An Innovative Phase I Trial Design Allowing for the Identification of Multiple Potential Maximum Tolerated Doses with Combination Therapy of Targeted Agents

Treatment for cancer often involves combination therapies used both in medical practice and clinical trials. Korn and Simon listed three reasons for the utility of combinations: 1) biochemical synergism, 2) differential susceptibility of tumor cells to different agents, and 3) higher achievable dose intensity by exploiting non-overlapping toxicities to the host. Even if the toxicity profile of each agent of a given combination is known, the toxicity profile of the agents used in combination must be established. Thus, caution is required when designing and evaluating trials with combination therapies. Traditional clinical design is based on the consideration of a single drug. However, a trial of drugs in combination requires a dose-selection procedure that is vastly different than that needed for a single-drug trial. When two drugs are combined in a phase I trial, an important trial objective is to determine the maximum tolerated dose (MTD). The MTD is defined as the dose level below the dose at which two of six patients experience drug-related dose-limiting toxicity (DLT). In phase I trials that combine two agents, more than one MTD generally exists, although all are rarely determined. For example, there may be an MTD that includes high doses of drug A with lower doses of drug B, another one for high doses of drug B with lower doses of drug A, and yet another for intermediate doses of both drugs administered together. With classic phase I trial designs, only one MTD is identified. Our new trial design allows identification of more than one MTD efficiently, within the context of a single protocol. The two drugs combined in our phase I trial are temsirolimus and bevacizumab. Bevacizumab is a monoclonal antibody targeting the vascular endothelial growth factor (VEGF) pathway which is fundamental for tumor growth and metastasis. One mechanism of tumor resistance to antiangiogenic therapy is upregulation of hypoxia inducible factor 1α (HIF-1α) which mediates responses to hypoxic conditions. Temsirolimus has resulted in reduced levels of HIF-1α making this an ideal combination therapy. Dr. Donald Berry developed a trial design schema for evaluating low, intermediate and high dose levels of two drugs given in combination as illustrated in a recently published paper in Biometrics entitled “A Parallel Phase I/II Clinical Trial Design for Combination Therapies.” His trial design utilized cytotoxic chemotherapy. We adapted this design schema by incorporating greater numbers of dose levels for each drug. Additional dose levels are being examined because it has been the experience of phase I trials that targeted agents, when given in combination, are often effective at dosing levels lower than the FDA-approved dose of said drugs. A total of thirteen dose levels including representative high, intermediate and low dose levels of temsirolimus with representative high, intermediate, and low dose levels of bevacizumab will be evaluated. We hypothesize that our new trial design will facilitate identification of more than one MTD, if they exist, efficiently and within the context of a single protocol. Doses gleaned from this approach could potentially allow for a more personalized approach in dose selection from among the MTDs obtained that can be based upon a patient’s specific co-morbid conditions or anticipated toxicities.

Identification of putative 1p36 tumor suppressor genes involved in oligodendroglioma development

Oligodendrogliomas are primary neoplasms of the central nervous system (CNS). One of the most common and characteristic chromosomal abnormalities observed in oligodendroglioma is allelic loss of 1p (Reifenberger et al., 1994; Bello et al., 1995). Since 1p loss has been reported for both well-differentiated and anaplastic oligodendroglioma, it is believed to occur early in tumor development (Bello et al., 1995). This allelic loss also has clinical significance, for oligodendroglioma patients with 1p loss generally respond significantly better to combination chemotherapy and have longer average survival than do oligodendroglioma patients without 1p loss (Cairncross et al., 1998). To date, no genes on 1p have been implicated as essential to the development or treatment response of oligodendroglioma. In order to localize and/or identify a gene involved in oligodendroglioma development, I tested 170 oligodendrogliomas for deletions of 1p and tested 26 tumors for differential expression of genes in the region of 1p36. Evidence obtained from these methods implicated two genes, SHREW1 and the gene encoding DNA fragmentation factor beta (DFFB). The function for the SHREW1 locus is currently not well known, but preliminary data suggests that it a novel member of adherens junctions. The DFFB gene is an enhancer for apoptosis. Thus, both SHREW1 and DFFB may be candidates for an oligodendroglioma tumor suppressor. Mutational analysis of both genes did not uncover any mutations. Future studies will evaluate other mechanisms that may be responsible for inactivation of these genes in oligodendrogliomas. ^

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

Identification and characterization of cellular genes differentially expressed in a subset of tumors with non -functional WT1

Wilms tumor (WT) or nephroblastoma is a genetically heterogeneous pediatric renal tumor that accounts for 6–7% of all childhood cancers in the U.S. WT1, located at 11p13, is the sole WT gene cloned to date. Additional genomic regions containing genes that play a role in the development of Wilms tumor include 11p15, 7p, 16q, 1p, 17q and 19q. This heterogeneity has made it extremely difficult to develop an understanding of the pathways involved in the development of WT, even in the 5–20% of tumors that show mutations at the WT1 locus. My research addresses this gap in our current comprehension of the development of WT. ^ I have used two complementary approaches to extend the current understanding of molecular changes involved in the development of WT. In order to minimize complexities due to genetic heterogeneity, I confined my analysis to the WT1 pathway by assessing those genetically defined tumors that carry WT1 mutations. WT1 encodes a zinc finger transcription factor, and in vitro studies have identified many genes that are potentially regulated in vivo by WT1. However, there is very little in vivo data that suggests that they are transcriptionally regulated endogenously by WT1. In one approach I assessed the role of WT1 in the in vivo regulation of PDGFA and IGF2, two genes that are strong contenders for endogenous regulation by WT1. Using primary tissue samples, I found no correlation between the level of RNA expression of WT1 with either PDGFA or IGF2, suggesting that WT1 does not play a critical role in their expression in either normal kidney or WT. ^ In a parallel strategy, using differential display analysis I compared global gene expression in a subset of tumors with known homozygous inactivating WT1 mutations (WT1-tumors) to the gene expression in a panel of appropriate control tissues (fetal kidney, normal kidney, rhabdoid tumor and pediatric renal cell carcinoma). Transcripts that are aberrantly expressed in this subset of Wilms tumors are candidates for endogenous transcriptional regulation by WT1 as well as for potentially functioning in the development of WT. By this approach I identified several differentially expressed transcripts. I further characterized two of these transcripts, identifying a candidate WT gene in the process. I then performed a detailed analysis of this WT candidate gene, which maps to 7p. Future studies will shed more light on the role of these differentially expressed genes in WT. ^