Abstract 5436
Background
MLH1 knock out mice develop mismatch repair deficient (MMR-D) neoplasias spontaneously and reflect the diverse clinical presentation of MMR-D-driven carcinogenesis in men. The tumor spectrum includes a high prevalence of early Non-Hodgkin T cell lymphomas (NHL), lymphoid skin lesions as well as later developing epithelial tumors of the gastrointestinal tract (GIT).
Methods
Using whole-exome sequencing on MLH1-/- tumors (2x GIT, 1x splenic NHL, 1x skin lymphoma) as well as GIT-derived cell lines (n = 2), we focused on identification of (I) shared and (II) mutually exclusive mutations and described the processes of ongoing mutational events in tumor-derived cultures.
Results
MLH1-/- tumors show high tumor mutational burden with 3/4 primary tumor samples even being ultra-hypermutated (> 100 mut/MB). Missense mutations were more frequent than nonsense mutations, base changes were mainly due to transitions (C>T; A>G). The resulting mutational landscape was heterogeneous and in accordance with the human counterpart, MLH1-/- tumors frequently harbor mutations in PIK3CA, EGFR, KRAS, and/or ERBB3. Of note, only a few shared mutations were detectable among different tumor entities, among them were ARID1A and IDH2. Mutations in classical tumor suppressor genes SMAD4 and POLE were mutually exclusive in lymphomas, most likely contributing to a more aggressive in vivo phenotype. Comparing the mutational profile of selected tumors and their corresponding cell line revealed continuous increased numbers of somatic gene mutations. The same was true for coding microsatellite mutations in MMR-D target genes. Partial overlap was detectable, yet recognizing shared antigens. Two promising candidates are AKT3, a RAC-gamma serine/threonine-protein kinase and the endonuclease ERCC5 (Excision Repair 5), involved in DNA excision repair.
Conclusions
The present study is the first reporting results of a comparison between different spontaneously developing tumors as models for MMR-D driven tumorigenesis. Additionally to identifying ARID1A as causative mutation hotspot, this comprehensive characterization of the mutational landscape may be a good starting point to predict antigens for vaccination approaches.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
german research foundation (DFG); grant number: MA5799/2-1.
Disclosure
All authors have declared no conflicts of interest.
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