Personalized cancer medicine: molecular diagnostics, predictive biomarkers, and drug resistance.

The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution.

Selective FLT3 inhibition of FLT3-ITD+ acute myeloid leukaemia resulting in secondary D835Y mutation: a model for emerging clinical resistance patterns.

Acquired resistance to selective FLT3 inhibitors is an emerging clinical problem in the treatment of FLT3-ITD(+) acute myeloid leukaemia (AML). The paucity of valid pre-clinical models has restricted investigations to determine the mechanism of acquired therapeutic resistance, thereby limiting the development of effective treatments. We generated selective FLT3 inhibitor-resistant cells by treating the FLT3-ITD(+) human AML cell line MOLM-13 in vitro with the FLT3-selective inhibitor MLN518, and validated the resistant phenotype in vivo and in vitro. The resistant cells, MOLM-13-RES, harboured a new D835Y tyrosine kinase domain (TKD) mutation on the FLT3-ITD(+) allele. Acquired TKD mutations, including D835Y, have recently been identified in FLT3-ITD(+) patients relapsing after treatment with the novel FLT3 inhibitor, AC220. Consistent with this clinical pattern of resistance, MOLM-13-RES cells displayed high relative resistance to AC220 and Sorafenib. Furthermore, treatment of MOLM-13-RES cells with AC220 lead to loss of the FLT3 wild-type allele and the duplication of the FLT3-ITD-D835Y allele. Our FLT3-Aurora kinase inhibitor, CCT137690, successfully inhibited growth of FLT3-ITD-D835Y cells in vitro and in vivo, suggesting that dual FLT3-Aurora inhibition may overcome selective FLT3 inhibitor resistance, in part due to inhibition of Aurora kinase, and may benefit patients with FLT3-mutated AML.

FLIP: a targetable mediator of resistance to radiation in non-small cell lung cancer

Resistance to radiotherapy due to insufficient cancer cell death is a significant cause of treatment failure in non-small cell lung cancer (NSCLC). The endogenous caspase-8 inhibitor, FLIP, is a critical regulator of cell death that is frequently overexpressed in NSCLC and is an established inhibitor of apoptotic cell death induced via the extrinsic death receptor pathway. Apoptosis induced by ionizing radiation (IR) has been considered to be mediated predominantly via the intrinsic apoptotic pathway; however, we found that IR-induced apoptosis was significantly attenuated in NSCLC cells when caspase-8 was depleted using RNA interference (RNAi), suggesting involvement of the extrinsic apoptosis pathway. Moreover, overexpression of wild-type FLIP, but not a mutant form that cannot bind the critical death receptor adaptor protein FADD, also attenuated IR-induced apoptosis, confirming the importance of the extrinsic apoptotic pathway as a determinant of response to IR in NSCLC. Importantly, when FLIP protein levels were down-regulated by RNAi, IR-induced cell death was significantly enhanced. The clinically relevant histone deacetylase (HDAC) inhibitors vorinostat and entinostat were subsequently found to sensitize a subset of NSCLC cell lines to IR in a manner that was dependent on their ability to suppress FLIP expression and promote activation of caspase-8. Entinostat also enhanced the anti-tumor activity of IR in vivo. Therefore, FLIP down-regulation induced by HDAC inhibitors is a potential clinical strategy to radio-sensitize NSCLC and thereby improve response to radiotherapy. Overall, this study provides the first evidence that pharmacological inhibition of FLIP may improve response of NCSLC to IR.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Determination of soybean cultivar resistance to soybean cyst nematode with quantitative polymerase chain reaction

Heterodera glycines, the soybean cyst nematode, is the major pathogen of Glycine max (soybean). Effective management of this pathogen is contingent on the use of resistant cultivars, thus screening for resistant cultivars is essential. The purpose of this research was to develop a method to assess infection of soybean roots by H. glycines with real-time quantitative Polymerase Chain Reaction (qPCR), a prelude to differentiation of resistance levels in soybean cultivars. Two experiments were conducted. In the first one, a consistent inoculation method was developed using to provide active second-stage juveniles (J2). Two-day-old soybean roots were infested with 0 and 1000 J2/mL. Twenty-four hours after infestation, the roots were surface sterilized and DNA was extracted with the DNA FastKit (MP Biomedicals, Santa Ana, CA)). For the qPCR assay, primer pair for single copy gene HgSNO, which codes for a protein involved in the production of vitamin B6, was selected for H. glycines DNA amplification within soybean roots. In the second experiment, compatible Lee 74, incompatible Peking and cultivars with different levels of resistance to H. glycines were inoculated with 0 and 1,000 J2/seedlings. Twenty-four hours post inoculation they were transplanted into pasteurized soil. Subsequently they were harvested at 1, 7, 10, 14 and 21 days post inoculation for DNA extraction. With the qPCR assay, the time needed to differentiate highly resistant cultivars from the rest was reduced. Quantification of H. glycines infection by traditional means (numbers of females produced in 30 days) is a time-consuming practice; the qPCR method can replace the traditional one and improve precision in determining infection levels.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Development of radiotracers for nuclear imaging of poly(ADP-ribose) polymerase-1 and the translocator protein in glioblastoma.

Glioblastoma (GBM) is a highly aggressive and fatal brain cancer that is associated with a number of diagnostic, therapeutic, and treatment monitoring challenges. At the time of writing, inhibition of a protein called poly (ADP-ribose) polymerase-1 (PARP-1) in combination with chemotherapy was being investigated as a novel approach for the treatment of these tumours. However, human studies have encountered toxicity problems due to sub-optimal PARP-1 inhibitor and chemotherapeutic dosing regiments. Nuclear imaging of PARP-1 could help to address these issues and provide additional insight into potential PARP-1 inhibitor resistance mechanisms. Furthermore, nuclear imaging of the translocator protein (TSPO) could be used to improve GBM diagnosis, pre-surgical planning, and treatment monitoring as TSPO is overexpressed by GBM lesions in good contrast to surrounding brain tissue. To date, relatively few nuclear imaging radiotracers have been discovered for PARP-1. On the other hand, numerous tracers exist for TSPO many of which have been investigated in humans. However, these TSPO radiotracers suffer from either poor pharmacokinetic properties or high sensitivity to human TSPO polymorphism that can affect their binding to TSPO. Bearing in mind the above and the high attrition rates associated with advancement of radiotracers to the clinic, there is a need for novel radiotracers that can be used to image PARP-1 and TSPO. This thesis reports the pre-clinical discovery programme that led to the identification of two potent PARP-1 inhibitors, 4 and 17, that were successfully radiolabelled to generate the potential SPECT and PET imaging agents [123I]-4 and [18F]-17 respectively. Evaluation of these radiotracers in mice bearing subcutaneous human GBM xenografts using ex vivo biodistribution techniques revealed that the agents were retained in tumour tissue due to specific PARP-1 binding. This thesis also describes the pre-clinical in vivo evaluation of [18F]-AB5186, which is a novel radiotracer discovered previously within the research group with potential for PET imaging of TSPO. Using ex vivo autoradiography and PET imaging the agent was revealed to accumulate in intracranial human GBM tumour xenografts in good contrast to surrounding brain tissue, which was due to specific binding to TSPO. The in vivo data for all three radiolabelled compounds warrants further pre-clinical investigations with potential for clinical advancement in mind.

Combined anti-Galectin-1 and anti-EGFR siRNA-loaded chitosan-lipid nanocapsules decrease temozolomide resistance in glioblastoma: In vivo evaluation

International audience

Insecticidal activity of a protein extracted from bulbs of Phycella australis Ravenna against the aphids Acyrthosiphon pisum Harris and Myzus persicae Sulzer

Aphids cause significant losses in many agricultural crops and in many cases cause repeated insecticide sprays, which increase the risk of resistance. Therefore, other alternatives are needed to control them. The toxic, antireproductive, and feeding deterrent effects of a mannosebinding lectin isolated from bulbs of Phycella australis Ravenna (Amaryllidaceae), named Phycella australis agglutinin (PAA) was assayed on nymphs of the aphids Acyrthosiphon pisum Harris and Myzus persicae Sulzer fed with an artificial diet. After 72 h of PAA exposure, lethal concentration (LC50) values were 109 and 313 μg mL-1 for A. pisum and M. persicae, respectively, while LC90 values were 248 and 634 μg mL-1. Sub-lethal concentrations of PAA significantly reduced the aphid fecundity at a concentration of 80 μg mL-1. Only a total of 5.7 descendants per female were recorded for A. pisum (32% control progeny) and 12.4 for M. persicae (39% control progeny). Acyrthosiphon pisum was strongly deterred by PAA under choice conditions, as after 72 h exposed to 80 μg PAA mL-1 of diet, the feeding deterrent index was 0.91 for A. pisum and only 0.38 for M. persicae. In conclusion, the mannosebinding lectin isolated from bulbs of P. australis showed acute and chronical insecticidal activity against the pea and green peach aphids.

Association between ferritin, high sensitivity c-reactive protein (hsCRP) and relative abundance of Hepcidin mRNA with the risk of type 2 diabetes in obese subjects

Obesity and Type 2 diabetes mellitus share a strong pro-inflammatory profile. It has been observed that iron is a risk factor in the development of type 2 diabetes. The aim of this study was to evaluate the relationship between iron nutritional status and inflammation with the risk of type 2 diabetes development in obese subjects. We studied 30 obese men with type 2 diabetes (OBDM); 30 obese subjects without diabetes (OB) and 30 healthy subjects (Cn). We isolated peripheral mononuclear cells (PMCs) and challenged them with high Fe concentrations. Total mRNA was isolated and relative abundance of TNF-αIL-6 and hepcidin were determined by qPCR. Iron status, biochemical, inflammatory and oxidative stress parameters were also characterized. OBDM and OB patients showed increased hsCRP levels compared to the Cn group. OBDM subjects showed higher levels of ferritin than the Cn group. TNF-α and IL-6 mRNA relative abundances were increased in OBDM PMCs treated with high/Fe. Hepcidin mRNA was increased with basal and high iron concentration. We found that the highest quartile of ferritin was associated with an increased risk of type 2 diabetes when it was adjusted to BMI and HOMA-IR; this association was independent of the inflammatory status. The highest level of hepcidin gene expression also showed a trend of increased risk of diabetes, however it was not significant. Levels of hsCRP over 2 mg/L showed a significant trend of increasing the risk of diabetes. In conclusion, iron may stimulate the expression of pro-inflammatory genes (TNF-α and IL-6), and both hepcidin and ferritin gene expression levels could be a risk factor for the development of type 2 diabetes. Subjects that have an increased cardiovascular risk also have a major risk to develop type 2 diabetes, which is independent of the BMI and insulin resistance state.

A genetic variant of the CAPN10 gene in Mexican subjects with dyslipidemia is associated with increased HDL-cholesterol concentrations after the consumption of a soy protein and soluble fiber dietary portfolio

Dyslipidemia is a major public health problem, and therefore, it is important to develop dietary strategies to diminish the prevalence of this disorder. It was recently reported that diet may play an important role in triggering insulin resistance by interacting with genetic variants at the CAPN10 gene locus in patients with metabolic syndrome. Nonetheless, it remains unknown whether genetic variants of genes involved in the development of type 2 diabetes are associated with variations in high-density lipoprotein cholesterol (HDL-C). The study used a single-center, prospective, cohort design. Here, we assessed the effect of four variants of the CAPN10 gene on HDL-C levels in response to a soy protein and soluble fiber dietary portfolio in subjects with dyslipidemia. In 31 Mexican dyslipidemic individuals, we analyzed four CAPN10 gene variants (rs5030952, rs2975762, rs3792267, and rs2975760) associated with type 2 diabetes. Subjects with the GG genotype of the rs2975762 variant of the CAPN10 gene were better responders to dietary intervention, showing increased HDL-C concentrations from the first month of treatment. HDL-C concentrations in participants with the wild type genotype increased by 17.0%, whereas the HDL-C concentration in subjects with the variant genotypes increased by only 3.22% (p = 0.03); the low-density lipoprotein cholesterol levels of GG carriers tended to decrease (-12.6%). These results indicate that Mexican dyslipidemic carriers of the rs2975762-GG genotype are better responders to this dietary intervention.

A bacterial acetyltransferase targets the protein kinase ZIP1, a positive regulator of plant immunity

Pseudomonas syringae is a model bacterial pathogen that penetrates the leaf to reach the plant apoplast, where it replicates causing disease. In order to do that, the pathogen must interfere and suppress a two-tiered plant defense response: PTI (PAMP-Triggered Immunity, or basal resistance) and ETI (Effector-Triggered Immunity). P. syringae uses a type III secretion system to directly deliver effector proteins inside the plant cell cytosol, many of which are known to suppress PTI, some of which are known to trigger ETI, and a handful of which are known to suppress ETI. Bacterial infection can also trigger a systemic plant defense response that protects the plant against additional pathogen attacks known as SAR (Systemic Acquired Resistance). We are particularly interested in the molecular and cellular mechanisms involved in effector-mediated defense evasion by P. syringae, in particular those involved in the suppression of ETI and SAR, and/or mediation of hormone signaling. Here we present data describing effector-mediated interference with plant immunity, by means of acetylation of a key positive regulator of local and systemic responses. Our work identifies a novel plant target for effector function, and characterizes its function. This work illustrates how analyzing the means by which a given effector interferes with its target can provide novel information regarding eukaryotic molecular mechanisms.

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

Characterization of TRIB2-mediated resistance to anti-cancer drugs

Dissertação de Mestrado, Oncobiologia: Mecanismos Moleculares do Cancro, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

Design and synthesis of novel quinolones directed to the Plasmodium falciparum bc1 protein complex

Tese de Doutoramento, Química, Especialização em Química Orgânica, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016