RESUMO
Characterizing a pancreatic or periampullary mass lesion as benign or malignant on conventional imaging is difficult due to overlapping morphological features. 18F-FDG PET/CT is a molecular imaging technique with reportedly higher sensitivity and specificity in the differentiation of benign and malignant pancreatic and periampullary masses. In this prospective study, we evaluated the utility of 18F-FDG PET/CT in patients with recently diagnosed pancreatic and periampullary masses. Based on FDG uptake pattern, diffuse or absent uptake was considered benign and focal increased uptake as malignant. Among the 32 patients included in the study, pathological examination confirmed 25 as positive for malignancy and the remaining 7 as benign etiology. Based on FDG uptake pattern, sensitivity, specificity, PPV, NPV, and accuracy of the study were 92%, 42.8%, 85.2%, 60%, and 81.3% respectively. 18F-FDG PET/CT had a statistically significant higher detection rate in the evaluation of regional lymph nodes and distant organ metastases compared to radiological imaging. In 7/25 (14%) malignant cases, 18F-FDG PET/CT detected additional distant metastases which were not detected by conventional imaging and thus resulting in change in management from curative resection to palliative therapy. To conculde, 18F-FDG PET/CT uptake pattern can characterize pancreatic and periampullary masses as benign or malignant with a relatively good accuracy. Using 18F-FDG PET/CT for initial staging of pancreatic and periampullary cancer helps in appropriate staging and optimal selection of treatment modality compared to conventional imaging techniques.
RESUMO
Cervical cancer is one of the most malignant reproductive diseases seen in women worldwide. The identification of dysregulated genes in clinical samples of cervical cancer may pave the way for development of better prognostic markers and therapeutic targets. To identify the dysregulated genes (DEGs), we have retrospectively collected 10 biopsies, seven from cervical cancer patients and three from normal subjects who underwent a hysterectomy. Total RNA isolated from biopsies was subjected to microarray analysis using the human Clariom D Affymetrix platform. Based on the results of principal component analysis (PCA), only eight samples are qualified for further studies; GO and KEGG were used to identify the key genes and were compared with TCGA and GEO datasets. Identified genes were further validated by quantitative real-time PCR and receiver operating characteristic (ROC) curves, and the highest Youden index was calculated in order to evaluate cutoff points (COPs) that allowed distinguishing of tissue samples of cervical squamous carcinoma patients from those of healthy individuals. By comparative microarray analysis, a total of 108 genes common across the six patients' samples were chosen; among these, 78 genes were upregulated and 26 genes were downregulated. The key genes identified were SPP1, LYN, ARRB2, COL6A3, FOXM1, CCL21, TTK, and MELK. Based on their relative expression, the genes were ordered as follows: TTK > ARRB2 > SPP1 > FOXM1 > LYN > MELK > CCL21 > COL6A3; this generated data is in sync with the TCGA datasets, except for ARRB2. Protein-protein interaction network analysis revealed that TTK and MELK are closely associated with SMC4, AURKA, PLK4, and KIF18A. The candidate genes SPP1, FOXM1, LYN, COL6A3, CCL21, TTK and MELK at mRNA level, emerge as promising candidate markers for cervical cancer prognosis and also emerge as potential therapeutic drug targets.
