ROR1-STAT3 signaling contributes to ovarian cancer intra-tumor heterogeneity.

Wnt pathway dysregulation through genetic and non-genetic alterations occurs in multiple cancers, including ovarian cancer (OC). The aberrant expression of the non-canonical Wnt signaling receptor ROR1 is thought to contribute to OC progression and drug resistance. However, the key molecular events mediated by ROR1 that are involved in OC tumorigenesis are not fully understood. Here, we show that ROR1 expression is enhanced by neoadjuvant chemotherapy, and Wnt5a binding to ROR1 can induce oncogenic signaling via AKT/ERK/STAT3 activation in OC cells. Proteomics analysis of isogenic ROR1-knockdown OC cells identified STAT3 as a downstream effector of ROR1 signaling. Transcriptomics analysis of clinical samples (n = 125) revealed that ROR1 and STAT3 are expressed at higher levels in stromal cells than in epithelial cancer cells of OC tumors, and these findings were corroborated by multiplex immunohistochemistry (mIHC) analysis of an independent OC cohort (n = 11). Our results show that ROR1 and its downstream STAT3 are co-expressed in epithelial as well as stromal cells of OC tumors, including cancer-associated fibroblasts or CAFs. Our data provides the framework to expand the clinical utility of ROR1 as a therapeutic target to overcome OC progression.

Novel therapeutic approaches for pleural mesothelioma identified by functional ex vivo drug sensitivity testing.

OBJECTIVES: Pleural mesothelioma (PM) is an aggressive malignancy with limited treatment options. The first-line therapy has remained unchanged for two decades and consists of pemetrexed in combination with cisplatin. Immune-checkpoint inhibitors (nivolumab plus ipilimumab) have high response rates, resulting in recent updates in treatment recommendations by the U.S. Food and Drug Administration. However, the overall benefits of combination treatment are modest, suggesting that other targeted therapy options should be investigated. MATERIALS AND METHODS: We employed high-throughput drug sensitivity and resistance testing on five established PM cell lines using 527 cancer drugs in a 2D setting. Drugs of the greatest potential (n = 19) were selected for further testing in primary cell models derived from pleural effusions of seven PM patients. RESULTS: All established and primary patient-derived PM cell models were sensitive to the mTOR inhibitor AZD8055. Furthermore, another mTOR inhibitor (temsirolimus) showed efficacy in most of the primary patient-derived cells, although a less robust effect was observed when compared with the established cell lines. Most of the established cell lines and all patient-derived primary cells exhibited sensitivity to the PI3K/mTOR/DNA-PK inhibitor LY3023414. The Chk1 inhibitor prexasertib showed activity in 4/5 (80%) of the established cell lines and in 2/7 (29%) of the patient-derived primary cell lines. The BET family inhibitor JQ1 showed activity in four patient-derived cell models and in one established cell line. CONCLUSION: mTOR and Chk1 pathways had promising results with established mesothelioma cell lines in an ex vivo setting. In patient-derived primary cells, drugs targeting mTOR pathway in particular showed efficacy. These findings may inform novel treatment strategies for PM.

Comparison of two supporting matrices for patient-derived cancer cells in 3D drug sensitivity and resistance testing assay (3D-DSRT).

Central to the success of functional precision medicine of solid tumors is to perform drug testing of patient-derived cancer cells (PDCs) in tumor-mimicking ex vivo conditions. While high throughput (HT) drug screening methods have been well-established for cells cultured in two-dimensional (2D) format, this approach may have limited value in predicting clinical responses. Here, we describe the results of the optimization of drug sensitivity and resistance testing (DSRT) in three-dimensional (3D) growth supporting matrices in a HT mode (3D-DSRT) using the hepatocyte cell line (HepG2) as an example. Supporting matrices included widely used animal-derived Matrigel and cellulose-based hydrogel, GrowDex, which has earlier been shown to support 3D growth of cell lines and stem cells. Further, the sensitivity of ovarian cancer PDCs, from two patients included in the functional precision medicine study, was tested for 52 drugs in 5 different concentrations using 3D-DSRT. Shortly, in the optimized protocol, the PDCs are embedded with matrices and seeded to 384-well plates to allow the formation of the spheroids prior to the addition of drugs in nanoliter volumes with acoustic dispenser. The sensitivity of spheroids to drug treatments is measured with cell viability readout (here, 72 h after addition of drugs). The quality control and data analysis are performed with openly available Breeze software. We show the usability of both matrices in established 3D-DSRT, and report 2D vs 3D growth condition dependent differences in sensitivities of ovarian cancer PDCs to MEK-inhibitors and cytotoxic drugs. This study provides a proof-of-concept for robust and fast screening of drug sensitivities of PDCs in 3D-DSRT, which is important not only for drug discovery but also for personalized ex vivo drug testing in functional precision medicine studies. These findings suggest that comparing results of 2D- and 3D-DSRT is essential for understanding drug mechanisms and for selecting the most effective treatment for the patient.

Protocol for 3D drug sensitivity and resistance testing of patient-derived cancer cells in 384-well plates.

Establishment of drug testing of patient-derived cancer cells (PDCs) in physiologically relevant 3-dimensional (3D) culture is central for drug discovery and cancer research, as well as for functional precision medicine. Here, we describe the detailed protocol allowing the 3D drug testing of PDCs - or any type of cells of interest - in Matrigel in 384-well plate format using automation. We also provide an alternative protocol, which does not require supporting matrices. The cancer tissue is obtained directly from clinics (after surgery or biopsy) and processed into single cell suspension. Systematic drug sensitivity and resistance testing (DSRT) is carried out on the PDCs directly after cancer cell isolation from tissue or on cells expanded for a few passages. In the 3D-DSRT assay, the PDCs are plated in 384-well plates in Matrigel, grown as spheroids, and treated with compounds of interest for 72 h. The cell viability is directly measured using a luminescence-based assay. Alternatively, prior to the cell viability measurement, drug-treated cells can be directly subjected to automated high-content bright field imaging or stained for fluorescence (live) cell microscopy for further image analysis. This is followed by the quality control and data analysis. The 3D-DSRT can be performed within a 1-3-week timeframe of the clinical sampling of cancer tissue, depending on the amount of the obtained tissue, growth rate of cancer cells, and the number of drugs being tested. The 3D-DSRT method can be flexibly modified, e.g., to be carried out with or without supporting matrices with U-bottom 384-well plates when appropriate for the PDCs or other cell models used.

Drug response profiles in patient-derived cancer cells across histological subtypes of ovarian cancer: real-time therapy tailoring for a patient with low-grade serous carcinoma.

Many efforts are underway to develop novel therapies against the aggressive high-grade serous ovarian cancers (HGSOCs), while our understanding of treatment options for low-grade (LGSOC) or mucinous (MUCOC) of ovarian malignancies is not developing as well. We describe here a functional precision oncology (fPO) strategy in epithelial ovarian cancers (EOC), which involves high-throughput drug testing of patient-derived ovarian cancer cells (PDCs) with a library of 526 oncology drugs, combined with genomic and transcriptomic profiling. HGSOC, LGSOC and MUCOC PDCs had statistically different overall drug response profiles, with LGSOCs responding better to targeted inhibitors than HGSOCs. We identified several subtype-specific drug responses, such as LGSOC PDCs showing high sensitivity to MDM2, ERBB2/EGFR inhibitors, MUCOC PDCs to MEK inhibitors, whereas HGSOCs showed strongest effects with CHK1 inhibitors and SMAC mimetics. We also explored several drug combinations and found that the dual inhibition of MEK and SHP2 was synergistic in MAPK-driven EOCs. We describe a clinical case study, where real-time fPO analysis of samples from a patient with metastatic, chemorefractory LGSOC with a CLU-NRG1 fusion guided clinical therapy selection. fPO-tailored therapy with afatinib, followed by trastuzumab and pertuzumab, successfully reduced tumour burden and blocked disease progression over a five-year period. In summary, fPO is a powerful approach for the identification of systematic drug response differences across EOC subtypes, as well as to highlight patient-specific drug regimens that could help to optimise therapies to individual patients in the future.

Multiomics characterization implicates PTK7 in ovarian cancer EMT and cell plasticity and offers strategies for therapeutic intervention.

Most patients with ovarian cancer (OC) are diagnosed at a late stage when there are very few therapeutic options and a poor prognosis. This is due to the lack of clearly defined underlying mechanisms or an oncogenic addiction that can be targeted pharmacologically, unlike other types of cancer. Here, we identified protein tyrosine kinase 7 (PTK7) as a potential new therapeutic target in OC following a multiomics approach using genetic and pharmacological interventions. We performed proteomics analyses upon PTK7 knockdown in OC cells and identified novel downstream effectors such as synuclein-γ (SNCG), SALL2, and PP1γ, and these findings were corroborated in ex vivo primary samples using PTK7 monoclonal antibody cofetuzumab. Our phosphoproteomics analyses demonstrated that PTK7 modulates cell adhesion and Rho-GTPase signaling to sustain epithelial-mesenchymal transition (EMT) and cell plasticity, which was confirmed by high-content image analysis of 3D models. Furthermore, using high-throughput drug sensitivity testing (525 drugs) we show that targeting PTK7 exhibited synergistic activity with chemotherapeutic agent paclitaxel, CHK1/2 inhibitor prexasertib, and PLK1 inhibitor GSK461364, among others, in OC cells and ex vivo primary samples. Taken together, our study provides unique insight into the function of PTK7, which helps to define its role in mediating aberrant Wnt signaling in ovarian cancer.

High-throughput ex vivo drug testing identifies potential drugs and drug combinations for NRAS-positive malignant melanoma.

Therapy options for patients with metastatic melanoma (MM) have considerably improved over the past decade. However, many patients still need effective therapy after unsuccessful immunotherapy, especially patients with BRAF-negative tumors who lack the option of targeted treatment second line. Therefore, the elucidation of efficient and personalized therapy options for these patients is required. In this study, three patient-derived cancer cells (PDCs) were established from NRAS Q61-positive MM patients. The response of PDCs and five established melanoma cell lines (two NRAS-positive, one wild type, and two BRAF V600-positive) was evaluated toward a panel of 527 oncology drugs using high-throughput drug sensitivity and resistance testing. The PDCs and cell lines displayed strong responses to MAPK inhibitors, as expected. Additionally, the PDCs and cell lines were responsive to PI3K/mTOR, mTOR, and PLK1 inhibitors among other effective drugs currently undergoing clinical trials. Combinations with a MEK inhibitor were tested with other targeted agents to identify effective synergies. MEK inhibitor showed synergy with multikinase inhibitor ponatinib, ABL inhibitor nilotinib, PI3K/mTOR inhibitor pictilisib, and pan-RAF inhibitor LY3009120. The application of the patients' cancer cells for functional drug testing ex vivo is one step further in the process of identifying potential agents and agent combinations to personalize treatment for patients with MM. Our preliminary study results suggest that this approach has the potential for larger-scale drug testing and personalized treatment applications in our expansion trial. Our results show that drug sensitivity and resistance testing may be implementable in the treatment planning of patients with MM.

Evaluating Targeted Therapies in Ovarian Cancer Metabolism: Novel Role for PCSK9 and Second Generation mTOR Inhibitors.

BACKGROUND: Dysregulated lipid metabolism is emerging as a hallmark in several malignancies, including ovarian cancer (OC). Specifically, metastatic OC is highly dependent on lipid-rich omentum. We aimed to investigate the therapeutic value of targeting lipid metabolism in OC. For this purpose, we studied the role of PCSK9, a cholesterol-regulating enzyme, in OC cell survival and its downstream signaling. We also investigated the cytotoxic efficacy of a small library of metabolic (n = 11) and mTOR (n = 10) inhibitors using OC cell lines (n = 8) and ex vivo patient-derived cell cultures (PDCs, n = 5) to identify clinically suitable drug vulnerabilities. Targeting PCSK9 expression with siRNA or PCSK9 specific inhibitor (PF-06446846) impaired OC cell survival. In addition, overexpression of PCSK9 induced robust AKT phosphorylation along with increased expression of ERK1/2 and MEK1/2, suggesting a pro-survival role of PCSK9 in OC cells. Moreover, our drug testing revealed marked differences in cytotoxic responses to drugs targeting metabolic pathways of high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC) PDCs. Our results show that targeting PCSK9 expression could impair OC cell survival, which warrants further investigation to address the dependency of this cancer on lipogenesis and omental metastasis. Moreover, the differences in metabolic gene expression and drug responses of OC PDCs indicate the existence of a metabolic heterogeneity within OC subtypes, which should be further explored for therapeutic improvements.

STRN-ALK rearranged pediatric malignant peritoneal mesothelioma - Functional testing of 527 cancer drugs in patient-derived cancer cells.

Genetic rearrangements involving the anaplastic lymphoma kinase (ALK) gene create oncogenic drivers for several cancers, including malignant peritoneal mesothelioma (MPeM). Here, we report genomic and functional precision oncology profiling on a rare case of a 5-year old patient diagnosed with wide-spread and aggressive MPeM, driven by STRN-ALK rearrangement. We established genomically representative patient-derived cancer cells (PDCs) from the tumor sample and performed high-throughput drug sensitivity testing with 527 oncology compounds to identify potent inhibitors. As expected, the PDCs were overall sensitive to the ALK inhibitors, although the eight different inhibitors tested had variable efficacy. We also discovered other effective inhibitors, such as MEK/ERK inhibitors and those targeting pathways downstream of ALK as well as Bcl-xl inhibitors. In contrast, most cytotoxic drugs were not very effective. ALK inhibitors synergized with MEK and PI3K/mTOR inhibitors, highlighting potential combinatorial strategies to enhance drug efficacy and tackle drug resistance. Based on genomic data and associated functional validation, the patient was treated with the ALK inhibitor crizotinib in combination with conventional chemotherapy (cisplatin and gemcitabine). A complete disease remission was reached, lasting now for over 3 years. Our results illustrate a rare pediatric cancer case, and highlight the potential of functional precision oncology to discover pathogenetic drivers, validate dependency on driver signals, compare different inhibitors against each other and potentially enhance targeted treatments by drug combinations. Such real-time implementation of functional precision oncology could pave the way towards safer and more effective personalized cancer therapies for individual pediatric cancer patients with rare tumors.

Glucocorticoids induce differentiation and chemoresistance in ovarian cancer by promoting ROR1-mediated stemness.

Glucocorticoids are routinely used in the clinic as anti-inflammatory and immunosuppressive agents as well as adjuvants during cancer treatment to mitigate the undesirable side effects of chemotherapy. However, recent studies have indicated that glucocorticoids may negatively impact the efficacy of chemotherapy by promoting tumor cell survival, heterogeneity, and metastasis. Here, we show that dexamethasone induces upregulation of ROR1 expression in ovarian cancer (OC), including platinum-resistant OC. Increased ROR1 expression resulted in elevated RhoA, YAP/TAZ, and BMI-1 levels in a panel of OC cell lines as well as primary ovarian cancer patient-derived cells, underlining the translational relevance of our studies. Importantly, dexamethasone induced differentiation of OC patient-derived cells ex vivo according to their molecular subtype and the phenotypic expression of cell differentiation markers. High-throughput drug testing with 528 emerging and clinical oncology compounds of OC cell lines and patient-derived cells revealed that dexamethasone treatment increased the sensitivity to several AKT/PI3K targeted kinase inhibitors, while significantly decreasing the efficacy of chemotherapeutics such as taxanes, as well as anti-apoptotic compounds such as SMAC mimetics. On the other hand, targeting ROR1 expression increased the efficacy of taxane drugs and SMAC mimetics, suggesting new combinatorial targeted treatments for patients with OC.

Wnt5a and ROR1 activate non-canonical Wnt signaling via RhoA in TCF3-PBX1 acute lymphoblastic leukemia and highlight new treatment strategies via Bcl-2 co-targeting.

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with TCF3-PBX1 fusion gene expression has constitutively elevated levels of Wnt16b and ROR1 (receptor tyrosine kinase-like orphan receptor), a ligand and a receptor from the Wnt signaling pathway, respectively. Although survival rate is usually high after the initial chemotherapy, many TCF3-PBX1 BCP-ALL patients relapse and subsequently develop treatment resistance, resulting in poor prognosis. Here, we aimed to investigate the molecular signaling associated with Wnt16b and ROR1 overexpression in TCF3-PBX1 cell lines and primary samples, and to identify effective treatment options via ROR1 targeting. We detected higher ROR1 expression on TCF3-PBX1 leukemic cells even at a later stage of patient relapse, providing a strong rationale for the use of ROR1-targeted therapy. We found that Wnt5a-ROR1 signaling enhances proliferation of TCF3-PBX1 cells via RhoA/Rac1 GTPases activation and STAT3 upregulation. Wnt16b also activated the RhoA/Rac1 signaling cascade suggesting the activation of a non-canonical Wnt pathway in TCF3-PBX1 cells. Wnt16 could interact with ROR1 but not in TCF3-PBX1 cells, suggesting that Wnt5a is the ligand signaling via ROR1 in TCF3-PBX1 cells. By high throughput drug-sensitivity testing of TCF3-PBX1 cells before and after ROR1 knockdown we found that targeting ROR1 significantly improves the therapeutic efficacy of Bcl-2 family inhibitors venetoclax and navitoclax, and this synergism was confirmed ex vivo using a drug-resistant primary sample from a relapsed TCF3-PBX1 patient. Our work underlines a new type of targeted combination therapy that could be clinically advantageous for patients with TCF3-PBX1 BCP-ALL.

Anagrelide for Gastrointestinal Stromal Tumor.

PURPOSE: Gastrointestinal stromal tumor (GIST) is a common type of soft-tissue sarcoma. Imatinib, an inhibitor of KIT, platelet-derived growth factor receptor alpha (PDGFRA), and a few other tyrosine kinases, is highly effective for GIST, but advanced GISTs frequently progress on imatinib and other approved tyrosine kinase inhibitors. We investigated phosphodiesterase 3 (PDE3) as a potential therapeutic target in GIST cell lines and xenograft models. EXPERIMENTAL DESIGN: The GIST gene expression profile was interrogated in the MediSapiens IST Online transcriptome database comprising human tissue and cancer samples, and PDE3A and PDE3B expression was studied using IHC on tissue microarrays (TMA) consisting of 630 formalin-fixed human tissue samples. GIST cell lines were screened for sensitivity to 217 anticancer compounds, and the efficacy of PDE inhibitors on GIST was further studied in GIST cell lines and patient-derived mouse xenograft models. RESULTS: GISTs expressed PDE3A and PDE3B frequently compared with other human normal or cancerous tissues both in the in silico database and the TMAs. Anagrelide was identified as the most potent of the PDE3 modulators evaluated. It reduced cell viability, promoted cell death, and influenced cell signaling in GIST cell lines. Anagrelide inhibited tumor growth in GIST xenograft mouse models. Anagrelide was also effective in a GIST xenograft mouse model with KIT exon 9 mutation that may pose a therapeutic challenge, as these GISTs require a high daily dose of imatinib. CONCLUSIONS: PDE3A and PDE3B are frequently expressed in GIST. Anagrelide had anticancer efficacy in GIST xenograft models and warrants further testing in clinical trials.

Drug-Sensitivity Screening and Genomic Characterization of 45 HPV-Negative Head and Neck Carcinoma Cell Lines for Novel Biomarkers of Drug Efficacy.

There is an unmet need for effective targeted therapies for patients with advanced head and neck squamous cell carcinoma (HNSCC). We correlated gene expression, gene copy numbers, and point mutations in 45 human papillomavirus-negative HNSCC cell lines with the sensitivity to 220 anticancer drugs to discover predictive associations to genetic alterations. The drug response profiles revealed diverse efficacy of the tested drugs across the cell lines. Several genomic abnormalities and gene expression differences were associated with response to mTOR, MEK, and EGFR inhibitors. NOTCH1 and FAT1 were the most commonly mutated genes after TP53 and also showed some association with response to MEK and/or EGFR inhibitors. MYC amplification and FAM83H overexpression associated with sensitivity to EGFR inhibitors, and PTPRD deletion with poor sensitivity to MEK inhibitors. The connection between high FAM83H expression and responsiveness to the EGFR inhibitor erlotinib was validated by gene silencing and from the data set at the Cancer Cell Line Encyclopedia. The data provide several novel genomic alterations that associated to the efficacy of targeted drugs in HNSCC. These findings require further validation in experimental models and clinical series. Mol Cancer Ther; 17(9); 2060-71. ©2018 AACR.

Colorectal Cancer Consensus Molecular Subtypes Translated to Preclinical Models Uncover Potentially Targetable Cancer Cell Dependencies.

Purpose: Response to standard oncologic treatment is limited in colorectal cancer. The gene expression-based consensus molecular subtypes (CMS) provide a new paradigm for stratified treatment and drug repurposing; however, drug discovery is currently limited by the lack of translation of CMS to preclinical models.Experimental Design: We analyzed CMS in primary colorectal cancers, cell lines, and patient-derived xenografts (PDX). For classification of preclinical models, we developed an optimized classifier enriched for cancer cell-intrinsic gene expression signals, and performed high-throughput in vitro drug screening (n = 459 drugs) to analyze subtype-specific drug sensitivities.Results: The distinct molecular and clinicopathologic characteristics of each CMS group were validated in a single-hospital series of 409 primary colorectal cancers. The new, cancer cell-adapted classifier was found to perform well in primary tumors, and applied to a panel of 148 cell lines and 32 PDXs, these colorectal cancer models were shown to recapitulate the biology of the CMS groups. Drug screening of 33 cell lines demonstrated subtype-dependent response profiles, confirming strong response to EGFR and HER2 inhibitors in the CMS2 epithelial/canonical group, and revealing strong sensitivity to HSP90 inhibitors in cells with the CMS1 microsatellite instability/immune and CMS4 mesenchymal phenotypes. This association was validated in vitro in additional CMS-predicted cell lines. Combination treatment with 5-fluorouracil and luminespib showed potential to alleviate chemoresistance in a CMS4 PDX model, an effect not seen in a chemosensitive CMS2 PDX model.Conclusions: We provide translation of CMS classification to preclinical models and uncover a potential for targeted treatment repurposing in the chemoresistant CMS4 group. Clin Cancer Res; 24(4); 794-806. ©2017 AACR.

Drug sensitivity and resistance testing identifies PLK1 inhibitors and gemcitabine as potent drugs for malignant peripheral nerve sheath tumors.

Patients with malignant peripheral nerve sheath tumor (MPNST), a rare soft tissue cancer associated with loss of the tumor suppressor neurofibromin (NF1), have poor prognosis and typically respond poorly to adjuvant therapy. We evaluated the effect of 299 clinical and investigational compounds on seven MPNST cell lines, two primary cultures of human Schwann cells, and five normal bone marrow aspirates, to identify potent drugs for MPNST treatment with few side effects. Top hits included Polo-like kinase 1 (PLK1) inhibitors (volasertib and BI2536) and the fluoronucleoside gemcitabine, which were validated in orthogonal assays measuring viability, cytotoxicity, and apoptosis. DNA copy number, gene expression, and protein expression were determined for the cell lines to assess pharmacogenomic relationships. MPNST cells were more sensitive to BI2536 and gemcitabine compared to a reference set of 94 cancer cell lines. PLK1, RRM1, and RRM2 mRNA levels were increased in MPNST compared to benign neurofibroma tissue, and the protein level of PLK1 was increased in the MPNST cell lines compared to normal Schwann cells, indicating an increased dependence on these drug targets in malignant cells. Furthermore, we observed an association between increased mRNA expression of PLK1, RRM1, and RRM2 in patient samples and worse disease outcome, suggesting a selective benefit from inhibition of these genes in the most aggressive tumors.

Targeting ROR1 identifies new treatment strategies in hematological cancers.

Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is a member of the ROR receptor family consisting of two closely related type I transmembrane proteins ROR1 and ROR2. Owing to mutations in their canonical motifs required for proper kinase activity, RORs are classified as pseudokinases lacking detectable catalytic activity. ROR1 stands out for its selective and high expression in numerous blood and solid malignancies compared with a minimal expression in healthy adult tissues, suggesting high potential for this molecule as a drug target for cancer therapy. Current understanding attributes a survival role for ROR1 in cancer cells; however, its oncogenic function is cancer-type-specific and involves various signaling pathways. High interest in ROR1-targeted therapies resulted in the development of ROR1 monoclonal antibodies such as cirmtuzumab, currently in a phase I clinical trial for chronic lymphocytic leukemia. Despite these advances in translational studies, the molecular mechanism employed by ROR1 in different cancers is not yet fully understood; therefore, more insights into the oncogenic role of ROR1 signaling are crucial in order to optimize the use of targeted drugs. Recent studies provided evidence that targeting ROR1 simultaneously with inhibition of B-cell receptor (BCR) signaling is more effective in killing ROR1-positive leukemia cells, suggesting a synergistic correlation between co-targeting ROR1 and BCR pathways. Although this synergy has been previously reported for B-cell acute lymphoblastic leukemia, the molecular mechanism appears rather different. These results provide more insights into ROR1-BCR combinatorial treatment strategies in hematological malignancies, which could benefit in tailoring more effective targeted therapies in other ROR1-positive cancers.

Crosstalk between ROR1 and BCR pathways defines novel treatment strategies in mantle cell lymphoma.

Mantle cell lymphoma (MCL) is an aggressive form of non-Hodgkin B-cell lymphoma with poor prognosis due to drug resistance. Introduction of the Bruton tyrosine kinase (BTK) inhibitor ibrutinib has markedly improved MCL therapy outcome, but drug resistance remains a challenge. The selective cell-surface expression of oncogenic receptor tyrosine kinase-like orphan receptor 1 (ROR1) pseudokinase in hematological malignancies has made this receptor a promising candidate for targeted therapy. We sought to identify the molecular mechanism underlying divergent ROR1-mediated apoptotic responses in MCL cell lines and primary samples. We show that targeting ROR1 expression resulted in downregulation of NF-κB p65 levels and that activation of the NF-κB pathway can antagonize ROR1-mediated apoptotic responses. High-throughput drug-sensitivity testing of MCL cells before and after ROR1 targeting revealed synergistic effects between cotargeting of ROR1 and the B-cell antigen receptor (BCR) or Bcl-2 family, underlining the high potential for ROR1-targeted therapies in overcoming MCL drug resistance. However, inhibition of the BCR pathway by targeted drugs such as ibrutinib can impair ROR1 expression and consequently ROR1-targeted treatments, underscoring the importance of inhibiting both pathways to augment cancer cell killing. Considering the central role of NF-κB pathway activation in B-cell malignancies, this study highlights key factors that can modulate ROR1-targeted treatments in hematological cancers.

Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization.

MOTIVATION: A key goal of computational personalized medicine is to systematically utilize genomic and other molecular features of samples to predict drug responses for a previously unseen sample. Such predictions are valuable for developing hypotheses for selecting therapies tailored for individual patients. This is especially valuable in oncology, where molecular and genetic heterogeneity of the cells has a major impact on the response. However, the prediction task is extremely challenging, raising the need for methods that can effectively model and predict drug responses. RESULTS: In this study, we propose a novel formulation of multi-task matrix factorization that allows selective data integration for predicting drug responses. To solve the modeling task, we extend the state-of-the-art kernelized Bayesian matrix factorization (KBMF) method with component-wise multiple kernel learning. In addition, our approach exploits the known pathway information in a novel and biologically meaningful fashion to learn the drug response associations. Our method quantitatively outperforms the state of the art on predicting drug responses in two publicly available cancer datasets as well as on a synthetic dataset. In addition, we validated our model predictions with lab experiments using an in-house cancer cell line panel. We finally show the practical applicability of the proposed method by utilizing prior knowledge to infer pathway-drug response associations, opening up the opportunity for elucidating drug action mechanisms. We demonstrate that pathway-response associations can be learned by the proposed model for the well-known EGFR and MEK inhibitors. AVAILABILITY AND IMPLEMENTATION: The source code implementing the method is available at http://research.cs.aalto.fi/pml/software/cwkbmf/ CONTACTS: muhammad.ammad-ud-din@aalto.fi or samuel.kaski@aalto.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.