CRISPR Screening Identifies Mechanisms of Resistance to KRASG12C and SHP2 Inhibitor Combinations in Non-Small Cell Lung Cancer.

Although KRASG12C inhibitors show clinical activity in patients with KRAS G12C mutated non-small cell lung cancer (NSCLC) and other solid tumor malignancies, response is limited by multiple mechanisms of resistance. The KRASG12C inhibitor JDQ443 shows enhanced preclinical antitumor activity combined with the SHP2 inhibitor TNO155, and the combination is currently under clinical evaluation. To identify rational combination strategies that could help overcome or prevent some types of resistance, we evaluated the duration of tumor responses to JDQ443 ± TNO155, alone or combined with the PI3Kα inhibitor alpelisib and/or the cyclin-dependent kinase 4/6 inhibitor ribociclib, in xenograft models derived from a KRASG12C-mutant NSCLC line and investigated the genetic mechanisms associated with loss of response to combined KRASG12C/SHP2 inhibition. Tumor regression by single-agent JDQ443 at clinically relevant doses lasted on average 2 weeks and was increasingly extended by the double, triple, or quadruple combinations. Growth resumption was accompanied by progressively increased KRAS G12C amplification. Functional genome-wide CRISPR screening in KRASG12C-dependent NSCLC lines with distinct mutational profiles to identify adaptive mechanisms of resistance revealed sensitizing and rescuing genetic interactions with KRASG12C/SHP2 coinhibition; FGFR1 loss was the strongest sensitizer, and PTEN loss the strongest rescuer. Consistently, the antiproliferative activity of KRASG12C/SHP2 inhibition was strongly enhanced by PI3K inhibitors. Overall, KRAS G12C amplification and alterations of the MAPK/PI3K pathway were predominant mechanisms of resistance to combined KRASG12C/SHP2 inhibitors in preclinical settings. The biological nodes identified by CRISPR screening might provide additional starting points for effective combination treatments. SIGNIFICANCE: Identification of resistance mechanisms to KRASG12C/SHP2 coinhibition highlights the need for additional combination therapies for lung cancer beyond on-pathway combinations and offers the basis for development of more effective combination approaches. See related commentary by Johnson and Haigis, p. 4005.

Prognostic value of blood biomarkers in steroid-refractory or steroid-dependent acute graft-versus-host disease: a REACH2 analysis.

Systemic steroids are the standard first-line treatment for acute graft-versus-host disease (aGVHD), but ∼50% of patients become steroid-refractory or dependent (SR/D). Ruxolitinib is the only Food and Drug Administration- and European Medicines Agency-approved therapy for patients with SR/D aGVHD. In the phase 3 REACH2 trial (NCT02913261), ruxolitinib demonstrated superior efficacy in SR/D aGVHD, with a significantly higher overall response rate (ORR) on day 28, durable ORR on day 56, and longer median overall survival compared with the best available therapy (BAT). Identifying biomarkers and clinical characteristics associated with increased probability of response can guide treatment decisions. In this exploratory analysis of the REACH2 study (first biomarker study), we developed baseline (pretreatment) and day 14 models to identify patient characteristics and biomarkers (12 aGVHD-associated cytokines/chemokines, 6 immune cell types, and 3 inflammatory proteins) before and during treatment, which affected the probability of response at day 28. Treatment with ruxolitinib, conditioning, skin involvement, and age were strongly associated with an increased likelihood of response in the ≥1 model. Lower levels of most aGVHD and immune cell markers at baseline were associated with an increased probability of response. In the day 14 model, levels of aGVHD markers at day 14, rather than changes from baseline, affected the probability of response. For both models, the bias-corrected area under the receiver operating characteristic values (baseline, 0.73; day 14, 0.80) indicated a high level of correspondence between the fitted and actual outcomes. Our results suggest potential prognostic value of selected biomarkers and patient characteristics.

A reversible SRC-relayed COX2 inflammatory program drives resistance to BRAF and EGFR inhibition in BRAFV600E colorectal tumors.

BRAFV600E mutation confers a poor prognosis in metastatic colorectal cancer (CRC) despite combinatorial targeted therapies based on the latest understanding of signaling circuitry. To identify parallel resistance mechanisms induced by BRAF-MEK-EGFR co-targeting, we used a high-throughput kinase activity mapping platform. Here we show that SRC kinases are systematically activated in BRAFV600E CRC following targeted inhibition of BRAF ± EGFR and that coordinated targeting of SRC with BRAF ± EGFR increases treatment efficacy in vitro and in vivo. SRC drives resistance to BRAF ± EGFR targeted therapy independently of ERK signaling by inducing transcriptional reprogramming through ß-catenin (CTNNB1). The EGFR-independent compensatory activation of SRC kinases is mediated by an autocrine prostaglandin E2 loop that can be blocked with cyclooxygenase-2 (COX2) inhibitors. Co-targeting of COX2 with BRAF + EGFR promotes durable suppression of tumor growth in patient-derived tumor xenograft models. COX2 inhibition represents a drug-repurposing strategy to overcome therapeutic resistance in BRAFV600E CRC.

Preclinical studies on the use of a P-selectin-blocking monoclonal antibody to halt progression of myelofibrosis in the Gata1low mouse model.

The bone marrow (BM) and spleen from patients with myelofibrosis (MF), as well as those from the Gata1low mouse model of the disease contain increased number of abnormal megakaryocytes. These cells express high levels of the adhesion receptor P-selectin on their surface, which triggers a pathologic neutrophil emperipolesis, leading to increased bioavailability of transforming growth factor-ß (TGF-ß) in the microenvironment and disease progression. With age, Gata1low mice develop a phenotype similar to that of patients with MF, which is the most severe of the Philadelphia-negative myeloproliferative neoplasms. We previously demonstrated that Gata1low mice lacking the P-selectin gene do not develop MF. In the current study, we tested the hypothesis that pharmacologic inhibition of P-selectin may normalize the phenotype of Gata1low mice that have already developed MF. To test this hypothesis, we have investigated the phenotype expressed by aged Gata1low mice treated with the antimouse monoclonal antibody RB40.34, alone and also in combination with ruxolitinib. The results indicated that RB40.34 in combination with ruxolitinib normalizes the phenotype of Gata1low mice with limited toxicity by reducing fibrosis and the content of TGF-ß and CXCL1 (two drivers of fibrosis in this model) in the BM and spleen and by restoring hematopoiesis in the BM and the architecture of the spleen. In conclusion, we provide preclinical evidence that treatment with an antibody against P-selectin in combination with ruxolitinib may be more effective than ruxolitinib alone to treat MF in patients.

Genetic heterogeneity and clonal evolution during metastasis in breast cancer patient-derived tumor xenograft models.

Genetic heterogeneity within a tumor arises by clonal evolution, and patients with highly heterogeneous tumors are more likely to be resistant to therapy and have reduced survival. Clonal evolution also occurs when a subset of cells leave the primary tumor to form metastases, which leads to reduced genetic heterogeneity at the metastatic site. Although this process has been observed in human cancer, experimental models which recapitulate this process are lacking. Patient-derived tumor xenografts (PDX) have been shown to recapitulate the patient's original tumor's intra-tumor genetic heterogeneity, as well as its genomics and response to treatment, but whether they can be used to model clonal evolution in the metastatic process is currently unknown. Here, we address this question by following genetic changes in two breast cancer PDX models during metastasis. First, we discovered that mouse stroma can be a confounding factor in assessing intra-tumor heterogeneity by whole exome sequencing, thus we developed a new bioinformatic approach to correct for this. Finally, in a spontaneous, but not experimental (tail-vein) metastasis model we observed a loss of heterogeneity in PDX metastases compared to their orthotopic "primary" tumors, confirming that PDX models can faithfully mimic the clonal evolution process undergone in human patients during metastatic spreading.

Mapping phospho-catalytic dependencies of therapy-resistant tumours reveals actionable vulnerabilities.

Phosphorylation networks intimately regulate mechanisms of response to therapies. Mapping the phospho-catalytic profile of kinases in cells or tissues remains a challenge. Here, we introduce a practical high-throughput system to measure the enzymatic activity of kinases using biological peptide targets as phospho-sensors to reveal kinase dependencies in tumour biopsies and cell lines. A 228-peptide screen was developed to detect the activity of >60 kinases, including ABLs, AKTs, CDKs and MAPKs. Focusing on BRAFV600E tumours, we found mechanisms of intrinsic resistance to BRAFV600E-targeted therapy in colorectal cancer, including targetable parallel activation of PDPK1 and PRKCA. Furthermore, mapping the phospho-catalytic signatures of melanoma specimens identifies RPS6KB1 and PIM1 as emerging druggable vulnerabilities predictive of poor outcome in BRAFV600E patients. The results show that therapeutic resistance can be caused by the concerted upregulation of interdependent pathways. Our kinase activity-mapping system is a versatile strategy that innovates the exploration of actionable kinases for precision medicine.

Deciphering mechanisms of response and resistance in large-scale mouse cancer screens.

Acquired resistance is a major limitation for the successful treatment of cancer patients. Although numerous efficacious cancer therapeutics have been developed in the past decades, resistance arises due to a variety of reasons including tumoral genetic alterations, or modulation of factors in the tumor environment. Understanding the mechanistic reasons for tumor relapse supports the identification of novel combination therapies that could lead to more durable responses. Here, we will review large-scale in vivo screens in pre-clinical cancer models that employed genetic and pharmacological agents toward elucidating acquired drug resistance and informing on beneficial combinations to be tested in clinical trials.

Comparative Network Reconstruction using mixed integer programming.

Motivation: Signal-transduction networks are often aberrated in cancer cells, and new anti-cancer drugs that specifically target oncogenes involved in signaling show great clinical promise. However, the effectiveness of such targeted treatments is often hampered by innate or acquired resistance due to feedbacks, crosstalks or network adaptations in response to drug treatment. A quantitative understanding of these signaling networks and how they differ between cells with different oncogenic mutations or between sensitive and resistant cells can help in addressing this problem. Results: Here, we present Comparative Network Reconstruction (CNR), a computational method to reconstruct signaling networks based on possibly incomplete perturbation data, and to identify which edges differ quantitatively between two or more signaling networks. Prior knowledge about network topology is not required but can straightforwardly be incorporated. We extensively tested our approach using simulated data and applied it to perturbation data from a BRAF mutant, PTPN11 KO cell line that developed resistance to BRAF inhibition. Comparing the reconstructed networks of sensitive and resistant cells suggests that the resistance mechanism involves re-establishing wild-type MAPK signaling, possibly through an alternative RAF-isoform. Availability and implementation: CNR is available as a python module at https://github.com/NKI-CCB/cnr. Additionally, code to reproduce all figures is available at https://github.com/NKI-CCB/CNR-analyses. Supplementary information: Supplementary data are available at Bioinformatics online.

A System-wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells.

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread up-regulation of receptor tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally compensating for the MAPK pathway inhibition.

Modelling signalling networks from perturbation data.

Motivation: Intracellular signalling is realized by complex signalling networks, which are almost impossible to understand without network models, especially if feedbacks are involved. Modular Response Analysis (MRA) is a convenient modelling method to study signalling networks in various contexts. Results: We developed the software package STASNet (STeady-STate Analysis of Signalling Networks) that provides an augmented and extended version of MRA suited to model signalling networks from incomplete perturbation schemes and multi-perturbation data. Using data from the Dialogue on Reverse Engineering Assessment and Methods challenge, we show that predictions from STASNet models are among the top-performing methods. We applied the method to study the effect of SHP2, a protein that has been implicated in resistance to targeted therapy in colon cancer, using a novel dataset from the colon cancer cell line Widr and a SHP2-depleted derivative. We find that SHP2 is required for mitogen-activated protein kinase signalling, whereas AKT signalling only partially depends on SHP2. Availability and implementation: An R-package is available at https://github.com/molsysbio/STASNet. Supplementary information: Supplementary data are available at Bioinformatics online.

SHP2 is required for growth of KRAS-mutant non-small-cell lung cancer in vivo.

RAS mutations are frequent in human cancer, especially in pancreatic, colorectal and non-small-cell lung cancers (NSCLCs)1-3. Inhibition of the RAS oncoproteins has proven difficult4, and attempts to target downstream effectors5-7 have been hampered by the activation of compensatory resistance mechanisms8. It is also well established that KRAS-mutant tumors are insensitive to inhibition of upstream growth factor receptor signaling. Thus, epidermal growth factor receptor antibody therapy is only effective in KRAS wild-type colon cancers9,10. Consistently, inhibition of SHP2 (also known as PTPN11), which links receptor tyrosine kinase signaling to the RAS-RAF-MEK-ERK pathway11,12, was shown to be ineffective in KRAS-mutant or BRAF-mutant cancer cell lines13. Our data also indicate that SHP2 inhibition in KRAS-mutant NSCLC cells under normal cell culture conditions has little effect. By contrast, SHP2 inhibition under growth factor-limiting conditions in vitro results in a senescence response. In vivo, inhibition of SHP2 in KRAS-mutant NSCLC also provokes a senescence response, which is exacerbated by MEK inhibition. Our data identify SHP2 inhibition as an unexpected vulnerability of KRAS-mutant NSCLC cells that remains undetected in cell culture and can be exploited therapeutically.

PTPN11 Is a Central Node in Intrinsic and Acquired Resistance to Targeted Cancer Drugs.

Most BRAF (V600E) mutant melanomas are sensitive to selective BRAF inhibitors, but BRAF mutant colon cancers are intrinsically resistant to these drugs because of feedback activation of EGFR. We performed an RNA-interference-based genetic screen in BRAF mutant colon cancer cells to search for phosphatases whose knockdown induces sensitivity to BRAF inhibition. We found that suppression of protein tyrosine phosphatase non-receptor type 11 (PTPN11) confers sensitivity to BRAF inhibitors in colon cancer. Mechanistically, we found that inhibition of PTPN11 blocks signaling from receptor tyrosine kinases (RTKs) to the RAS-MEK-ERK pathway. PTPN11 suppression is lethal to cells that are driven by activated RTKs and prevents acquired resistance to targeted cancer drugs that results from RTK activation. Our findings identify PTPN11 as a drug target to combat both intrinsic and acquired resistance to several targeted cancer drugs. Moreover, activated PTPN11 can serve as a biomarker of drug resistance resulting from RTK activation.

Intrinsic resistance to MEK inhibition in KRAS mutant lung and colon cancer through transcriptional induction of ERBB3.

There are no effective therapies for the ~30% of human malignancies with mutant RAS oncogenes. Using a kinome-centered synthetic lethality screen, we find that suppression of the ERBB3 receptor tyrosine kinase sensitizes KRAS mutant lung and colon cancer cells to MEK inhibitors. We show that MEK inhibition results in MYC-dependent transcriptional upregulation of ERBB3, which is responsible for intrinsic drug resistance. Drugs targeting both EGFR and ERBB2, each capable of forming heterodimers with ERBB3, can reverse unresponsiveness to MEK inhibition by decreasing inhibitory phosphorylation of the proapoptotic proteins BAD and BIM. Moreover, ERBB3 protein level is a biomarker of response to combinatorial treatment. These data suggest a combination strategy for treating KRAS mutant colon and lung cancers and a way to identify the tumors that are most likely to benefit from such combinatorial treatment.

Reversible and adaptive resistance to BRAF(V600E) inhibition in melanoma.

Treatment of BRAF(V600E) mutant melanoma by small molecule drugs that target the BRAF or MEK kinases can be effective, but resistance develops invariably. In contrast, colon cancers that harbour the same BRAF(V600E) mutation are intrinsically resistant to BRAF inhibitors, due to feedback activation of the epidermal growth factor receptor (EGFR). Here we show that 6 out of 16 melanoma tumours analysed acquired EGFR expression after the development of resistance to BRAF or MEK inhibitors. Using a chromatin-regulator-focused short hairpin RNA (shRNA) library, we find that suppression of sex determining region Y-box 10 (SOX10) in melanoma causes activation of TGF-ß signalling, thus leading to upregulation of EGFR and platelet-derived growth factor receptor-ß (PDGFRB), which confer resistance to BRAF and MEK inhibitors. Expression of EGFR in melanoma or treatment with TGF-ß results in a slow-growth phenotype with cells displaying hallmarks of oncogene-induced senescence. However, EGFR expression or exposure to TGF-ß becomes beneficial for proliferation in the presence of BRAF or MEK inhibitors. In a heterogeneous population of melanoma cells having varying levels of SOX10 suppression, cells with low SOX10 and consequently high EGFR expression are rapidly enriched in the presence of drug, but this is reversed when the drug treatment is discontinued. We find evidence for SOX10 loss and/or activation of TGF-ß signalling in 4 of the 6 EGFR-positive drug-resistant melanoma patient samples. Our findings provide a rationale for why some BRAF or MEK inhibitor-resistant melanoma patients may regain sensitivity to these drugs after a 'drug holiday' and identify patients with EGFR-positive melanoma as a group that may benefit from re-treatment after a drug holiday.

MED12 controls the response to multiple cancer drugs through regulation of TGF-ß receptor signaling.

Inhibitors of the ALK and EGF receptor tyrosine kinases provoke dramatic but short-lived responses in lung cancers harboring EML4-ALK translocations or activating mutations of EGFR, respectively. We used a large-scale RNAi screen to identify MED12, a component of the transcriptional MEDIATOR complex that is mutated in cancers, as a determinant of response to ALK and EGFR inhibitors. MED12 is in part cytoplasmic where it negatively regulates TGF-ßR2 through physical interaction. MED12 suppression therefore results in activation of TGF-ßR signaling, which is both necessary and sufficient for drug resistance. TGF-ß signaling causes MEK/ERK activation, and consequently MED12 suppression also confers resistance to MEK and BRAF inhibitors in other cancers. MED12 loss induces an EMT-like phenotype, which is associated with chemotherapy resistance in colon cancer patients and to gefitinib in lung cancer. Inhibition of TGF-ßR signaling restores drug responsiveness in MED12(KD) cells, suggesting a strategy to treat drug-resistant tumors that have lost MED12.

Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR.

Inhibition of the BRAF(V600E) oncoprotein by the small-molecule drug PLX4032 (vemurafenib) is highly effective in the treatment of melanoma. However, colon cancer patients harbouring the same BRAF(V600E) oncogenic lesion have poor prognosis and show only a very limited response to this drug. To investigate the cause of the limited therapeutic effect of PLX4032 in BRAF(V600E) mutant colon tumours, here we performed an RNA-interference-based genetic screen in human cells to search for kinases whose knockdown synergizes with BRAF(V600E) inhibition. We report that blockade of the epidermal growth factor receptor (EGFR) shows strong synergy with BRAF(V600E) inhibition. We find in multiple BRAF(V600E) mutant colon cancers that inhibition of EGFR by the antibody drug cetuximab or the small-molecule drugs gefitinib or erlotinib is strongly synergistic with BRAF(V600E) inhibition, both in vitro and in vivo. Mechanistically, we find that BRAF(V600E) inhibition causes a rapid feedback activation of EGFR, which supports continued proliferation in the presence of BRAF(V600E) inhibition. Melanoma cells express low levels of EGFR and are therefore not subject to this feedback activation. Consistent with this, we find that ectopic expression of EGFR in melanoma cells is sufficient to cause resistance to PLX4032. Our data suggest that BRAF(V600E) mutant colon cancers (approximately 8-10% of all colon cancers), for which there are currently no targeted treatment options available, might benefit from combination therapy consisting of BRAF and EGFR inhibitors.