Lee:Research

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The goals of our research are i) to better understand the genetic and molecular bases for variable drug response and drug interactions with a focus on membrane transporters; ii) to develop novel anticancer drugs targeting the proteasomes and their delivery strategies to achieve desirable pharmacokinetic and pharmacodynamic profiles; iii) to evaluate the pharmacokinetics and pharmacogenomics of anticancer drugs in early clinical trial settings and to assess the drug exposure and response in vivo using pharmacometric modeling and simulation.

I. Investigation of the impact of splicing and other genetic variations on drug transporters and proteasomes

Comparison of cancer-type and liver-type OATP1B3

The production of distinct mRNA transcripts from a single gene via alternative splicing is a common, yet important mechanism of generating proteomic diversity in eukaryotic cells. Alterations in splicing patterns have been increasingly associated with disease development and variable response to drug therapy. We have been investigating the functional significance and regulatory mechanisms of splicing variants of genes encoding membrane transporters or molecular targets for cancer therapy such as proteasomes.

Our group was the first to report that colon and pancreatic cancer cells express the cancer-type variant of OATP1B3 (ct-OATP1B3) with the distinct mRNA and protein identity from the liver-type OATP1B3 detected in non-malignant hepatocytes (Thakkar et al. Mol Pharm 2013). In our follow-up investigation, we identified hypoxia-inducible factor 1alpha (HIF-1alpha) as a positive regulator of ct-OATP1B3 expression (Han et al. Biochem Pharmacol 2013). Recently, we reported that the N-terminal region of OATP1B3 (which is present in liver-type OATP1B3, but absent in ct-OATP1B3) plays a crucial role in regulating membrane trafficking of lt-OATP1B3 (Chun et al. Biochem Pharmacol 2017).

We have also been investigating the impact of various genetic variations associated with different subunits that constitute the multi-subunit protease complex called proteasomes. The β1i subunit of the immunoproteasome harbors frequently occurring genetic variations (p.60R>H) and conflicting results had been reported with regard to its functional impact on the immunoproteasome activity. We reported that the codon 60 genetic variations of the β1i subunit do not account for variable expression/activity of the immunoproteasome (Park et al. PLoS One 2013). Currently, we are investigating the impact of alternatively spliced transcripts of the proteasome subunits on the proteasome function.

  1. Thakkar N, Kim K, Jang ER, Han S, Kim K, Kim D, Merchant N, Lockhart AC, and Lee W. A cancer-specific variant of the SLCO1B3 gene encodes a novel human organic anion transporting polypeptide 1B3 (OATP1B3) localized mainly in the cytoplasm of colon and pancreatic cancer cells. Mol Pharm. 2013 Jan 7;10(1):406-16. DOI:10.1021/mp3005353 | PubMed ID:23215050 | HubMed [Thakkar2013]
  2. Han S, Kim K, Thakkar N, Kim D, and Lee W. Role of hypoxia inducible factor-1α in the regulation of the cancer-specific variant of organic anion transporting polypeptide 1B3 (OATP1B3), in colon and pancreatic cancer. Biochem Pharmacol. 2013 Sep 15;86(6):816-23. DOI:10.1016/j.bcp.2013.07.020 | PubMed ID:23924606 | HubMed [Han2013]
  3. Park JE, Ao L, Miller Z, Kim K, Wu Y, Jang ER, Lee EY, Kim KB, and Lee W. PSMB9 codon 60 polymorphisms have no impact on the activity of the immunoproteasome catalytic subunit B1i expressed in multiple types of solid cancer. PLoS One. 2013;8(9):e73732. DOI:10.1371/journal.pone.0073732 | PubMed ID:24040045 | HubMed [Park2013]
  4. Thakkar N, Lockhart AC, and Lee W. Role of Organic Anion-Transporting Polypeptides (OATPs) in Cancer Therapy. AAPS J. 2015 May;17(3):535-45. DOI:10.1208/s12248-015-9740-x | PubMed ID:25735612 | HubMed [Thakkar2015]
  5. Chun SE, Thakkar N, Oh Y, Park JE, Han S, Ryoo G, Hahn H, Maeng SH, Lim YR, Han BW, and Lee W. The N-terminal region of organic anion transporting polypeptide 1B3 (OATP1B3) plays an essential role in regulating its plasma membrane trafficking. Biochem Pharmacol. 2017 May 1;131:98-105. DOI:10.1016/j.bcp.2017.02.013 | PubMed ID:28216016 | HubMed [Chun2017]
  6. Park JE, Ryoo G, and Lee W. Alternative Splicing: Expanding Diversity in Major ABC and SLC Drug Transporters. AAPS J. 2017 Nov;19(6):1643-1655. DOI:10.1208/s12248-017-0150-0 | PubMed ID:28971357 | HubMed [Park2017]
All Medline abstracts: PubMed | HubMed

II. Development of novel proteasome inhibitor drugs and delivery strategies to improve anticancer efficacy and expand therapeutic utilities

FDA-approved proteasome inhibitor drugs

The proteasome is a valid anticancer target, firmly validated by the three FDA-approved drugs, bortezomib (Velcade®), carfilzomib (Kyprolis®) and ixazomib (Ninlalo®). These drugs have transformed the treatment landscape for multiple myeloma and other hematological malignancies. In particular, the second-generation proteasome inhibitor drug carfilzomib has placed itself as part of the frontline multiple myeloma therapy, thanks to its much-improved safety and efficacy profiles over bortezomib. Despite these remarkable successes, carfilzomib has shown limited efficacy in patients with solid cancers, possibly due to its short half-life in blood and insufficient access of active drug to tumor tissues. Working together with experts in the field of drug delivery (Drs. Yoonsoo Bae, University of Kentucky; Dr. Yoon Yeo, Purdue University), we are developing novel nano-formulations for carfilzomib that can improve the biopharmaceutical properties and the anticancer efficacy in multiple myeloma and other types of cancers (Ao et al. J Pharm Exp Ther 2015; Park et al. PLoS One, 2017; Park et al. J Controlled Rel, 2019).

We also collaborate with scientists who have expertise and experience in the development of novel proteasome inhibitors (Dr. Kyung Bo Kim, University of Kentucky). Our goal is to develop novel proteasome inhibitor drugs that can overcome the biopharmaceutical limitations of existing proteasome inhibitor drugs. Like many cancer therapeutics, proteasome inhibitor drugs are subject to de novo or acquired resistance, which is a major clinical obstacle. We have been investigating the molecular mechanisms underlying cancer resistance to carfilzomib and potential strategies to overcome resistance (Ao et al. Mol. Pharmaceutics 2012). A better mechanistic understanding of cancer resistance to proteasome inhibitors has been utilized to screen and develop novel next-generation proteasome inhibitor drugs that can be effective in patients who do not have any further therapeutic options (Miller et al. J Med Chem 2015; Lee et al. J Med Chem 2019). We also investigate the biological impact and therapeutic potential of novel inhibitors for the immunoproteasome (an alternative type of proteasome that is often upregulated in cancer cells).

  1. Park JE, Chun SE, Reichel D, Min JS, Lee SC, Han S, Ryoo G, Oh Y, Park SH, Ryu HM, Kim KB, Lee HY, Bae SK, Bae Y, and Lee W. Polymer micelle formulation for the proteasome inhibitor drug carfilzomib: Anticancer efficacy and pharmacokinetic studies in mice. PLoS One. 2017;12(3):e0173247. DOI:10.1371/journal.pone.0173247 | PubMed ID:28273121 | HubMed [Park2017]
  2. Ao L, Reichel D, Hu D, Jeong H, Kim KB, Bae Y, and Lee W. Polymer micelle formulations of proteasome inhibitor carfilzomib for improved metabolic stability and anticancer efficacy in human multiple myeloma and lung cancer cell lines. J Pharmacol Exp Ther. 2015 Nov;355(2):168-73. DOI:10.1124/jpet.115.226993 | PubMed ID:26311812 | HubMed [Ao2015]
  3. Miller Z, Kim KS, Lee DM, Kasam V, Baek SE, Lee KH, Zhang YY, Ao L, Carmony K, Lee NR, Zhou S, Zhao Q, Jang Y, Jeong HY, Zhan CG, Lee W, Kim DE, and Kim KB. Proteasome inhibitors with pyrazole scaffolds from structure-based virtual screening. J Med Chem. 2015 Feb 26;58(4):2036-41. DOI:10.1021/jm501344n | PubMed ID:25658656 | HubMed [Miller2015]
  4. Park JE, Miller Z, Jun Y, Lee W, and Kim KB. Next-generation proteasome inhibitors for cancer therapy. Transl Res. 2018 Aug;198:1-16. DOI:10.1016/j.trsl.2018.03.002 | PubMed ID:29654740 | HubMed [Park2018]
  5. Park JE, Park J, Jun Y, Oh Y, Ryoo G, Jeong YS, Gadalla HH, Min JS, Jo JH, Song MG, Kang KW, Bae SK, Yeo Y, and Lee W. Expanding therapeutic utility of carfilzomib for breast cancer therapy by novel albumin-coated nanocrystal formulation. J Control Release. 2019 May 28;302:148-159. DOI:10.1016/j.jconrel.2019.04.006 | PubMed ID:30954620 | HubMed [Park2019]
  6. Lee MJ, Bhattarai D, Yoo J, Miller Z, Park JE, Lee S, Lee W, Driscoll JJ, and Kim KB. Development of Novel Epoxyketone-Based Proteasome Inhibitors as a Strategy To Overcome Cancer Resistance to Carfilzomib and Bortezomib. J Med Chem. 2019 May 9;62(9):4444-4455. DOI:10.1021/acs.jmedchem.8b01943 | PubMed ID:30964987 | HubMed [Lee2019]
  7. Jun Y, Xu J, Kim H, Park JE, Jeong YS, Min JS, Yoon N, Choi JY, Yoo J, Bae SK, Chung SJ, Yeo Y, and Lee W. Carfilzomib Delivery by Quinic Acid-Conjugated Nanoparticles: Discrepancy Between Tumoral Drug Accumulation and Anticancer Efficacy in a Murine 4T1 Orthotopic Breast Cancer Model. J Pharm Sci. 2020 Apr;109(4):1615-1622. DOI:10.1016/j.xphs.2020.01.008 | PubMed ID:31945310 | HubMed [Jun2020]
All Medline abstracts: PubMed | HubMed

III. Clinical Pharmacokinetics, Pharmacogenomics & Pharmacometrics

Interindividual differences in drug response and toxicities are consistently observed with most chemotherapeutic agents or regimens and many clinical variables (e.g., age, gender, diet, drug-drug interactions) affect drug responses. In particular, inherited variations in drug disposition (metabolism and transport) and drug target genes are known to substantially contribute to the observed variability in cancer treatment outcomes. In our collaborative Phase II clinical study, we investigated the clinical utility of pharmacogenomically selected treatment using genetic polymorphisms in patients with gastric and gastroesophageal junction (GEJ) cancer (Goff et al. PLoS One 2014). Working together with clinical investigators, we investigate the pharmacokinetics of novel cancer drugs, drug formulations or new combination regimens in early clinical trial settings. Our group is also interested in pharmacometric modeling and simulation using preclinical and clinical data.

  1. Goff LW, Thakkar N, Du L, Chan E, Tan BR, Cardin DB, McLeod HL, Berlin JD, Zehnbauer B, Fournier C, Picus J, Wang-Gillam A, Lee W, and Lockhart AC. Thymidylate synthase genotype-directed chemotherapy for patients with gastric and gastroesophageal junction cancers. PLoS One. 2014;9(9):e107424. DOI:10.1371/journal.pone.0107424 | PubMed ID:25232828 | HubMed [Goff2014]
  2. Wang-Gillam A, Thakkar N, Lockhart AC, Williams K, Baggstrom M, Naughton M, Suresh R, Ma C, Tan B, Lee W, Jiang X, Mwandoro T, Trull L, Belanger S, Creekmore AN, Gao F, Fracasso PM, and Picus J. A phase I study of pegylated liposomal doxorubicin and temsirolimus in patients with refractory solid malignancies. Cancer Chemother Pharmacol. 2014 Aug;74(2):419-26. DOI:10.1007/s00280-014-2493-x | PubMed ID:24916546 | HubMed [Wang-Gillam2014]
  3. Michel L, Ley J, Wildes TM, Schaffer A, Robinson A, Chun SE, Lee W, Lewis J Jr, Trinkaus K, and Adkins D. Phase I trial of palbociclib, a selective cyclin dependent kinase 4/6 inhibitor, in combination with cetuximab in patients with recurrent/metastatic head and neck squamous cell carcinoma. Oral Oncol. 2016 Jul;58:41-8. DOI:10.1016/j.oraloncology.2016.05.011 | PubMed ID:27311401 | HubMed [Michel2016]
  4. Asaumi R, Toshimoto K, Tobe Y, Hashizume K, Nunoya KI, Imawaka H, Lee W, and Sugiyama Y. Comprehensive PBPK Model of Rifampicin for Quantitative Prediction of Complex Drug-Drug Interactions: CYP3A/2C9 Induction and OATP Inhibition Effects. CPT Pharmacometrics Syst Pharmacol. 2018 Mar;7(3):186-196. DOI:10.1002/psp4.12275 | PubMed ID:29368402 | HubMed [Asaumi2018]
  5. Sato M, Toshimoto K, Tomaru A, Yoshikado T, Tanaka Y, Hisaka A, Lee W, and Sugiyama Y. Physiologically Based Pharmacokinetic Modeling of Bosentan Identifies the Saturable Hepatic Uptake As a Major Contributor to Its Nonlinear Pharmacokinetics. Drug Metab Dispos. 2018 May;46(5):740-748. DOI:10.1124/dmd.117.078972 | PubMed ID:29475833 | HubMed [Sato2018]
  6. Nakamura T, Toshimoto K, Lee W, Imamura CK, Tanigawara Y, and Sugiyama Y. Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen. CPT Pharmacometrics Syst Pharmacol. 2018 Jul;7(7):474-482. DOI:10.1002/psp4.12307 | PubMed ID:29920987 | HubMed [Nakamura2018]
  7. Nishiyama K, Toshimoto K, Lee W, Ishiguro N, Bister B, and Sugiyama Y. Physiologically-Based Pharmacokinetic Modeling Analysis for Quantitative Prediction of Renal Transporter-Mediated Interactions Between Metformin and Cimetidine. CPT Pharmacometrics Syst Pharmacol. 2019 Jun;8(6):396-406. DOI:10.1002/psp4.12398 | PubMed ID:30821133 | HubMed [Nishiyama2019]
All Medline abstracts: PubMed | HubMed