Literature DB >> 20406975

Molecular target class is predictive of in vitro response profile.

Joel Greshock1, Kurtis E Bachman, Yan Y Degenhardt, Junping Jing, Yuan H Wen, Stephen Eastman, Elizabeth McNeil, Christopher Moy, Ronald Wegrzyn, Kurt Auger, Mary Ann Hardwicke, Richard Wooster.   

Abstract

Preclinical cellular response profiling of tumor models has become a cornerstone in the development of novel cancer therapeutics. As efforts to predict clinical efficacy using cohorts of in vitro tumor models have been successful, expansive panels of tumor-derived cell lines can recapitulate an "all comers" efficacy trial, thereby identifying which tumors are most likely to benefit from treatment. The response profile of a therapy is most often studied in isolation; however, drug treatment effect patterns in tumor models across a diverse panel of compounds can help determine the value of unique molecular target classes in specific tumor cohorts. To this end, a panel of 19 compounds was evaluated against a diverse group of cancer cell lines (n = 311). The primary oncogenic targets were a key determinant of concentration-dependent proliferation response, as a total of five of six, four of four, and five of five phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway, insulin-like growth factor-I receptor (IGF-IR), and mitotic inhibitors, respectively, clustered with others of that common target class. In addition, molecular target class was correlated with increased responsiveness in certain histologies. A cohort of PI3K/AKT/mTOR inhibitors was more efficacious in breast cancers compared with other tumor types, whereas IGF-IR inhibitors more selectively inhibited growth in colon cancer lines. Finally, specific phenotypes play an important role in cellular response profiles. For example, luminal breast cancer cells (nine of nine; 100%) segregated from basal cells (six of seven; 86%). The convergence of a common cellular response profile for different molecules targeting the same oncogenic pathway substantiates a rational clinical path for patient populations most likely to benefit from treatment. Cancer Res; 70(9); 3677-86. (c)2010 AACR.

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Year:  2010        PMID: 20406975     DOI: 10.1158/0008-5472.CAN-09-3788

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  67 in total

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