Next Generation Sequencing Based Cancer Diagnostics

Abstract

Ovarian cancer is the most lethal gynecologic cancer. The diagnosis of ovarian cancer is hard due to nonspecific symptoms and possibly asymptomatic early stage of the disease. Current diagnostics methods for ovarian cancer consists of inaccurate biomarker tests that can lead to false-positive results and therefore invasive examinations. Next generation sequencing (NGS) is DNA sequencing method that allows massively parallel sequencing. This improves the speed and accuracy and lowers the cost of sequencing when samples are pooled together with the help of barcoded primers. The use of NGS in cancer diagnostics studies could provide discovery of new diagnostics and prognostics biomarkers. Cancer genomic studies would also give valuable information about tumor’s molecular characteristics and lead to more specific cancer treatments. In this study, sequencing was done for antibodies from phage display library that binds to CA-125 containing molecular components within ovarian cyst fluid samples. Sequencing was performed with Illumina MiSeq platform for five classes of samples: non-neoplastic (NN), benign, borderline, malignant type I (MTI) and malignant type II (MTII). Various bioinformatic methods was used for analysis of sequencing data. The data showed differences in the amount of unique CDRH3 (complementary-determining region) sequences when compared between different sample types. The amount of unique sequences is higher in malignant samples (MTII, 11.4%; MTI, 12.9 % from all sequences) than in benign samples (NN, 6.6%; benign, 8.6% from all sequences).