Genome-wide Study of Oral Cavity and Pharyngeal Cancer

Peer reviewed

The Role of the Stroma and CYR61 in Chemoresistance in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer in part due to inherent resistance to chemotherapy, including the first-line drug gemcitabine. Gemcitabine is a nucleoside pyrimidine analog that has long been the backbone of chemotherapy for PDAC, both as a single agent, and more recently, in combination with nab-paclitaxel. Since gemcitabine is hydrophilic, it must be transported through the hydrophobic cell membrane by transmembrane nucleoside transporters. Human equilibrative nucleoside transporter-1 (hENT1) and human concentrative nucleoside transporter-3 (hCNT3) both have important roles in the cellular uptake of the nucleoside analog gemcitabine. While low expression of hENT1 and hCNT3 has been linked to gemcitabine resistance clinically, mechanisms regulating their expression in the PDAC tumor microenvironment are largely unknown. We identified that the matricellular protein Cysteine-Rich Angiogenic Inducer 61 (CYR61) negatively regulates expression of hENT1 and hCNT3. CRISPR/Cas9-mediated knockout of CYR61 significantly increased expression of hENT1 and hCNT3 and cellular uptake of gemcitabine. CRSIPR-mediated knockout of CYR61 sensitized PDAC cells to gemcitabine-induced apoptosis. Conversely, adenovirus-mediated overexpression of CYR61 decreased hENT1 expression and reduced gemcitabine-induced apoptosis. We demonstrate that CYR61 is expressed primarily by stromal pancreatic stellate cells (PSCs) within the PDAC tumor microenvironment, with Transforming Growth Factor- β (TGF-β) inducing the expression of CYR61 in PSCs through canonical TGF-β-ALK5-Smad signaling. Activation of TGF-β signaling or expression of CYR61 in PSCs promotes resistance to gemcitabine in an in vitro co-culture assay with PDAC cells. Our results identify CYR61 as a TGF-β induced stromal-derived factor that regulates gemcitabine sensitivity in PDAC and suggest that targeting CYR61 may improve chemotherapy response in PDAC patients.

Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.

OBJECTIVE: To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND: Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. METHODS: We developed a causal model of the factors related to combined oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+) and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%) increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an increased prevalence of CIN2+ associated with COC, evidence is insufficient to conclude causality. Priority areas for future studies to better satisfy causal criteria are identified.

Current status of gene therapy for breast cancer: progress and challenges

Breast cancer is characterized by a series of genetic mutations and is therefore ideally placed for gene therapy intervention. The aim of gene therapy is to deliver a nucleic acid-based drug to either correct or destroy the cells harboring the genetic aberration. More recently, cancer gene therapy has evolved to also encompass delivery of RNA interference technologies, as well as cancer DNA vaccines. However, the bottleneck in creating such nucleic acid pharmaceuticals lies in the delivery. Deliverability of DNA is limited as it is prone to circulating nucleases; therefore, numerous strategies have been employed to aid with biological transport. This review will discuss some of the viral and nonviral approaches to breast cancer gene therapy, and present the findings of clinical trials of these therapies in breast cancer patients. Also detailed are some of the most recent developments in nonviral approaches to targeting in breast cancer gene therapy, including transcriptional control, and the development of recombinant, multifunctional bio-inspired systems. Lastly, DNA vaccines for breast cancer are documented, with comment on requirements for successful pharmaceutical product development.

HER2 in high-risk rectal cancer patients treated in EXPERT-C, a randomized phase II trial of neoadjuvant capecitabine and oxaliplatin (CAPOX) and chemoradiotherapy (CRT) with or without cetuximab.

BACKGROUND: HER2 is an established therapeutic target in breast and gastric cancers. The role of HER2 in rectal cancer is unclear, as conflicting data on the prevalence of HER2 expression in this disease have been reported. We evaluated the prevalence of HER2 and its impact on the outcome of high-risk rectal cancer patients treated with neoadjuvant CAPOX and CRT±cetuximab in the EXPERT-C trial. PATIENTS AND METHODS: Eligible patients with available tumour tissue for HER2 analysis were included. HER2 expression was determined by immunohistochemistry (IHC) in pre-treatment biopsies and/or surgical specimens (score 0-3+). Immunostaining was scored according to the consensus panel recommendations on HER2 scoring for gastric cancer. Tumours with equivocal IHC result (2+) were tested for HER2 amplification by D-ISH. Tumours with IHC 3+ or D-ISH ratio ≥2.0 were classified as HER2+. The impact of HER2 on primary and secondary end points of the study was analysed. RESULTS: Of 164 eligible study patients, 104 (63%) biopsy and 114 (69%) surgical specimens were available for analysis. Only 3 of 104 (2.9%) and 3 of 114 (2.6%) were HER2+, respectively. In 77 patients with paired specimens, concordance for HER2 status was found in 74 (96%). Overall, 141 patients were assessable for HER2 and 6 out of 141 (4.3%) had HER2 overexpression and/or amplification. The median follow-up was 58.6 months. HER2 was not associated with a difference in the outcome for any of the study end points, including in the subset of 90 KRAS/BRAF wild-type patients treated±cetuximab. CONCLUSIONS: Based on the low prevalence of expression as recorded in the EXPERT-C trial, HER2 does not appear to represent a useful therapeutic target in high-risk rectal cancer. However, the role of HER2 as a potential predictive biomarker of resistance to anti-EGFR-based treatments and a therapeutic target in anti-EGFR refractory metastatic colorectal cancer (CRC) warrants further investigation. TRIAL REGISTRATION: ISRCTN Register: 99828560.

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.

Marine casualty report : entanglement of the submersible Johnson Sea Link with submerged wreckage off Key West, Florida on or about 17 June 1973 with loss of life : U.S. Coast Guard Marine Board of Investigation report and commandant's action : action by National Transportation Safety Board /

Cover title.

Marine casualty report : SS C. V. Sea Witch - SS Esso Brussels (Belgium) : collision and fire in New York Harbor on June 1973 with loss of life : U.S. Coast Guard Marine Board of Investigation report and commandant's action : action by National Transportation Safety Board.

"Report no. USCG/NTSB-MAR-75-6."