scholarly journals Ex vivo activity of cytotoxic drugs and targeted agents in small intestinal neuroendocrine tumors

2018 ◽  
Vol 25 (4) ◽  
pp. 471-480
Author(s):  
Kosmas Daskalakis ◽  
Olov Norlén ◽  
Andreas Karakatsanis ◽  
Per Hellman ◽  
Rolf Larsson ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Drug Sensitivity ◽  
Kinase Inhibitors ◽  
Ex Vivo ◽  
Great Variability ◽  
Protein Kinase Inhibitors ◽  
Cytotoxic Drugs ◽  
Targeted Agents ◽  
Small Intestinal ◽  
Tumor Types

Small intestinal neuroendocrine tumors (SI-NETs) are generally considered resistant to systemic treatment. To date, predictive markers for drug activity are lacking. Tumor samples from 27 patients with SI-NETs were analyzed ex vivo for sensitivity to a panel of cytotoxic drugs and targeted agents using a short-term total cell kill assay. Samples of renal cancer, colorectal cancer (CRC), ovarian cancer and chronic lymphocytic leukemia (CLL) were included for comparison. For the SI-NET subset, drug sensitivity was analyzed in relation to clinicopathological variables and pre-treatment biomarkers. For cytotoxic drugs, SI-NETs demonstrated similar or higher sensitivity to 5-FU, platinum, gemcitabine and doxorubicin compared with CRC. For several of the targeted kinase inhibitors, SI-NET was among the most sensitive solid tumor types. CLL and ovarian cancer were generally the most sensitive tumor types to both cytotoxic drugs and protein kinase inhibitors. SI-NET was more sensitive to the mTOR inhibitor sirolimus than the other solid tumor types tested. Individual SI-NET samples demonstrated great variability in ex vivo sensitivity for most drugs. Cross-resistance between different drugs also varied considerably, being higher among protein kinase inhibitors. Age, stage, grade, peritoneal carcinomatosis and extra-abdominal metastases as well as serum chromogranin A and urine 5-HIAA concentrations at diagnosis did not correlate to drug sensitivity ex vivo. SI-NETs exhibit intermediate sensitivity ex vivo to cytotoxic and targeted drugs. Clinicopathological factors and currently used biomarkers are not clearly associated to ex vivo sensitivity, challenging these criteria for treatment decisions in SI-NET. The great variability in drug sensitivity calls for individualized selection of therapy.

scholarly journals Ex Vivo Analysis of Primary Tumor Specimens for Evaluation of Cancer Therapeutics

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Cristina E. Tognon ◽  
Rosalie C. Sears ◽  
Gordon B. Mills ◽  
Joe W. Gray ◽  
Jeffrey W. Tyner
Keyword(s):  
Primary Tumor ◽  
Cancer Biology ◽  
Drug Sensitivity ◽  
Ex Vivo ◽  
Publication Date ◽  
Sensitivity Testing ◽  
Drug Activity ◽  
Drug Sensitivity Testing ◽  
Cancer Pathogenesis ◽  
Tumor Types

The use of ex vivo drug sensitivity testing to predict drug activity in individual patients has been actively explored for almost 50 years without delivering a generally useful predictive capability. However, extended failure should not be an indicator of futility. This is especially true in cancer research, where ultimate success is often preceded by less successful attempts. For example, both immune- and genetic-based targeted therapies for cancer underwent numerous failed attempts before biological understanding, improved targets, and optimized drug development matured to facilitate an arsenal of transformational drugs. Similarly, directly assessing drug sensitivity of primary tumor biopsies—and the use of this information to help direct therapeutic approaches—has a long history with a definitive learning curve. In this review, we survey the history of ex vivo testing and the current state of the art for this field. We present an update on methodologies and approaches, describe the use of these technologies to test cutting-edge drug classes, and describe an increasingly nuanced understanding of tumor types and models for which this strategy is most likely to succeed. We consider the relative strengths and weaknesses of predicting drug activity across the broad biological context of cancer patients and tumor types. This includes an analysis of the potential for ex vivo drug sensitivity testing to accurately predict drug activity within each of the biological hallmarks of cancer pathogenesis. Expected final online publication date for the Annual Review of Cancer Biology, Volume 5 is March 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Ovarian cancer stem cells (OCSCs): Therapy for advanced chemoresistant ovarian cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e16542-e16542
Author(s):  
Prattusha Sengupta ◽  
Sudeshna Gangopadhyay ◽  
Saubhik Sengupta ◽  
Ujjal Kanti Ray ◽  
Ashis Mukhopadhyay
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Drug Sensitivity ◽  
Ex Vivo ◽  
Cancer Site ◽  
Chemotherapeutic Drugs ◽  
Ovarian Cancer Stem Cells

e16542 Background: Invasive and mesenchymal property of Ovarian Cancer Stem Cells (OCSCs)with CD44+/CD133+has made them promising target for targeted treatment. Chemotherapy treatment uses medicine to weaken and destroy cancer cells in body, including cells at original cancer site and any cancer cells that may have spread to another part of body. Chemotherapeutic drugs for advanced chemo-resistant ovarian cancer are yet to be well defined. Combination of drugs is also not fully known. Our objective is to define chemotherapeutic drugs and its action in OCSC which is the major reason for chemo resistance in case of advanced chemo-resistant ovarian cancer patients. Methods: A total of twenty biopsy proven advanced chemo-resistant ovarian cancer patients in the age group of 22-36 years were selected randomly and tested for CD44/CD133 via flow cytometry. Isolated OCSCs were cultured for ex vivo drug sensitivity towards platinum, anthracyclin, docetaxel, rapamycin, sunitinib, sorafenib and gefitinib. Correlation was drawn between cell differentiations, % of stem cells and drug response. Accordingly chemotherapy was designed for a particular patient. Results: We detected OCSCs in 90% of cases. Among positive samples ex vivo drug sensitivity was seen in 4(20%) to rapamycin, 1(5%) to sunitinib, 1(5%) to sorafenib, 1(5%) to gefitinib, 3(15%) to platinum, 1(5%) to anthracyclin, 1(5%) to docetaxel and rest showed no sensitivity to any drug. Conclusions: Thus primary aim to target OCSCs at onset of tumors in ovarian cancer patients to control metastasis and relapse of disease was somewhat obtained. Most interestingly, we found that the chemotherapeutic drugs which were less prescribed for ovarian cancer showed greater sensitivity in comparison to the widely used ones. We like to do animal model study followed by phase I, II and III human clinical trial to establish our hypothesis for better management of chemo-resistant ovarian cancer.

scholarly journals Ex vivo drug screening defines novel drug sensitivity patterns for informing personalized therapy in myeloid neoplasms

2020 ◽  
Vol 4 (12) ◽  
pp. 2768-2778 ◽  
Author(s):  
Michael A. Spinner ◽  
Alexey Aleshin ◽  
Marianne T. Santaguida ◽  
Steven A. Schaffert ◽  
James L. Zehnder ◽  
...  
Keyword(s):  
Feasibility Study ◽  
Predictive Value ◽  
Histone Deacetylase Inhibitors ◽  
Drug Sensitivity ◽  
Kinase Inhibitors ◽  
Ex Vivo ◽  
Personalized Therapy ◽  
Differential Sensitivity ◽  
Myeloid Neoplasms

Abstract Precision medicine approaches such as ex vivo drug sensitivity screening (DSS) are appealing to inform rational drug selection in myelodysplastic syndromes (MDSs) and acute myeloid leukemia, given their marked biologic heterogeneity. We evaluated a novel, fully automated ex vivo DSS platform that uses high-throughput flow cytometry in 54 patients with newly diagnosed or treatment-refractory myeloid neoplasms to evaluate sensitivity (blast cytotoxicity and differentiation) to 74 US Food and Drug Administration–approved or investigational drugs and 36 drug combinations. After piloting the platform in 33 patients, we conducted a prospective feasibility study enrolling 21 patients refractory to hypomethylating agents (HMAs) to determine whether this assay could be performed within a clinically actionable time frame and could accurately predict clinical responses in vivo. When assayed for cytotoxicity, ex vivo drug sensitivity patterns were heterogeneous, but they defined distinct patient clusters with differential sensitivity to HMAs, anthracyclines, histone deacetylase inhibitors, and kinase inhibitors (P < .001 among clusters) and demonstrated synergy between HMAs and venetoclax (P < .01 for combinations vs single agents). In our feasibility study, ex vivo DSS results were available at a median of 15 days after bone marrow biopsy, and they informed personalized therapy, which frequently included venetoclax combinations, kinase inhibitors, differentiative agents, and androgens. In 21 patients with available ex vivo and in vivo clinical response data, the DSS platform had a positive predictive value of 0.92, negative predictive value of 0.82, and overall accuracy of 0.85. These data demonstrate the utility of this approach for identifying potentially useful and often novel therapeutic drugs for patients with myeloid neoplasms refractory to standard therapies.

scholarly journals Ovarian Cancer Treatment Stratification Using Ex Vivo Drug Sensitivity Testing

2019 ◽  
Vol 39 (8) ◽  
pp. 4023-4030 ◽  
Author(s):  
INES LOHSE ◽  
DIANA J. AZZAM ◽  
HASSAN AL-ALI ◽  
CLAUDE-HENRY VOLMAR ◽  
SHAUN P. BROTHERS ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Treatment ◽  
Drug Sensitivity ◽  
Ex Vivo ◽  
Sensitivity Testing ◽  
Drug Sensitivity Testing

scholarly journals Targeting BCL-2, BCL-XL, BCL-W and MDM2 in B-Cell Acute Lymphoblastic Leukemia Is Highly Effective Ex Vivo

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3975-3975
Author(s):  
Helena Hohtari ◽  
Shady Awad ◽  
Olli Dufva ◽  
Swapnil Potdar ◽  
Caroline A Heckman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Tyrosine Kinase ◽  
B Cell ◽  
Research Funding ◽  
Drug Sensitivity ◽  
Kinase Inhibitors ◽  
Ex Vivo ◽  
Lymphoblastic Leukemia ◽  
Highly Sensitive

Abstract Despite the advances in the treatment of acute lymphoblastic leukemia (ALL), a major fraction of adult patients still succumb to leukemia- or treatment-related events. In particular, the outcome of elderly ALL patients remains dismal. Our aim was to discover new or repurposed drugs for B-cell ALL in a clinically relevant ex vivo drug sensitivity testing platform. We analyzed 19 primary B-ALL samples using a well-established drug sensitivity and resistance testing platform and a drug panel including 65 drugs in five different concentrations. The main drug classes were glucocorticoids, MDM2 antagonists, and inhibitors of BCR-ABL1, VEGFR, BCL-2, BCL-XL, BET, MEK, JAK, Aurora kinase, PI3K, MTOR, IGF1R, ERK, STAT3, STAT5, HSP90 and NAMPT proteins. The samples were viably frozen bone marrow (BM) mononuclear cells collected at diagnosis. The cohort included both Philadelphia-positive (Ph+) (n=10) and Ph-negative (Ph-) (n=9) patients with a median age of 43 years (range 22-68). Cell viability (CellTiter-Glo) was measured after plating and after a three-day incubation with the drugs. A drug sensitivity score (DSS) was calculated from the viability readouts, which takes into account the area under the dose response curve, measuring both drug efficacy and potency. DSS values >10 are considered effective and >20 highly effective. As an overall view of drug sensitivity, a heatmap and dendrograms from DSS values are shown in Figure 1A. As expected, most patients were sensitive to glucocorticoids and tyrosine kinase inhibitors (TKIs) showed efficacy in Ph+ ALL. In addition, two Ph-negative patients were sensitive to TKIs, suggesting a Philadelphia-like disease. Drugs that showed pan-ALL efficacy included BCL-2 family inhibitors, idasanutlin (MDM2 inhibitor), luminespib (HSP90 inhibitor), daporinad (NMPRT inhibitor) and plicamycin (antineoplastic antibiotic). For the other drugs, only individual patients showed sensitivity, in line with the diverse molecular background of ALL. Strikingly, 17/19 (89%) of patients in our cohort were highly sensitive (DSS>20) to navitoclax (a BCL-2, BCL-XL and BCL-W inhibitor), whereas the BCL-2-specific inhibitor venetoclax was effective only in a distinct subset of patients (Figure 1B). 6/19 (32%) of patients were highly sensitive (DSS>20) to venetoclax and represented all risk classes based on age, white blood cell counts and karyotype, but interestingly, all were Ph-negative. Overall, response to venetoclax correlated with response to navitoclax (Spearman, r=0.85; P<0.0001). To examine differential gene expression of anti-apoptotic proteins between Ph+ and Ph- patients, we analyzed microarray gene expression data from ArrayExpress public database (www.ebi.ac.uk/arrayexpress, E-MTAB-5035). The analyzed cohort included 96 Ph- and 41 Ph+ adult B-ALL patients. Ph-negative samples were characterized with higher BCL-2 expression, whereas Ph-positive samples showed higher BCL-W expression and a trend to higher BCL-XL expression (Figure 1C). Thus, lack of venetoclax efficacy ex vivo in Ph-positive ALL indicated dependence on BCL-W and BCL-XL, as also reflected in the gene expression analyses. Inhibitors of BCL-2, such as navitoclax and venetoclax, potently induce apoptosis in a variety of cancer cells. Both inhibitors showed promising efficacy in our B-ALL samples. Dose-limiting thrombocytopenia has limited the use of navitoclax in solid tumors. However, in our assay navitoclax showed more uniform potency, particularly in Ph+ samples suggesting a rational combination with tyrosine kinase inhibitors. Similar to conventional cytotoxic agents used in ALL, a therapeutic window may exist for safe use of navitoclax in acute leukemia. In conclusion, targeting the multidomain anti-apoptotic proteins (BCL-2, BCL-XL, BCL-W, MCL-1) and TP53 with MDM2, possibly in combination, is a promising strategy for improving outcome of adult B-ALL. Figure 1. Figure 1. Disclosures Hohtari: Incyte: Research Funding. Heckman:Novartis: Research Funding; Celgene: Research Funding; Orion Pharma: Research Funding. Wennerberg:Novartis: Research Funding. Mustjoki:Ariad: Research Funding; Pfizer: Honoraria, Research Funding; Celgene: Honoraria; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Porkka:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.

Identification Of AML Subtype-Selective Drugs By Functional Ex Vivo Drug Sensitivity and Resistance Testing and Genomic Profiling

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 482-482
Author(s):  
Tea Pemovska ◽  
Mika Kontro ◽  
Bhagwan Yadav ◽  
Henrik Edgren ◽  
Samuli Eldfors ◽  
...  
Keyword(s):  
Research Funding ◽  
Drug Response ◽  
Drug Sensitivity ◽  
Kinase Inhibitors ◽  
Ex Vivo ◽  
Resistance Testing ◽  
Clinical Use ◽  
Second Line ◽  
Flt3 Mutations ◽  
Flt3 Inhibitors

Introduction Adult acute myeloid leukemia (AML) exemplifies the challenges of modern cancer drug discovery and development in that molecularly targeted therapies are yet to be translated into clinical use. No effective second-line therapy exists once standard chemotherapy fails. While many genetic events have been linked with the onset and progression of AML, the fundamental disease mechanisms remain poorly understood. There is significant genomic and molecular heterogeneity among patients. Several targeted therapies have been investigated for improved second-line AML therapy but none has been approved for clinical use to date. It would be critically important to identify patient subgroups that would benefit from such therapies and to identify combinations of drugs that are likely to be effective. Methods To identify and optimize novel therapies for AML, we studied 28 samples from 18 AML patients with an individualized systems medicine (ISM) approach. The ISM platform includes functional profiling of AML patient cells ex vivo with drug sensitivity and resistance testing (DSRT), comprehensive molecular profiling as well as clinical background information. Data integration was done to identify disease- and patient-specific molecular vulnerabilities for translation in the clinic. The DSRT platform comprises 306 anti-cancer agents, each tested in a dose response series. We calculated differential drug sensitivity scores by comparing AML responses to those of control cells in order to distinguish cancer-specific drug effects. Next generation RNA- and exome-sequencing was used to identify fusion transcripts and mutations that link to drug sensitivities. Results Individual AML patient samples had a distinct drug sensitivity pattern, but unsupervised hierarchical clustering of the drug sensitivity profiles of the 28 AML patient samples identified 5 functional AML drug response subtypes. Each subtype was characterized by distinct combinations of sensitivities: Bcl-2 inhibitors (e.g. navitoclax; Group 1), JAK inhibitors (e.g. ruxolitinib) (Group 2) and MEK inhibitors (e.g. trametinib) (Groups 2 and 4), PI3K/mTOR inhibitors (e.g. temsirolimus; Groups 4 and 5), broad spectrum receptor tyrosine kinase inhibitors (e.g. dasatinib) (Groups 3, 4 and 5) and FLT3 inhibitors (e.g. quizartinib, sunitinib) (Group 5). Correlation of overall drug responses with genomic profiles revealed that RAS and FLT3 mutations were significantly linked with the drug response subgroups 4 and 5, respectively. Activating FLT3 mutations contributed to sensitivity to FLT3 inhibitors, as expected, but also to tyrosine kinase inhibitors not targeting FLT3, such as dasatinib. Hence, these data point to the potential synergistic combinatorial effects of FLT3 inhibitors with dasatinib for improved therapy outcome (Figure). Early clinical translational results based on compassionate use support this hypothesis. Therefore, by combinations of drugs we expect to see synergistic drug responses that can be translated into efficacious and safe therapies for relapsed AML cases in the clinic. Clinical application of DSRT results in the treatment of eight recurrent chemorefractory patients led to objective responses in three cases according to ELN criteria, whereas four of the remaining five patients had meaningful responses not meeting ELN criteria. After disease progression, AML patient cells showed ex vivo resistance to the drugs administered to the patients, as well as significant changes in clonal architecture during treatment response. Furthermore, we saw genomic alterations potentially explaining drug resistance, such as appearance of novel fusion genes. Summary The ISM approach represents an opportunity for improving therapies for cancer patients, one patient at the time. We show that the platform can be used to identify functional groups of AML linking to vulnerabilities to single targeted drugs and, importantly, unexpected drug combinations. This information can in turn be used for personalized medicine strategies and for creating hypotheses to be explored in systematic clinical trials, both for approved and investigational drugs. Disclosures: Off Label Use: Many of the compounds included in our DSRT platform are not indicated for AML therapy. Mustjoki:BMS: Honoraria, Research Funding; Novartis: Honoraria. Porkka:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Kallioniemi:Medisapiens: Membership on an entity’s Board of Directors or advisory committees; Roche: Research Funding.

scholarly journals Correlating Clinical and Genomic Features with Ex Vivo Drug Sensitivity in Patients with Myelodysplastic Syndromes and Related Myeloid Neoplasms

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 19-20
Author(s):  
Michael A Spinner ◽  
Steven A Schaffert ◽  
Alexey Aleshin ◽  
Marianne T Santaguida ◽  
Hiroomi Tada ◽  
...  
Keyword(s):  
Research Funding ◽  
Drug Sensitivity ◽  
Kinase Inhibitors ◽  
Ex Vivo ◽  
Parp Inhibitors ◽  
Differential Sensitivity ◽  
Genomic Features ◽  
Secondary Aml ◽  
Myeloid Neoplasms ◽  
Drug Classes

Background Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms characterized by ineffective hematopoiesis, dysplasia, cytopenias, and a variable risk of progression to acute myeloid leukemia (AML). The biologic heterogeneity of MDS and related myeloid neoplasms relates to the genomic complexity of these disorders with different combinations of cytogenetic abnormalities and mutations associated with distinct clinical phenotypes. Ex vivo drug sensitivity screening (DSS) is a promising tool that may inform personalized therapy in MDS, particularly in patients refractory to standard therapies such as hypomethylating agents (HMAs). We report our updated experience using a fully automated ex vivo DSS platform in 64 patients with MDS and related myeloid neoplasms and identify correlations between clinical and genomic features and ex vivo drug sensitivity. Methods Patients: Patients were evaluated at the Stanford MDS Center between September 2016 and May 2020 and had a diagnosis of MDS, MDS/MPN, or secondary AML. Bone marrow (BM) aspirate and peripheral blood (PB) samples were procured for mutation testing (164-gene panel) and ex vivo DSS (Notable Labs, Foster City, CA). Ex vivo DSS: Fresh BM aspirate and PB specimens were RBC-lysed and resuspended in serum-free media with cytokines as previously described (Spinner et al, Blood Adv 2020;4(12):2768-78). Samples were plated in 384-well microtiter plates and screened against a collection of up to 74 drugs and 36 drug combinations in triplicate. Specimens were treated for 72 hours and assayed using high-throughput, multi-parametic flow cytometry, gating on the blast population (expressing CD34, CD33, and/or HLA-DR) to assess for blast viability. Patient clustering & statistical analysis: The Euclidean distance metric and Ward minimum variance method were used to identify patient clusters with distinct ex vivo drug sensitivity patterns. A 1-way repeated measures ANOVA was used to identify drug classes with variable sensitivity across clusters and to identify associations between clusters and clinical variables, including blast count, mutations and cytogenetic groups, IPSS-R risk group, and prior HMA exposure. A generalized estimation equation model was used to identify associations between mutations and ex vivo drug sensitivity. Results Ex vivo DSS was performed in 64 patients with myeloid neoplasms including 43 with MDS (67%), 11 with MDS/MPNs (17%), and 10 with secondary AML (16%). The median age was 75 years (range 23-90) and 78% were male. The majority of patients had higher risk disease with IPSS-R &gt;3.5 (66%), excess blasts (58%), and adverse cytogenetics or mutations (53%) by IPSS-R or the ELN classification. Patients had a median of 2 pathogenic mutations (range 0-7), with the most frequent including TET2, ASXL1, DNMT3A, SF3B1, RUNX1, STAG2, SRSF2, NRAS, KRAS, BCOR, TP53, and EZH2. The majority of patients (64%) had prior HMA exposure. Ex vivo DSS defined three distinct patient clusters with differential sensitivity to numerous drug classes (Figure 1). Cluster 1 (N=13) demonstrated the greatest ex vivo sensitivity to HMAs, HMA/venetoclax combinations, cytotoxic agents, kinase inhibitors, mTOR inhibitors, HDAC inhibitors, and PARP inhibitors, while cluster 3 (N=19) demonstrated the greatest ex vivo resistance (p&lt;0.0001 for all comparisons). Correlating clinical variables with drug sensitivity clusters, only IPSS-R score differed significantly among clusters, with fewer higher risk patients in cluster 3 (p=0.02). Correlating specific mutations with ex vivo drug sensitivity, STAG2 mutations were associated with greater ex vivo sensitivity to HMAs (p=0.002), HMA/venetoclax combinations (p=0.003), kinase inhibitors (p=0.002), and PARP inhibitors (p=0.003). TP53 mutations were associated with greater ex vivo sensitivity to proteasome inhibitors (p=0.0002). Conclusions Ex vivo DSS defined distinct patient clusters with differential sensitivity to numerous drug classes. Specific mutations, such as STAG2 and TP53, were associated with greater ex vivo sensitivity to specific drug classes. A larger sample size is needed to evaluate combinations of mutations and better define associations between genotype and drug sensitivity phenotype. Ultimately, combining both genomics and functional screening may further refine personalized therapy selection for patients with MDS and related myeloid neoplasms. Figure Disclosures Spinner: Notable Labs: Honoraria. Schaffert:Notable Labs: Current Employment. Aleshin:Notable Labs: Consultancy. Santaguida:Notable Labs: Current Employment. Tada:Notable Labs: Current Employment, Current equity holder in private company. Greenberg:BMS: Research Funding; Aprea: Research Funding; H3 Biotech: Research Funding; Notable Labs: Research Funding.

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

2020 ◽  
Vol 11 (9) ◽  
Author(s):  
Hanna Karvonen ◽  
Mariliina Arjama ◽  
Laura Kaleva ◽  
Wilhelmiina Niininen ◽  
Harlan Barker ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cell Lines ◽  
Drug Testing ◽  
Kinase Inhibitors ◽  
Molecular Subtype ◽  
Ex Vivo ◽  
Immunosuppressive Agents ◽  
Phenotypic Expression ◽  
Differentiation Markers ◽  
Smac Mimetics

Abstract 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.

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