancer mechanism remained to be further studied at the molecular levels. Ivermectin-related molecule-panel changes will serve a useful tool for its personalized drug therapy and prognostic assessment in OCs.

PURPOSE

To explore the functional significance of ivermectin-mediated lncRNA-EIF4A3-mRNA axes in OCs and ivermectin-related molecule-panel for its personalized drug therapy monitoring.

METHODS

Based on our previous study, a total of 16 lncRNA expression patterns were analyzed using qRT-PCR before and after ivermectin-treated different OC cell lines (TOV-21G and A2780). Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of EIF4A3 and EIF4A3-binding mRNAs in ovarian cancer cells treated with and without ivermectin. A total of 411 OC patients from the Cancer Genome Atlas (TCGA) database with the selected lncRNA expressions and the corresponding clinical data were included. Lasso regression was constructed to examine the relationship between lncRNA signature and OC survival risk. The overall survival analysis between high-risk and low-risk groups used the Kaplan-Meier method. Heatmap showed the correlation between risk groups and clinical characteristics. The univariate and multivariate models were established with Cox regression.

RESULTS

SILAC-based quantitative proteomics found the protein expression levels of EIF4A3 and 116 EIF4A3-binding mRNAs were inhibited by ivermectin in OC cells. Among the analyzed 16 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, LINC00565, SNHG3, PLCH1-AS1, WWTR1-AS1, LINC00517, AL109767.1, STARD13-IT1, LBX2-AS1, LEMD1-AS1, and HOXC-AS3), only 7 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, and LINC00565) were obtained for further lasso regression when combined with the results of drug testing and overall survival analysis. Lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565). The high-risk and low-risk groups based on the prognostic model were significantly related to overall survival and clinicopathologic characteristics (survival status, lymphatic invasion, cancer status, and clinical stage) in OC patients and remained independent risk factors according to multivariate COX analysis (p < 0.05).

CONCLUSION

Those findings provided the potential targeted lncRNA-EIF4A3-mRNA pathways of ivermectin in OC, and constructed the effective prognostic model, which benefits discovery of novel mechanism of ivermectin to suppress ovarian cancer cells, and the ivermectin-related molecule-panel changes benefit for its personalized drug therapy and prognostic assessment towards its predictive, preventive, and personalized medicine (PPPM) in OCs.

LncRNA SNHG5: A new budding star in human cancers

Long non-coding RNA (LncRNA) belongs to non-coding RNAs longer than 200 nucleic acids. More and more studies have revealed that lncRNA can participate in the occurrence and pathophysiology of diseases, especially in cancers. Although research on lncRNAs has doubled year by year, little is known about the specific regulatory mechanisms of lncRNAs in diseases. The main purpose of this review is to explore the molecular mechanism and clinical significance of SNHG5 in cancers. We systematically search Pubmed to obtain relevant literature on SNHG5. In this review, the functional role, molecular mechanism, and clinical significance of SNHG5 in human cancers are described in detail. Small nucleolar RNA host gene 5 (SNHG5) has been shown to be involved in the development and tumorigenesis of a variety of cancers (colorectal, bladder, gastric, endometrial, acute lymphocytic leukemia, osteosarcoma, etc.). Its disorder is closely related to metastasis, pathological staging, and prognosis. LncRNA SNHG5 might be a potential and novel diagnostic marker for cancer patients, a target for molecular targeted therapy, and a prognostic diagnostic marker.