Accession Number : AD1039006


Title :   Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer


Descriptive Note : Technical Report,30 Sep 2012,29 Sep 2015


Corporate Author : Massachusetts General Hospital Boston United States


Personal Author(s) : Birrer,Michael J ; Poveda,Andres ; Kristensen,Gunnar ; McNeish,Tain


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1039006.pdf


Report Date : 01 Dec 2015


Pagination or Media Count : 31


Abstract : The second year of the grant required the following tasks:1. RNAseq of 400 training specimens (Months 12-18) 2. Import raw data into public databases (Months 12-18)3. Generate preliminary gene signature through bioinformatic and statistical analysis (Months 18-24). In year 1) we had identified 592 early-stage high-grade ovarian cancers with 5-year follow-up, clinical annotation and accurate pathological review (228 recurrent and 364 non-recurrent), 2) established a specimen repository and clinical data inventory at MGH, 3) micro-dissected and isolated RNA from 110 tumors, and 3) optimized the preparation of cDNA libraries using NuGene WT-Ovation FFPE System V2. Given the fact that RNA sequencing is in its early stage of application, and application of this technology to FFPE tissue is still being fully developed, we have been working a work-process with different Nextgen facilities to successfully apply this technology to our FFPE samples. This included sequencing a sample test of 10 tumors and comparing the sequencing results of these early stage samples with publicly available RNAseq data for early and advanced ovarian cancers. Once the SOP were set we have been able to sequence the first 100 samples of our biorepository.


Descriptors :   Ovarian Cancer , Ribonucleic acidS


Subject Categories : Medicine and Medical Research


Distribution Statement : APPROVED FOR PUBLIC RELEASE