bioRxivCell BiologyPreprint
Theileria annulata Infection Promotes p53 suppression, Genomic Instability and DNA deaminase APOBEC3H upregulation leading to cancer-like phenotype in host cells
p. sharma, D. Dandesena, a. suresh, R. Budhwar, J. Godwin, s. singh, M. Subudhi, A. T, s. roy, V. M. A, v. bhandari
Abstract
Theileria annulata-infected host leukocytes display cancer-like phenotypes, though the precise mechanism is yet to be fully understood. The occurrence of cancer-like phenotypes in Theileria-infected leukocytes may be attributed to various factors, including genomic instability and acquired mutations, a crucial trait that underpins the genetic foundation of cancer. This paper presents WGS data and bioinformatic analyses to reveal point mutations and large-scale alterations in six clinically relevant T. annulata-infected cell lines. We identified 7867 exon-linked somatic mutations common to all cell lines, and cancer association analysis showed significant accumulation in oncogenes (FLT4, NOTCH2, MAP3K1, DAXX, FCGR2B, ROS1) and tumor suppressor genes (BARD1, KMT2C, GRIN2A, BAP1) implicated in established critical cancer processes. We demonstrated that a crizotinib-induced blockade of the ROS1 oncogenic protein, which harbored the most mutations, led to the death of infected leukocytes. This is consistent with the significant role of ROS1 in parasite-induced leukocyte transformation. In addition, we found somatic mutations in genes involved in genome instability and the DDR pathway. Our findings support the notion that ROS1 and Nutulin 3a are valid targets for intervention, and the suppression of TP53, a crucial tumor suppressor gene, may play a significant role in cell immortalization. We also show that upon infection with the parasite, bovine cells upregulate the expression of APOBEC3H, a DNA mutator likely responsible for the detected mutations. Our study highlights how T. annulata transforms leukocytes to gain selective advantage via mutation, and our observations could steer future research towards a mechanistic understanding of disease pathogenesis.
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: gene regulatory network inference
- approach: statistical model
- approach: biophysical modeling
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