Head and Neck Pathology
Sahar Assar; Sepideh Assar; Heidar-Ali Mardanifard; Zohreh Jaafari-Ashkavandi
Abstract
Background & Objective: There is no consensus on the prevalence of salivary gland tumors (SGTs) in Iran. Thus, we systematically reviewed the literature about the prevalence of SGTs in Iran and applied the last world health organization (WHO) classification.Methods: The systematic literature search ...
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Background & Objective: There is no consensus on the prevalence of salivary gland tumors (SGTs) in Iran. Thus, we systematically reviewed the literature about the prevalence of SGTs in Iran and applied the last world health organization (WHO) classification.Methods: The systematic literature search was performed in EMBASE, Scopus, PubMed MEDLINE, Google Scholar, Scientific Information Database (SID), and Magiran; we searched for "salivary gland," "tumor," "prevalence," and "Iran" until 1 March 2021. The studies included were written in the English and Farsi languages. The weighted mean prevalence of SGTs was calculated as prevalence (%) * (N/the sum of all N). We used the unpaired Two-sample T-test to compare the weighted means.Results: A total of 17 studies, including 2870 patients, were selected for the data synthesis. The weighted mean prevalence of benign and malignant tumors was 66% (95% CI: 59-73) and 34% (95% CI: 27-41), respectively. The patients' mean age was reported in 10 out of the 17 studies. The weighted mean age of the patients was 40 (95% CI: 37-42) and 49 (95% CI: 43-55) years for benign and malignant tumors, respectively (P=0.01). Pleomorphic adenoma (PA), followed by Warthin's tumor (WT), was the most prevalent benign tumor. Moreover, the most common malignant tumors were mucoepidermoid carcinoma (MEC) and adenoid cystic carcinoma (AdCC).Conclusion: More than one-third of SGTs in Iran were malignant, which is higher than the reports from Middle Eastern countries. Information about risk factors and the burden of SGTs in Iran is insufficient. Thus, further well-designed longitudinal studies are warranted.
Biology & Genetic
Malihe Ram; Ali Najafi; Mohammad Taghi Shakeri
Abstract
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used ...
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Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and small-n. Therefore, RF can be used to select and rank the genes for the diagnosis and effective treatment of cancer. Methods: The microarray gene expression data of colon, leukemia, and prostate cancers were collected from public databases. Primary preprocessing was done on them using limma package, and then, the RF classification method was implemented on datasets separately in R software. Finally, the selected genes in each of the cancers were evaluated and compared with those of previous experimental studies and their functionalities were assessed in molecular cancer processes. Result: The RF method extracted very small sets of genes while it retained its predictive performance. About colon cancer data set DIEXF, GUCA2A, CA7, and IGHA1 key genes with the accuracy of 87.39 and precision of 85.45 were selected. The SNCA, USP20, and SNRPA1 genes were selected for prostate cancer with the accuracy of 73.33 and precision of 66.67. Also, key genes of leukemia data set were BAG4, ANKHD1-EIF4EBP3, PLXNC1, and PCDH9 genes, and the accuracy and precision were 100 and 95.24, respectively. Conclusion: The current study results showed most of the selected genes involved in the processes and cancerous pathways were previously reported and had an important role in shifting from normal cell to abnormal.