Endpoints for agents that slow tumor growth.

The endpoints of confirmed response and progression are widely used in oncology clinical trials. These endpoints originated at a time when agents used to treat cancer were primarily cytotoxic. Increasingly agents that are cytostatic are being investigated in combination with agents that are cytotoxic. Since tumor growth rates often depend on the volume of the tumor, combining cytotoxic agents that reduce tumor volume with cytostatic agents may mask the activity of the cytostatic agent. This paper explores the sensitivity of time to progression/progression free survival (TTP/PFS) as an endpoint for evaluating the efficacy of cytostatic drugs when combined with cytotoxic agents. Mathematical models of tumor growth are used to describe tumor growth over time. The models account for the impact of chemotherapy and an agent that slows tumor growth in the context of the Gompertzian growth kinetics. We use a clinical trial of an angiogenesis inhibitor in metastatic breast cancer as a motivating example. We demonstrate that the endpoint TTP/PFS may not be sensitive to the effects of active cytostatic agents when they are combined with chemotherapy, and measuring time to regrowth would be more sensitive to the activity of a cytostatic agent. We conclude that an active cytostatic agent may not appear effective when combined with chemotherapy and evaluated with TTP/PFS in a clinical trial.

Assessing therapeutic responses in Kras mutant cancers using genetically engineered mouse models.

The low rate of approval of novel anti-cancer agents underscores the need for better preclinical models of therapeutic response as neither xenografts nor early-generation genetically engineered mouse models (GEMMs) reliably predict human clinical outcomes. Whereas recent, sporadic GEMMs emulate many aspects of their human disease counterpart more closely, their ability to predict clinical therapeutic responses has never been tested systematically. We evaluated the utility of two state-of-the-art, mutant Kras-driven GEMMs--one of non-small-cell lung carcinoma and another of pancreatic adenocarcinoma--by assessing responses to existing standard-of-care chemotherapeutics, and subsequently in combination with EGFR and VEGF inhibitors. Standard clinical endpoints were modeled to evaluate efficacy, including overall survival and progression-free survival using noninvasive imaging modalities. Comparisons with corresponding clinical trials indicate that these GEMMs model human responses well, and lay the foundation for the use of validated GEMMs in predicting outcome and interrogating mechanisms of therapeutic response and resistance.

Identification of direct target genes using joint sequence and expression likelihood with application to DAF-16.

A major challenge in the post-genome era is to reconstruct regulatory networks from the biological knowledge accumulated up to date. The development of tools for identifying direct target genes of transcription factors (TFs) is critical to this endeavor. Given a set of microarray experiments, a probabilistic model called TRANSMODIS has been developed which can infer the direct targets of a TF by integrating sequence motif, gene expression and ChIP-chip data. The performance of TRANSMODIS was first validated on a set of transcription factor perturbation experiments (TFPEs) involving Pho4p, a well studied TF in Saccharomyces cerevisiae. TRANSMODIS removed elements of arbitrariness in manual target gene selection process and produced results that concur with one's intuition. TRANSMODIS was further validated on a genome-wide scale by comparing it with two other methods in Saccharomyces cerevisiae. The usefulness of TRANSMODIS was then demonstrated by applying it to the identification of direct targets of DAF-16, a critical TF regulating ageing in Caenorhabditis elegans. We found that 189 genes were tightly regulated by DAF-16. In addition, DAF-16 has differential preference for motifs when acting as an activator or repressor, which awaits experimental verification. TRANSMODIS is computationally efficient and robust, making it a useful probabilistic framework for finding immediate targets.

Regional activation of chromosomal arm 7q with and without gene amplification in taxane-selected human ovarian cancer cell lines.

Taxanes are important drugs in the treatment of ovarian and other cancers, but their efficacy is limited by intrinsic and acquired drug resistance. Expression of the multidrug transporter P-glycoprotein, encoded by the MDR1 (ABCB1) gene, is one of the causes of clinical drug resistance to taxanes. To study the mechanisms of MDR1 activation related to taxanes, we established 11 multidrug-resistant variants from six ovarian cancer cell lines by continuous exposure to either paclitaxel or docetaxel. We profiled gene expression and gene copy number alterations in these cell lines using cDNA microarrays and identified a cluster of genes coactivated with MDR1 in 7q21.11-13. Regional activation was evident in nine resistant variants displaying a coexpression pattern of up to 22 genes over an 8-Mb area, including SRI, MGC4175, CLDN12, CROT, and CDK6. In six of these variants, regional activation was driven by gene copy number alterations, with low-level gains or high-level amplifications spanning the involved region. However, three variants displayed regional increases in gene expression even without concomitant gene copy number changes. These results suggest that regional gene activation may be a fundamental mechanism for acquired drug resistance, with or without changes in gene dosage. In addition to numerical and structural chromosomal changes driven by genome instability in cancer cells, other mechanisms might be involved in MDR1 regional activation, such as chromatin remodeling and DNA or histone modifications of the 7q21 region.

Tumor necrosis factor-alpha-induced protein 3 as a putative regulator of nuclear factor-kappaB-mediated resistance to O6-alkylating agents in human glioblastomas.

PURPOSE: Pre-existing and acquired drug resistance are major obstacles to the successful treatment of glioblastomas. METHODS: We used an integrated resistance model and genomics tools to globally explore molecular factors and cellular pathways mediating resistance to O6-alkylating agents in glioblastoma cells. RESULTS: We identified a transcriptomic signature that predicts a common in vitro and in vivo resistance phenotype to these agents, a proportion of which is imprinted recurrently by gene dosage changes in the resistant glioblastoma genome. This signature was highly enriched for genes with functions in cell death, compromise, and survival. Modularity was a predominant organizational principle of the signature, with functions being carried out by groups of interacting molecules in overlapping networks. A highly significant network was built around nuclear factor-kappaB (NF-kappaB), which included the persistent alterations of various NF-kappaB pathway elements. Tumor necrosis factor-alpha-induced protein 3 (TNFAIP3) was identified as a new regulatory component of a putative cytoplasmic signaling cascade that mediates NF-kappaB activation in response to DNA damage caused by O6-alkylating agents. Expression of the corresponding zinc finger protein A20 closely mirrored the expression of the TNFAIP3 transcript, and was inversely related to NF-kappaB activation status in the resistant cells. A prediction model based on the resistance signature enabled the subclassification of an independent, validation cohort of 31 glioblastomas into two outcome groups (P = .037) and revealed TNFAIP3 as part of an optimized four-gene predictor associated significantly with patient survival (P = .022). CONCLUSION: Our results offer strong evidence for TNFAIP3 as a key regulator of the cytoplasmic signaling to activate NF-kappaB en route to O6-alkylating agent resistance in glioblastoma cells. This pathway may be an attractive target for therapeutic modulation of glioblastomas.