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Benes, C.

Publications and source records attributed to Benes, C..

3 recordsLinked to original sources

APOBEC3A drives acquired resistance to targeted therapies in non-small cell lung cancer

Acquired drug resistance to even the most effective anti-cancer targeted therapies remains an unsolved clinical problem. Although many drivers of acquired drug resistance have been identified1-6, the underlying molecular mechanisms shaping tumor evolution during treatment are incompletely understood. The extent to which therapy actively drives tumor evolution by promoting mutagenic processes7 or simply provides the selective pressure necessary for the outgrowth of drug-resistant clones8 remains an open question. Here, we report that lung cancer targeted therapies commonly used in the clinic induce the expression of cytidine deaminase APOBEC3A (A3A), leading to sustained mutagenesis in drug-tolerant cancer cells persisting during therapy. Induction of A3A facilitated the formation of double-strand DNA breaks (DSBs) in cycling drug-treated cells, and fully resistant clones that evolved from drug-tolerant intermediates exhibited an elevated burden of chromosomal aberrations such as copy number alterations and structural variations. Preventing therapy-induced A3A mutagenesis either by gene deletion or RNAi-mediated suppression delayed the emergence of drug resistance. Finally, we observed accumulation of A3A mutations in lung cancer patients who developed drug resistance after treatment with sequential targeted therapies. These data suggest that induction of A3A mutagenesis in response to targeted therapy treatment may facilitate the development of acquired resistance in non-small-cell lung cancer. Thus, suppressing expression or enzymatic activity of A3A may represent a potential therapeutic strategy to prevent or delay acquired resistance to lung cancer targeted therapy.

cancer biology↗

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR/Cas9 screening

Many gene fusions have been reported in tumours and for most their role remains unknown. As fusions can be used clinically for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their functional implications in cancer. To investigate the role of fusions in tumor cell fitness, we developed a systematic analysis utilising RNA-sequencing data from 1,011 human cancer cell lines to functionally link 8,354 gene fusion events with genomic data, sensitivity to >350 anti-cancer drugs and CRISPR-Cas9 loss-of-fitness information. Established clinically-relevant fusions were readily identified. Overall, functional fusions were rare, including those involving cancer driver genes, suggesting that many fusions are dispensable for tumor cell fitness. Novel therapeutically actionable fusions involving RAF1, BRD4 and ROS1 were verified in new histologies. In addition, recurrent YAP1-MAML2 fusions were identified as activators of Hippo-pathway signaling in multiple cancer types, supporting therapeutic targeting of Hippo signalling. Our approach discriminates functional fusions, identifying new drivers of carcinogenesis and fusions that could have important clinical implications. SignificanceWe identify fusions as new potential candidates for drug repurposing and drivers of carcinogenesis. These results support histology agnostic marker-driven precision cancer medicine. Most fusions are not functional with implications for interpreting cancer fusions reported from clinical sequencing studies.

cancer biology↗

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here we perform a genome-wide prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

cancer biology↗