Integrated computational screening and liquid biopsy approach to uncover the role of biomarkers for oral cancer lymph node metastasis.

Cancer is an abnormal, heterogeneous growth of cells with the ability to invade surrounding tissue and even distant organs. Worldwide, GLOBOCAN had an estimated 18.1 million new cases and 9.6 million death rates of cancer in 2018. Among all cancers, Oral cancer (OC) is the sixth most common cancer worldwide, and the third most common in India, the most frequent type, oral squamous cell carcinoma (OSCC), tends to spread to lymph nodes in advanced stages. Throughout the past few decades, the molecular landscape of OSCC biology has remained unknown despite breakthroughs in our understanding of the genome-scale gene expression pattern of oral cancer particularly in lymph node metastasis. Moreover, due to tissue variability in single-cohort studies, investigations on OSCC gene-expression profiles are scarce or inconsistent. The work provides a comprehensive analysis of changed expression and lays a major focus on employing a liquid biopsy base method to find new therapeutic targets and early prediction biomarkers for lymph node metastasis. Therefore, the current study combined the profile information from GSE9844, GSE30784, GSE3524, and GSE2280 cohorts to screen for differentially expressed genes, and then using gene enrichment analysis and protein-protein interaction network design, identified the possible candidate genes and pathways in lymph node metastatic patients. Additionally, the mRNA expression of discovered genes was assessed using real-time PCR, and the Human Protein Atlas database was utilized to determine the protein levels of hub genes in tumor and normal tissues. Angiogenesis was been investigated using the Chorioallentoic membrane (CAM) angiogenesis test. In a cohort of OSCC patients, fibronectin (FN1), C-X-C Motif Chemokine Ligand 8 (CXCL8), and matrix metallopeptidase 9 (MMP9) were significantly upregulated, corroborating these findings. Our identified significant gene signature showed greater serum exosome effectiveness in early detection and clinically linked with intracellular communication in the establishment of the premetastatic niche. Also, the results of the CAM test reveal that primary OC derived exosomes may have a function in angiogenesis. As a result, our study finds three potential genes that may be used as a possible biomarker for lymph node metastasis early detection and sheds light on the underlying processes of exosomes that cause a premetastatic condition.

Identification of hub genes associated with prognosis of lung cancer via integrated bioinformatics and in vitro approach.

Lung cancer is a severe health problem that affects more men than women around the world. The goal of this study was to identify the biomarker hub genes for lung cancer in order to ascertain the biological pathway and protein- protein interaction networks. The microarray datasets GSE80796, GSE68571, GSE118370 and GSE43458 were retrieved from the GEO database and were analysed using GEO2R. STRING, Cytoscape, and cytoHubba were used to construct the PPI network and hub genes. GEPIA was used to obtain the overall survival and expression level in LUAD/LUSC and normal tissue. The MTT assay was used to examine antiproliferative activity. PI staining was used to determine the cell cycle arrest. qPCR was used to analyse gene expressions. The datasets revealed a total of 401 common DEGs, with 258 up-regulated genes and 143 down-regulated genes. Further, in-vitro study of gallic acid cytotoxic effect in human lung cancer cell line A549 indicated that gallic acid dramatically suppressed cell growth in A549 cells. Gallic acid also, significantly promoted programmed cell death by halting cells in the G0/G1 phase of the cell cycle. Taken together, our study indicated that gallic acid is a promising natural STAT1 inhibitor as it hindered lung cancer progression by inducing cell cycle arrest and apoptosis which can be employed to increase the therapeutic efficacy of existing lung cancer treatments and to improve overall patient survival.Communicated by Ramaswamy H. Sarma.

Identification of crucial hub genes and potential molecular mechanisms in breast cancer by integrated bioinformatics analysis and experimental validation.

Breast cancer (BC) is a malignancy that affects a large number of women around the world. The purpose of the current study was to use bioinformatics analysis to uncover gene signatures during BC and their potential mechanisms. The gene expression profiles (GSE29431, GSE10810, and GSE42568) were retrieved from the Gene Expression Omnibus database, and the differential expressed genes (DEGs) were identified in normal tissues and tumour tissue samples from BC patients. In total, 296 DEGs were identified in BC, including 46 upregulated genes and 250 downregulated genes. GO and KEGG pathway analysis were performed. A PPI network of the DEGs was also constructed. GO analysis results showed that upregulated DEGs were significantly enriched in biological processes (BP), including cell division, mitotic cell cycle, chromosome separation, and cell division. MF analysis showed that upregulated DEGs controlled the microtubule cytoskeleton, the microtubule organising center, the cytoskeleton, and the chromosome-centric region. KEGG analysis revealed the upregulated DEGs mainly regulated p53 signaling, while the downregulated DEGs were enriched in the AMPK signalling pathway and PPAR signalling pathway. Moreover, five hub genes with a high degree of stability were identified, including NUSAP1, MELK, CENPF, TOP2A, and PPARG. Experimental validation showed that all five hub genes had the same expression trend as predicted. The overall survival and expression levels of hub genes were detected by Kaplan-Meier-plotter and the UALCAN database and were further validated using the Human Protein Atlas database. Taken together, the identified key genes enhance our understanding of the molecular pathways that underpin BC pathogenesis. As a result, our novel findings could be used as molecular targets and diagnostic biomarkers in the treatment of BC. This study is based on empirical evidence, making it an appealing read for the global scientific community.

Saliva based non invasive screening of Oral Submucous Fibrosis using ATR-FTIR spectroscopy.

Oral Submucous Fibrosis (OSMF) is a type of precancerous condition of Oral cancer and considered to have the greatest malignant potential. Biopsy is an ultimate option for the conformation of the malignancy. But the invasiveness of the procedure makes it interdict. Therefore, there is an urgent need to identify effective screening and diagnostic methods which would be less invasive, rapid, more accurate and cost effective. Here, we used Attenuated Total Reflection- Fourier transform infrared spectroscopy (ATR-FTIR) with Chemometric analysis coupled with estimation of total salivary protein to discriminate OSMF and Healthy Control (HC). The present study showed the specific Infrared spectrum for OSMF patients, which was specifically differentiated from HC based on the spectral shift of proteins/amide II, carbohydrate and nucleic acid using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) with small data sets. ATR-FTIR spectroscopy of saliva coupled with total protein estimation can be used to discriminate between OSMF and HC. However, large sample size should be needed to evaluate the ATR-FTIR for consideration as a screening tool for an early diagnosis OSMF.