Identification and Validation of Novel Long Non-coding RNA Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma

Comprehensive analysis of the relationship between RNA modification writers and immune microenvironment in head and neck squamous cell carcinoma

OBJECTIVES

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Four types of RNA modification writers (m6A, m1A, A-I editing, and APA) are widely involved in tumorigenesis and the TME. We aimed to comprehensively explore the role of the four RNA modification writers in the progression and immune microenvironment of HNSCC.

MATERIALS AND METHODS

We first obtained transcription profile data and transcriptional variation of the four types of RNA modification writers from The Cancer Genome Atlas (TCGA) database. HNSCC patients in TCGA dataset were divided into different clusters based on the four types of RNA modification writers. Univariate Cox and Least absolute shrinkage and selection operator (LASSO) analyses were performed to conduct a Writer-score scoring system, which was successfully verified in the GSE65858 dataset and our clinical sample dataset. Finally, we evaluated the relationship between different RNA modification clusters (Writer-score) and immunological characteristics of HNSCC.

RESULTS

Two different RNA modification clusters (A and B) were obtained. These RNA modification clusters (Writer-score) were strongly associated with immunological characteristics (immunomodulators, cancer immunity cycles, infiltrating immune cells (TIICs), inhibitory immune checkpoints, and T cell inflamed score (TIS)) of HNSCC.

CONCLUSIONS

This study identified two different RNA modification clusters and explored the potential relationship between RNA modification clusters (Writer-score) and immunological characteristics, offering a new theoretical basis for precision immunotherapy in patients with HNSCC.

Novel insights on oral squamous cell carcinoma management using long non-coding RNAs

Oral squamous cell carcinoma (OSCC) is one of the most prevalent forms of head and neck squamous cell carcinomas (HNSCC) with a poor overall survival rate (about 50%), particularly in cases of metastasis. RNA-based cancer biomarkers are a relatively advanced concept, and non-coding RNAs currently have shown promising roles in the detection and treatment of various malignancies. This review underlines the function of long non-coding RNAs (lncRNAs) in the OSCC and its subsequent clinical implications. LncRNAs, a class of non-coding RNAs, are larger than 200 nucleotides and resemble mRNA in numerous ways. However, unlike mRNA, lncRNA regulates multiple druggable and non-druggable signaling molecules through simultaneous interaction with DNA, RNA, proteins, or microRNAs depending on concentration and localization in cells. Upregulation of oncogenic lncRNAs and down-regulation of tumor suppressor lncRNAs are evident in OSCC tissues and body fluids such as blood and saliva indicating their potential as valuable biomarkers. Targeted inhibition of candidate oncogenic lncRNAs or over-expression of tumor suppressor lncRNAs showed potential therapeutic roles in in-vivo animal models. The types of lncRNAs that are expressed differentially in OSCC tissue and bodily fluids have been systematically documented with specificity and sensitivity. This review thoroughly discusses the biological functions of such lncRNAs in OSCC cell survival, proliferation, invasion, migration, metastasis, angiogenesis, metabolism, epigenetic modification, tumor immune microenvironment, and drug resistance. Subsequently, we addressed the diagnostic and therapeutic importance of lncRNAs in OSCC pre-clinical and clinical systems, providing details on ongoing research and outlining potential future directions for advancements in this field. In essence, this review could be a valuable resource by offering comprehensive and current insights into lncRNAs in OSCC for researchers in fundamental and clinical domains.

CRISPR-Based Precision Molecular Diagnostics for Disease Detection and Surveillance

Sensitive, rapid, and portable molecular diagnostics is the future of disease surveillance, containment, and therapy. The recent SARS-CoV-2 pandemic has reminded us of the vulnerability of lives from ever-evolving pathogens. At the same time, it has provided opportunities to bridge the gap by translating basic molecular biology into therapeutic tools. One such molecular biology technique is CRISPR (clustered regularly interspaced short palindromic repeat) which has revolutionized the field of molecular diagnostics at the need of the hour. The use of CRISPR-Cas systems has been widespread in biology research due to the ease of performing genetic manipulations. In 2012, CRISPR-Cas systems were, for the first time, shown to be reprogrammable, i.e., capable of performing sequence-specific gene editing. This discovery catapulted the field of CRISPR-Cas research and opened many unexplored avenues in the field of gene editing, from basic research to therapeutics. One such field that benefitted greatly from this discovery was molecular diagnostics, as using CRISPR-Cas technologies enabled existing diagnostic methods to become more sensitive, accurate, and portable, a necessity in disease control. This Review aims to capture some of the trajectories and advances made in this arena and provides a comprehensive understanding of the methods and their potential use as point-of-care diagnostics.

Identification of optimal feature genes in patients with thyroid associated ophthalmopathy and their relationship with immune infiltration: a bioinformatics analysis

Background

Thyroid associated ophthalmopathy (TAO) is an organ-specific autoimmune disease that has a significant impact on individuals and society. The etiology of TAO is complicated and poorly understood. Thus, the goal of this study was to use bioinformatics to look into the pathogenesis of TAO and to identify the optimum feature genes (OFGs) and immune infiltration patterns of TAO.

Methods

Firstly, the GSE58331 microarray data set was utilized to find 366 differentially expressed genes (DEGs). To find important modular genes, the dataset was evaluated using weighted gene coexpression network analysis (WGCNA). Then, the overlap genes of major module genes and DEGs were further assessed by applying three machine learning techniques to find the OFGs. The CIBERSORT approach was utilized to examine immune cell infiltration in normal and TAO samples, as well as the link between optimum characteristic genes and immune cells. Finally, the related pathways of the OFGs were predicted using single gene set enrichment analysis (ssGSEA).

Results

KLB, TBC1D2B, LINC01140, SGCG, TMEM37, and LINC01697 were the six best feature genes that were employed to create a nomogram with high predictive performance. The immune cell infiltration investigation revealed that the development of TAO may include memory B cells, T cell follicular helper cells, resting NK cells, macrophages of type M0, macrophages of type M1, resting dendritic cells, active mast cells, and neutrophils. In addition, ssGSEA results found that these characteristic genes were closely associated with lipid metabolism pathways.

Conclusion

In this research, we found that KLB, TBC1D2B, LINC01140, SGCG, TMEM37, and LINC01697 are intimately associated with the development and progression of TAO, as well as with lipid metabolism pathways.

A snapshot of miRNAs in oral squamous cell carcinoma: Difference between cancer cells and corresponding normal cells

Oral squamous cell carcinoma (OSCC) constitutes the most aggressive tumors of the oral cavity and is one of the leading causes of cancer mortality worldwide. Although recent clinical treatment strategies have improved the survival rate, the outcome of OSCC patients still remains dismal because of the lack of efficient diagnostic and treatment tools. As one of the main actors of OSCC scenario, microRNAs (miRNAs) are involved in triggering, progression and metastasis through the regulation of various cancer-related signaling pathways. Identification followed by precise study of the biology and mechanism of action of miRNAs will greatly help to provide valuable insights regarding OSCC development and can be considered as an anti-OSCC target. In the current review, we have provided a focused summary of the latest published papers on the role of miRNAs in apoptosis, cell cycle, proliferation, EMT and metastasis of OSCC as well as the role of long noncoding RNAs in the modulation of miRNAs in OSCC.

Metabolism-related long non-coding RNA in the stomach cancer associated with 11 AMMLs predictive nomograms for OS in STAD

Background: The metabolic processes involving amino acids are intimately linked to the onset and progression of cancer. Long non-coding RNAs (LncRNAs) perform an indispensable function in the modulation of metabolic processes as well as the advancement of tumors. Non-etheless, research into the role that amino acid metabolism-related LncRNAs (AMMLs) might play in predicting the prognosis of stomach adenocarcinoma (STAD) has not been done. Therefore, This study sought to design a model for AMMLs to predict STAD-related prognosis and elucidate their immune properties and molecular mechanisms.

Methods: The STAD RNA-seq data in the TCGA-STAD dataset were randomized into the training and validation groups in a 1:1 ratio, and models were constructed and validated respectively. In the molecular signature database, This study screened for genes involved in amino acid metabolism. AMMLs were obtained by Pearson’s correlation analysis, and predictive risk characteristics were established using least absolute shrinkage and selection operator (LASSO) regression, univariate Cox analysis, and multivariate Cox analysis. Subsequently, the immune and molecular profiles of high- and low-risk patients and the benefit of the drug were examined.

Results: Eleven AMMLs (LINC01697, LINC00460, LINC00592, MIR548XHG, LINC02728, RBAKDN, LINCOG, LINC00449, LINC01819, and UBE2R2-AS1) were used to develop a prognostic model. Moreover, high-risk individuals had worse overall survival (OS) than low-risk patients in the validation and comprehensive groups. A high-risk score was associated with cancer metastasis as well as angiogenic pathways and high infiltration of tumor-associated fibroblasts, Treg cells, and M2 macrophages; suppressed immune responses; and a more aggressive phenotype.

Conclusion: This study identified a risk signal associated with 11 AMMLs and established predictive nomograms for OS in STAD. These findings will help us personalize treatment for gastric cancer patients.

Qualification of Necroptosis-Related lncRNA to Forecast the Treatment Outcome, Immune Response, and Therapeutic Effect of Kidney Renal Clear Cell Carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is considered as a highly immune infiltrative tumor. Necroptosis is an inflammatory programmed cell death associated with a wide range of diseases. Long noncoding RNAs (lncRNAs) play important roles in gene regulation and immune function. lncRNA associated with necroptosis could systematically explore the prognostic value, regulate tumor microenvironment (TME), etc.

Method

The patients' data was collected from TCGA datasets. We used the univariate Cox regression (UCR) to select prediction lncRNAs that are related to necroptosis. Meanwhile, risk models were constructed using LASSO Cox regression (LCR). Kaplan–Meier (KM) analysis, accompanied with receiver operating characteristic (ROC) curves, was performed to assess the independent risk factors of different clinical characteristics. The evaluated factors are age, gender, disease staging, grade, and their related risk score. Databases such as Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to search the probable biological characteristics that could influence the risk groups, containing signaling pathway and immue-related pathways. The single-sample gene set enrichment analysis (ssGSEA) was chosen to perform gene set variation analysis (GSVA), and the GSEABase package was selected to detect the immune and inflammatory infiltration profiles. The TIDE and IC₅₀ evaluation were used to estimate the effectiveness of clinical treatment on KIRC.

Results

Based on the above analysis, we have got a conclusion that patients who show high risk had higher immune infiltration, immune checkpoint expression, and poorer prognosis. We identified 19 novel prognostic necroptosis-related lncRNAs, which could offer opinions for a deeper study of KIRC.

Conclusion

The risk model we constructed makes it possible to predict the prognosis of KIRC patients and offers directions for further research on the prognostication and treatment strategies for KIRC.

TNF and HNRNPL Related Immunoregulatory Long non-coding RNA (THRIL) and long intergenic noncoding RNA-p21 (lincRNA-p21) as potential useful biomarkers for the diagnosis of tuberculosis

Early diagnosis is crucial in controlling tuberculosis globally and in developing countries with the emergence of drug-resistant Mycobacterium tuberculosis strains. Long non-coding RNAs (lncRNAs) are promising tuberculosis diagnostic biomarkers. Two lncRNA diagnostic markers, lncRNA THRIL and lincRNA-p21, were studied as tuberculosis diagnostic biomarkers. This cross-sectional study was conducted at the Center of Respiratory Diseases of LAQUINTINIE hospital and the National Veterinary Laboratory of Douala from December 2020 to August 2021. The ability of lncRNAs to distinguish between 19 healthy controls, 15 latent tuberculosis, and 21 active tuberculosis was estimated using quantitative polymerase chain reaction and Receiver Operating Characteristic curve analysis. Our analysis showed that lncRNA THRIL and lincRNA-p21 were significantly upregulated (P <0.05) in active and latent tuberculosis compared with healthy controls. LincRNA-p21 expression was significantly increased (P <0.05) in active tuberculosis compared with latent tuberculosis, whereas lncRNA THRIL was not significantly affected (P ≥0.05). Both lncRNA THRIL and lincRNA-p21 showed excellent performance in classifying latent tuberculosis and healthy controls (AUC = 92.86%). Furthermore, lncRNA THRIL was good at discriminating active tuberculosis from healthy controls (AUC = 89.79%), while lincRNA-p21 showed excellent discriminating performance (AUC = 100%). LncRNA THRIL was identified as a poor discriminator of latent tuberculosis from active tuberculosis (AUC = 64.28%), while lincRNA-p21 showed excellent diagnostic performance in this distinction (AUC = 92.86%). Our cross-sectional study suggests that lncRNA THRIL and lincRNA-p21 are promising tuberculosis diagnostic biomarkers that can differentiate between latent and active infection.

Screening and validation of platelet activation-related lncRNAs as potential biomarkers for prognosis and immunotherapy in gastric cancer patients

Background: Platelets (PLT) have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs (PLT-related lncRNAs) in gastric cancer (GC) is still poorly understood. In this study, we screened and validated PLT-related lncRNAs as potential biomarkers for prognosis and immunotherapy in GC patients.

Methods: We obtained relevant datasets from the Cancer Genome Atlas (TCGA) and Gene Ontology (GO) Resource Database. Pearson correlation analysis was used to identify PLT-related lncRNAs. By using the univariate, least absolute shrinkage and selection operator (LASSO) Cox regression analyses, we constructed the PLT-related lncRNAs model. Kaplan-Meier survival analysis, univariate, multivariate Cox regression analysis, and nomogram were used to verify the model. The Gene Set Enrichment Analysis (GSEA), drug screening, tumor immune microenvironment analysis, epithelial-mesenchymal transition (EMT), and DNA methylation regulators correlation analysis were performed in the high- and low-risk groups. Patients were regrouped based on the risk model, and candidate compounds and immunotherapeutic responses aimed at GC subgroups were also identified. The expression of seven PLT-related lncRNAs was validated in clinical medical samples using quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

Results: In this study, a risk prediction model was established using seven PLT-related lncRNAs -(AL355574.1, LINC01697, AC002401.4, AC129507.1, AL513123.1, LINC01094, and AL356417.2), whose expression were validated in GC patients. Kaplan-Meier survival analysis, the receiver operating characteristic (ROC) curve analysis, univariate, multivariate Cox regression analysis verified the accuracy of the model. We screened multiple targeted drugs for the high-risk patients. Patients in the high-risk group had a poorer prognosis since low infiltration of immune killer cells, activation of immunosuppressive pathways, and poor response to immunotherapy. In addition, we revealed a close relationship between risk scores and EMT and DNA methylation regulators. The nomogram based on risk score suggested a good ability to predict prognosis and high clinical benefits.

Conclusion: Our findings provide new insights into how PLT-related lncRNAs biomarkers affect prognosis and immunotherapy. Also, these lncRNAs may become potential biomarkers and therapeutic targets for GC patients.

Integrated analysis of necroptosis-related lncRNAs for prognosis and immunotherapy of patients with pancreatic adenocarcinoma

Accumulating studies have revealed that necroptosis plays a vital role in the occurrence and development of pancreatic adenocarcinoma (PAAD). We aimed to construct a prognostic model for PAAD on the basis of necroptosis-related lncRNAs (NRLs). A coexpression network between necroptosis-related mRNAs and NRLs based on The Cancer Genome Atlas (TCGA) was constructed. Then, differentially expressed necroptosis-related lncRNAs (DENRLs) were screened from TCGA and Genotype-Tissue Expression project (GTEx) datasets. Univariate Cox regression (uni-Cox) analysis was performed on these DENRLs to identify lncRNAs significantly correlated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression was performed for preventing overfitting on these lncRNAs. Multivariate Cox analysis (multi-Cox) was performed to establish a risk model based on lncRNAs that served as an independent prognostic factor. Next, the Kaplan–Meier analysis, time-dependent receiver operating characteristics (ROC), uni-Cox, multi-Cox regression, nomogram, and calibration curves were constructed to support the accuracy of the model. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were also performed on risk groups, and it was found that the low-risk group was closely correlated with immune infiltration and immunotherapy. To further evaluate the immune differences between different clusters, we divided the patients into two clusters. Cluster 2 was more significantly infiltrated with immune cells and had higher immune scores. These results shed new light on the pathogenesis of PAAD based on NRLs and develop a prognostic model for diagnosing and guiding personalized immunotherapy of PAAD patients.

Lipid metabolism-related lncRNA SLC25A21-AS1 promotes the progression of oesophageal squamous cell carcinoma by regulating the NPM1/c-Myc axis and SLC25A21 expression

BACKGROUND

Obesity alters metabolic microenvironment and is thus associated with several tumours. The aim of the present study was to investigate the role, molecular mechanism of action, and potential clinical value of lipid metabolism-related long non-coding RNA (lncRNA) SLC25A21-AS1 in oesophageal squamous cell carcinoma (ESCC).

METHODS

A high-fat diets (HFDs)-induced obesity nude mouse model was established, and targeted metabolomics analysis was used to identify critical medium-long chain fatty acids influencing the growth of ESCC cells. Transcriptomic analysis of public dataset GSE53625 confirmed that lncRNA SLC25A21-AS1 was a lipid metabolism-related lncRNA. The biological function of lncRNA SLC25A21-AS1 in ESCC was investigated both in vivo and in vitro. Chromatin immunoprecipitation(ChIP)assay, RNA-pull down, mass spectrometry, co-IP, and RNA IP(RIP) were performed to explore the molecular mechanism. Finally, an ESCC cDNA microarray was used to determine the clinical prognostic value of SLC25A21-AS1 by RT-qPCR.

RESULTS

Palmitic acid (PA) is an important fatty acid component of HFD and had an inhibitory effect on ESCC cell lines. LncRNA SLC25A21-AS1 expression was downregulated by PA and associated with the proliferation and migration of ESCC cells in vitro and in vivo. Mechanistically, SLC25A21-AS1 interacted with nucleophosmin-1 (NPM1) protein to promote the downstream gene transcription of the c-Myc in the nucleus. In the cytoplasm, SLC25A21-AS1 maintained the stability of SLC25A21 mRNA and reduced the intracellular NAD+ /NADH ratio by influencing tryptophan catabolism. Finally, we demonstrated that high expression of SLC25A21-AS1 promoted resistance to cisplatin-induced apoptosis and was correlated with poor tumour grade and overall survival.

CONCLUSIONS

HFD/PA has an inhibitory effect on ESCC cells and SLC25A21-AS1 expression. SLC25A21-AS1 promotes the proliferation and migration of ESCC cells by regulating the NPM1/c-Myc axis and SLC25A21 expression. In addition, lncRNA SLC25A21-AS1 may serve as a favourable prognostic biomarker and a potential therapeutic target for ESCC.

Gold nanomaterials for oral cancer diagnosis and therapy: Advances, challenges, and prospects

Early diagnosis and treatment of oral cancer are vital for patient survival. Since the oral cavity accommodates the second largest and most diverse microbiome community after the gut, the diagnostic and therapeutic approaches with low invasiveness and minimal damage to surrounding tissues are keys to preventing clinical intervention-related infections. Gold nanoparticles (AuNPs) are widely used in the research of cancer diagnosis and therapy due to their excellent properties such as surface-enhanced Raman spectroscopy, surface plasma resonance, controlled synthesis, the plasticity of surface morphology, biological safety, and stability. AuNPs had been used in oral cancer detection reagents, tumor-targeted therapy, photothermal therapy, photodynamic therapy, and other combination therapies for oral cancer. AuNPs-based noninvasive diagnosis and precise treatments further reduce the clinical intervention-related infections. This review is focused on the recent advances in research and application of AuNPs for early screening, diagnostic typing, drug delivery, photothermal therapy, radiotherapy sensitivity treatment, and combination therapy of oral cancer. Distinctive reports from the literature are summarized to highlight the latest advances in the development and application of AuNPs in oral cancer diagnosis and therapy. Finally, this review points out the challenges and prospects of possible applications of AuNPs in oral cancer diagnosis and therapy.

SLC8A1 antisense RNA 1 suppresses papillary thyroid cancer malignant progression via the FUS RNA binding protein (FUS)/NUMB like endocytic adaptor protein (Numbl) axis

Papillary thyroid cancer (PTC) is one of the most prevalent endocrine malignancies and is associated with severe morbidity and high mortality. This study aimed to explore the role of long non-coding RNA (lncRNA) SLC8A1 antisense RNA 1 (SLC8A1-AS1) in the pathogenesis of PTC. In this study, we explored the function of SLC8A1-AS1 in PTC progression. We observed that the expression of SLC8A1-AS1 was downregulated in clinical PTC samples and PTC cell lines compared to that in normal controls. Cell counting kit (CCK)-8 assays demonstrated that the overexpression of SLC8A1-AS1 significantly reduced the proliferation of PTC cells. Consistently, apoptosis of PTC cells was enhanced by SLC8A1-AS1 overexpression. SLC8A1-AS1 overexpression attenuated the invasion and migration of PTC cells. Mechanistically, SLC8A1-AS1 maintained NUMB like endocytic adaptor protein (Numbl) mRNA stability by interacting with FUS RNA Binding Protein (FUS) in PTC cells. Depletion of Numbl reversed the inhibitory effect of SLC8A1-AS1 overexpression on PTC. Thus, we concluded that SLC8A1-AS1 suppresses PTC progression via the FUS/Numbl axis. Our findings provide novel insights into the mechanism underlying SLC8A1-AS1 attenuation of the malignant development of PTC, improving our understanding of the association between lncRNAs and PTC. SLC8A1-AS1 and FUS may be potential targets for PTC treatment.

Identification of novel key regulatory lncRNAs in gastric adenocarcinoma

Background

Stomach adenocarcinoma (STAD) is one of the most common and deadly cancers worldwide. Recent evidence has demonstrated that dysregulation of long noncoding RNAs (lncRNA) is associated with different hallmarks of cancer. lncRNAs also were suggested as novel promising biomarkers for cancer diagnosis and prognosis. Despite these previous investigations, the expression pattern, diagnostic role, and hallmark association of lncRNAs in STAD remain unclear.

Results

In this study, The STAD lncRNA-mRNA network was constructed based on RNAs that differentially expressed among tumor and normal samples and had a strong expression correlation with others. The high degree nodes of the network were associated with overall survival. In addition, we found that the hubs’ regulatory roles have previously been confirmed in different types of cancers by literature. For example, the HCG22 hub inhibited cell proliferation and invasion and induced apoptosis in oral squamous cell carcinoma (OSCC) cells. The levels of PCNA, Vimentin, and Bcl2 were decreased and E-cadherin and Bax expression was elevated in OSCC cells after HCG22 overexpression. Additionally, HCG22 overexpression inhibited the Akt, mTOR, and Wnt/β-catenin pathways.

Then lncRNAs were mapped to their related GO terms and cancer hallmarks. Based on these mappings, we predict the hallmarks that might be associated with each lncRNA. Finally, the literature review confirmed our prediction.

Among the 20 lncRNAs of the STAD network, 11 lncRNAs (LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1, ENSG00000262756) demonstrated expression correlation with overall survival (OS). Based on expression analysis, survival analysis, hallmark associations, and literature review, LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1 plays a regulatory role in STAD. For example, our prediction of association between C5orf66-AS1 expression dysregulation and “sustaining proliferative signal” and “Activating invasion and metastasis” has been confirmed in STAD, OSCC and cervical cancer. Finally, we developed a lncRNA signature with SOX21-AS1 and LINC02560, which classified patients into high and low-risk subgroups with significantly different survival outcomes. The mortality rate of the high-risk patients was significantly higher compared to the low-risk patients (28/1% vs 60.13).

Conclusion

These findings help in designing more precise and detailed experimental studies to find STAD biomarkers and therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08578-6.

The Emerging role of EMT-related lncRNAs in therapy resistance and their application as biomarkers

Cancer is the world's second largest cause of death. The most common cancer treatments are surgery, radiation therapy, and chemotherapy. Drug resistance, epithelial-to-mesenchymal transition (EMT), and metastasis are all pressing issues in cancer therapy today. Increasing evidence showed that drug-resistant and EMT are co-related with each other. Indeed, drug-resistant cancer cells possess enhanced EMT and invasive ability. Recent researches have demonstrated lncRNAs (long noncoding RNAs) are noncoding transcripts, which play an important role in the regulation of EMT, metastasis, and drug resistance in different cancers. However, the relationships among lncRNAs, EMT, and drug resistance are still unclear. These effects could be exerted via several signaling pathways such as TGF-β, PI3K-AKT, and Wnt/β-catenin. Identifying the crucial regulatory roles of lncRNAs in these pathways and processes leads to the development of novel targeted therapies. We review the key aspects of lncRNAs associated with EMT and therapy resistance. We focus on the crosstalk between lncRNAs and molecular signaling pathways affecting EMT and drug resistance. Moreover, each of the mentioned lncRNAs could be used as a potential diagnostic, prognostic, and therapeutic biomarker for cancer. Although, there are still many challenges to investigate lncRNAs for clinical applications.

Identification and Validation of HOTAIRM1 as a Novel Biomarker for Oral Squamous Cell Carcinoma

ORAL squamous cell carcinoma (OSCC) is a malignant tumor with the highest incidence among tumors involving the oral cavity maxillofacial region, and is notorious for its high recurrence and metastasis potential. Long non-coding RNAs (lncRNAs), which regulate the genesis and evolution of cancers, are potential prognostic biomarkers. This study identified HOTAIRM1 as a novel significantly upregulated lncRNA in OSCC, which is strongly associated with unfavorable prognosis of OSCC. Systematic bioinformatics analyses demonstrated that HOTAIRM1 was closely related to tumor stage, overall survival, genome instability, the tumor cell stemness, the tumor microenvironment, and immunocyte infiltration. Using biological function prediction methods, including Weighted gene co-expression network analysis (WGCNA), Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA), HOTAIRM1 plays a pivotal role in OSCC cell proliferation, and is mainly involved in the regulation of the cell cycle. In vitro, cell loss-functional experiments confirmed that HOTAIRM1 knockdown significantly inhibited the proliferation of OSCC cells, and arrested the cell cycle in G1 phase. At the molecular level, PCNA and CyclinD1 were obviously reduced after HOTAIRM1 knockdown. The expression of p53 and p21 was upregulated while CDK4 and CDK6 expression was decreased by HOTAIRM1 knockdown. In vivo, knocking down HOTAIRM1 significantly inhibited tumor growth, including the tumor size, weight, volume, angiogenesis, and hardness, monitored by ultrasonic imaging and magnetic resonance imaging In summary, our study reports that HOTAIRM1 is closely associated with tumorigenesis of OSCC and promotes cell proliferation by regulating cell cycle. HOTAIRM1 could be a potential prognostic biomarker and a therapeutic target for OSCC.

Characterization of Cancer Stem Cell Characteristics and Development of a Prognostic Stemness Index Cell-Related Signature in Oral Squamous Cell Carcinoma

Objective

Cancer stem cells (CSCs) with self-renewal and plasticity contribute to tumor initiation and progression. This study developed an mRNA expression-based stemness index- (mRNAsi-) associated signature and validated biological functions of stem cell-related genes in oral squamous cell carcinoma (OSCC).

Methods

Here, mRNAsi was measured for OSCC samples from TCGA cohort, and prognosis and tumor microenvironment (stromal/immune scores, tumor purity) in high- and low-mRNAsi samples were evaluated with survival analyses and ESTIMATE algorithm. Based on prognostic mRNAsi-related genes, a risk score model was constructed by the LASSO method. The predictive accuracy was evaluated by uni- and multivariate Cox analyses and ROC curves. Among the genes in the model, the functions of H2AFZ on proliferation, apoptosis, invasion, and EMT were investigated in OSCC cells.

Results

High mRNAsi was distinctly associated with undesirable prognosis, increased stromal and immune scores, and lowered tumor purity. The mRNAsi-associated signature containing 11 genes was developed, and high-risk score was distinctly related to poor survival outcomes. Moreover, this signature was an independent and robust risk factor. H2AFZ upregulation significantly enhanced proliferative and invasive capacities and facilitated EMT as well as lowered apoptotic levels in Cal-27 and HSC-3 cells.

Conclusion

Our study characterized cancer stem cell characteristics that were closely related to tumor microenvironment and developed a stemness index cell-related signature that could assist prognosis prediction and risk stratification for OSCC. H2AFZ could become a potential therapeutic target against OSCC.

Integrated Analysis of lncRNA-Associated ceRNA Network Identifies Two lncRNA Signatures as a Prognostic Biomarker in Gastric Cancer

Background

Gastric cancer (GC) is a malignant tumour that originates in the gastric mucosal epithelium and is associated with high mortality rates worldwide. Long noncoding RNAs (lncRNAs) have been identified to play an important role in the development of various tumours, including GC. Yet, lncRNA biomarkers in a competing endogenous RNA network (ceRNA network) that are used to predict survival prognosis remain lacking. The aim of this study was to construct a ceRNA network and identify the lncRNA signature as prognostic factors for survival prediction.

Methods

The lncRNAs with overall survival significance were used to construct the ceRNA network. Function enrichment, protein-protein interaction, and cluster analysis were performed for dysregulated mRNAs. Multivariate Cox proportional hazards regression was performed to screen the potential prognostic lncRNAs. RT-qPCR was used to measure the relative expression levels of lncRNAs in cell lines. CCK8 assay was used to assess the proliferation of GC cells transfected with sh-lncRNAs.

Results

Differentially expressed genes were identified including 585 lncRNAs, 144 miRNAs, and 2794 mRNAs. The ceRNA network was constructed using 35 DElncRNAs associated with overall survival of GC patients. Functional analysis revealed that these dysregulated mRNAs were enriched in cancer-related pathways, including TGF-beta, Rap 1, calcium, and the cGMP-PKG signalling pathway. A multivariate Cox regression analysis and cumulative risk score suggested that two of those lncRNAs (LINC01644 and LINC01697) had significant prognostic value. Furthermore, the results indicate that LINC01644 and LINC01697 were upregulated in GC cells. Knockdown of LINC01644 or LINC01697 suppressed the proliferation of GC cells.

Conclusions

The authors identified 2-lncRNA signature in ceRNA regulatory network as prognostic biomarkers for the prediction of GC patient survival and revealed that silencing LINC01644 or LINC01697 inhibited the proliferation of GC cells.

Identification of the RP11-21C4.1/SVEP1 gene pair associated with FAT2 mutations as a potential biomarker in gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide. Despite rapid advances in systemic therapy, GC remains the third leading cause of cancer-related deaths. We aimed to identify a novel prognostic signature associated with FAT2 mutations in GC. We analyzed the expression levels of FAT2-mutant and FAT2-wildtype GC samples obtained from The Cancer Genome Atlas (TCGA). The Kaplan–Meier survival curve showed that patients with FAT2 mutations showed better prognosis than those without the mutation. Sixteen long non-coding RNAs (lncRNAs) and 62 messenger RNAs (mRNAs) associated with FAT2 mutations were correlated with the prognosis of GC. We then constructed a 4-mRNA signature and a 5-lncRNA signature for GC. Finally, we identified the most relevant RP11-21 C4.1/SVEP1 gene pair as a prognostic signature of GC that exhibited superior predictive performance in comparison with the 4-mRNA or 5-lncRNA signature by weighted gene correlation network analysis (WGCNA) and Cox proportional hazards regression analysis. In this study, we constructed a prognostic signature of GC by integrative genomics analysis, which also provided insights into the molecular mechanisms linked to FAT2 mutations in GC.

Identification and Characterization of Non-Coding RNAs in Thymoma

BACKGROUND Thymoma is the most common tumor of the anterior mediastinum, and can be caused by infrequent malignancies arising from the epithelial cells of the thymus. Unfortunately, blood-based diagnostic markers are not currently available. High-throughput sequencing technologies, such as RNA-seq with next-generation sequencing, have facilitated the detection and characterization of both coding and non-coding RNAs (ncRNAs), which play significant roles in genomic regulation, transcriptional and post-transcriptional regulation, and imprinting and epigenetic modification. The knowledge about fusion genes and ncRNAs in thymomas is scarce. MATERIAL AND METHODS For this study, we gathered large-scale RNA-seq data belonging to samples from 25 thymomas and 25 healthy thymus specimens and analyzed them to identify fusion genes, lncRNAs, and miRNAs. RESULTS We found 21 fusion genes, including KMT2A-MAML2, HADHB-REEP1, COQ3-CGA, MCM4-SNTB1, and IFT140-ACTN4, as the most frequent and significant in thymomas. We also detected 65 differentially-expressed lncRNAs in thymomas, including AFAP1-AS1, LINC00324, ADAMTS9-AS1, VLDLR-AS1, LINC00968, and NEAT1, that have been validated with the TCGA database. Moreover, we identified 1695 miRNAs from small RNA-seq data that were overexpressed in thymomas. Our network analysis of the lncRNA-mRNA-miRNA regulation axes identified a cluster of miRNAs upregulated in thymomas, that can trigger the expression of target protein-coding genes, and lead to the disruption of several biological pathways, including the PI3K-Akt signaling pathway, FoxO signaling pathway, and HIF-1 signaling pathway. CONCLUSIONS Our results show that overexpression of this miRNA cluster activates PI3K-Akt, FoxO, HIF-1, and Rap-1 signaling pathways, suggesting pathway inhibitors may be therapeutic candidates against thymoma.

A seven-gene signature to predict the prognosis of oral squamous cell carcinoma

The prognosis of oral squamous cell carcinoma (OSCC) patients remains poor without implemented biomarkers in the clinical routine practice to help in the patient's management. With this study we aimed to identify specific prognostic biomarkers for OSCC using a whole genome technology as well as to verify the clinical utility of a head and neck cancer-specific multiplex ligation-dependent probe amplification (MLPA) panel. A genomic characterization of tumor samples from 62 OSCC patients was performed using array comparative genomic hybridization (aCGH) and a more straightforward and cost-effective molecular technology, MLPA. The identification of a genomic signature and prognosis biomarkers was carried out by applying several statistical methods. With aCGH we observed that the chromosomes most commonly altered were 3p, 3q, 5q, 6p, 7q, 8p, 8q, 11q, 15q, 17q, and 18q. The MLPA results showed that the chromosomes with a higher frequency of alterations were 3p, 3q, 8p, 8q, and 11q. We identified a genomic signature with seven genes OCLN (3p21.31), CLDN16 (3q29), SCRIB (3q29), IKBKB (3q22.3), PAK2 (8q22.3), PIK3CB (3q28), and YWHAZ (8q24.3) that together allow to differentiate the patients that developed metastases or relapses after primary tumor treatment, with an overall accuracy of 79%. Amplification of PIK3CB as a predictor of metastases or relapses development was validated using TCGA data. This amplified gene showed a reduction in more than 5 years in the median survival of the patients. The identified biomarkers might have a significant impact in the patients' management and could leverage the OSCC precision medicine.