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Dietzen, M.

Publications and source records attributed to Dietzen, M..

3 recordsLinked to original sources

Targeted cancer therapy induces APOBEC fuelling the evolution of drug resistance

Introductory paragraphThe clinical success of targeted cancer therapy is limited by drug resistance that renders cancers lethal in patients1-4. Human tumours can evolve therapy resistance by acquiring de novo genetic alterations and increased heterogeneity via mechanisms that remain incompletely understood1. Here, through parallel analysis of human clinical samples, tumour xenograft and cell line models and murine model systems, we uncover an unanticipated mechanism of therapy-induced adaptation that fuels the evolution of drug resistance. Targeted therapy directed against EGFR and ALK oncoproteins in lung cancer induced adaptations favoring apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC)-mediated genome mutagenesis. In human oncogenic EGFR-driven and ALK-driven lung cancers and preclinical models, EGFR or ALK inhibitor treatment induced the expression and DNA mutagenic activity of APOBEC3B via therapy-mediated activation of NF-{kappa}B signaling. Moreover, targeted therapy also mediated downregulation of certain DNA repair enzymes such as UNG2, which normally counteracts APOBEC-catalyzed DNA deamination events. In mutant EGFR-driven lung cancer mouse models, APOBEC3B was detrimental to tumour initiation and yet advantageous to tumour progression during EGFR targeted therapy, consistent with TRACERx data demonstrating subclonal enrichment of APOBEC-mediated mutagenesis. This study reveals how cancers adapt and drive genetic diversity in response to targeted therapy and identifies APOBEC deaminases as future targets for eliciting more durable clinical benefit to targeted cancer therapy.

cancer biology↗

Copy number-aware deconvolution of tumor-normal DNA methylation profiles

Aberrant methylation is a hallmark of cancer, but bulk tumor data is confounded by admixed normal cells and copy number changes. Here, we introduce Copy number-Aware Methylation Deconvolution Analysis of Cancers (CAMDAC; https://github.com/VanLoo-lab/CAMDAC), which outputs tumor purity, allele-specific copy number and deconvolved methylation estimates. We apply CAMDAC to 122 multi-region samples from 38 TRACERx non-small cell lung cancers profiled by reduced representation bisulfite sequencing. CAMDAC copy number profiles parallel those derived from genome sequencing and highlight widespread chromosomal instability. Deconvolved polymorphism-independent methylation rates enable unbiased tumor-normal and tumor-tumor differential methylation calling. Read-phasing validates CAMDAC methylation rates and directly links genotype and epitype. We show increased epigenetic instability in adenocarcinoma vs. squamous cell carcinoma, frequent hypermethylation at sites carrying somatic mutations, and parallel copy number losses and methylation changes at imprinted loci. Unlike bulk methylomes, CAMDAC profiles recapitulate tumor phylogenies and evidence distinct patterns of epigenetic heterogeneity in lung cancer.

genomics↗

Whole Genome Doubling mitigates Muller’s Ratchet in Cancer Evolution

Whole genome doubling (WGD) is a prevalent macro-evolutionary event in cancer, involving a doubling of the entire chromosome complement. However, despite its prevalence and clinical prognostic relevance, the evolutionary selection pressures for WGD have not been investigated. Here, we explored whether WGD may act to mitigate the irreversible, inexorable ratchet-like, accumulation of deleterious mutations in essential genes. Utilizing 1050 tumor regions from 816 non-small cell lung cancers (NSCLC), we temporally dissect mutations to determine their temporal acquisition in relation to WGD. We find evidence for strong negative selection against homozygous loss of essential cancer genes prior to WGD. However, mutations in essential genes occurring after duplication were not subject to significant negative selection, consistent with WGD providing a buffering effect, decreasing the likelihood of homozygous loss. Finally, we demonstrate that loss of heterozygosity and temporal dissection of mutations can be exploited to identify signals of positive selection in lung, breast, colorectal cancer and other cancer types, enabling the elucidation of novel tumour suppressor genes and a deeper characterization of known cancer genes.

genomics↗