Chromosomal Translocations Detection in Cancer Cells Using Chromosomal Conformation Capture Data.
Muhammad Muzammal AdeelKhaista RehmanYan ZhangYibeltal AregaGuo Liang LiPublished in: Genes (2022)
Complex chromosomal rearrangements such as translocations play a critical role in oncogenesis. Translocation detection is vital to decipher their biological role in activating cancer-associated mechanisms. High-throughput chromosomal conformations capture (Hi-C) data have shown promising progress in unveiling the genome variations in a disease condition. Until now, multiple structural data (Hi-C)-based methods are available that can detect translocations in cancer genomes. However, the consistency and specificity of Hi-C-based translocation results still need to be validated with conventional methods. This study used Hi-C data of cancerous cell lines, namely lung cancer (A549), Chronic Myelogenous Leukemia (K562), and Acute Monocytic Leukemia (THP-1), to detect the translocations. The results were cross-validated through whole-genome sequencing (WGS) and paired-read analysis. Moreover, PCR amplification validated the presence of translocated reads in different chromosomes. By integrating different data types, we showed that the results of Hi-C data are as reliable as WGS and can be utilized as an assistive method for detecting translocations in the diseased genome. Our findings support the utility of Hi-C technology to detect the translocations and study their effects on the three-dimensional architecture of the genome in cancer condition.
Keyphrases
- electronic health record
- big data
- high throughput
- acute myeloid leukemia
- bone marrow
- data analysis
- signaling pathway
- squamous cell
- squamous cell carcinoma
- liver failure
- dna methylation
- label free
- artificial intelligence
- molecular dynamics simulations
- single molecule
- drug induced
- quantum dots
- real time pcr
- nucleic acid