Academic Publications
Dimitrios Iliopoulos, PhD, MBA
Senior Scientific Advisor & Board Member
135
Academic Publications
Summary:
We define a new antitumorous function of the histone lysine (K)-specific methyltransferase 2D (KMT2D) in pancreatic cancer. KMT2D is transcriptionally repressed in human pancreatic tumours through DNA methylation. Clinically, lower levels of this methyltransferase associate with poor prognosis and significant weight alterations. RNAi-based genetic inactivation of KMT2D promotes tumour growth and results in loss of H3K4me3 mark. In addition, KMT2D inhibition increases aerobic glycolysis and alters the lipidomic profiles of pancreatic cancer cells. Further analysis of this phenomenon identified the glucose transporter SLC2A3 as a mediator of KMT2D-induced changes in cellular, metabolic and proliferative rates.
Summary:
Crohn’s disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an ‘-ome’) in isolation without consideration of the interaction among all relevant -omes that yield an overall ‘network effect’. The outcome of this effect is the ‘IBD interactome’, defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.
Summary:
Many diseases that affect modern humans fall in the category of complex diseases, thus called because they result from a combination of multiple aetiological and pathogenic factors. Regardless of the organ or system affected, complex diseases present major challenges in diagnosis, classification, and management. Current forms of therapy are usually applied in an indiscriminate fashion based on clinical information, but even the most advanced drugs only benefit a limited number of patients and to a variable and unpredictable degree. This ‘one measure does not fit all’ situation has spurred the notion that therapy for complex disease should be tailored to individual patients or groups of patients, giving rise to the notion of ‘precision medicine’ [PM]. Inflammatory bowel disease [IBD] is a prototypical complex disease where the need for PM has become increasingly clear. This prompted the European Crohn’s and Colitis Organisation to focus the 7 th Scientific Workshop on this emerging theme. The articles in this special issue of the Journal address the various complementary aspects of PM in IBD, including what is PM; why it is needed and how it can be used; how PM can contribute to prediction and prevention of IBD; how IBD PM can aid in prognosis and improve response to therapy; and the challenges and future directions of PM in IBD. This first article of this series is structured on three simple concepts [what, why, and how] and addresses the definition of PM, discusses the rationale for the need of PM in IBD, and outlines the methodology required to implement PM in IBD in a correct and clinically meaningful way.
Summary:
We have identified a signature of 12 circulating microRNAs that differentiate patients with UC from control subjects. Moreover, 6 of these microRNAs significantly correlated with UC disease activity. Importantly, a set of 4 microRNAs (hsa-miR-4454, hsa-miR-223-3p, hsa-miR-23a-3p, and hsa-miR-320e), which correlated with UC disease activity were found to have higher sensitivity and specificity values than C-reactive protein. Circulating microRNAs provide a novel diagnostic and prognostic marker for patients with UC. The use of an FDA-approved platform could accelerate the application of microRNA screening in a gastrointenstinal clinical setting. When used in combination with current diagnostic and disease activity assessment modalities, microRNAs could improve both IBD screening and care management.
Summary:
miR-124 appears to regulate the expression of STAT3. Reduced levels of miR-124 in colon tissues of children with active UC appear to increase expression and activity of STAT3, which could promote inflammation and the pathogenesis of UC in children. Thus, the activation of miR-124 could have a therapeutic potential in IBD patients.
Konstantine Arkoudas, PhD
Chief Technology Officer
47
Academic Publications
Low-Resource Compositional Semantic Parsing with Concept Pretraining
Summary:
Semantic parsing plays a key role in digital voice assistants such as Alexa, Siri, and Google Assistant by mapping natural language to structured meaning representations. When we want to improve the capabilities of a voice assistant by adding a new domain, the underlying semantic parsing model needs to be retrained using thousands of annotated examples from the new domain, which is time-consuming and expensive. In this work, we present an architecture to perform such domain adaptation automatically, with only a small amount of metadata about the new domain and without any new training data (zero-shot) or with very few examples (few-shot). We use a base seq2seq (sequence-to-sequence) architecture and augment it with a concept encoder that encodes intent and slot tags from the new domain. We also introduce a novel decoder-focused approach to pretrain seq2seq models to be concept aware using Wikidata and use it to help our model learn important concepts and perform well in low-resource settings. We report few-shot and zero-shot results for compositional semantic parsing on the TOPv2 dataset and show that our model outperforms prior approaches in few-shot settings for the TOPv2 and SNIPS datasets.
Summary:
We present results from a large-scale experiment on pretraining encoders with non-embedding parameter counts ranging from 700M to 9.3B, their subsequent distillation into smaller models ranging from 17M-170M parameters, and their application to the Natural Language Understanding (NLU) component of a virtual assistant system. Though we train using 70% spoken-form data, our teacher models perform comparably to XLM-R and mT5 when evaluated on the written-form Cross-lingual Natural Language Inference (XNLI) corpus. We perform a second stage of pretraining on our teacher models using in-domain data from our system, improving error rates by 3.86% relative for intent classification and 7.01% relative for slot filling. We find that even a 170M-parameter model distilled from our Stage 2 teacher model has 2.88% better intent classification and 7.69% better slot filling error rates when compared to the 2.3B-parameter teacher trained only on public data (Stage 1), emphasizing the importance of in-domain data for pretraining. When evaluated offline using labeled NLU data, our 17M-parameter Stage 2 distilled model outperforms both XLM-R Base (85M params) and DistillBERT (42M params) by 4.23% to 6.14%, respectively. Finally, we present results from a full virtual assistant experimentation platform, where we find that models trained using our pretraining and distillation pipeline outperform models distilled from 85M-parameter teachers by 3.74%-4.91% on an automatic measurement of full-system user dissatisfaction.
Allan J. Pantuck, MD
Senior Medical Advisor
268
Academic Publications
Summary:
The largest, multicenter, prospective analysis of patients with high-risk nonmetastatic ccRCC demonstrates the utility of CAIX score as a statistically significant prognostic biomarker for survival. It recommends that CAIX score be quantified for all patients with high-risk disease after nephrectomy.
Summary:
predictive model consisting of smoking history (p=0.040), T stage (p<0.0001), Fuhrman grade (p<0.0001), Eastern Cooperative Oncology Group performance status (p<0.0001), and microvascular invasion (p<0.0001) was independently associated with lymphatic spread. After adjustment with these clinical variables, low carbonic anhydrase IX (CAIX) (p=0.043) and high epithelial vascular endothelial growth factor receptor 2 (p=0.033) protein expression were associated with a higher risk of lymphatic spread, and loss of chromosome 3p (p<0.0001) with a lower risk.
Summary:
In patients with RCC, a history of smoking was associated with worse pathologic features and survival outcomes and with an increased risk of having mutated p53. Further investigation of the genetic and molecular mechanisms associated with decreased CSS in patients with RCC who have a history of smoking is indicated.
Summary:
CAIX was expressed differentially in noninvasive versus invasive tumors, in low-grade versus high-grade bladder cancer, and in primary tumors versus metastases. The current results indicated that CAIX is a strong predictor of recurrence, progression, and overall survival of patients with bladder cancer; and the integration of CAIX expression into conventional prognostic models significantly improved their predictive accuracy. The data suggest a tripartite role of CAIX as a diagnostic, prognostic, and therapeutic molecular marker in bladder cancer.
Summary:
Among patients with locoregional clear-cell renal-cell carcinoma at high risk for tumor recurrence after nephrectomy, the median duration of disease-free survival was significantly longer in the sunitinib group than in the placebo group, at a cost of a higher rate of toxic events.
Athanasios Papatsoris, MD PhD
Senior Medical Advisor
203
Academic Publications
Summary:
The unique structure of darolutamide is characterized by a high affinity for androgen receptors and detainment of antagonist activity in mutant isoforms of androgen receptors. In clinical practice, this is the main reason that makes darolutamide exceptional in terms of safety and efficacy compared to other drugs in this category. Darolutamide is considered to have the lowest probability for adverse events (AEs) compared to apalutamide and enzalutamide. Future studies, along with real-world clinical data are warranted to improve personalized treatment strategies as well as sequencing treatment between approved novel drugs.
Summary:
Development of tumor-specific algorithms for the risk of VTEs is advisable. Patients with aUTC and a history of vascular events are at high risk for VTE development, and prophylaxis should be prospectively studied in this group.
Summary:
Prostate cancer is the most common cancer in men. Regardless of the initial treatment of localized disease, almost all patients develop castration resistant prostate cancer (CRPC). A better understanding of the molecular mechanisms behind castration resistance has led to the approval of novel oral androgen receptor (AR) antagonists, such as enzalutamide and apalutamide. Indeed, research has accelerated with numerous agents being studied for the management of CRPC. Areas covered: Herein, the authors present currently used and emerging AR antagonists for the treatment of CRPC. Emerging agents include darolutamide, EZN-4176, AZD-3514, and AZD-5312, apatorsen, galeterone, ODM-2014, TRC-253, BMS-641988, and proxalutamide. Expert opinion: Further understanding of the mechanisms leading to castration resistance in prostate cancer can reveal potential targets for the development of novel AR antagonists. Current novel agents are associated with modest clinical and survival benefit, while acquired resistance and safety issues are under continuous evaluation. The combination of AR antagonists used and ideal sequencing strategies are key tasks ahead, along with the investigation of molecular biomarkers for future personalized targeted therapies. In the future, the challenge will be to determine an AR antagonist with the best combination of outcome and tolerability.
Summary:
The aim of the study was to identify prognostic molecular profiles in patients with mRCC treated with sunitinib, we performed immunohistochemical analysis for VEGF and PI3K/Akt/mTOR pathway components. Immunohistochemistry for VEGF and p-mTOR proteins may discriminate patients refractory to first-line sunitinib with poor prognosis.
Summary:
Further understanding of the mechanisms leading to castration resistance in prostate cancer can reveal potential targets for the development of novel anti-cancer agents. Except for the development of novel antiandrogens and CYP-17 modulators, bipolar androgen therapy is an interesting therapeutic approach. The combinations of the novel agents tested in Phase I and II studies with established agents is another field of interest. The real challenge is to distinguish a novel anti-cancer agent with acceptable tolerability and the best outcome.
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