Growth impairment of small-cell cancer by targeting pro-vasopressin with MAG-1 antibody.

Autor: North, William G., Cole, Bernard, Akerman, Bonnie, Pang, Roy H. L.
Předmět:
Zdroj: Frontiers in Oncology; Feb2014, Vol. 4, p1-7, 7p
Abstrakt: Previously we demonstrated that human small-cell lung cancer (SCLC) seems to universally express the vasopressin gene, and this leads to the presence of a cell surface marker representing the entire pro-hormone precursor. In this study, we show this marker can be targeted with MAG-1, a mouse monoclonal antibody against a C-terminal moiety on pro-vasopressin. In vitro targeting of cell lines derived from primary and recurrent disease demonstrates attachment of antibody to the cell surface followed by internalization. In vivo targeting with 99Tc-labeled Fab fragments of MAG-1 shows selective attachment to xenografts. In vivo treatment of tumors from classical cell line, NCI H345, with either ∼1.65 mCi (∼1.65 mg)/kg body weight (BW) of 90Yttrium-labeled MAG-1, or ∼1.65 mg/kg BW native MAG-1, delivered every second day for 6 days produced similar reductions in the growth rate to ∼50% (p <0.03).When dosing with native MAG-1was escalated to daily amounts of ∼3.3 mg/kg BW over 16 days, tumor growth rates fell to ∼33% of saline controls (p <0.005). Examination of tumors treated with this higher dosing demonstrated the presence in several of extensive apoptosis. Normal tissues seemed to be unaffected. A larger dosage of MAG-1 (∼6.6 mg/kg BW) given daily for 14 days was used to treat xenografts of the variant cell line NCI H82 representing recurrent disease. This treatment decreased the rate of increase in tumor size by half, and doubling time ∼3-fold. Increases in cleaved PARP supported increased apoptosis with antibody treatment. We believe these data provide evidence that the growth rate of SCLC tumors can be extensively reduced by treatment with MAG-1 antibody, and that a humanized form of this antibody could, in future, be potentially used for targeting therapy onto recurrent SCLC in patients. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index