Most lung cancer patients with metastatic cancer eventually relapse with drug-resistant disease following treatment and EGFR mutant lung cancer is no exception. Genome-wide CRISPR screens, to either knock out or overexpress all protein-coding genes in cancer cell lines, revealed the landscape of pathways that cause resistance to the EGFR inhibitors osimertinib or gefitinib in EGFR mutant lung cancer. Among the most recurrent resistance genes were those that regulate the Hippo pathway. Following osimertinib treatment a subpopulation of cancer cells are able to survive and over time develop stable resistance. These 'persister' cells can exploit non-genetic (transcriptional) programs that enable cancer cells to survive drug treatment. Using genetic and pharmacologic tools we identified Hippo signalling as an important non-genetic mechanism of cell survival following osimertinib treatment. Further, we show that combinatorial targeting of the Hippo pathway and EGFR is highly effective in EGFR mutant lung cancer cells and patient-derived organoids, suggesting a new therapeutic strategy for EGFR mutant lung cancer patients.
Abstract Background: Almost 10% of colon cancers harbor the canonical activating V600 BRAF mutation that in melanoma cancers has been shown to dramatically sensitize cells to targeted therapy and prolong survival. In the colon, such tumors are associated with worse survival. Recent clinical trials of combination therapies targeting the EGFR and MAPK pathways in these tumors have demonstrated impressive response rates. However, the clinical benefit has been limited by the rapid emergence of drug resistance. Identifying and targeting the genes complicit in this process and thus re-sensitize resistant cancer cells may be of clinical benefit. The landscape of drug resistance in cancer patients is composed of (a) loss-of-function (LoF), (b) gain-of-function (GoF) and (c) point mutation-mediated perturbations of genes, with often no single mechanism being predominant. Therefore, capturing the full breadth of resistance genes for any drug would require multiple genetic screens to be executed in parallel. Methods: We performed 3 genome-wide genetic screens in parallel in BRAF mutant colon cancer cells treated with a BRAF/MEK/EGFR inhibitor combination, to capture all of the resistance mechanisms described above. To screen for LoF events we used a genome-wide CRISPR/Cas9 sgRNA library. For GoF resistance events, a lentiviral-based insertional mutagenesis vector was used to randomly integrate the SFFV enhancer/promoter sequence throughout the genome. Finally, to saturate the genome of each cell line with point mutations we used N-Ethyl-N-nitrosourea (ENU) to randomly mutagenize every base in the genome. Each genetic screen was analysed separately to identify the relevant genes and pathways that confer drug resistance before aggregating the outputs of all three screens for a more comprehensive view of the drug resistance landscape. Results: The most recurrent and strongest hit from the CRISPR knockout screen was the inhibitor of Src family kinases, CSK. A Gaussian Kernal Convolution analysis for recurrent integrations detected in resistant clones following the insertional mutagenesis screen identified five genes as likely resistance candidates - BRAF, SOS1, MET, FRS2 and KRAS. Finally, Illumina exome sequencing of resistant clones following ENU mutagenesis revealed statistical enrichment for non-synonymous point mutations in three genes in the MAPK pathway, namely MAP2K1, NRAS and KRAS. Of note, loss of CSK was also shown to confer resistance to targeted therapies in other cancer types. Conclusion: Genome-wide genetic screens identified genes in the MAPK pathway likely to cause resistance clinically, and many of which are amenable to therapeutic targeting. Of note, the resistance as a result of loss of CSK instead activates Src signalling. It can be overcome through the addition of a Src inhibitor, and may be relevant across a range of cancer types as a resistance mechanism. Citation Format: Jonathan Brammeld, Marco Ranzani, Elizabeth A. Coker, Stacey Price, Theodoros I. Roumeliotis, Barbara Lupo, Mi Petljak, Steven P. Williams, Francesco Iorio, Francesco Sassi, Nanne Aben, Kosuke Yusa, Livio Trusolino, Lodewyk Wessels, David J. Adams, Mathew Garnett, Bissan Al-Lazikani, Jyoti S. Choudhary, Andrea Bertotti, Ultan McDermott. Genome-wide genetic screens define the drug resistance landscape of BRAF mutant colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1821.
<p>Figure S1. A subset MPM cell lines respond to FGFR inhibition. A) AZD4547 at a fixed dose of 500nM and B) BGJ-398 at a fixed dose of 300nM. Figure S2. A subset of pleural fluid derived early passage primary cultures (EPL) respond to FGFR inhibition. Figure S3. BAP1 mutation status does not correlate fully with protein expression. Figure S4. BAP1 null cell lines show increased activity of multiple receptor tyrosine kinases. Figure S5. FGF9 activates FGFR3 and modulates growth and phenotype. Figure S6. Gene expression studies comparing H226 BAP1 C91 vs BAP1 wt construct cell line. Figure S7. xenograft Immunohistochemistry for ki67, Caspase 3 under various experimental conditions. Figure S8. Anchor based combination drug screen in MPM using Pi3 kinase inhibitor as anchor drug.</p>
Abstract 10-20% of lung adenocarcinoma patients harbour activating mutations in EGFR. Although treatment with the EGFR kinase inhibitor osimertinib has improved overall survival in such patients, almost all patients ultimately develop drug resistance. In many cases the molecular resistance mechanisms remain unknown. A systematic identification of the involved genes and pathways is critical to overcome osimertinib resistance. To define the resistance landscape of EGFR kinase inhibition we performed genome-wide gain and loss of function CRISPR screens in EGFR mutant lung cancer cell lines treated with osimertinib. Resistance hits were enriched for genes in previously identified resistance pathways including PI3K (PTEN, TSC2), MAPK (NF1, MET), cell death (BCL2L11, BAX), the mediator complex (MED24, MED19) and ubiquitination (KCTD5, LZTR1). A secondary screen of 63 resistance genes that combined high content microscopy with CRISPR gene knockouts demonstrated that 21% (13/63) of genes were associated with increased nuclear localisation of YAP1/WWTR1, indicating transcriptional activation of the Hippo pathway. According to our screening data, many resistance hits mapped onto the Hippo signaling axis - upstream regulators (NF2, AMOTL2), core signaling genes (LATS1, LATS2), main effectors (WWTR1, YAP1), transcriptional co-effectors (TEAD3, FOSL1, VGLL4) and the SWI/SNF complex (ARID2, SMARCA4, SMARCB1, PBRM1). Hippo signaling is mediated through YAP1 and WWTR1 which bind to TEAD transcription factors and activate transcriptional programs affecting cell proliferation and apoptosis. We confirmed using CRISPR that knockout (NF2) or overexpression (YAP1, WWTR1) of key Hippo genes in the EGFR mutant lung cancer cell lines PC-9, HCC827 and HCC4006 resulted in up to 60-fold increased resistance to osimertinib and elevated activity of a TEAD reporter system, indicating activation of Hippo transcriptional programs. To maintain osimertinib resistance, expression of both YAP1 and WWTR1 was necessary, suggesting non-redundant roles for both Hippo main effectors in mediating osimertinib resistance. The combination of osimertinib and a TEAD inhibitor (MYF-01-37) reversed the resistance phenotype in NF2 KO cell line models in long-term proliferation assays and also substantially repressed the emergence of drug-tolerant persister cells in PC-9, HCC827 and HCC4006 cell lines following osimertinib treatment. These cells exhibited an enhanced apoptotic response when treated with combination of osimertinib and TEAD inhibitor. Consequently, we propose Hippo signaling as an important target mechanism for the prevention of resistance to osimertinib. Citation Format: Matthias Pfeifer, Jonathan S. Brammeld, Stacey Price, Matthew Martin, Hannah Thorpe, Aurelie Bornot, Erica Banks, Nin Guan, Shanade Dunn, Maria Luisa Guerriero, Daniel O'Neill, James Pilling, Davide Gianni, James Brownell, Paul Smith, Ultan McDermott. Gain and loss of function genome-wide CRISPR screens identify Hippo signaling as an important driver of resistance in EGFR mutant lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1100.
<p>Figure S1. A subset MPM cell lines respond to FGFR inhibition. A) AZD4547 at a fixed dose of 500nM and B) BGJ-398 at a fixed dose of 300nM. Figure S2. A subset of pleural fluid derived early passage primary cultures (EPL) respond to FGFR inhibition. Figure S3. BAP1 mutation status does not correlate fully with protein expression. Figure S4. BAP1 null cell lines show increased activity of multiple receptor tyrosine kinases. Figure S5. FGF9 activates FGFR3 and modulates growth and phenotype. Figure S6. Gene expression studies comparing H226 BAP1 C91 vs BAP1 wt construct cell line. Figure S7. xenograft Immunohistochemistry for ki67, Caspase 3 under various experimental conditions. Figure S8. Anchor based combination drug screen in MPM using Pi3 kinase inhibitor as anchor drug.</p>
Cancer genomics has revealed complex landscapes of molecular aberrations in human tumours. These tend to converge into a limited set of cellular processes, suggesting that the knowledge of signaling pathways can be used to functionally characterize large sets of cancer somatic alterations. A rigorous identification of significantly altered biological pathways is challenged by the high heterogeneity among samples, their differences in mutation rates, and the combinatorial properties arising from cancer evolution.
We present SLAPenrich, a statistical approach implemented in an open source R package to search for pathways that are genomically altered in a recurrent manner across the mutations observed in heterogeneous populations of samples. Differently from other tools, our approach assumes the functionality of a given pathway to be potentially disregulated if at least one of its genes is somatically altered. SLAPenrich performs enrichment analysis of pathways at the population level, accounting for differences in mutation rates between samples, exonic lengths of genes in a given pathway, and possible trends of mutational mutual exclusivity among genes of the same pathway. Analyzing a set of somatic mutations from a cohort of lung adenocarcinoma (LUAD) patients we show that SLAPenrich is able to detect well-known LUAD altered pathways, novel pathways recently proposed as therapeutic targets, and to detect established associations with clinicopathological features. Most importantly, we used SLAPenrich to explore, for the first time, the landscape of pathways contributing to the acquisition of the canonical cancer hallmarks, and we show how this analysis can point at novel cancer driver genes and networks.
SLAPenrich is a tool to analyze any type of biological dataset amenable to be modeled as a binary matrix equipped with routines to report and visualize results. Our versatile formalism allows differential enrichment analysis of sub-populations, and enabled us to assemble a data-driven landscape of cancer hallmark acquisitions across different cancer types.
ABSTRACT Cancer hallmarks are evolutionary traits required by a tumour to develop. While extensively characterised, the way these traits are achieved through the accumulation of somatic mutations in key biological pathways is not fully understood. To shed light on this subject, we characterised the landscape of pathway alterations associated with somatic mutations observed in 4,415 patients across ten cancer types, using 374 orthogonal pathway gene-sets mapped onto canonical cancer hallmarks. Towards this end, we developed SLAPenrich: a computational method based on population-level statistics, freely available as an open source R package. Assembling the identified pathway alterations into sets of hallmark signatures allowed us to connect somatic mutations to clinically interpretable cancer mechanisms. Further, we explored the heterogeneity of these signatures, in terms of ratio of altered pathways associated with each individual hallmark, assuming that this is reflective of the extent of selective advantage provided to the cancer type under consideration. Our analysis revealed the predominance of certain hallmarks in specific cancer types, thus suggesting different evolutionary trajectories across cancer lineages. Finally, although many pathway alteration enrichments are guided by somatic mutations in frequently altered high-confidence cancer genes, excluding these driver mutations preserves the hallmark heterogeneity signatures, thus the detected hallmarks’ predominance across cancer types. As a consequence, we propose the hallmark signatures as a ground truth to characterise tails of infrequent genomic alterations and identify potential novel cancer driver genes and networks.
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