Generating a Murine PTEN Null Cell Line to Discover the Key Role of p110ß-PAK1 in Castration-Resistant Prostate Cancer Invasion.

Although androgen deprivation treatment often effectively decreases prostate cancer, incurable metastatic castration-resistant prostate cancer (CRPC) eventually occurs. It is important to understand how CRPC metastasis progresses, which is not clearly defined. The loss of PTEN, a phosphatase to dephosphorylate phosphatidylinositol 3,4,5-trisphosphate in the PI3K pathway, occurs in up to 70% to 80% of CRPC. We generated a mouse androgen-independent prostate cancer cell line (PKO) from PTEN null and Hi-Myc transgenic mice in C57BL/6 background. We confirmed that this PKO cell line has an activated PI3K pathway and can metastasize into the femur and tibia of immunodeficient nude and immunocompetent C57BL/6 mice. In vitro, we found that androgen deprivation significantly enhanced PKO cell migration/invasion via the p110ß isoform-depended PAK1-MAPK activation. Inhibition of the p110ß-PAK1 axis significantly decreased prostate cancer cell migration/invasion. Of note, our analysis using clinical samples showed that PAK1 is more activated in CRPC than in advanced prostate cancer; high PAK1/phosphorylated-PAK1 levels are associated with decreased survival rates in patients with CRPC. All the information suggests that this cell line reflects the characteristics of CRPC cells and can be applied to dissect the mechanism of CRPC initiation and progression. This study also shows that PAK1 is a potential target for CRPC treatment. IMPLICATIONS: This study uses a newly generated PTEN null prostate cancer cell line to define a critical functional role of p110ß-PAK1 in CRPC migration/invasion. This study also shows that the p110ß-PAK1 axis can potentially be a therapeutic target in CRPC metastasis.

Expressed Barcoding Enables High-Resolution Tracking of the Evolution of Drug Tolerance.

For a majority of patients with non-small cell lung cancer with EGFR mutations, treatment with EGFR inhibitors (EGFRi) induces a clinical response. Despite this initial reduction in tumor size, residual disease persists that leads to disease relapse. Elucidating the preexisting biological differences between sensitive cells and surviving drug-tolerant persister cells and deciphering how drug-tolerant cells evolve in response to treatment could help identify strategies to improve the efficacy of EGFRi. In this study, we tracked the origins and clonal evolution of drug-tolerant cells at a high resolution by using an expressed barcoding system coupled with single-cell RNA sequencing. This platform enabled longitudinal profiling of gene expression and drug sensitivity in response to EGFRi across a large number of clones. Drug-tolerant cells had higher expression of key survival pathways such as YAP and EMT at baseline and could also differentially adapt their gene expression following EGFRi treatment compared with sensitive cells. In addition, drug combinations targeting common downstream components (MAPK) or orthogonal factors (chemotherapy) showed greater efficacy than EGFRi alone, which is attributable to broader targeting of the heterogeneous EGFRi-tolerance mechanisms present in tumors. Overall, this approach facilitates thorough examination of clonal evolution in response to therapy that could inform the development of improved diagnostic approaches and treatment strategies for targeting drug-tolerant cells. SIGNIFICANCE: The evolution and heterogeneity of EGFR inhibitor tolerance are identified in a large number of clones at enhanced cellular and temporal resolution using an expressed barcode technology coupled with single-cell RNA sequencing.

Contribution and clinical relevance of germline variation to the cancer transcriptome.

BACKGROUND: Somatic alterations in the cancer genome, some of which are associated with changes in gene expression, have been characterized in multiple studies across diverse cancer types. However, less is known about germline variants that influence tumor biology by shaping the cancer transcriptome. METHODS: We performed expression quantitative trait loci (eQTL) analyses using multi-dimensional data from The Cancer Genome Atlas to explore the role of germline variation in mediating the cancer transcriptome. After accounting for associations between somatic alterations and gene expression, we determined the contribution of inherited variants to the cancer transcriptome relative to that of somatic variants. Finally, we performed an interaction analysis using estimates of tumor cellularity to identify cell type-restricted eQTLs. RESULTS: The proportion of genes with at least one eQTL varied between cancer types, ranging between 0.8% in melanoma to 28.5% in thyroid cancer and was correlated more strongly with intratumor heterogeneity than with somatic alteration rates. Although contributions to variance in gene expression was low for most genes, some eQTLs accounted for more than 30% of expression of proximal genes. We identified cell type-restricted eQTLs in genes known to be cancer drivers including LPP and EZH2 that were associated with disease-specific mortality in TCGA but not associated with disease risk in published GWAS. Together, our results highlight the need to consider germline variation in interpreting cancer biology beyond risk prediction.

Blocking PI3K p110ß Attenuates Development of PTEN-Deficient Castration-Resistant Prostate Cancer.

A common outcome of androgen deprivation in prostate cancer therapy is disease relapse and progression to castration-resistant prostate cancer (CRPC) via multiple mechanisms. To gain insight into the recent clinical findings that highlighted genomic alterations leading to hyperactivation of PI3K, we examined the roles of the commonly expressed p110 catalytic isoforms of PI3K in a murine model of Pten-null invasive CRPC. While blocking p110α had negligible effects in the development of Pten-null invasive CRPC, either genetic or pharmacologic perturbation of p110ß dramatically slowed CRPC initiation and progression. Once fully established, CRPC tumors became partially resistant to p110ß inhibition, indicating the acquisition of new dependencies. Driven by our genomic analyses highlighting potential roles for the p110ß/RAC/PAK1 and ß-catenin pathways in CRPC, we found that combining p110ß with RAC/PAK1 or tankyrase inhibitors significantly reduced the growth of murine and human CRPC organoids in vitro and in vivo. Because p110ß activity is dispensable for most physiologic processes, our studies support novel therapeutic strategies both for preventing disease progression into CRPC and for treating CRPC. IMPLICATIONS: This work establishes p110ß as a promising target for preventing the progression of primary PTEN-deficient prostate tumors to CRPC, and for treating established CRPC in combination with RAC/PAK1 or tankyrase inhibitors.

A Proof of Concept for Biomarker-Guided Targeted Therapy against Ovarian Cancer Based on Patient-Derived Tumor Xenografts.

Advanced ovarian cancers are a leading cause of cancer-related death in women and are currently treated with surgery and chemotherapy. This standard of care is often temporarily successful but exhibits a high rate of relapse, after which, treatment options are few. Here we investigate whether biomarker-guided use of multiple targeted therapies, including small molecules and antibody-drug conjugates, is a viable alternative. A panel of patient-derived ovarian cancer xenografts (PDX), similar in genetics and chemotherapy responsiveness to human tumors, was exposed to 21 monotherapies and combination therapies. Three monotherapies and one combination were found to be active in different subsets of PDX. Analysis of gene expression data identified biomarkers associated with responsiveness to each of the three targeted therapies, none of which directly inhibits an oncogenic driver. While no single treatment had as high a response rate as chemotherapy, nearly 90% of PDXs were eligible for and responded to at least one biomarker-guided treatment, including tumors resistant to standard chemotherapy. The distribution of biomarker positivity in The Cancer Genome Atlas data suggests the potential for a similar precision approach in human patients. SIGNIFICANCE: This study exploits a panel of patient-derived xenografts to demonstrate that most ovarian tumors can be matched to effective biomarker-guided treatments.

Patient-derived glioblastoma cultures as a tool for small-molecule drug discovery.

There is a compelling need for new therapeutic strategies for glioblastoma multiforme (GBM). Preclinical target and therapeutic discovery for GBMs is primarily conducted using cell lines grown in serum-containing media, such as U-87 MG, which do not reflect the gene expression profiles of tumors found in GBM patients. To address this lack of representative models, we sought to develop a panel of patient-derived GBM models and characterize their genomic features, using RNA sequencing (RNA-seq) and growth characteristics, both when grown as neurospheres in culture, and grown orthotopically as xenografts in mice. When we compared these with commonly used GBM cell lines in the Cancer Cell Line Encyclopedia (CCLE), we found these patient-derived models to have greater diversity in gene expression and to better correspond to GBMs directly sequenced from patient tumor samples. We also evaluated the potential of these models for targeted therapy, by using the genomic characterization to identify small molecules that inhibit the growth of distinct subsets of GBMs, paving the way for precision medicines for GBM.

Targeting FGFR overcomes EMT-mediated resistance in EGFR mutant non-small cell lung cancer.

Evolved resistance to tyrosine kinase inhibitor (TKI)-targeted therapies remains a major clinical challenge. In epidermal growth factor receptor (EGFR) mutant non-small-cell lung cancer (NSCLC), failure of EGFR TKIs can result from both genetic and epigenetic mechanisms of acquired drug resistance. Widespread reports of histologic and gene expression changes consistent with an epithelial-to-mesenchymal transition (EMT) have been associated with initially surviving drug-tolerant persister cells, which can seed bona fide genetic mechanisms of resistance to EGFR TKIs. While therapeutic approaches targeting fully resistant cells, such as those harboring an EGFRT790M mutation, have been developed, a clinical strategy for preventing the emergence of persister cells remains elusive. Using mesenchymal cell lines derived from biopsies of patients who progressed on EGFR TKI as surrogates for persister populations, we performed whole-genome CRISPR screening and identified fibroblast growth factor receptor 1 (FGFR1) as the top target promoting survival of mesenchymal EGFR mutant cancers. Although numerous previous reports of FGFR signaling contributing to EGFR TKI resistance in vitro exist, the data have not yet been sufficiently compelling to instigate a clinical trial testing this hypothesis, nor has the role of FGFR in promoting the survival of persister cells been elucidated. In this study, we find that combining EGFR and FGFR inhibitors inhibited the survival and expansion of EGFR mutant drug-tolerant cells over long time periods, preventing the development of fully resistant cancers in multiple vitro models and in vivo. These results suggest that dual EGFR and FGFR blockade may be a promising clinical strategy for both preventing and overcoming EMT-associated acquired drug resistance and provide motivation for the clinical study of combined EGFR and FGFR inhibition in EGFR-mutated NSCLCs.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Tumor-derived IFN triggers chronic pathway agonism and sensitivity to ADAR loss.

Interferons (IFNs) are cytokines that play a critical role in limiting infectious and malignant diseases 1-4 . Emerging data suggest that the strength and duration of IFN signaling can differentially impact cancer therapies, including immune checkpoint blockade 5-7 . Here, we characterize the output of IFN signaling, specifically IFN-stimulated gene (ISG) signatures, in primary tumors from The Cancer Genome Atlas. While immune infiltration correlates with the ISG signature in some primary tumors, the existence of ISG signature-positive tumors without evident infiltration of IFN-producing immune cells suggests that cancer cells per se can be a source of IFN production. Consistent with this hypothesis, analysis of patient-derived tumor xenografts propagated in immune-deficient mice shows evidence of ISG-positive tumors that correlates with expression of human type I and III IFNs derived from the cancer cells. Mechanistic studies using cell line models from the Cancer Cell Line Encyclopedia that harbor ISG signatures demonstrate that this is a by-product of a STING-dependent pathway resulting in chronic tumor-derived IFN production. This imposes a transcriptional state on the tumor, poising it to respond to the aberrant accumulation of double-stranded RNA (dsRNA) due to increased sensor levels (MDA5, RIG-I and PKR). By interrogating our functional short-hairpin RNA screen dataset across 398 cancer cell lines, we show that this ISG transcriptional state creates a novel genetic vulnerability. ISG signature-positive cancer cells are sensitive to the loss of ADAR, a dsRNA-editing enzyme that is also an ISG. A genome-wide CRISPR genetic suppressor screen reveals that the entire type I IFN pathway and the dsRNA-activated kinase, PKR, are required for the lethality induced by ADAR depletion. Therefore, tumor-derived IFN resulting in chronic signaling creates a cellular state primed to respond to dsRNA accumulation, rendering ISG-positive tumors susceptible to ADAR loss.

Correction of copy number induced false positives in CRISPR screens.

Cell autonomous cancer dependencies are now routinely identified using CRISPR loss-of-function viability screens. However, a bias exists that makes it difficult to assess the true essentiality of genes located in amplicons, since the entire amplified region can exhibit lethal scores. These false-positive hits can either be discarded from further analysis, which in cancer models can represent a significant number of hits, or methods can be developed to rescue the true-positives within amplified regions. We propose two methods to rescue true positive hits in amplified regions by correcting for this copy number artefact. The Local Drop Out (LDO) method uses the relative lethality scores within genomic regions to assess true essentiality and does not require additional orthogonal data (e.g. copy number value). LDO is meant to be used in screens covering a dense region of the genome (e.g. a whole chromosome or the whole genome). The General Additive Model (GAM) method models the screening data as a function of the known copy number values and removes the systematic effect from the measured lethality. GAM does not require the same density as LDO, but does require prior knowledge of the copy number values. Both methods have been developed with single sample experiments in mind so that the correction can be applied even in smaller screens. Here we demonstrate the efficacy of both methods at removing the copy number effect and rescuing hits from some of the amplified regions. We estimate a 70-80% decrease of false positive hits with either method in regions of high copy number compared to no correction.

Antitumor Properties of RAF709, a Highly Selective and Potent Inhibitor of RAF Kinase Dimers, in Tumors Driven by Mutant RAS or BRAF.

Resistance to the RAF inhibitor vemurafenib arises commonly in melanomas driven by the activated BRAF oncogene. Here, we report antitumor properties of RAF709, a novel ATP-competitive kinase inhibitor with high potency and selectivity against RAF kinases. RAF709 exhibited a mode of RAF inhibition distinct from RAF monomer inhibitors such as vemurafenib, showing equal activity against both RAF monomers and dimers. As a result, RAF709 inhibited MAPK signaling activity in tumor models harboring either BRAFV600 alterations or mutant N- and KRAS-driven signaling, with minimal paradoxical activation of wild-type RAF. In cell lines and murine xenograft models, RAF709 demonstrated selective antitumor activity in tumor cells harboring BRAF or RAS mutations compared with cells with wild-type BRAF and RAS genes. RAF709 demonstrated a direct pharmacokinetic/pharmacodynamic relationship in in vivo tumor models harboring KRAS mutation. Furthermore, RAF709 elicited regression of primary human tumor-derived xenograft models with BRAF, NRAS, or KRAS mutations with excellent tolerability. Our results support further development of inhibitors like RAF709, which represents a next-generation RAF inhibitor with unique biochemical and cellular properties that enables antitumor activities in RAS-mutant tumors.Significance: In an effort to develop RAF inhibitors with the appropriate pharmacological properties to treat RAS mutant tumors, RAF709, a compound with potency, selectivity, and in vivo properties, was developed that will allow preclinical therapeutic hypothesis testing, but also provide an excellent probe to further unravel the complexities of RAF kinase signaling. Cancer Res; 78(6); 1537-48. ©2018 AACR.

BRAF-inhibitor Associated MEK Mutations Increase RAF-Dependent and -Independent Enzymatic Activity.

Alterations in MEK1/2 occur in cancers, both in the treatment-naïve state and following targeted therapies, most notably BRAF and MEK inhibitors in BRAF-V600E-mutant melanoma and colorectal cancer. Efforts were undertaken to understand the effects of these mutations, based upon protein structural location, and MEK1/2 activity. Two categories of MEK1/2 alterations were evaluated, those associated with either the allosteric pocket or helix-A. Clinically, MEK1/2 alterations of the allosteric pocket are rare and we demonstrate that they confer resistance to MEK inhibitors, while retaining sensitivity to BRAF inhibition. Most mutations described in patients fall within, or are associated with, helix-A. Mutations in this region reduce sensitivity to both BRAF and MEK inhibition and display elevated phospho-ERK1/2 levels, independent from increases in phospho-MEK1/2. Biochemical experiments with a representative helix-A variant, MEK1-Q56P, reveal both increased catalytic efficiency of the activated enzyme, and phosphorylation-independent activity relative to wild-type MEK1. Consistent with these findings, MEK1/2 alterations in helix A retain sensitivity to downstream antagonism via pharmacologic inhibition of ERK1/2. This work highlights the importance of classifying mutations based on structural and phenotypic consequences, both in terms of pathway signaling output and response to pharmacologic inhibition.Implications: This study suggests that alternate modes of target inhibition, such as ERK inhibition, will be required to effectively treat tumors harboring these MEK1/2-resistant alleles. Mol Cancer Res; 15(10); 1431-44. ©2017 AACR.

CRISPR Screens Provide a Comprehensive Assessment of Cancer Vulnerabilities but Generate False-Positive Hits for Highly Amplified Genomic Regions.

UNLABELLED: CRISPR/Cas9 has emerged as a powerful new tool to systematically probe gene function. We compared the performance of CRISPR to RNAi-based loss-of-function screens for the identification of cancer dependencies across multiple cancer cell lines. CRISPR dropout screens consistently identified more lethal genes than RNAi, implying that the identification of many cellular dependencies may require full gene inactivation. However, in two aneuploid cancer models, we found that all genes within highly amplified regions, including nonexpressed genes, scored as lethal by CRISPR, revealing an unanticipated class of false-positive hits. In addition, using a CRISPR tiling screen, we found that sgRNAs targeting essential domains generate the strongest lethality phenotypes and thus provide a strategy to rapidly define the protein domains required for cancer dependence. Collectively, these findings not only demonstrate the utility of CRISPR screens in the identification of cancer-essential genes, but also reveal the need to carefully control for false-positive results in chromosomally unstable cancer lines. SIGNIFICANCE: We show in this study that CRISPR-based screens have a significantly lower false-negative rate compared with RNAi-based screens, but have specific liabilities particularly in the interrogation of regions of genome amplification. Therefore, this study provides critical insights for applying CRISPR-based screens toward the systematic identification of new cancer targets. Cancer Discov; 6(8); 900-13. ©2016 AACR.See related commentary by Sheel and Xue, p. 824See related article by Aguirre et al., p. 914This article is highlighted in the In This Issue feature, p. 803.

ERG signaling in prostate cancer is driven through PRMT5-dependent methylation of the Androgen Receptor.

The TMPRSS2:ERG gene fusion is common in androgen receptor (AR) positive prostate cancers, yet its function remains poorly understood. From a screen for functionally relevant ERG interactors, we identify the arginine methyltransferase PRMT5. ERG recruits PRMT5 to AR-target genes, where PRMT5 methylates AR on arginine 761. This attenuates AR recruitment and transcription of genes expressed in differentiated prostate epithelium. The AR-inhibitory function of PRMT5 is restricted to TMPRSS2:ERG-positive prostate cancer cells. Mutation of this methylation site on AR results in a transcriptionally hyperactive AR, suggesting that the proliferative effects of ERG and PRMT5 are mediated through attenuating AR's ability to induce genes normally involved in lineage differentiation. This provides a rationale for targeting PRMT5 in TMPRSS2:ERG positive prostate cancers. Moreover, methylation of AR at arginine 761 highlights a mechanism for how the ERG oncogene may coax AR towards inducing proliferation versus differentiation.

Inhibition of Casein Kinase 1 Alpha Prevents Acquired Drug Resistance to Erlotinib in EGFR-Mutant Non-Small Cell Lung Cancer.

Patients with lung tumors harboring activating mutations in the EGF receptor (EGFR) show good initial treatment responses to the EGFR tyrosine kinase inhibitors (TKI) erlotinib or gefitinib. However, acquired resistance invariably develops. Applying a focused shRNA screening approach to identify genes whose knockdown can prevent and/or overcome acquired resistance to erlotinib in several EGFR-mutant non-small cell lung cancer (NSCLC) cell lines, we identified casein kinase 1 α (CSNK1A1, CK1α). We found that CK1α suppression inhibits the NF-κB prosurvival signaling pathway. Furthermore, downregulation of NF-κB signaling by approaches independent of CK1α knockdown can also attenuate acquired erlotinib resistance, supporting a role for activated NF-κB signaling in conferring acquired drug resistance. Importantly, CK1α suppression prevented erlotinib resistance in an HCC827 xenograft model in vivo. Our findings suggest that patients with EGFR-mutant NSCLC might benefit from a combination of EGFR TKIs and CK1α inhibition to prevent acquired drug resistance and to prolong disease-free survival.

High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

Studying clonal dynamics in response to cancer therapy using high-complexity barcoding.

Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.

Inhibiting Tankyrases sensitizes KRAS-mutant cancer cells to MEK inhibitors via FGFR2 feedback signaling.

Tankyrases (TNKS) play roles in Wnt signaling, telomere homeostasis, and mitosis, offering attractive targets for anticancer treatment. Using unbiased combination screening in a large panel of cancer cell lines, we have identified a strong synergy between TNKS and MEK inhibitors (MEKi) in KRAS-mutant cancer cells. Our study uncovers a novel function of TNKS in the relief of a feedback loop induced by MEK inhibition on FGFR2 signaling pathway. Moreover, dual inhibition of TNKS and MEK leads to more robust apoptosis and antitumor activity both in vitro and in vivo than effects observed by previously reported MEKi combinations. Altogether, our results show how a novel combination of TNKS and MEK inhibitors can be highly effective in targeting KRAS-mutant cancers by suppressing a newly discovered resistance mechanism.