Mass Spectrometry Imaging of Lumpectomy Specimens Deciphers Diacylglycerols as Potent Biomarkers for the Diagnosis of Breast Cancer.

Detecting breast tumor markers with a fast turnaround time from frozen sections should foster intraoperative histopathology in breast-conserving surgery, reducing the need for a second operation. Hence, rapid label-free discrimination of the spatially resolved molecular makeup between cancer and adjacent normal breast tissue is of growing importance. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) of fresh-frozen excision specimens, including cancer and paired adjacent normal sections, obtained from the lumpectomy of 73 breast cancer patients. The results demonstrate that breast cancer tissue posits sharp metabolic upregulation of diacylglycerol, a lipid second messenger that activates protein kinase C for promoting tumor growth. We identified four specific sn-1,2-diacylglycerols that outperformed all other lipids simultaneously mapped by the positive ion mode DESI-MSI for distinguishing cancers from adjacent normal specimens. This result contrasts with several previous DESI-MSI studies that probed metabolic dysregulation of glycerophospholipids, sphingolipids, and free fatty acids for cancer diagnoses. A random forest-based supervised machine learning considering all detected ion signals also deciphered the highest diagnostic potential of these four diacylglycerols with the top four importance scores. This led us to construct a classifier with 100% overall prediction accuracy of breast cancer by using the parsimonious set of four diacylglycerol biomarkers only. The metabolic pathway analysis suggested that increased catabolism of phosphatidylcholine in breast cancer contributes to diacylglycerol overexpression. These results open up opportunities for mapping diacylglycerol signaling in breast cancer in the context of novel therapeutic and diagnostic developments, including the intraoperative assessment of breast cancer margin status.

HPV genotype prevalence in Indian women with cervical disease and estimation of the potential impact of HPV vaccines on prevention of cervical cancer.

PURPOSE: Human papillomavirus (HPV) causes genital and oropharyngeal cancers worldwide. There are significant gaps exist in the data on HPV genotype prevalence in this part of the country. HPV vaccination is one of the best preventive methods available currently. HPV genotyping plays an important role in the selection of appropriate vaccines and monitoring vaccine efficacy and coverage. The present study aimed to determine the HPV genotype prevalence and to estimate the potential impact of HPV vaccines on invasive cervical cancer. MATERIALS AND METHODS: A total of 204 cervical biopsy samples collected from symptomatic women were subjected to an in-house designed and standardised nested multiplex PCR (NM-PCR) assay. The NM-PCR was designed to detect 38 Mucosal HPV types as a pooled result and genotyping of 15 HPV types. Further, the HPV genotype data was used to estimate the HPV vaccine bivalent, quadrivalent and nonavalent impact on the population using a mathematical formula. RESULTS: Out of 204 samples 188 were subjected to HPV-nested PCR. A total of 163 (86.7%) samples were positive for at least one HPV type. Multiple genotypes were identified in 30% of samples processed. HPV-16 (85.3%) was the most frequently detected genotype followed by HPV-18 (13.5%) and HPV-33 (11.0%). Other genotypes were observed less frequently. Based on the HPV prevalence observed in the study a mathematical model estimated the efficacy of bivalent, quadrivalent and nonavalent vaccines were 76.1%, 76.7%, and 91.1% (average) respectively. CONCLUSIONS: HPV-16 was the most prevalent (>85%) genotype detected in this study. Multiple infections observed in 30% of samples were quite high as compared to the majority of national, and global reference (15-25.4%) data. The Mathematical model showed that a nonavalent vaccine would give better protection.

Utility of Fluorine18 Fluoro-2-deoxy-D-glucose Positron Emission Tomography/Computed Tomography in Metabolic Characterization of Solid Renal Mass Lesion and Localization of Extra Renal Lesions in the Body - A Prospective Study from the Tertiary Care Center in South India.

Purpose of the Study: Renal mass lesions in majority of the cases are due to malignant etiology and about one-third of them are reported with metastatic lesions at the time of presentation. Thus proper investigational workup is needed for staging and thereby treatment planning. The current fluorine18 fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F18-FDG PET/CT) study was designed to characterize renal mass lesions metabolically and identifying other metabolically active lesions in the body suggesting metastatic disease. Materials and Methods: A total of 24 patients (males - 18 and females - 6) with a mean age of 53.8 ± 12.3 years were recruited in this study for dual time-point PET/CT scan. All patients with renal mass lesions underwent contrast-enhanced CT prior to PET/CT. Metabolic parameters such as maximum standardized uptake value (max.SUV) with a cut off ≥2.5 and retention index (RI) of ≥10% were used to label the lesion as malignant and remaining less than cutoff as benign. The final diagnosis of lesion on imaging was confirmed with a histopathological examination (HPE). Results: Using max.SUV cut off value, 17/24 renal mass lesions were characterized as malignant and remaining 7/24 renal lesions of benign etiology. PET/CT showed sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 80%, 75%, 94.1%, 42.8%, and 79.1%, respectively, by considering HPE as a gold standard. Nine patients were diagnosed with distant site involvement suggestive of metastases. Conclusion: F18-FDG PET/CT can efficiently characterize solid renal mass lesion as benign and malignant using metabolic parameters such as max.SUV and RI. In addition, whole-body survey identified distant site involvement in 25% of the patients, thus contributing change in management.