Lack of Salivary Long Non-Coding RNA XIST Expression Is Associated with Increased Risk of Oral Squamous Cell Carcinoma: A Cross-Sectional Study

Salivary biomarkers: Effective diagnostic tool for oral leukoplakia and oral squamous cell carcinoma

OBJECTIVE

To identify potential salivary biomarkers for the diagnosis and monitoring of disease progression in oral squamous cell carcinoma and oral leukoplakia.

MATERIALS AND METHODS

An advance search from PubMed and Hindawi was performed with keywords; oral leukoplakia/oral squamous cell carcinoma, salivary biomarker and diagnosis/prognosis. An additional search of articles was done through a manual search from the Google Scholar database.

RESULTS

Twenty studies involving salivary biomarkers as diagnostic tools for oral squamous cell carcinoma and/or oral leukoplakia were identified. A narrative review was carried out.

CONCLUSION

Single or multiple salivary biomarkers reported by most studies have shown great potential as diagnostic tools for oral squamous cell carcinoma and oral leukoplakia. However, the validation of sensitivity and specificity should be carried out to ensure the accuracy of the biomarkers. Furthermore, a standardised method for saliva collection should be established to prevent variability in the expression of biomarkers.

The roles of long non-coding RNAs in ovarian cancer: from functions to therapeutic implications

Long non-coding RNAs (lncRNAs) are multifunctional and participate in a variety of biological processes and gene regulatory networks. The deregulation of lncRNAs has been extensively implicated in diverse human diseases, especially in cancers. Overwhelming evidence demonstrates that lncRNAs are essential to the pathophysiological processes of ovarian cancer (OC), acting as regulators involved in metastasis, cell death, chemoresistance, and tumor immunity. In this review, we illustrate the expanded functions of lncRNAs in the initiation and progression of OC and elaborate on the signaling pathways in which they pitch. Additionally, the potential clinical applications of lncRNAs as biomarkers in the diagnosis and treatment of OC were emphasized, cementing the bridge of communication between clinical practice and basic research.

Machine Learning Reveals Impacts of Smoking on Gene Profiles of Different Cell Types in Lung

Smoking significantly elevates the risk of lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. This risk is attributed to the harmful chemicals in tobacco smoke that damage lung tissue and impair lung function. Current research on the impact of smoking on gene expression in specific lung cells is limited. This study addresses this gap by analyzing gene expression profiles at the single-cell level from 43,539 lung endothelial cells, 234,349 lung epithelial cells, 189,843 lung immune cells, and 16,031 lung stromal cells using advanced machine learning techniques. The data, categorized by different lung cell types, were classified into three smoking states: active smoker, former smoker, and never smoker. Each cell sample encompassed 28,024 feature genes. Employing an incremental feature selection method within a computational framework, several specific genes have been identified as potential markers of smoking status in different lung cell types. These include B2M, EEF1A1, and TPT1 in lung endothelial cells; FTL and MT-ATP8 in lung epithelial cells; HLA-B and HLA-C in lung immune cells; and HSP90B1 and LCN2 in lung stroma cells. Additionally, this study developed quantitative rules for representing the gene expression patterns related to smoking. This research highlights the potential of machine learning in oncology, enhancing our molecular understanding of smoking's harm and laying the groundwork for future mechanism-based studies.

LncRNAs in non-small cell lung cancer: novel diagnostic and prognostic biomarkers

Non-small cell lung cancer (NSCLC) is one of the main causes of cancer-related death worldwide, with a serious impact on human health and life. The identification of NSCLC at an early stage is a formidable task that frequently culminates in a belated diagnosis. LncRNA is a kind of noncoding RNA with limited protein-coding capacity, and its expression is out of balance in many cancers, especially NSCLC. A large number of studies have reported that lncRNA acts a vital role in regulating angiogenesis, invasion, metastasis, and the proliferation and apoptosis of tumor cells, affecting the occurrence and development of NSCLC. Abundant evidence demonstrates that lncRNAs may serve as potential biomarkers for NSCLC diagnosis and prognosis. In this review, we summarize the latest progress in characterizing the functional mechanism of lncRNAs involved in the development of NSCLC and further discuss the role of lncRNAs in NSCLC therapy and chemotherapy resistance. We also discuss the advantages, limitations, and challenges of using lncRNAs as diagnostic or prognostic biomarkers in the management of NSCLC.

Salivary microbiome changes distinguish response to chemoradiotherapy in patients with oral cancer

BACKGROUND

Oral squamous cell carcinoma (SCC) is associated with oral microbial dysbiosis. In this unique study, we compared pre- to post-treatment salivary microbiome in patients with SCC by 16S rRNA gene sequencing and examined how microbiome changes correlated with the expression of an anti-microbial protein.

RESULTS

Treatment of SCC was associated with a reduction in overall bacterial richness and diversity. There were significant changes in the microbial community structure, including a decrease in the abundance of Porphyromonaceae and Prevotellaceae and an increase in Lactobacillaceae. There were also significant changes in the microbial community structure before and after treatment with chemoradiotherapy, but not with surgery alone. In patients treated with chemoradiotherapy alone, several bacterial populations were differentially abundant between responders and non-responders before and after therapy. Microbiome changes were associated with a change in the expression of DMBT1, an anti-microbial protein in human saliva. Additionally, we found that salivary DMBT1, which increases after treatment, could serve as a post-treatment salivary biomarker that links to microbial changes. Specifically, post-treatment increases in human salivary DMBT1 correlated with increased abundance of Gemella spp., Pasteurellaceae spp., Lactobacillus spp., and Oribacterium spp. This is the first longitudinal study to investigate treatment-associated changes (chemoradiotherapy and surgery) in the oral microbiome in patients with SCC along with changes in expression of an anti-microbial protein in saliva.

CONCLUSIONS

The composition of the oral microbiota may predict treatment responses; salivary DMBT1 may have a role in modulating the oral microbiome in patients with SCC. After completion of treatment, 6 months after diagnosis, patients had a less diverse and less rich oral microbiome. Leptotrichia was a highly prevalent bacteria genus associated with disease. Expression of DMBT1 was higher after treatment and associated with microbiome changes, the most prominent genus being Gemella Video Abstract.

Emerging cell cycle related non-coding RNA biomarkers from saliva and blood for oral squamous cell carcinoma

The unnotified or undifferentiable early stages of oral squamous cell carcinoma (OSCC) progression are the prime reasons for late-stage detection and poor survival outcomes of oral cancer. This review summarizes the prior research and recent advancements on the influence of dysregulated non-coding RNA (ncRNA) on cell cycle and their employability as diagnostic and prognostic biomarkers of oral cancer. The literature search was performed using the following keywords: 'serum/saliva non-coding RNAs' and 'serum/saliva non-coding RNAs and cell cycle', 'serum/saliva dysregulated ncRNAs and cell cycle', 'Cdk/CKI and ncRNAs', 'tissue ncRNAs' concerning 'oral cancer''. The compiled data focuses mainly on the diagnostic and prognostic significance of MicroRNAs (miRNAs), Circular RNAs (circRNAs), and Long noncoding RNAs (lncRNAs) on oral cancer and all other cancers as well as subject-relevant articles published in languages other than English are beyond the scope of this review and excluded from the study. Moreover, articles focusing on DNA, protein, and metabolite markers are eliminated from the study. While there exist various potential biomolecules such as DNA, RNA, proteins, metabolites, and specific antigens representing predictive biomarkers in body fluids for oral cancer, this review completely focuses on non-coding RNAs restricted to saliva and blood, picking out a few of the reliable ones amongst the recent investigations based on the sophisticated techniques, cohort, and sensitivity as well as specificity, i.e., salivary miR-1307-5p, miR-3928, hsa_circ_0001874 and ENST00000412740, NR_131012, ENST00000588803, NR_038323, miR-21 in circulation. Thus, further studies are required to clinically confirm the usage of these non-invasive biomarkers in oral cancer.

Long non-coding RNA as a potential diagnostic biomarker in head and neck squamous cell carcinoma: A systematic review and meta-analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a group of malignancies arising from the epithelium of the head and neck. Despite efforts in treatment, results have remained unsatisfactory, and the death rate is high. Early diagnosis of HNSCC has clinical importance due to its high rates of invasion and metastasis. This systematic review and meta-analysis evaluated the diagnostic accuracy of lncRNAs in HNSCC patients.

METHODS

PubMed, ISI, SCOPUS, and EMBASE were searched for original publications published till April 2023 using MeSH terms and free keywords "long non-coding RNA" and "head and neck squamous cell carcinoma" and their expansions. The Reitsma bivariate random effect model pooled diagnostic test performance for studies that reported specificity and sensitivity; diagnostic AUC values from all trials were meta-analyzed using the random effects model with the inverse variance method.

RESULTS

The initial database search yielded 3209 articles, and 25 studies met our criteria. The cumulative sensitivity and specificity for lncRNAs in the diagnosis of HNSCC were 0.74 (95%CI: 0.68-0.7 (and 0.79 (95%CI: 0.74-0.83), respectively. The pooled AUC value for all specimen types was found to be 0.83. Using the inverse variance method, 71 individual lncRNAs yielded a pooled AUC of 0.77 (95%CI: 0.74-0.79). Five studies reported on the diagnostic accuracy of the MALAT1 lncRNA with a pooled AUC value of 0.83 (95%CI: 0.73-0.94).

CONCLUSIONS

LncRNAs could be used as diagnostic biomarkers for HNSCC, but further investigation is needed to validate clinical efficacy and elucidate mechanisms. High-throughput sequencing and bioinformatics should be used to ascertain expression profiles.

Current Approach and Future Directions in the Diagnosis and Prognosis of Keratinocyte Carcinomas

Keratinocyte carcinomas (KCs) are malignancies developed from keratinocytes or their precursors [...].

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

Circulating Long Non-Coding RNAs Could Be the Potential Prognostic Biomarker for Liquid Biopsy for the Clinical Management of Oral Squamous Cell Carcinoma

Long non-coding RNA (lncRNA) have little or no coding potential. These transcripts are longer than 200 nucleotides. Since lncRNAs are master regulators of almost all biological processes, recent evidence proves that aberrantly expressed lncRNAs are pathogenic for oral squamous cell carcinoma (OSCC) and other diseases. LncRNAs influence chromatin modifications, transcriptional modifications, post-transcriptional modifications, genomic imprinting, cell proliferation, invasion, metastasis, and apoptosis. Consequently, they have an impact on the disease transformation, progression, and morbidity in OSCC. Therefore, circulating lncRNAs could be the potential cancer biomarker for the better clinical management (diagnosis, prognosis, and monitoring) of OSCC to provide advanced treatment strategies and clinical decisions. In this review, we report and discuss the recent understandings and perceptions of dysregulated lncRNAs with a focus on their clinical significance in OSCC-disease monitoring and treatment. Evidence clearly indicates that a specific lncRNA expression signature could act as an indicator for the early prediction of diagnosis and prognosis for the initiation, progression, recurrence, metastasis and other clinical prognostic-factors (overall survival, disease-free survival, etc.) in OSCC. The present review demonstrates the current knowledge that all potential lncRNA expression signatures are molecular biomarkers for the early prediction of prognosis in OSCC. Finally, the review provides information about the clinical significance, challenges and limitations of the clinical usage of circulating lncRNAs in a liquid biopsy method in early, pre-symptomatic, sub-clinical, accurate OSCC prognostication. More studies on lncRNA are required to unveil the biology of the inherent mechanisms involved in the process of the development of differential prognostic outcomes in OSCC.

Long non-coding RNA and RNA-binding protein interactions in cancer: Experimental and machine learning approaches

Understanding the complex and specific roles played by non-coding RNAs (ncRNAs), which comprise the bulk of the genome, is important for understanding virtually every hallmark of cancer. This large group of molecules plays pivotal roles in key regulatory mechanisms in various cellular processes. Regulatory mechanisms, mediated by long non-coding RNA (lncRNA) and RNA-binding protein (RBP) interactions, are well documented in several types of cancer. Their effects are enabled through networks affecting lncRNA and RBP stability, RNA metabolism including N⁶-methyladenosine (m⁶A) and alternative splicing, subcellular localization, and numerous other mechanisms involved in cancer. In this review, we discuss the reciprocal interplay between lncRNAs and RBPs and their involvement in epigenetic regulation via histone modifications, as well as their key role in resistance to cancer therapy. Other aspects of RBPs including their structural domains, provide a deeper knowledge on how lncRNAs and RBPs interact and exert their biological functions. In addition, current state-of-the-art knowledge, facilitated by machine and deep learning approaches, unravels such interactions in better details to further enhance our understanding of the field, and the potential to harness RNA-based therapeutics as an alternative treatment modality for cancer are discussed.

Effects of Ethanol on Expression of Coding and Noncoding RNAs in Murine Neuroblastoma Neuro2a Cells

Excessive use of alcohol can induce neurobiological and neuropathological alterations in the brain, including the hippocampus and forebrain, through changes in neurotransmitter systems, hormonal systems, and neuroimmune processes. We aimed to investigate the effects of ethanol on the expression of coding and noncoding RNAs in a brain-derived cell line exposed to ethanol. After exposing Neuro2a cells, a neuroblastoma cell line, to ethanol for 24 and 72 h, we observed cell proliferation and analyzed up- and downregulated mRNAs and long noncoding RNAs (lncRNAs) using total RNA-Seq technology. We validated the differential expression of some mRNAs and lncRNAs by RT-qPCR and analyzed the expression of Cebpd and Rnu3a through knock-down of Cebpd. Cell proliferation was significantly reduced in cells exposed to 100 mM ethanol for 72 h, with 1773 transcripts up- or downregulated by greater than three-fold in ethanol-treated cells compared to controls. Of these, 514 were identified as lncRNAs. Differentially expressed mRNAs and lncRNAs were mainly observed in cells exposed to ethanol for 72 h, in which Atm and Cnr1 decreased, but Trib3, Cebpd, and Spdef increased. On the other hand, lncRNAs Kcnq1ot1, Tug1, and Xist were changed by ethanol, and Rnu3a in particular was greatly increased by chronic ethanol treatment through inhibition of Cebpd. Our results increase the understanding of cellular and molecular mechanisms related to coding and noncoding RNAs in an in vitro model of acute and chronic exposure to ethanol.