Agent-based approaches for biological modeling in oncology: A literature review.

CONTEXT: Computational modeling involves the use of computer simulations and models to study and understand real-world phenomena. Its application is particularly relevant in the study of potential interactions between biological elements. It is a promising approach to understand complex biological processes and predict their behavior under various conditions. METHODOLOGY: This paper is a review of the recent literature on computational modeling of biological systems. Our study focuses on the field of oncology and the use of artificial intelligence (AI) and, in particular, agent-based modeling (ABM), between 2010 and May 2023. RESULTS: Most of the articles studied focus on improving the diagnosis and understanding the behaviors of biological entities, with metaheuristic algorithms being the models most used. Several challenges are highlighted regarding increasing and structuring knowledge about biological systems, developing holistic models that capture multiple scales and levels of organization, reproducing emergent behaviors of biological systems, validating models with experimental data, improving computational performance of models and algorithms, and ensuring privacy and personal data protection are discussed.

OncoSNIPE® Study Protocol, a study of molecular profiles associated with development of resistance in solid cancer patients.

BACKGROUND: Nowadays, evaluation of the efficacy and the duration of treatment, in context of monitoring patients with solid tumors, is based on the RECIST methodology. With these criteria, resistance and/or insensitivity are defined as tumor non-response which does not allow a good understanding of the diversity of the underlying mechanisms. The main objective of the OncoSNIPE® collaborative clinical research program is to identify early and late markers of resistance to treatment. METHODS: Multicentric, interventional study with the primary objective to identify early and / or late markers of resistance to treatment, in 600 adult patients with locally advanced or metastatic triple negative or Luminal B breast cancer, non-small-cell lung cancer or pancreatic ductal adenocarcinoma. Patients targeted in this study have all rapid progression of their pathology, making it possible to obtain models for evaluating markers of early and / or late responses over the 2-year period of follow-up, and thus provide the information necessary to understand resistance mechanisms. To explore the phenomena of resistance, during therapeutic response and / or progression of the pathology, we will use a multidisciplinary approach including high-throughput sequencing (Exome-seq and RNAseq), clinical data, medical images and immunological profile by ELISA. Patients will have long-term follow-up with different biological samples, at baseline (blood and biopsy) and at each tumoral evaluation or tumoral progression evaluated by medical imaging. Clinical data will be collected through a dedicated Case Report Form (CRF) and enriched by semantic extraction based on the French ConSoRe (Continuum Soins Recherche) initiative, a dedicated Semantic Clinical Data Warehouse (SCDW) to cancer. The study is sponsored by Oncodesign (Dijon, France) and is currently ongoing. DISCUSSION: The great diversity of intrinsic or acquired molecular mechanisms involved in resistance to treatment constitutes a real therapeutic issue. Improving understanding of mechanisms of resistance of cancer cells to anti-tumor treatments is therefore a major challenge. The OncoSNIPE cohort will lead to a better understanding of the mechanisms of resistance and will allow to explore new mechanisms of actions and to discover new therapeutic targets or strategies making it possible to circumvent the escape in different types of cancer. TRIAL REGISTRATION: Clinicaltrial.gov. Registered 16 September 2020, https://clinicaltrials.gov/ct2/show/NCT04548960?term=oncosnipe&draw=2&rank=1 and ANSM ID RCB 2017-A02018-45.

Induction of transglutaminase 2 by a liver X receptor/retinoic acid receptor alpha pathway increases the clearance of apoptotic cells by human macrophages.

RATIONALE: Liver X receptors (LXRs) are oxysterol-activated nuclear receptors that are involved in the control of cholesterol homeostasis and inflammatory response. Human monocytes and macrophages express high levels of these receptors and are appropriate cells to study the response to LXR agonists. OBJECTIVE: The purpose of this study was to identify new LXR targets in human primary monocytes and macrophages and the consequences of their activation. METHODS AND RESULTS: We show that LXR agonists significantly increase the mRNA and protein levels of the retinoic acid receptor (RAR)alpha in primary monocytes and macrophages. LXR agonists promote RARalpha gene transcription through binding to a specific LXR response element on RARalpha gene promoter. Preincubation of monocytes or macrophages with LXR agonists before RARalpha agonist treatment enhances synergistically the expression of several RARalpha target genes. One of these genes encodes transglutaminase (TGM)2, a key factor required for macrophage phagocytosis. Accordingly, the combination of LXR and RARalpha agonists at concentrations found in human atherosclerotic plaques markedly enhances the capabilities of macrophages to engulf apoptotic cells in a TGM2-dependent manner. CONCLUSIONS: These results indicate an important role for LXRs in the control of phagocytosis through an RARalpha-TGM2-dependent mechanism. A combination of LXR/RARalpha agonists that may operate in atherosclerosis could also constitute a promising strategy to improve the clearance of apoptotic cells by macrophages in other pathological situations.

From transcriptomics to bibliomics.

BACKGROUND: Current biological investigations tend to operate with genomes, instead of genes as during the last century. It is possible to compare entire genomes, transcriptomes or proteomes, using alphanumeric data corresponding to the differential expression levels of thousands of genes. What remains difficult is to link array results to factual or bibliographical data and retrieve information that is highly structured and - in Shannon's sense - rare. MATERIAL/METHODS: We have developed a tool, Documentation and Information LIBrary (DILIB), that enables us to retrieve, organize and analyze huge amounts of data available on the Internet and related to microarray experiments. DILIB can link hundreds of differentially expressed genes - through their Single Identifier or GenBank accession number - to hundreds of Medline records, and can retrieve, analyze, and compare automatically thousands of non-trivial descriptors related to gene clusters. RESULTS: As exemplified with frequency comparison of MEdical Subject Headings and Registry Number descriptors, we reanalyzed the involvement of 'integrin', 'interleukin' and 'CD Antigens' in mesotheliomas. Thus, DILIB allowed us to: (i). associate literature to expressed genes, (ii). link functional transcriptomes in various experiments, (iii). associate specific descriptors to experiments, (iv). define new research areas, and eventually (v). find new functions for co-expressed genes. CONCLUSIONS: We propose a new concept, 'bibliomics', representing a subset of high quality and rare information, retrieved and organized by systematic literature-searching tools from existing databases, and related to a subset of genes functioning together in '-omic' sciences.