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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. [ABSTRACT FROM AUTHOR]

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases., Competing Interests: The authors declare no conflict of interest., (© 2021 Biomedical Informatics.)