DM4
(Synonyms: N2'-去乙酰基-N2'-(4-巯基-4-甲基-1-氧代戊基)-美登素) 目录号 : GC32810
A derivative of maytansine
Cas No.:796073-69-3
Sample solution is provided at 25 µL, 10mM.
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Quality Control & SDS
- View current batch:
- Purity: >98.50%
- COA (Certificate Of Analysis)
- SDS (Safety Data Sheet)
- Datasheet
DM4 is a thiol-containing derivative of the tubulin polymerization inhibitor maytansine.1,2 It is cytotoxic to SK-BR-3 cells (IC50 = 3.3 nM).1 DM4, conjugated to a humanized CD205-targeting monoclonal antibody, is selectively cytotoxic to a variety of CD205-expressing human cancer cells (EC50s = 0.1-1.32 nM) over non-CD205-expressing cells (EC50s = 14.2-22.66 nM) and reduces tumor growth in various mouse xenograft and patient-derived (PDX) cancer models.3
1.Widdison, W.C., Wilhelm, S.D., Cavanagh, E.E., et al.Semisynthetic maytansine analogues for the targeted treatment of cancerJ. Med. Chem.49(14)4392-4408(2006) 2.Remillard, S., Rebhun, L.I., Howie, G.A., et al.Antimitotic activity of the potent tumor inhibitor maytansineScience189(4207)1002-1005(1975) 3.Merlino, G., Fiascarelli, A., Bigioni, M., et al.MEN1309/OBT076, a first-in-class antibody-drug conjugate targeting CD205 in solid tumorsMol. Cancer Ther.18(9)1533-1543(2019)
| Cas No. | 796073-69-3 | SDF | |
| 别名 | N2'-去乙酰基-N2'-(4-巯基-4-甲基-1-氧代戊基)-美登素 | ||
| Canonical SMILES | C[C@]1([C@H](CC(N(C(C=C2C=C3OC)=C3Cl)C)=O)OC([C@H](C)N(C)C(CCC(C)(S)C)=O)=O)[C@H]([C@@H]([C@](OC4=O)([H])C[C@]([C@](/C=C/C=C(C)/C2)([H])OC)(N4)O)C)O1 | ||
| 分子式 | C38H54ClN3O10S | 分子量 | 780.37 |
| 溶解度 | DMSO : 100 mg/mL (128.14 mM) | 储存条件 | Store at -20°C |
| General tips | 请根据产品在不同溶剂中的溶解度选择合适的溶剂配制储备液；一旦配成溶液，请分装保存，避免反复冻融造成的产品失效。 储备液的保存方式和期限：-80°C 储存时，请在 6 个月内使用，-20°C 储存时，请在 1 个月内使用。 为了提高溶解度，请将管子加热至37℃，然后在超声波浴中震荡一段时间。 |
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| Shipping Condition | 评估样品解决方案：配备蓝冰进行发货。所有其他可用尺寸：配备RT，或根据请求配备蓝冰。 | ||
| 制备储备液 | |||
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1 mg | 5 mg | 10 mg |
| 1 mM | 1.2814 mL | 6.4072 mL | 12.8144 mL |
| 5 mM | 0.2563 mL | 1.2814 mL | 2.5629 mL |
| 10 mM | 0.1281 mL | 0.6407 mL | 1.2814 mL |
| 第一步：请输入基本实验信息（考虑到实验过程中的损耗，建议多配一只动物的药量） | ||||||||||
| 给药剂量 | mg/kg |  |
动物平均体重 | g | |
每只动物给药体积 | ul | |
动物数量 | 只 |
| 第二步：请输入动物体内配方组成（配方适用于不溶于水的药物；不同批次药物配方比例不同，请联系GLPBIO为您提供正确的澄清溶液配方） | ||||||||||
| % DMSO % % Tween 80 % saline | ||||||||||
| 计算重置 | ||||||||||
计算结果:
工作液浓度： mg/ml；
DMSO母液配制方法： mg 药物溶于 μL DMSO溶液（母液浓度 mg/mL，
体内配方配制方法：取 μL DMSO母液，加入 μL PEG300，混匀澄清后加入μL Tween 80，混匀澄清后加入 μL saline，混匀澄清。
1. 首先保证母液是澄清的；
2.
一定要按照顺序依次将溶剂加入，进行下一步操作之前必须保证上一步操作得到的是澄清的溶液，可采用涡旋、超声或水浴加热等物理方法助溶。
3. 以上所有助溶剂都可在 GlpBio 网站选购。
Phase III, randomized trial of mirvetuximab soravtansine versus chemotherapy in patients with platinum-resistant ovarian cancer: primary analysis of FORWARD I
Ann Oncol 2021 Jun;32(6):757-765.PMID:33667670DOI:10.1016/j.annonc.2021.02.017.
Background: Mirvetuximab soravtansine (MIRV) is an antibody-drug conjugate comprising a folate receptor alpha (FRα)-binding antibody, cleavable linker, and the maytansinoid DM4, a potent tubulin-targeting agent. The randomized, open-label, phase III study FORWARD I compared MIRV and investigator's choice chemotherapy in patients with platinum-resistant epithelial ovarian cancer (EOC). Patients and methods: Eligible patients with 1-3 prior lines of therapy and whose tumors were positive for FRα expression were randomly assigned, in a 2 : 1 ratio, to receive MIRV (6 mg/kg, adjusted ideal body weight) or chemotherapy (paclitaxel, pegylated liposomal doxorubicin, or topotecan). The primary endpoint was progression-free survival [PFS, Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, blinded independent central review] in the intention-to-treat (ITT) population and in the prespecified FRα high population. Results: A total of 366 patients were randomized; 243 received MIRV and 109 received chemotherapy. The primary endpoint, PFS, did not reach statistical significance in either the ITT [hazard ratio (HR), 0.98, P = 0.897] or the FRα high population (HR, 0.69, P = 0.049). Superior outcomes for MIRV over chemotherapy were observed in all secondary endpoints in the FRα high population including improved objective response rate (24% versus 10%), CA-125 responses (53% versus 25%), and patient-reported outcomes (27% versus 13%). Fewer treatment-related grade 3 or higher adverse events (25.1% versus 44.0%), and fewer events leading to dose reduction (19.8% versus 30.3%) and treatment discontinuation (4.5% versus 8.3%) were seen with MIRV compared with chemotherapy. Conclusions: In patients with platinum-resistant EOC, MIRV did not result in a significant improvement in PFS compared with chemotherapy. Secondary endpoints consistently favored MIRV, particularly in patients with high FRα expression. MIRV showed a differentiated and more manageable safety profile than chemotherapy.
Clinical toxicity of antibody drug conjugates: a meta-analysis of payloads
Invest New Drugs 2018 Feb;36(1):121-135.PMID:29027591DOI:10.1007/s10637-017-0520-6.
Background Antibody drug conjugates (ADCs) utilize a monoclonal antibody to deliver a cytotoxic payload specifically to tumor cells, limiting exposure to healthy tissues. Major clinical toxicities of ADCs include hematologic, hepatic, neurologic, and ophthalmic events, which are often dose-limiting. These events may be off-target effects caused by premature release of payload in circulation. A meta-analysis was performed to summarize key clinical safety data for ADCs by payload, and data permitting, establish a dose-response model for toxicity incidence as a function of payload, dose/regimen, and cancer type. Methods A literature search was performed to identify and extract data from clinical ADC studies. Toxicity incidence and severity were collected by treatment arm for anemia, neutropenia, thrombocytopenia, leukopenia, hepatic toxicity, peripheral neuropathy, and ocular toxicity. Exploratory plots, descriptive summaries, and logistic regression modelling were used to explore Grade ≥ 3 (G3/4) toxicities and assess the impact of covariates, including cancer type and dose/regimen. Results The dataset contained 70 publications; quantitative analysis included 43 studies with G3/4 toxicity information reported for the endpoints above. G3/4 anemia, neutropenia and peripheral neuropathy were consistently reported for MMAE ADCs, thrombocytopenia and hepatic toxicity for DM1, and ocular toxicity for MMAF. Safety profiles of MMAE, DM1, and DM4 ADCs differed between solid and hematologic cancers. Conclusions Published ADC clinical data is limited by non-uniform reporting for toxicity and lack of dosing information, limiting the ability to develop quantitative models relating toxicity to exposure. However, the current analysis suggests that key G3/4 toxicities of ADCs in the clinic are likely off-target and related to payload.
Analysis of QTL DM4.1 for Downy Mildew Resistance in Cucumber Reveals Multiple subQTL: A Novel RLK as Candidate Gene for the Most Important subQTL
Front Plant Sci 2020 Oct 22;11:569876.PMID:33193500DOI:10.3389/fpls.2020.569876.
One of the biggest problems in cucumber cultivation is cucurbit downy mildew (DM), caused by the obligate biotroph Pseudoperonospora cubensis. Whereas DM in cucumber was previously efficiently controlled by the dm-1 gene from Indian cucumber accession PI 197087, this resistance was broken by new DM strains, prompting the search for novel sources of resistance. A promising source of resistance is the wild cucumber accession PI 197088. It was previously shown that DM resistance in this genotype inherits polygenically. In this paper, we put the focus on one of the QTL, DM4.1 that is located on chromosome 4. QTL DM4.1 was shown to consist of three subQTL: DM4.1.1 affected pathogen-induced necrosis, DM4.1.2 was shown to have an additive effect on sporulation, and DM4.1.3 had a recessive effect on chlorosis as well as an effect on sporulation. Near-isogenic lines (NILs) were produced by introgressing the subQTLs into a susceptible cucumber line (HS279) with good horticultural traits. Transcriptomic analysis revealed that many genes in general, and defense pathway genes in particular, were differentially expressed in NIL DM4.1.1/.2 compared to NIL DM4.1.3 and the susceptible parent HS279. This indicates that the resistance from subQTL DM4.1.1 and/or subQTL DM4.1.2 likely involves defense signaling pathways, whereas resistance due to subQTL DM4.1.3 is more likely to be independent of known defense pathways. Based on fine-mapping data, we identified the RLK gene CsLRK10L2 as a likely candidate for subQTL DM4.1.2, as this gene was found to have a loss-of-function mutation in the susceptible parent HS279, and was strongly upregulated by P. cubensis inoculation in NIL DM4.1.1/.2. Heterologous expression of this gene triggered necrosis, providing further evidence that this gene is indeed causal for subQTL DM4.1.2.
Sensitive LC-MS/MS quantification of unconjugated maytansinoid DM4 and its metabolite S-methyl-DM4 in human plasma
Bioanalysis 2022 Mar;14(6):357-368.PMID:35234045DOI:10.4155/bio-2021-0275.
Aim: To report the development and validation of an LC-MS/MS method for the simultaneous determination of unconjugated payload DM4 and its metabolite S-methyl-DM4 in human plasma. Methodology: A workflow of protein precipitation followed by reduction and solid phase extraction was employed to remove antibody-maytansinoid conjugates from plasma matrix, release DM4 from endogenous conjugates, and generate a clean sample extract for analysis, respectively. Sodium adduct species of both analytes were selected for multiple reaction monitoring to meet the assay sensitivity requirement in liquid chromatography with tandem mass spectrometry. Conclusion: The method was fully validated for a dynamic range of 0.100-50.0 ng/ml for both analytes along with desired stability and acceptable incurred sample reanalysis.
Covariate analysis of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate, based on first-in-human study
CPT Pharmacometrics Syst Pharmacol 2022 Mar;11(3):384-394.PMID:35191618DOI:10.1002/psp4.12769.
Tusamitamab ravtansine is an anti-CEACAM5 antibody-drug conjugate indicated in patients with solid tumors. Based on a previous developed semimechanistic model describing simultaneously pharmacokinetic (PK) of SAR408701, two of its active metabolites: DM4 and methyl-DM4 and naked antibody, with integration of drug-to-antibody data, the main objective of the present analysis was to evaluate covariate's impact in patients from phase I/II study (n = 254). Demographic and pathophysiologic baseline covariates were explored to explain interindividual variability on each entity PK parameter. Model parameters were estimated with good precision. Five covariates were included in the final PK model: body surface area (BSA), tumor burden, albumin, circulating target, and gender. Comparison of BSA-adjusted dosing and flat dosing supported the current BSA-based dosing regimen, to limit under and over exposure in patients with extreme BSA. Overall, this model characterized accurately the PKs of all entities and highlighted sources of PK variability. By integrating mechanistic considerations, this model aimed to improve understanding of the SAR408701 complex disposition while supporting key steps of clinical development.