Bayesian adaptive designs in early phase clinical trials

There are two practical challenges in the phase I clinical trial conduct: lack of transparency to physicians, and the late onset toxicity. In my dissertation, Bayesian approaches are used to address these two problems in clinical trial designs. The proposed simple optimal designs cast the dose finding problem as a decision making process for dose escalation and deescalation. The proposed designs minimize the incorrect decision error rate to find the maximum tolerated dose (MTD). For the late onset toxicity problem, a Bayesian adaptive dose-finding design for drug combination is proposed. The dose-toxicity relationship is modeled using the Finney model. The unobserved delayed toxicity outcomes are treated as missing data and Bayesian data augment is employed to handle the resulting missing data. Extensive simulation studies have been conducted to examine the operating characteristics of the proposed designs and demonstrated the designs' good performances in various practical scenarios.^

Cellular Uptake of Neutrohpil Elastase Links Inflammation to Adaptive Immunity

Many tumors arise from sites of inflammation providing evidence that innate immunity is a critical component in the development and progression of cancer. Neutrophils are primary mediators of the innate immune response. Upon activation, an important function of neutrophils is release of an assortment of proteins from their granules including the serine protease neutrophil elastase (NE). The effect of NE on cancer has been attributed primarily to its ability to degrade the extracellular matrix thereby promoting invasion and metastasis. Recently, it was shown that NE could be taken up by lung cancer cells leading to degradation of insulin receptor substrate-1 thereby promoting hyperactivity of the phosphatidylinositol-3 kinase (PI3K) pathway and tumor cell proliferation. To our knowledge, nobody has investigated uptake of NE by other tumor types. In addition, NE has broad substrate specificity suggesting that uptake of NE by tumor cells could impact processes regulating tumorigenensis other than activation of the PI3K pathway. Neutrophil elastase has been identified in breast cancer specimens where high levels of NE have prognostic significance. These studies have assessed NE levels in whole tumor lysates. Because the major source of NE is from activated neutrophils, we hypothesized that breast cancer cells do not have endogenous NE but may take up NE released by tumor associated neutrophils in the tumor microenvironment and that this could provide a link between the innate immune response to tumors and specific adaptive immune responses. In this thesis, we show that breast cancer cells lack endogenous NE expression and that they are able to take up NE resulting in increased generation of low molecular weight cyclin E (CCNE) and enhanced susceptibility to lysis by CCNE-specific cytotoxic T lymphocytes. We also show that after taking up NE and proteinase 3 (PR3), a second primary granule protease with significant homology to NE, breast cancer cells cross-present the NE- and PR3-derived peptide PR1 rendering them susceptible to PR1-targeted therapies. Taken together, our data support a role for NE uptake in modulating adaptive immune responses against breast cancer.

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Phenotypic evolution in a fossil gastropod species lineage: evidence for adaptive radiation?

Detecting speciation in the fossil record is a particularly challenging matter. Palaeontologists are usually confronted with poor preservation and limited knowledge on the palaeoenvironment. Even in the contrary case of adequate preservation and information, the linkage of pattern to process is often obscured by insufficient temporal resolution. Consequently, reliable documentations of speciation in fossils with discussions on underlying mechanisms are rare. Here we present a well-resolved pattern of morphological evolution in a fossil species lineage of the gastropod Melanopsis in the long-lived Lake Pannon. These developments are related to environmental changes, documented by isotope and stratigraphical data. After a long period of stasis, the ancestral species experiences a phenotypic change expressed as shift and expansion of the morphospace. The appearance of several new phenotypes along with changes in the environment is interpreted as adaptive radiation. Lake-level high stands affect distribution and availability of habitats and, as a result of varied functional demands on shell geometry, the distribution of phenotypes. The on-going divergence of the morphospace into two branches argues for increasing reproductive isolation, consistent with the model of ecological speciation. In the latest phase, however, progressively unstable conditions restrict availability of niches, allowing survival of one branch only.

Adaptive variability to low-pH river discharges in Acartia tonsa and stress responses to high PCO2 conditions

Environmental transitions leading to spatial physical-chemical gradients are of ecological and evolutionary interest because they are able to induce variations in phenotypic plasticity. Thus, the adaptive variability to low-pH river discharges may drive divergent stress responses [ingestion rates (IR) and expression of stress-related genes such as Heat shock protein 70 (Hsp70) and Ferritin] in the neritic copepod Acartia tonsa facing changes in the marine chemistry associated to ocean acidification (OA). These responses were tested in copepod populations inhabiting two environments with contrasting carbonate system parameters (an estuarine versus coastal area) in the Southern Pacific Ocean, and assessing an in situ and 96-h experimental incubation under conditions of high pressure of CO2 (PCO2 1200 ppm). Adaptive variability was a determining factor in driving variability of copepods' responses. Thus, the food-rich but colder and corrosive estuary induced a traits trade-off expressed as depressed IR under in situ conditions. However, this experience allowed these copepods to tolerate further exposure to high PCO2 levels better, as their IRs were on average 43% higher than those of the coastal individuals. Indeed, expression of both the Hsp70 and Ferritin genes in coastal copepods was significantly higher after acclimation to high PCO2 conditions. Along with other recent evidence, our findings confirm that adaptation to local fluctuations in seawater pH seems to play a significant role in the response of planktonic populations to OA-associated conditions. Facing the environmental threat represented by the inter-play between multiple drivers of climate change, this biological feature should be examined in detail as a potential tool for risk mitigation policies in coastal management arrangements.

Long-term dynamics of adaptive evolution in a globally important coccolithophore to ocean acidification

Recent evolution experiments have revealed that marine phytoplankton may adapt to global change, for example to ocean warming or acidification. Long-term adaptation to novel environments is a dynamic process and phenotypic change can take place thousands of generations after exposure to novel conditions. Using the longest evolution experiment performed in any marine species to date (4 yrs, = 2100 generations), we show that in the coccolithophore Emiliania huxleyi, long-term adaptation to ocean acidification is complex and initial phenotypic responses may revert for important traits. While fitness increased continuously, calcification was restored within the first 500 generations but later reduced in response to selection, enhancing physiological declines of calcification in response to ocean acidification. Interestingly, calcification was not constitutively reduced but revealed rates similar to control treatments when transferred back to present-day CO2 conditions. Growth rate increased with time in controls and adaptation treatments, although the effect size of adaptation assessed through reciprocal assay experiments varied. Several trait changes were associated with selection for higher cell division rates under laboratory conditions, such as reduced cell size and lower particulate organic carbon content per cell. Our results show that phytoplankton may evolve phenotypic plasticity that can affect biogeochemically important traits, such as calcification, in an unforeseen way under future ocean conditions.