scholarly journals ATR/CHK1/WEE1 Dependency in SRSF2-Mutated MDS/AML

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3661-3661
Author(s):  
Samuli Eldfors ◽  
Sumit Rai ◽  
Vineet Sharma ◽  
Angelique N Gilbert ◽  
Kimmo Porkka ◽  
...  

Abstract Background: Mutations in splicing factor gene SRSF2 are recurrent drivers in 5-15 % of patients with myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). A key property of SRSF2 mutations is that they occur early in the pathogenesis of MDS and are therefore present in all tumor cells in a patient. This property makes targetable vulnerabilities caused by SRSF2 mutations exceptionally important as they provide a way to inhibit the whole tumor. We previously demonstrated that splicing factor mutations induce R-loop-dependent activation of ATR, rendering cells sensitive to ATR inhibition. R-loops are transcription intermediates consisting of an RNA:DNA hybrid and a displaced single-stranded DNA. Accumulation of aberrant R-loops induces the ATR kinase, which activates the G2-M cell cycle checkpoint via CHK1- and WEE1-mediated signaling. In normal cells, activation of the G2-M checkpoint halts the cell cycle until R-loops have been resolved. When the ATR pathway is inhibited, checkpoint activation does not occur, causing cells with unresolved R-loops to proceed to mitosis, resulting in DNA damage and cell death. We, therefore, sought to assess primary human MDS/AML samples for sensitivity to perturbation of the ATR/CHK1/WEE1 pathway and identify mechanisms of resistance. Methods: Sensitivity of 147 AML patient samples to 515 oncology drugs was tested ex vivo. Bone marrow mononuclear cells were incubated with 5 concentrations of each drug for 72 h followed by measurement of cell viability by CTG assay. Somatic mutations were identified by exome sequencing of matched leukemic bone marrow and skin biopsy samples. Isogenic K562 cell line clones carrying SRSF2 P95H/L/R mutations were generated using CRISPR/Cas9 editing. The presence of SRSF2 mutation was confirmed by CRISPR-sequencing and expression by whole transcriptome RNA-sequencing. Drug sensitivity of the K562 clones with and without SRSF2 mutation was determined by incubating cells with 16 concentrations of prexasertib, SRA-737, adavosertib, or BAY-1895344, followed by determination of cell viability by the MTS assay. Results: Analysis of ex vivo drug sensitivities in AML patient samples identified vulnerability to CHK1 and WEE1 inhibition in SRSF2-mutated AML: SRSF2 mutation is associated with sensitivity to the CHK1 inhibitors prexasertib (p = 0.006) (Fig 1 A and B) and PF-00477736 (p = 0.002) and the WEE1 inhibitor adavosertib (p = 0.003). To establish whether the isogenic SRSF2-mutant K562 cell line models recapitulate known downstream aberrations associated with SRSF2 mutations in patients, we analyzed gene expression and splicing. SRSF2 contains an RNA binding domain with affinity to CCNG or GGNG exonic splicing enhancer sequences. Similar to what has been observed in patients, the K562 clones with SRSF2 mutation show reduced use of GGNG sequence motifs at skipped exons. These results demonstrate that isogenic K562 clones recapitulate known alterations caused by mutant SRSF2. To determine whether SRSF2 mutations induce sensitivity to inhibition of ATR, CHK1, and WEE1, we tested 10 isogenic SRSF2 mutant and 4 wild-type K562 clones. Cells with SRSF2 mutation show increased sensitivity to ATR/CHK1/WEE1 inhibition (Fig 1C). We found no significant difference in drug sensitivity between clones carrying SRSF2 P95H/L/R substitutions. Clones with higher SRSF2 mutant allele dosage are more sensitive (Fig 1D). We identified a subset of SRSF2 mutated AML samples that were resistant to CHK1 and WEE1 inhibition. All resistant AML have co-occurring RUNX1 mutations (Fig 1B). In AML, RUNX1 mutations are associated with therapy resistance, suggesting that these mutations contribute to drug resistance. To test whether RUNX1 mutations induce resistance to ATR/CHK1/WEE1 inhibition in SRSF2-mutant leukemia, we introduced RUNX1 loss-of-function mutations in isogenic K562 carrying SRSF2 mutations. Candidate resistance factors identified by ATAC and RNA-sequencing will be validated in functional assays. Conclusions: Our results indicate that SRSF2-mutated leukemia harbor a vulnerability to the inhibition of ATR, CHK1, and WEE1 kinases. Cell line models indicate that sensitivity is similar across mutant alleles and dependent on allelic copy number. Several ATR/CHK1 and WEE1 inhibitors are in development, and our results suggest that these compounds could be effective treatments for SRSF2-mutated MDS and AML. Figure 1 Figure 1. Disclosures Graubert: astrazeneca: Research Funding; Janssen: Research Funding; Calico: Research Funding.

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2487-2487
Author(s):  
Mika Kontro ◽  
Caroline Heckman ◽  
Evgeny Kulesskiy ◽  
Tea Pemovska ◽  
Maxim Bespalov ◽  
...  

Abstract Abstract 2487 Introduction: The molecular drivers of adult AML as well as the determinants of drug response are poorly understood. While AML genomes have recently been sequenced, many cases do not harbor druggable mutations. Treatment options are particularly limited for relapsed and refractory AML. Due to the molecular heterogeneity of the disease, optimal therapy would likely consist of individualized combinations of targeted and non-targeted drugs, which poses significant challenges for the conventional paradigm of clinical drug testing. In order to better understand the molecular driver signals, identify individual variability of drug response, and to discover clinically actionable therapeutic combinations and future opportunities with emerging drugs, we established a diagnostic ex-vivo drug sensitivity and resistance testing (DSRT) platform for adult AML covering the entire cancer pharmacopeia as well as many emerging anti-cancer compounds. Methods: DSRT was implemented for primary cells from adult AML patients, focusing on relapsed and refractory cases. Fresh mononuclear cells from bone marrow aspirates (>50% blast count) were screened in a robotic high-throughput screening system using 384-well plates. The primary screening panel consisted of a comprehensive collection of FDA/EMA-approved small molecule and conventional cytotoxic drugs (n=120), as well as emerging, investigational and pre-clinical oncology compounds (currently n=90), such as major kinase (e.g. RTKs, checkpoint and mitotic kinases, Raf, MEK, JAKs, mTOR, PI3K), and non-kinase inhibitors (e.g. HSP, Bcl, activin, HDAC, PARP, Hh). The drugs are tested over a 10,000-fold concentration range resulting in a dose-response curve for each compound and with combinations of effective drugs explored in follow-up screens. The same samples also undergo deep molecular profiling including exome- and transcriptome sequencing, as well as phosphoproteomic analysis. Results: DSRT data from 11 clinical AML samples and 2 normal bone marrow controls were bioinformatically processed and resulted in several exciting observations. First, overall drug response profiles of the AML samples and the controls were distinctly different suggesting multiple leukemia-selective inhibitory effects. Second, the MEK and mTOR signaling pathways emerged as potential key molecular drivers of AML cells when analyzing targets of leukemia-specific active drugs. Third, potent new ex-vivo combinations of approved targeted drugs were uncovered, such as mTOR pathway inhibitors with dasatinib. Fourth, data from ex-vivo DSRT profiles showed excellent agreement with clinical response when serial samples were analyzed from leukemia patients developing clinical resistance to targeted agents. Summary: The rapid and comprehensive DSRT platform covering the entire cancer pharmacopeia and many emerging agents has already generated powerful insights into the molecular events underlying adult AML, with significant potential to facilitate individually optimized combinatorial therapies, particularly for recurrent leukemias. DSRT will also serve as a powerful hypothesis-generator for clinical trials, particularly for emerging drugs and drug combinations. The ability to correlate response profiles of hundreds of drugs in clinical ex vivo samples with deep molecular profiling data will yield exciting new translational and pharmacogenomic opportunities for clinical hematology. Disclosures: Mustjoki: Novartis: Honoraria; Bristol-Myers Squibb: Honoraria. Porkka:Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Kallioniemi:Abbot/Vysis: Patents & Royalties; Medisapiens: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Bayer Schering Pharma: Research Funding; Roche: Research Funding.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 288-288
Author(s):  
Caroline A Heckman ◽  
Mika Kontro ◽  
Tea Pemovska ◽  
Samuli Eldfors ◽  
Henrik Edgren ◽  
...  

Abstract Abstract 288 Introduction: Recent genomic analyses of acute myeloid leukemia (AML) patients have provided new information on mutations contributing to the disease onset and progression. However, the genomic changes are often complex and highly diverse from one patient to another and often not actionable in clinical care. To rapidly identify novel patient-specific therapies, we developed a high-throughput drug sensitivity and resistance testing (DSRT) platform to experimentally validate therapeutic options for individual patients with relapsed AML. By integrating the results with exome and transcriptome sequencing plus proteomic analysis, we were able to define specific drug-sensitive subgroups of patients and explore predictive biomarkers. Methods: Ex vivo DSRT was implemented for 29 samples from 16 adult AML patients at the time of relapse and chemoresistance and from 5 healthy donors. Fresh mononuclear cells from bone marrow aspirates (>50% blast count) were screened against a comprehensive collection of cytotoxic chemotherapy agents (n=103) and targeted preclinical and clinical drugs (n=100, later 170). The drugs were tested over a 10,000-fold concentration range resulting in a dose-response curve for each compound and each leukemia sample. A leukemia-specific drug sensitivity score (sDSS) was derived from the area under each dose response curve in relation to the total area, and comparing leukemia samples with normal bone marrow results. The turnaround time for the DSRT assay was 4 days. All samples also underwent deep exome (40–100×) and transcriptome sequencing to identify somatic mutations and fusion transcripts, as well as phosphoproteomic array analysis to uncover active cell signaling pathways. Results: The drug sensitivity profiles of AML patient samples differed markedly from healthy bone marrow controls, with leukemia-specific responses mostly observed for molecularly targeted drugs. Individual AML patient samples clustered into distinct subgroups based on their chemoresponse profiles, thus suggesting that the subgroups were driven by distinct signaling pathways. Similarly, compounds clustered based on the response across the samples revealing functional groups of compounds of both expected and unexpected composition. Furthermore, subsets of patient samples stood out as highly sensitive to different compounds. Specifically, dasatinib, rapalogs, MEK inhibitors, ruxolitinib, sunitinib, sorafenib, ponatinib, foretinib and quizartinib were found to be selectively active in 5 (31%), 5 (31%), 4 (25%), 4 (25%), 3 (19%), 3 (19%), 2 (13%), 2 (13%), and 1 (6%) of the AML patients ex vivo, respectively. DSRT assays of serial samples from the same patient at different stages of leukemia progression revealed patterns of resistance to the clinically applied drugs, in conjunction with evidence of dynamic changes in the clonal genomic architecture. Emergence of vulnerabilities to novel pathway inhibitors was seen at the time of drug resistance, suggesting potential combinatorial or successive cycles of drugs to achieve remissions in an increasingly chemorefractory disease. Genomic and molecular profiling of the same patient samples not only highlighted potential biomarkers reflecting the ex vivo DSRT response patterns, but also made it possible to follow in parallel the drug sensitivities and the clonal progression of the disease in serial samples from the same patients. Summary: The comprehensive analysis of drug responses by DSRT in samples from human chemorefractory AML patients revealed a complex pattern of sensitivities to distinct inhibitors. Thus, these results suggest tremendous heterogeneity in drug response patterns and underline the relevance of individual ex vivo drug testing in selecting optimal therapies for patients (personalized medicine). Together with genomic and molecular profiling, the DSRT analysis resulted in a comprehensive view of the drug response landscape and the underlying molecular changes in relapsed AML. These data can readily be translated into the clinic via biomarker-driven stratified clinical trials. Disclosures: Mustjoki: Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria. Kallioniemi:Roche: Research Funding; Medisapiens: Membership on an entity's Board of Directors or advisory committees. Porkka:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 475-475
Author(s):  
Y. Lynn Lynn Wang ◽  
Carrie Franzen ◽  
Shengchun Wang ◽  
Girish Venkataraman ◽  
Lei Li ◽  
...  

Ibrutinib (Ibr) is a specific inhibitor of Bruton tyrosine kinase, a component of the B-cell receptor (BCR) signaling. Venetoclax (Veneto) inhibits the anti-apoptotic protein BCL2. Both drugs are highly effective as monotherapy against chronic lymphocytic leukemia (CLL) (Byrd NEJM, Roberts, NEJM, 2015 and Roberts, Blood, 2019) and clinical trials using the combination therapy are ongoing. An interesting clinical observation is that the tumor cell sensitivity to these two drugs differ between different anatomic compartments. While lymph node-resident CLL cells are more sensitive to ibr, circulating CLL cells in the peripheral blood are more sensitive to the action of veneto. When these two drugs are used in combination to treat relapsed/refractory (Hillman ASH 2018 and Kater EHA 2019) or previously untreated CLL patients (Jain NEJM 2019), rate of complete response significantly increases compared to single drug alone. Moreover, negativity of bone marrow minimal residual disease continues to improve over time. However, the reason behind these observed compartmental responses is largely unknown, and we investigated the differential response using an ex vivo model that promotes CLL proliferation (CLL proliferation model). A better understanding of how these two drugs synergize would eventually help develop other rational combination strategies. We established the ex vivo model using fibroblasts derived from the bone marrow of a CLL patient. In this model, CLL cells closely interact with the bone marrow fibroblasts (BMF) (Fig.1) and divide and proliferate for several generations, as measured by CFSE labeling. The culture, in some cases, may continue for 10 weeks before cell death ensues. With this ability to promote long-term cell proliferation, the model recapitulates one of the most salient features observed histologically in the "proliferation centers" of the CLL lymph nodes. With the proliferation model, we first tested the effects of ibrutinib on cell division/proliferation as well as cell viability in samples taken from 30 CLL patients consisting of 22 ibr-naïve (thus sensitive) and 8 ibr-relapsed (thus resistant) patients. We demonstrate that there was lack of a significant inhibition of ibr on cell viability. In comparison, Ibr markedly inhibited cell proliferation in cells from ibr-naïve/sensitive patients (p<0.0001), while such inhibition was much less prominent in cells from ibr-relapsed/resistant patients (p=0.053). Overall, our data demonstrate that only the dividing subpopulation of CLL responds to ibr, and this response is highly correlated with patients' clinical response to the drug while cell viability responses are not. With the CLL proliferation model, we also evaluated how veneto works. Veneto, as expected, markedly decreased cell viability at clinically achievable concentrations. CFSE profiles of the remaining live cells, however, revealed an interesting pattern of distribution, showing that veneto induces cell death but it preferentially kills the resting CLL population (Fig. 2). In other words, the resting subpopulation of CLL, instead of the dividing one, preferentially responds to veneto as compared to ibr. Combination of the two drugs, as expected, worked most effectively, significantly reducing the total number of live cells, both resting and dividing subpopulations, in all cases. Analyses of CFSE profiles became less meaningful in many of these cases due to the small number of live cells remaining after the combination treatment. In conclusion, our study, comparing the actions of ibr and veneto in a clinically relevant CLL proliferation model, demonstrates for the first time that the drugs target distinct subpopulations of CLL cells with different proliferative capacity. The data also suggest that single drug therapy may leave a subpopulation behind that would potentially rise to cause a future relapse. Our study provides a strong laboratory rationale explaining why combining these two drugs has the potential to eradicate CLL disease. The findings are also in line with the clinical observations regarding the compartmental response; ibrutinib works primarily on the lymph nodes where CLL cells divide in the "proliferation centers" and veneto acts preferentially on the circulating CLL cells that are mostly non-dividing and resting. Disclosures Wang: Incyte Reaserch Institute: Employment. Ma:Abbvie: Research Funding; Xeme: Research Funding; Novartis: Research Funding; Bioverativ: Consultancy; Janssen: Consultancy, Speakers Bureau; Beigene: Research Funding; Kite: Consultancy; Gilead: Research Funding; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Acerta: Research Funding; Astra Zeneca: Consultancy, Research Funding, Speakers Bureau; Genentech: Consultancy; Incyte: Research Funding; Juno: Research Funding. Larson:Celgene: Consultancy; Agios: Consultancy; Novartis: Honoraria, Other: Contracts for clinical trials.


Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2130
Author(s):  
Regiane Costa de Oliveira ◽  
Gemilson Soares Pontes ◽  
Aleksandr Kostyuk ◽  
Gabriel B. Coutinho Camargo ◽  
Anamika Dhyani ◽  
...  

Cancer still remains a major public health concern around the world and the search for new potential antitumor molecules is essential for fighting the disease. This study evaluated the anticancer and immunomodulatory potential of the newly synthetized ellipticine derivate: sodium bromo-5,11-dimethyl-6H-pyrido[4,3-b]carbazole-7-sulfonate (Br-Ell-SO3Na). It was prepared by the chlorosulfonation of 9-bromoellipticine. The ellipticine-7-sulfonic acid itself is not soluble, but its saponification with sodium hydroxide afforded a water-soluble sodium salt. The cytotoxicity of Br-Ell-SO3Na was tested against cancerous (K562 cell line) and non-cancerous cells (Vero cell line and human peripheral blood mononuclear cells (PBMC)) using a Methylthiazoletetrazolium (MTT) assay. Cell cycle arrest was assessed by flow cytometry and the immunomodulatory activity was analyzed through an enzyme-linked immunosorbent assay (ELISA). The results showed that the Br-Ell-SO3Na molecule has specific anticancer activity (IC50 = 35 µM) against the K562 cell line, once no cytotoxicity effect was verified against non-cancerous cells. Cell cycle analysis demonstrated that K562 cells treated with Br-Ell-SO3Na were arrested in the phase S. Moreover, the production of IL-6 increased and the expression of IL-8 was inhibited in the human PBMC treated with Br-Ell-SO3Na. The results demonstrated that Br-Ell-SO3Na is a promising anticancer molecule attested by its noteworthy activity against the K562 tumor cell line and immunomodulatory activity in human PBMC cells.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 5004-5004
Author(s):  
Yuliya Linhares ◽  
Jade Dardine ◽  
Siavash Kurdistani

Abstract Abstract 5004 Introduction: Amiloride is an FDA approved potassium-sparing diuretic which targets Na+/H+ exchanger isoform 1 (NHE1). NHE1 is responsible for the regulation of the intracellular pH, as well as cell-cycle and apoptosis. In supra-pharmacologic concentrations, amiloride non-specifically inhibits protein kinases. Recent study demonstrated that proapoptotic effect of amiloride in CML cell lines is linked to the modulation of the alternative splicing of Bcl-x, HIPK3, and BCR/ABL genes and is independent of pHi. Here, we demonstrate that pharmacologic doses of amiloride preferentially induce growth inhibition, cell cycle arrest and apoptosis in Flt3-ITD positive acute myeloid leukemia cell lines as compared to Bcr-Abl positive leukemia cell line. Our data suggests that amiloride may have an effect on Flt3 signaling and that its treatment potential for Flt3-ITD positive acute myeloid leukemia needs to be explored. Methods: MV4-11, MOLM13 and K562 cells lines in log-phase growth were used for the experiments. Analysis of the baseline Flt3 expression and phosphorylation status was assessed via Flt3 immunoprecipitation and Western blotting for Flt3 and phosphotyrosine. Cells were incubated with various amiloride concentrations; equal volume dilutions of DMSO were used for control. Cell counting and trypan blue exclusion viability was performed on TC10 Bio-Rad automated cell counter. The cell cycle analysis was performed applying propidium iodide staining. To assess for apoptosis and cell death, we used annexin V/PI staining kit and flow cytometry. Results: MOLM13 and MV4-11 cell lines carry activating Flt3-ITD mutation. We confirmed the expression and constituative activation of Flt3 in MOLM13 and MV4-11 cells with Western blotting. Flt3 protein was not detectable in K562 cell line. Amiloride at 0.025 mM and 0.05 mM completely inhibited the growth of MV4-11 cells after 24 hrs of treatment with no significant increase in total or live cell numbers at 72 hrs, but only mildly affected K562 cell proliferation. While the above amiloride concentrations caused cell death in MV4-11 and MOLM13 cell lines, there was no increased cell death in K562 cells. Incubation of MOLM13 and MV4-11 cell lines with 0.05 mM amiloride for 20 hrs induced cell cycle arrest. In MV4-11 cell line, the proportion of S phase cells after amiloride treatment was 15.4% (SD=5.4%) as compared to 31.3% (SD=1.4%) in control. MOLM13 cell line demonstrated 15.3% (SD=4.7%) of cells in S after amiloride treatment as compared to 35.3% (SD=2.4%) cells in S phase in control treatment. In K562 cell line, there was less effect with 52% (SD=4.2%) of cells in S phase in control as compared to 37% (SD=8.9%) in amiloride treatment. MV4-11 and MOLM 13 cell lines were more sensitive than K562 cells to amiloride induced apoptosis with 28.8% (control 12.7%) of MV4-11 cells, 11.4% (control 7.4%) of MOLM13 cells, and 11.4% (control 8.6%) of K562 cells being apoptotic after 20 hr treatment with 0.05mM amiloride. At 72 hrs of amiloride treatment 34% (control 1.5%) of MV4-11 cells, 17% (control 5%) of MOLM13 cells and 11% of K562 cells (control 8.9%) were apoptotic. Amiloride had similar effect on the number of dead cells with no increase in total cell death in K562 cell line. Upon treatment with increasing amiloride concentrations, there was dose-dependent increase in cell death and apoptosis in all three cell lines with K562 line showing relative resistance to amiloride. Discussion: Our results demonstrate that amiloride induces cell cycle arrest and inhibits proliferation of Flt3-ITD positive cell lines MV4-11 and MOLM13 as well as K562 cell line at a pharmacologic concentration of 0.05 mM. Both, cell cycle arrest and antiproliferative effect are more pronounced in Flt3-ITD positive cells lines while it is mild in Bcr-Abl positive K562 cell line. Pharmacologic doses of amiloride induce cell death and apoptosis in Flt3-ITD positive cell lines but not in K562 cell line. Both, Bcr-Abl and Flt3 signaling stimulates proliferation and inhibits apoptosis in myeloid leukemia cells. Our study suggests that amiloride may induce cell cycle arrest and apoptosis via modulating Flt3 signaling cascade. We are currently investigating the effects of amiloride on Flt3 phosphorylation. In conclusion, our data suggests that amiloride presents a potential treatment option for Flt3-ITD positive acute myeloid leukemia. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3139-3139
Author(s):  
Paavo Pietarinen ◽  
Tea Pemovska ◽  
Emma I Andersson ◽  
Perttu Koskenvesa ◽  
Mika Kontro ◽  
...  

Abstract BACKGROUND Most patients with chronic phase (CP) chronic myeloid leukemia (CML) are successfully treated with tyrosine kinase inhibitors (TKIs) targeting ABL1. Despite the good results, TKI treatment rarely results in cure, and some patients relapse and progress to advanced phases of CML. Accelerated phase and blast crisis (BC) have remained a therapy challenge. We set out to identify novel candidate drugs for chronic and advanced phase CML by using an unbiased high-throughput drug testing platform and utilizing both primary patient cells (CP and BC) and cell lines. METHODS CML BC cell lines used: K562 (erythroleukemic), MOLM-1 (megakaryocytic) and EM-2 (myeloid). Primary bone marrow (BM) and peripheral blood (PB) samples were derived from 3 CML patients with BC, two of which were TKI-resistant. Patient 1 had developed resistance to imatinib and nilotinib due to an E274K mutation in ABL1 kinase domain, whereas patient 2 was resistant to imatinib, nilotinib, and dasatinib due to a T315I mutation. In addition to BC patients, samples from 23 newly diagnosed CML CP patients were screened. BM cells from 4 healthy individuals were used as controls. Functional profiling of drug responses was performed with a high-throughput drug sensitivity and resistance testing (DSRT) platform comprising 306 anti-cancer agents. Cells were dispensed to pre-drugged 384-well plates and incubated for 72 h. Cell viability was measured using a luminescence cell viability assay (CellTiter-Glo, Promega). A Drug Sensitivity Score (DSS) was calculated for each drug using normalized dose response curve values. The drug sensitivities of the primary cells were further normalized against the median values from healthy controls, resulting in leukemia-specific sensitivity scores (sDSS). RESULTS Drug sensitivities of CML cell lines correlated closely (EM-2 vs. K-562, rS=0.89; EM-2 vs. MOLM-1, rS=0.82; K-562 vs. MOLM-1, rS=0.78; p<0.0001 for all correlations). Similarly, patient samples had good correlation with cell line samples (rS=0.82 based on median values; p<0.0001). The cell lines were highly sensitive to ABL1-targeted TKIs, with the exception of the MOLM-1, which showed only modest sensitivity (Figure). The clinically TKI-resistant patient samples were also resistant to BCR-ABL1 inhibitors ex vivo (e.g. T315I sensitive only to ponatinib), further validating the DSRT assay data. Other drugs that exhibited high DSS in the CML cell lines and high sDSS in the BC patient samples included mTORC1/2 inhibitors (e.g. AZD8055, AZD2014, INK128), HSP90 inhibitors (e.g. NVP-AUY922, BIIB021) and a NAMPT inhibitor daporinad. Remarkably, the DSRT results from newly diagnosed CML CP differed clearly from those derived from the cell line and CML BC samples. In the clustering analysis, CML BC and cell line samples clustered together, whereas CML CP samples formed a separate group (Figure). The leukemia-specific scores were generally much lower in CML CP samples, which made identifying novel candidate compounds challenging. Most surprisingly the responses to TKIs were practically nonexistent in CML CP samples. CP TKI insensitivity was further assessed with primary cells sorted in CD34pos and CD34neg fractions. Preliminary results from two patients suggested that CD34pos cells were more sensitive to TKIs when compared to CD34neg or whole mononuclear fraction. CONCLUSIONS DSRT is a powerful platform for identifying novel candidate molecules for CML BC patients. Our results indicate that mTORC1/2 inhibitors (such as AZD8055, or AZD2014), HSP90 (such as NVP-AUY922/luminespib) and NAMPT inhibitors in particular warrant further clinical evaluation. TKI-insensitivity of CML CP samples suggests that the survival of mature myeloid cells in vitro is not BCR-ABL1 dependent and reflects a clear biological difference between CP and BC patient cells. Figure 1 Figure 1. Disclosures Kallioniemi: Medisapiens: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mustjoki:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Porkka:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1541-1541
Author(s):  
Jeffrey W. Tyner ◽  
Brian J. Druker ◽  
Cristina E. Tognon ◽  
Stephen E Kurtz ◽  
Leylah M. Drusbosky ◽  
...  

Abstract Background: New prognostic factors have been recently identified in AML patient population that include frequent mutations of receptor tyrosine kinases (RTK) including KIT, PDGFR, FLT3, that are associated with higher risk of relapse. Thus, targeting RTKs could improve the therapeutic outcome in AML patients. Aim: To create a digital drug model for dasatinib and validate the predicted response in AML patient samples with ex vivo drug sensitivity testing. Methods: The Beat AML project (supported by the Leukemia & Lymphoma Society) collects clinical data and bone marrow specimens from AML patients. Bone marrow samples are analyzed by conventional cytogenetics, whole-exome sequencing, RNA-seq, and an ex vivo drug sensitivity assay. For 50 randomly chosen patients, every available genomic abnormality was inputted into a computational biology program (Cell Works Group Inc.) that uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated pathways. Digital drug simulations with dasatinib were conducted by quantitatively measuring drug effect on a composite AML disease inhibition score (DIS) (i.e., cell proliferation, viability, and apoptosis). Drug response was determined based on a DIS threshold reduction of > 65%. Computational predictions of drug response were compared to dasatinib IC50 values from the Beat AML ex vivo testing. Results: 23/50 (46%) AML patients had somatic mutations in an RTK gene (KIT, PDGFR, FLT3 (ITD (n=15) & TKD (n=4)), while 27/50 (54%) were wild type (WT) for the RTK genes. Dasatinib showed ex vivo cytotoxicity in 9/50 (18%) AML patients and was predicted by CBM to remit AML in 9/50 AML patients with 4 true responders and 5 false positive. Ex vivo dasatinib responses were correctly matched to the CBM prediction in 40/50 (80%) of patients (Table1), with 10 mismatches due to lack of sufficient genomic information resulting in profile creation issues and absence of sensitive loops in the profile. Only 4/23 (17%) RTK-mutant patients and 5/27(19%) RTK-WT patients were sensitive to dasatinib ex vivo, indicating that presence of somatic RTK gene mutations may not be essential for leukemia regression in response to dasatinib. Co-occurrence of mutations in NRAS, KRAS and NF1 seemed to associate with resistance as seen in 10 of the 14 profiles harboring these mutations. Conclusion: Computational biology modeling can be used to simulate dasatinib drug response in AML with high accuracy to ex vivo chemosensitivity. DNA mutations in RTK genes may not be required for dasatinib response in AML. Co-occurrence of NRAS, KRAS and NF1gene mutations may be important co-factors in modulating response to dasatinib. Disclosures Tyner: Leap Oncology: Equity Ownership; Syros: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; Incyte: Research Funding; Gilead: Research Funding; Genentech: Research Funding; AstraZeneca: Research Funding; Aptose: Research Funding; Takeda: Research Funding; Agios: Research Funding. Druker:Third Coast Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceuticals: Research Funding; Millipore: Patents & Royalties; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees; Oregon Health & Science University: Patents & Royalties; McGraw Hill: Patents & Royalties; Celgene: Consultancy; MolecularMD: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; GRAIL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Aptose Therapeutics: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Henry Stewart Talks: Patents & Royalties; Patient True Talk: Consultancy; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; ARIAD: Research Funding; Fred Hutchinson Cancer Research Center: Research Funding; Beta Cat: Membership on an entity's Board of Directors or advisory committees; Cepheid: Consultancy, Membership on an entity's Board of Directors or advisory committees; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; ALLCRON: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; Monojul: Consultancy. Sahu:Cellworks Research India Private Limited: Employment. Vidva:Cellworks Research India Private Limited: Employment. Kapoor:Cellworks Research India Private Limited: Employment. Azam:Cellworks Research India Private Limited: Employment. Kumar:Cellworks Research India Private Limited: Employment. Chickdipatti:Cellworks Research India Private Limited: Employment. Raveendaran:Cellworks Research India Private Limited: Employment. Gopi:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment. Cogle:Celgene: Other: Steering Committee Member of Connect MDS/AML Registry.


2019 ◽  
Vol 9 (4) ◽  
pp. 312-320
Author(s):  
Jéssica de Castro Nascimento ◽  
Rosa Maria do Vale Bosso ◽  
Maria Carolina Anholeti ◽  
Elaine da Silva Castro ◽  
Maximino Alencar Bezerra Junior ◽  
...  

Background: Phytochemical studies of Annona muricata showed the presence of bioactive components with anticancer activity. We compared the anticancer properties of crude acetonic and methanolic A. muricata leaf extracts. Methods: The viabilities of different cell lines (A549, U87, U251, K562 and VERO) treated with A. muricata acetonic or methanolic leaf extracts were measured using the MTT assay. Apoptosis induction, cell cycle and cytoskeleton rearrangements were evaluated in K562 by flow cytometry or fluorescence microscopy. Results: Chemical analyses of the A. muricata extracts showed differences in their composition. The K562 cell line was the most sensitive to the treatment with the acetonic and methanolic extracts, and the IC50 values, respectively were 28.82 (24.41 - 34.69) and 32.49 (27.21 - 40.16) μg/mL. Both extracts induced apoptotic cell death and G0/G1 phase cell cycle arrest. For the first time, cytoskeleton rearrangements were observed in the K562 cell line treated with methanolic extract. Conclusion: These findings suggest that both A. muricata extracts exhibit antileukemic potential and represent a promising source of novel compounds with anticancer activity.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1713-1713 ◽  
Author(s):  
Leylah Drusbosky ◽  
Taher Abbasi ◽  
Shireen Vali ◽  
Saumya Radhakrishnan ◽  
Neeraj Kumar Singh ◽  
...  

Abstract Background: Data from a small clinical trial of venetoclax in acute myeloid leukemia (AML) recently supported FDA breakthrough therapy designation for use in combination with hypomethylating agents in treatment-naïve patients who are ineligible for high-dose induction chemotherapy. Approval of this BCL-2 inhibitor raises the question of mechanism of action in AML and patient selection for treatment. Unfortunately, no biomarkers or methods exist to predict venetoclax response in AML, making treatment selection challenging. Aim: To define a novel genomic signature rule to predict AML response to venetoclax therapy and to validate the rule with ex vivo drug sensitivity testing. Methods: The Beat AML project (supported by the Leukemia & Lymphoma Society) collects clinical data and bone marrow specimens from AML patients. Bone marrow samples are analyzed by conventional cytogenetics, whole-exome sequencing, RNA-seq, and an ex vivo drug sensitivity assay. For 19 of these randomly chosen patients, every available genomic abnormality was inputted into a computational biology program (Cellworks Group) that uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated protein pathways. Digital drug simulations with venetoclax were conducted by quantitatively measuring drug effect on a composite AML disease inhibition score (i.e., cell proliferation, viability, and apoptosis). Computational predictions of drug response were compared to venetoclax IC50 values from the Beat AML ex vivo testing. Results: Ten of the 19 AML patients were predicted by computer simulation to respond to venetoclax, and 9 of those 10 patients had the lowest IC50 values to venetoclax. Nine of the 19 patients were predicted to not respond to venetoclax, and 8 of those 9 patients had the highest IC50 values to venetoclax. Ex vivo venetoclax responses were correctly matched to their computer simulation prediction in 17 of 19 cases, and incorrectly matched in 2 cases. The positive predictive value of the computational method was 90%, negative predictive value was 89%, sensitivity was 90%, specificity was 89%, and accuracy was 89%. Amplification of the genes RB1CC1 and/or RB1was predicted by computational modeling to increase MCL1, which made venetoclax less responsive in the digital drug simulation. This genomic rule was validated with 3 AML patients: one who received venetoclax as treatment and showed refractory disease, and 2 patients who achieved complete remission after venetoclax treatment. Conclusion: We identified a new genomic signature, confirmed by functional testing, that predicts AML response to venetoclax treatment. This unique computer-based approach is intended to inform the design of phase 2 and 3 clinical trials of venetoclax in AML patients for a forthcoming precision enrollment clinical trial. Disclosures Abbasi: Cellworks: Employment. Vali:Cellworks Group: Employment. Radhakrishnan:Cellworks: Employment. Kumar Singh:Cellworks: Employment. Usmani:Cellworks: Employment. Parashar:Cellworks: Employment. Vidva:Cellworks: Employment. Druker:Agios: Honoraria; Ambit BioSciences: Consultancy; ARIAD: Patents & Royalties, Research Funding; Array: Patents & Royalties; AstraZeneca: Consultancy; Blueprint Medicines: Consultancy, Equity Ownership, Other: travel, accommodations, expenses ; BMS: Research Funding; CTI: Equity Ownership; Curis: Patents & Royalties; Cylene: Consultancy, Equity Ownership; D3 Oncology Solutions: Consultancy; Gilead Sciences: Consultancy, Other: travel, accommodations, expenses ; Lorus: Consultancy, Equity Ownership; MolecularMD: Consultancy, Equity Ownership, Patents & Royalties; Novartis: Research Funding; Oncotide Pharmaceuticals: Research Funding; Pfizer: Patents & Royalties; Roche: Consultancy.


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