Selection of the treatments most likely to combat a patient’s tumor is a central aim of precision oncology. We are currently developing a functional precision oncology program at the University of Utah and Huntsman Cancer Institute that combines the multi-omic characterization of a patient's tumor with the functional screening of relevant drug candidates in patient-derived organoid tumor models to identify which drugs are uniquely capable of combating the patient’s cancer. Here we present our model-based approach for utilizing the multi-omic tumor data to computationally predict the patient’s response to each drug. In this approach, we first identify the genomic and transcriptomic vulnerabilities of the tumor as genes harboring somatic DNA mutations or copy number changes (from paired tumor/normal WGS/WES DNA sequencing data), as well as genes whose expression levels have been significantly altered in the tumor (based on bulk or single-cell RNA sequencing data). Second, using targeting information from drug-gene interaction databases (DGIdb) we compile a list of genes targeted by each drug relevant in the patient’s treatment. Third, we utilize gene interaction database knowledge (KEGG) to construct a gene interaction graph to link each drug’s gene targets with all of the tumor’s vulnerability genes. We then identify all gene interaction paths connecting specific drug target genes with specific vulnerability genes; and score each path and combine all path-specific scores for the target-vulnerability gene pair. Subsequently, we further combine all pairwise scores across all drug target genes and all tumor vulnerability genes and determine the statistical significance of the resulting score by sampling the background distribution of such scores across random drugs, target genes, and vulnerability genes. We have applied our algorithm to predict drug response in advanced breast cancer patients as well as using publicly available tumor cell line data (GDSC2). We have found a high level of concordance between our computational prediction and organoid/cell line screening results, clearly separating sensitive and non-sensitive models. Using Bayesian probability, we compare the drug-specific score distributions of sensitive and non-sensitive models and are able to identify sensitive cell lines/patients with high accuracy. By encapsulating available information on direct gene-gene interactions, the drug’s direct gene targets and the collected omic vulnerabilities of the tumor, our model is not only capable of predicting sensitivity to both targeted and chemotherapy agents, but can also provide a mechanistic understanding for the targeting of the tumor. Our approach will be validated and fine-tuned on a large cohort of breast and brain cancer patients as well as patient PDX models, interrogating gene-target interactions to identify novel relevant target genes/pathways. Citation Format: Szabolcs Tarapcsak, Yi Qiao, Xiaomeng Huang, Tony Di Sera, Matthew H. Bailey, Bryan E. Welm, Alana L. Welm, Gabor T. Marth. Model-based cancer therapy selection by linking tumor vulnerabilities to drug mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2723.

Letter to Blood| July 28, 2022 Subclonal evolution of CLL driver mutations is associated with relapse in ibrutinib- and acalabrutinib-treated patients Clinical Trials & Observations Gage S. Black, Gage S. Black Department of Human Genetics, University of Utah, Salt Lake City, UT; Utah Center for Genetic Discovery, School of Medicine, University of Utah, Salt Lake City, UT; https://orcid.org/0000-0003-2086-5266 Search for other works by this author on: This Site PubMed Google Scholar Xiaomeng Huang, Xiaomeng Huang Department of Human Genetics, University of Utah, Salt Lake City, UT; Utah Center for Genetic Discovery, School of Medicine, University of Utah, Salt Lake City, UT; Search for other works by this author on: This Site PubMed Google Scholar Yi Qiao, Yi Qiao Department of Human Genetics, University of Utah, Salt Lake City, UT; Utah Center for Genetic Discovery, School of Medicine, University of Utah, Salt Lake City, UT; Search for other works by this author on: This Site PubMed Google Scholar Szabolcs Tarapcsak, Szabolcs Tarapcsak Department of Human Genetics, University of Utah, Salt Lake City, UT; Utah Center for Genetic Discovery, School of Medicine, University of Utah, Salt Lake City, UT; https://orcid.org/0000-0001-7182-0135 Search for other works by this author on: This Site PubMed Google Scholar Kerry A. Rogers, Kerry A. Rogers Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH; https://orcid.org/0000-0001-5748-7874 Search for other works by this author on: This Site PubMed Google Scholar Shrilekha Misra, Shrilekha Misra Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH; Search for other works by this author on: This Site PubMed Google Scholar John C. Byrd, John C. Byrd Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH; and Search for other works by this author on: This Site PubMed Google Scholar Gabor T. Marth, Gabor T. Marth Department of Human Genetics, University of Utah, Salt Lake City, UT; Utah Center for Genetic Discovery, School of Medicine, University of Utah, Salt Lake City, UT; Search for other works by this author on: This Site PubMed Google Scholar Deborah M. Stephens, Deborah M. Stephens Division of Hematology and Hematologic Malignancies, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT https://orcid.org/0000-0001-9188-5008 Search for other works by this author on: This Site PubMed Google Scholar Jennifer A. Woyach Jennifer A. Woyach Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH; Search for other works by this author on: This Site PubMed Google Scholar Blood (2022) 140 (4): 401–405. https://doi.org/10.1182/blood.2021015132 Article history Submitted: December 12, 2021 Accepted: April 13, 2022 First Edition: April 27, 2022 Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Request Permissions Cite Icon Cite Search Site Citation Gage S. Black, Xiaomeng Huang, Yi Qiao, Szabolcs Tarapcsak, Kerry A. Rogers, Shrilekha Misra, John C. Byrd, Gabor T. Marth, Deborah M. Stephens, Jennifer A. Woyach; Subclonal evolution of CLL driver mutations is associated with relapse in ibrutinib- and acalabrutinib-treated patients. Blood 2022; 140 (4): 401–405. doi: https://doi.org/10.1182/blood.2021015132 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsBlood Search Subjects: Clinical Trials and Observations, Lymphoid Neoplasia TO THE EDITOR: Bruton’s tyrosine kinase (BTK) is a common target for therapeutic intervention in patients with chronic lymphocytic leukemia (CLL).1,2 Ibrutinib is a first-generation BTK inhibitor (BTKi) that covalently binds to BTK to disrupt the B-cell receptor signaling pathway.3,4 Although BTKis are known to be an effective therapy for CLL, treatment-related toxicities can lead to the discontinuation of therapy.5,6 Acalabrutinib is a second-generation BTKi developed to reduce off-target toxicities.7,8 Though BTKis have improved the management of CLL, some patients experience clinical resistance and relapse during treatment due to mutations in arising clonal cell populations.9,10 This clonal evolution occurs when a dividing cell develops a new mutation that results in a greater competitive advantage compared with the surrounding cells.11-13 Clonal evolution can lead to treatment resistance when an expanding subclone contains a mutation that... REFERENCES 1.Herman SEM, Gordon AL, Hertlein E, et al. Bruton tyrosine kinase represents a promising therapeutic target for treatment of chronic lymphocytic leukemia and is effectively targeted by PCI-32765. Blood. 2011;117(23):6287-6296.Google ScholarCrossrefSearch ADS PubMed 2.Woyach JA, Johnson AJ, Byrd JC. The B-cell receptor signaling pathway as a therapeutic target in CLL. Blood. 2012;120(6):1175-1184.Google ScholarCrossrefSearch ADS PubMed 3.Davids MS, Brown JR. Ibrutinib: a first in class covalent inhibitor of Bruton’s tyrosine kinase. Future Oncol. 2014;10(6):957-967.Google ScholarCrossrefSearch ADS PubMed 4.Burger JA, Tedeschi A, Barr PM, et al; RESONATE-2 Investigators. Ibrutinib as initial therapy for patients with chronic lymphocytic leukemia. N Engl J Med. 2015;373(25):2425-2437.Google ScholarCrossrefSearch ADS PubMed 5.Mato AR, Nabhan C, Thompson MC, et al. Toxicities and outcomes of 616 ibrutinib-treated patients in the United States: a real-world analysis. Haematologica. 2018;103(5):874-879.Google ScholarCrossrefSearch ADS PubMed 6.Maddocks KJ, Ruppert AS, Lozanski G, et al. Etiology of ibrutinib therapy discontinuation and outcomes in patients with chronic lymphocytic leukemia. JAMA Oncol. 2015;1(1):80-87.Google ScholarCrossrefSearch ADS PubMed 7.Byrd JC, Harrington B, O’Brien S, et al. Acalabrutinib (ACP-196) in relapsed chronic lymphocytic leukemia. N Engl J Med. 2016;374(4):323-332.Google ScholarCrossrefSearch ADS PubMed 8.Barf T, Covey T, Izumi R, et al. Acalabrutinib (ACP-196): a covalent bruton tyrosine kinase inhibitor with a differentiated selectivity and in vivo potency profile. J Pharmacol Exp Ther. 2017;363(2):240-252.Google ScholarCrossrefSearch ADS PubMed 9.Komarova NL, Burger JA, Wodarz D. Evolution of ibrutinib resistance in chronic lymphocytic leukemia (CLL). Proc Natl Acad Sci USA. 2014;111(38):13906-13911.Google ScholarCrossrefSearch ADS 10.Woyach JA, Furman RR, Liu T-M, et al. Resistance mechanisms for the Bruton’s tyrosine kinase inhibitor ibrutinib. N Engl J Med. 2014;370(24):2286-2294.Google ScholarCrossrefSearch ADS PubMed 11.Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338-345.Google ScholarCrossrefSearch ADS PubMed 12.Ferrando AA, López-Otín C. Clonal evolution in leukemia. Nat Med. 2017;23(10):1135-1145.Google ScholarCrossrefSearch ADS PubMed 13.Gerlinger M, Swanton C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Br J Cancer. 2010;103(8):1139-1143.Google ScholarCrossrefSearch ADS PubMed 14.Burger JA, Landau DA, Taylor-Weiner A, et al. Clonal evolution in patients with chronic lymphocytic leukaemia developing resistance to BTK inhibition. Nat Commun. 2016;7:11589.Google ScholarCrossrefSearch ADS PubMed 15.Ahn IE, Underbayev C, Albitar A, et al. Clonal evolution leading to ibrutinib resistance in chronic lymphocytic leukemia. Blood. 2017;129(11):1469-1479.Google ScholarCrossrefSearch ADS PubMed 16.Leeksma AC, Taylor J, Wu B, et al. Clonal diversity predicts adverse outcome in chronic lymphocytic leukemia. Leukemia. 2019;33(2):390-402.Google ScholarCrossrefSearch ADS PubMed 17.Landau DA, Tausch E, Taylor-Weiner AN, et al. Mutations driving CLL and their evolution in progression and relapse. Nature. 2015;526(7574):525-530.Google ScholarCrossrefSearch ADS PubMed 18.Woyach JA, Ruppert AS, Guinn D, et al. BTKC481S-mediated resistance to ibrutinib in chronic lymphocytic leukemia. J Clin Oncol. 2017;35(13):1437-1443.Google ScholarCrossrefSearch ADS PubMed 19.Liu T-M, Woyach JA, Zhong Y, et al. Hypermorphic mutation of phospholipase C, γ2 acquired in ibrutinib-resistant CLL confers BTK independency upon B-cell receptor activation. Blood. 2015;126(1):61-68.Google ScholarCrossrefSearch ADS PubMed 20.Landau DA, Sun C, Rosebrock D, et al. The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy. Nat Commun. 2017;8(1):2185.Google ScholarCrossrefSearch ADS PubMed 21.Gángó A, Alpár D, Galik B, et al. Dissection of subclonal evolution by temporal mutation profiling in chronic lymphocytic leukemia patients treated with ibrutinib. Int J Cancer. 2020;146(1):85-93.Google ScholarCrossrefSearch ADS PubMed 22.Rendeiro AF, Krausgruber T, Fortelny N, et al. Chromatin mapping and single-cell immune profiling define the temporal dynamics of ibrutinib response in CLL. Nat Commun. 2020;11(1):577.Google ScholarCrossrefSearch ADS PubMed 23.Woyach J, Huang Y, Rogers K, et al. Resistance to acalabrutinib in CLL is mediated primarily by BTK mutations. Blood. 2019;134:504.Google ScholarCrossrefSearch ADS 24.Zenz T, Kröber A, Scherer K, et al. Monoallelic TP53 inactivation is associated with poor prognosis in chronic lymphocytic leukemia: results from a detailed genetic characterization with long-term follow-up. Blood. 2008;112(8):3322-3329.Google ScholarCrossrefSearch ADS PubMed 25.Chakraborty S, Martines C, Porro F, et al. B-cell receptor signaling and genetic lesions in TP53 and CDKN2A/CDKN2B cooperate in Richter transformation. Blood. 2021;138(12):1053-1066.Google ScholarCrossrefSearch ADS PubMed © 2022 by The American Society of Hematology2022 © 2022 by The American Society of Hematology2022 You do not currently have access to this content. Sign in via your Institution

P-glycoprotein (Pgp, ABCB1) is a member of one of the largest families of active transporter proteins called ABC transporters. Thanks to its expression in tissues with barrier functions and its broad substrate spectrum, it is an important determinant of the absorption, metabolism and excretion of many drugs. Pgp and/or some other drug transporting ABC proteins (e.g., ABCG2, MRP1) are overexpressed in nearly all cancers and cancer stem cells by which cancer cells become resistant against many drugs. Thus, Pgp inhibition might be a strategy for fighting against drug-resistant cancer cells. Previous studies have shown that certain polyphenols interact with human Pgp. We tested the effect of 15 polyphenols of sour cherry origin on the basal and verapamil-stimulated ATPase activity of Pgp, calcein-AM and daunorubicin transport as well as on the conformation of Pgp using the conformation sensitive UIC2 mAb. We found that quercetin, quercetin-3-glucoside, narcissoside and ellagic acid inhibited the ATPase activity of Pgp and increased the accumulation of calcein and daunorubicin by Pgp-positive cells. Cyanidin-3O-sophoroside, catechin, naringenin, kuromanin and caffeic acid increased the ATPase activity of Pgp, while they had only a weaker effect on the intracellular accumulation of fluorescent Pgp substrates. Several tested polyphenols including epicatechin, trans-ferulic acid, oenin, malvin and chlorogenic acid were ineffective in all assays applied. Interestingly, catechin and epicatechin behave differently, although they are stereoisomers. We also investigated the effect of quercetin, naringenin and ellagic acid added in combination with verapamil on the transport activity of Pgp. In these experiments, we found that the transport inhibitory effect of the tested polyphenols and verapamil was additive or synergistic. Generally, our data demonstrate diverse interactions of the tested polyphenols with Pgp. Our results also call attention to the potential risks of drug–drug interactions (DDIs) associated with the consumption of dietary polyphenols concurrently with chemotherapy treatment involving Pgp substrate/inhibitor drugs.

Since cell penetrating peptides are promising tools for delivery of cargo into cells, factors limiting or facilitating their cellular uptake are intensely studied. Using labeling with pH-insensitive and pH-sensitive dyes we report that escape of penetratin from acidic endo-lysosomal compartments is retarded compared to its cellular uptake. The membrane dipole potential, known to alter transmembrane transport of charged molecules, is shown to be negatively correlated with the concentration of penetratin in the cytoplasmic compartment. Treatment of cells with therapeutically relevant concentrations of atorvastatin, an inhibitor of HMG-CoA reductase and cholesterol synthesis, significantly increased the release of penetratin from acidic endocytic compartments in two different cell types. This effect of atorvastatin correlated with its ability to decrease the membrane dipole potential. These results highlight the importance of the dipole potential in regulating cellular uptake of cell penetrating peptides and suggest a clinically relevant way of boosting this process.

Small cell lung cancer (SCLC) is a neuroendocrine tumor treated clinically as a single disease with poor outcomes. Distinct SCLC molecular subtypes have been defined based on expression of ASCL1, NEUROD1, POU2F3, or YAP1. Here, we use mouse and human models with a time-series single-cell transcriptome analysis to reveal that MYC drives dynamic evolution of SCLC subtypes. In neuroendocrine cells, MYC activates Notch to dedifferentiate tumor cells, promoting a temporal shift in SCLC from ASCL1(+) to NEUROD1(+) to YAP1(+) states. MYC alternatively promotes POU2F3(+) tumors from a distinct cell type. Human SCLC exhibits intratumoral subtype heterogeneity, suggesting that this dynamic evolution occurs in patient tumors. These findings suggest that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.

Osteosarcoma (OS) is the most common bone tumor in children and adolescents. Modern OS treatment, based on the combination of neoadjuvant chemotherapy (cisplatin + doxorubicin + methotrexate) with subsequent surgical removal of the primary tumor and metastases, has dramatically improved overall survival of OS patients. However, further research is needed to identify new therapeutic targets. Here we report that expression level of the nuclear NAD synthesis enzyme, nicotinamide mononucleotide adenylyltransferase-1 (NMNAT1), increases in U-2OS cells upon exposure to DNA damaging agents, suggesting the involvement of the enzyme in the DNA damage response. Moreover, genetic inactivation of NMNAT1 sensitizes U-2OS osteosarcoma cells to cisplatin, doxorubicin, or a combination of these two treatments. Increased cisplatin-induced cell death of NMNAT1−/− cells showed features of both apoptosis and necroptosis, as indicated by the protective effect of the caspase-3 inhibitor z-DEVD-FMK and the necroptosis inhibitor necrostatin-1. Activation of the DNA damage sensor enzyme poly(ADP-ribose) polymerase 1 (PARP1), a major consumer of NAD+ in the nucleus, was fully blocked by NMNAT1 inactivation, leading to increased DNA damage (phospho-H2AX foci). The PARP inhibitor, olaparib, sensitized wild type but not NMNAT1−/− cells to cisplatin-induced anti-clonogenic effects, suggesting that impaired PARP1 activity is important for chemosensitization. Cisplatin-induced cell death of NMNAT1−/− cells was also characterized by a marked drop in cellular ATP levels and impaired mitochondrial respiratory reserve capacity, highlighting the central role of compromised cellular bioenergetics in chemosensitization by NMNAT1 inactivation. Moreover, NMNAT1 cells also displayed markedly higher sensitivity to cisplatin when grown as spheroids in 3D culture. In summary, our work provides the first evidence that NMNAT1 is a promising therapeutic target for osteosarcoma and possibly other tumors as well.

Several ABC exporters carry a degenerate nucleotide binding site (NBS) that is unable to hydrolyze ATP at a rate sufficient for sustaining transport activity. A hallmark of a degenerate NBS is the lack of the catalytic glutamate in the Walker B motif in the nucleotide binding domain (NBD). The multidrug resistance transporter ABCB1 (P-glycoprotein) has two canonical NBSs, and mutation of the catalytic glutamate E556 in NBS1 renders ABCB1 transport-incompetent. In contrast, the closely related bile salt export pump ABCB11 (BSEP), which shares 49% sequence identity with ABCB1, naturally contains a methionine in place of the catalytic glutamate. The NBD-NBD interfaces of ABCB1 and ABCB11 differ only in four residues, all within NBS1. Mutation of the catalytic glutamate in ABCB1 results in the occlusion of ATP in NBS1, leading to the arrest of the transport cycle. Here we show that despite the catalytic glutamate mutation (E556M), ABCB1 regains its ATP-dependent transport activity, when three additional diverging residues are also replaced. Molecular dynamics simulations revealed that the rescue of ATPase activity is due to the modified geometry of NBS1, resulting in a weaker interaction with ATP, which allows the quadruple mutant to evade the conformationally locked pre-hydrolytic state to proceed to ATP-driven transport. In summary, we show that ABCB1 can be transformed into an active transporter with only one functional catalytic site by preventing the formation of the ATP-locked pre-hydrolytic state in the non-canonical site.

Abstract Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor that is treated clinically as a single disease with poor outcomes. However, SCLC is recently recognized to comprise multiple molecular subsets with unique therapeutic vulnerabilities. Four distinct subtypes of SCLC have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1. The origins of these subtypes remain unknown. We use mouse and human SCLC models with a time-series analysis of single-cell transcriptome profiling to reveal that the oncogene MYC drives the dynamic evolution of SCLC subtypes by activation of Notch signaling. MYC cooperates with Notch signaling to promote a temporal shift from an ASCL1-to-NEUROD1-to-YAP1-positive state from a neuroendocrine cell of origin, whereas MYC promotes POU2F3+ tumors from a distinct cell type. SCLC molecular subtypes are therefore not distinct, but rather represent dynamic stages of MYC-driven tumor evolution. Treatment-naive human SCLC exhibits intratumoral heterogeneity in SCLC subtypes, suggesting this dynamic evolution occurs in patient tumors. These findings demonstrate that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype. Given the reported unique therapeutic vulnerabilities of each subtype, we postulate that SCLC tumors represent a “moving therapeutic target” that may require more general, combinatorial, or plasticity-directed therapeutic approaches to combat this transcriptional flexibility. We anticipate that molecular subsets of other cancer types may also represent dynamic stages of tumor evolution. Citation Format: Abbie S. Ireland, Alexi M. Micinski, David W. Kastner, Bingqian Guo, Sarah J. Wait, Kyle B. Spainhower, Christopher C. Conley, Opal S. Chen, Matthew R. Guthrie, Danny Soltero, Yi Qiao, Xiaomeng Huang, Szabolcs Tarapcsak, Siddhartha Devarakonda, Milind D. Chalishazar, Jason Gertz, Justin C. Moser, Gabor Marth, Sonam Puri, Benjamin L. Witt, Benjamin T. Spike, Trudy G. Oliver. MYC drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-120.

Unexpectedly, the widely used anticancer agents Cisplatin (Cis-Pt) and Daunorubicin (Dauno) exhibited cell type- and concentration-dependent synergy or antagonism in vitro . We attempted to interpret these effects in terms of the changes elicited by the drugs in the chromatin, the target held primarily responsible for the cytotoxicity of both agents. We measured the effect of Cis-Pt on the levels of Dauno in different cell compartments, the effect of Cis-Pt on Dauno-induced nucleosome eviction, and assessed the influence of Dauno on DNA platination in flow- and laser scanning cytometry as well as in laser ablation-inductively coupled plasma-mass spectrometry assays. We show that the two drugs antagonize each other through a decrease of interstrand crosslinks upon co-treatment with Dauno, and also via the diminished Dauno uptake in the presence of Cis-Pt, and both effects are observed already at low Dauno concentrations. At high Dauno concentrations synergy becomes dominant because histone eviction by Dauno intercalation into the DNA is enhanced in the presence of co-treatment with Cis-Pt. These interactions may have an impact on the efficacy of combination treatment protocols, considering the long retention time of DNA adducts formed by both agents.

Abstract Chronic lymphocytic leukemia (CLL) is the most common type of adult leukemia and is considered incurable. Hyperactivity of B-cell receptor signaling is a central driver of CLL's molecular pathogenesis. Targeting this pathway with Bruton's tyrosine kinase inhibitors (BTKi) has improved clinical outcomes for CLL patients when compared to standard chemo-immunotherapies (Woyach, NEJM 2018; Shanafelt, NEJM 2019). To characterize cancer evolution in CLL patients who received BTKi treatment, we collected blood samples from 4 CLL patients at 3 timepoints: pre-treatment, 1 year, and 2 years after initiation of treatment. Sorted B and T cells (normal control) were subjected to 200X WES and 60X WGS. Using somatic mutations and their allele frequencies from WGS/WES data across the 3 timepoints, we reconstructed the subclonal evolution of the malignant B cell population using our subclone deconvolution algorithm SubcloneSeeker (Qiao, Genome Biol. 2014). Our analysis revealed diverse patterns of subclonal genomic evolution across patients in terms of (1) presence or absence of subclonal evolution between time points; (2) emergence of new subclones across time points; and (3) clonal replacement across time points.To elucidate subclone-specific phenotypic behavior in each patient, we collected single-cell RNA sequencing (sc-RNA-seq) and IgG VDJ sequencing (sc-VDJ-seq) from unsorted blood samples at the same time points at which we had the genomic data. Using our new scBayes algorithm (manuscript in preparation), we assigned individual cells in the scRNA-seq data to genomic subclones based on the presence or absence of subclone-defining DNA mutations. This allowed us to isolate and examine the expression phenotype corresponding to subclonal populations. We observed three patterns: 1) no/minimal genomic and transcriptomic evolution across time points; 2) no/minimal genomic subclonal evolution but transcriptomic shift of the same subclones across time points; 3) clonal/subclonal replacement with distinct transcriptomic and VDJ profiles. We found that the two patients in our study with no/minimal genomic and transcriptomic evolution had progressive disease. In contrast, the two other patients whose tumor showed transcriptomic shift and/or clonal replacement had clinically complete remission. Although larger sample sizes are needed to draw further biological conclusions, this study highlights the power of multi-omic, and especially single-cell transcriptional profiling of BTKi treatment impact on CLL patients. Citation Format: Xiaomeng Huang, Yi Qiao, Philip Moos, Szabolcs Tarapcsák, Jennifer A. Woyach, John C. Byrd, Deborah M. Stephens, Gabor T. Marth. The integration of bulk DNA sequencing and single-cell analysis reveals diverse clonal evolution in CLL patients treated with BTKi [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1517.

Cell penetrating peptides are promising tools for delivery of cargo into cells, but factors limiting or facilitating their cellular uptake are largely unknown. We set out to study the effect of the biophysical properties of the cell membrane on the uptake of penetratin, a cell penetrating peptide.

The anthocyanin content of Hungarian sour cherry is remarkable based on our preliminary investigations. Nutraceutical and pharmaceutical effects of anthocyanins have been extensively studied. The objective of this work was to investigate the the effect of purified sour cherry extract using human umbilical cord vein endothelial cells (HUVECs) as the inflammatory model. HUVECs were isolated by enzymatic digestion and characterized by flow cytometry. The optimal concentration range of sour cherry extract was selected based on MTT, apoptosis, and necrosis assays. Cells were divided into three groups, incubating with M199 medium as control, or with lipopolysaccharide (LPS) or with LPS plus anthocyanin extract (ACE). The effect of sour cherry extract on oxidative stress, pro-inflammatory factors, and arachidonic pathway was investigated. An amount of 50 μg/mL ACE (ACE50) was able to increase the level of glutathione and decrease the ROS, thereby improving the unbalanced redox status in inflammation. ACE50 lowered pro-inflammatory cytokine levels including Interleukin-6 (IL-6), regulated on activation, normal T cell expressed and secreted (RANTES), granulocyte-macrophage colony-stimulating factor (GM-CSF), and tumor necrosis factor alpha (TNF-α). ACE50 affected the arachidonic acid pathway by reducing the LPS-induced enzyme expression (cyclooxygenase-1, cyclooxygenase-2, and prostacyclin synthase). The extract under investigation seems to have a pleiotropic effect including anti-oxidative, anti-inflammatory, hemostatic, and vasoactive effects. Our results indicate that purified sour cherry extract could reduce the LPS-induced inflammatory response, thereby improving endothelial dysfunction.

Retinoids - derivatives of vitamin A - are important cell permeant signaling molecules that regulate gene expression through activation of nuclear receptors. P-glycoprotein (Pgp) and ABCG2 are plasma membrane efflux transporters affecting the tissue distribution of numerous structurally unrelated lipophilic compounds. In the present work we aimed to study the interaction of the above ABC transporters with retinoid derivatives. We have found that 13-cis-retinoic acid, retinol and retinylacetate inhibited the Pgp and ABCG2 mediated substrate transport as well as the substrate stimulated ATPase activity of these transporters. Interestingly, 9-cis-retinoic acid and ATRA (all-trans retinoic acid), both are stereoisomers of 13-cis-retinoic acid, did not have any effect on the transporters' activity. Our fluorescence anisotropy measurements revealed that 13-cis-retinoic acid, retinol and retinyl-acetate selectively increase the viscosity and packing density of the membrane. Thus, the mixed-type inhibition of both transporters by retinol and ABCG2 by 13-cis-retinoic acid may be the collective result of direct interactions of these retinoids with the substrate binding site(s) and of indirect interactions mediated by their membrane rigidifying effects.

P-glycoprotein (Pgp) is an ABC transporter responsible for the ATP-dependent efflux of chemotherapeutic compounds from multidrug resistant cancer cells. Better understanding of the molecular mechanism of Pgp-mediated transport could promote rational drug design to circumvent multidrug resistance. By measuring drug binding affinity and reactivity to a conformation-sensitive antibody we show here that nucleotide binding drives Pgp from a high to a low substrate-affinity state and this switch coincides with the flip from the inward- to the outward-facing conformation. Furthermore, the outward-facing conformation survives ATP hydrolysis: the post-hydrolytic complex is stabilized by vanadate, and the slow recovery from this state requires two functional catalytic sites. The catalytically inactive double Walker A mutant is stabilized in a high substrate affinity inward-open conformation, but mutants with one intact catalytic center preserve their ability to hydrolyze ATP and to promote drug transport, suggesting that the two catalytic sites are randomly recruited for ATP hydrolysis.

Stem cells are present in many tissues, such as dental pulp. Stem cells can be easily isolated from dental pulp because third molars are often removed from patients. Stem cells could be separated from the tissue derived heterogeneous cell population. There are two main methods to separate a cell type from the other ones: the fluorescence activated cell sorting (FACS) and the magnetic activated cell sorting (MACS). The aim of this study was to compare these methods' effect on cell surviving and population growth after sorting on dental pulp cells. The anti-STRO-1 antibody was used as primary antibody to specifically label stem cells. Two secondary antibodies were used: magnetic or fluorescent labelled. We sorted the cells by MACS or by FACS or by combination of both (MACS-FACS). Our results show that the effectivity of MACS and FACS sorting are comparable while of MACS-FACS was significantly higher (MACS 79.53 ± 5.78%, FACS 88.27 ± 3.70%, MACS-FACS 98.43 ± 0.67%). The cell surviving and the post-sorting population growth, on the contrary, are very different. The cell population is growing on first week after MACS but after FACS did not. Moreover, after MACS-FACS, on first week the cell number of population decreased. Taken together, our results suggest to use MACS instead of FACS, at least in case of sorting dental pulp stem cells with anti-STRO-1 antibody.

Munkánk során humán bölcsességfog pulpájából izoláltunk őssejteket. A pulpából származó heterogén sejtpopulációból ezeket az őssejteket fluoreszcensen vagy mágnesesen jelölt, valamilyen őssejt specifikus sejtfelszíni marker ellen termeltetett ellenanyaggal lehet kiválogatni. Munkánk célja az volt, hogy a fluoreszcens (fluorescent activated cell sorting – FACS) és a mágneses (magnetic activated cell sorting – MACS) sejtszeparálást összehasonlítsuk hatékonyságuk és a sejtekre gyakorolt hatásaik alapján. Eredményeink azt mutatták, hogy a válogatás hatékonysága hasonló (MACS 79,53 ± 5,78%, FACS 88,27 ± 3,70%) mindkét általunk használt módszer esetén, a MACS azonban sokkal kíméletesebbnek bizonyult, az abból származó sejtpopulációk gyorsabban növekedtek.