Resistance to chemotherapy and molecularly targeted therapies is a major problem facing current cancer research. The mechanisms of resistance to 'classical' cytotoxic chemotherapeutics and to therapies that are designed to be selective for specific molecular targets share many features, such as alterations in the drug target, activation of prosurvival pathways and ineffective induction of cell death. With the increasing arsenal of anticancer agents, improving preclinical models and the advent of powerful high-throughput screening techniques, there are now unprecedented opportunities to understand and overcome drug resistance through the clinical assessment of rational therapeutic drug combinations and the use of predictive biomarkers to enable patient stratification.

Cancer drug resistance: an evolving paradigm

The role of epithelial-to-mesenchymal transition (EMT) in metastasis is a longstanding source of debate, largely owing to an inability to monitor transient and reversible EMT phenotypes in vivo. Here we establish an EMT lineage-tracing system to monitor this process in mice, using a mesenchymal-specific Cre-mediated fluorescent marker switch system in spontaneous breast-to-lung metastasis models. We show that within a predominantly epithelial primary tumour, a small proportion of tumour cells undergo EMT. Notably, lung metastases mainly consist of non-EMT tumour cells that maintain their epithelial phenotype. Inhibiting EMT by overexpressing the microRNA miR-200 does not affect lung metastasis development. However, EMT cells significantly contribute to recurrent lung metastasis formation after chemotherapy. These cells survived cyclophosphamide treatment owing to reduced proliferation, apoptotic tolerance and increased expression of chemoresistance-related genes. Overexpression of miR-200 abrogated this resistance. This study suggests the potential of an EMT-targeting strategy, in conjunction with conventional chemotherapies, for breast cancer treatment.

/pdf/epithelial-to-mesenchymal-transition-is-not-required-for-3de8dxggx2.pdf

Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance

PIWI-interacting RNAs (piRNAs) are a distinct class of small non-coding RNAs that form the piRNA-induced silencing complex (piRISC) in the germ line of many animal species. The piRISC protects the integrity of the genome from invasion by 'genomic parasites' — transposable elements — by silencing them. Owing to their limited expression in gonads and their sequence diversity, piRNAs have been the most mysterious class of small non-coding RNAs regulating RNA silencing. Now, much progress is being made into our understanding of their biogenesis and molecular functions, including the specific subcellular compartmentalization of the piRNA pathway in granular cytoplasmic bodies.

PIWI-interacting small RNAs: the vanguard of genome defence.

Small-RNA-guided gene regulation has emerged as one of the fundamental principles in cell function, and the major protein players in this process are members of the Argonaute protein family. Argonaute proteins are highly specialized binding modules that accommodate the small RNA component - such as microRNAs (miRNAs), short interfering RNAs (siRNAs) or PIWI-associated RNAs (piRNAs) - and coordinate downstream gene-silencing events by interacting with other protein factors. Recent work has made progress in our understanding of classical Argonaute-mediated gene-silencing principles, such as the effects on mRNA translation and decay, but has also implicated Argonaute proteins in several other cellular processes, such as transcriptional regulation and splicing.

Argonaute proteins: functional insights and emerging roles

All patients with metastatic lung, colorectal, pancreatic or head and neck cancers who initially benefit from epidermal growth factor receptor (EGFR)-targeted therapies eventually develop resistance. An increasing understanding of the number and complexity of resistance mechanisms highlights the Herculean challenge of killing tumors that are resistant to EGFR inhibitors. Our growing knowledge of resistance pathways provides an opportunity to develop new mechanism-based inhibitors and combination therapies to prevent or overcome therapeutic resistance in tumors. We present a comprehensive review of resistance pathways to EGFR-targeted therapies in lung, colorectal and head and neck cancers and discuss therapeutic strategies that are designed to circumvent resistance.

/pdf/the-quest-to-overcome-resistance-to-egfr-targeted-therapies-2d5tjuoeck.pdf

The quest to overcome resistance to EGFR-targeted therapies in cancer

The epidermal growth-factor receptor (EGFR) tyrosine kinase inhibitor erlotinib has been proven to be highly effective in the treatment of nonsmall cell lung cancer (NSCLC) harboring oncogenic EGFR mutations. The majority of patients, however, will eventually develop resistance and succumb to the disease. Recent studies have identified secondary mutations in the EGFR (EGFR T790M) and amplification of the N-Methyl-N′-nitro-N-nitroso-guanidine (MNNG) HOS transforming gene (MET) oncogene as two principal mechanisms of acquired resistance. Although they can account for approximately 50% of acquired resistance cases together, in the remaining 50%, the mechanism remains unknown. In NSCLC-derived cell lines and early-stage tumors before erlotinib treatment, we have uncovered the existence of a subpopulation of cells that are intrinsically resistant to erlotinib and display features suggestive of epithelial-to-mesenchymal transition (EMT). We showed that activation of TGF-β–mediated signaling was sufficient to induce these phenotypes. In particular, we determined that an increased TGF-β–dependent IL-6 secretion unleashed previously addicted lung tumor cells from their EGFR dependency. Because IL-6 and TGF-β are prominently produced during inflammatory response, we used a mouse model system to determine whether inflammation might impair erlotinib sensitivity. Indeed, induction of inflammation not only stimulated IL-6 secretion but was sufficient to decrease the tumor response to erlotinib. Our data, thus, argue that both tumor cell-autonomous mechanisms and/or activation of the tumor microenvironment could contribute to primary and acquired erlotinib resistance, and as such, treatments based on EGFR inhibition may not be sufficient for the effective treatment of lung-cancer patients harboring mutant EGFR.

https://www.pnas.org/content/pnas/107/35/15535.full.pdf

TGF-β IL-6 axis mediates selective and adaptive mechanisms of resistance to molecular targeted therapy in lung cancer

Combining RNAi in cultured cells and analysis of mutant animals, we probed the roles of known Piwi-interacting RNA (piRNA) pathway components in the initiation and effector phases of transposon silencing. Squash associated physically with Piwi, and reductions in its expression led to modest transposon derepression without effects on piRNAs, consistent with an effector role. Alterations in Zucchini or Armitage reduced both Piwi protein and piRNAs, indicating functions in the formation of a stable Piwi RISC (RNA-induced silencing complex). Notably, loss of Zucchini or mutations within its catalytic domain led to accumulation of unprocessed precursor transcripts from flamenco, consistent with a role for this putative nuclease in piRNA biogenesis.

http://genesdev.cshlp.org/content/24/22/2499.full.pdf

Probing the initiation and effector phases of the somatic piRNA pathway in Drosophila

Cancer treatment with a combination of an Epidermal Growth Factor Receptor tyrosine kinase inhibitor and an Interleukin-6 inhibitor.

Methods for treating epidermal growth factor receptor tyrosine kinase inhibitor-resistant cancers

Methods of assessing therapeutic benefits of patients having cancers resistant to epidermal growth factor receptor kinase inhibitors


 CRISPR-based functional genomics screens are a powerful tool for identifying synthetically lethal cancer drug targets. Current strategies for analyzing pooled CRISPR screens usually rely on signals from single guide RNAs (sgRNA) with differential relative abundance between two experimental conditions. However, conventional approaches are susceptible to false positives and false negatives driven by outlier cell clones, since the sgRNA abundance does not account for the heterogeneous phenotypes resulting from different editing outcomes of the same sgRNA. To overcome this, we added DNA barcodes to each sgRNA to create unique molecular identifiers (UMIs) for CRISPR libraries and developed a companion analytical platform that enables robust, industry-scale CRISPR screens. Here, we present UMIBB, a novel nonparametric Bayesian approach for analyzing UMI-CRISPR data. The number of UMIs with normalized count depletion or enrichment compared to the control experimental condition for each sgRNA is modeled by a beta-binomial distribution. The gene level statistics are derived by combining z-scores of the sgRNAs level posterior probabilities weighted by the number of UMIs in each sgRNA. This approach minimizes the impact of outlier cell clones on statistics and prioritizes genes with consistent count differentials across multiple UMIs in each gene. To assess the power of UMIBB, we benchmarked it on a low coverage (200X) genome-scale negative-selection screen, comparing with results from a high coverage (1000X) screen. These screens were conducted on KRAS mutant cancer celllines (A549) treated with trametinib or vehicle control. Despite the high noise level usually observed in lower coverage screens, our method was able to uncover most of the validated sensitizer genes for trametinib and achieved the highest sensitivity compared to conventional methods. Furthermore, we applied UMIBB on a genome-scale positive-selection screen and successfully identified novel genes (RAD18 and UBE2K) as key mediators of USP1 dependency in BRCA1 mutant cell lines. Our studies demonstrate that UMIBB is highly robust against false positives due to clonal heterogeneity and is more likely to identify true genetic interactions.
 Citation Format: Ashley Choi, Samuel Meier, Silvia Fenoglio, Tianshu Feng, Justin Engel, Binzhang Shen, Shangtao Liu, Teng Teng, Tenzing Khendu, Alan Huang, Jannik Andersen, Xuewen Pan, Yi Yu. UMIBB: A novel nonparametric Bayesian method improves robustness and sensitivity of analysis in pooled CRISPR-Cas9 screens leveraging unique molecular identifiers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1224.

Abstract 1224: UMIBB: A novel nonparametric Bayesian method improves robustness and sensitivity of analysis in pooled CRISPR-Cas9 screens leveraging unique molecular identifiers

Silvia Fenoglio

Papers

TGF-β IL-6 axis mediates selective and adaptive mechanisms of resistance to molecular targeted therapy in lung cancer

Probing the initiation and effector phases of the somatic piRNA pathway in Drosophila

Methods for treating epidermal growth factor receptor tyrosine kinase inhibitor-resistant cancers

Methods of assessing therapeutic benefits of patients having cancers resistant to epidermal growth factor receptor kinase inhibitors

Abstract 1224: UMIBB: A novel nonparametric Bayesian method improves robustness and sensitivity of analysis in pooled CRISPR-Cas9 screens leveraging unique molecular identifiers