Field Of Personalized Medicine Research Articles

Перспективы применения иммуно-ПЦР в диагностике SARS-CоV-2

One of the main biological characteristics of SARS-CoV-2 is its remarkable ability to adapt to new environmental conditions. Accelerated evolution of the COVID-19 pathogen complicates anti-epidemic measures, including the need to update the antigenic composition of vaccines and maintain current vaccination measures, complicates the prognosis of the infection course, and reduces the efficacy of drugs based on monoclonal antibodies and specific antiviral inhibitors. Under these conditions, the search for new approaches to monitoring clinically and epidemiologically significant variants of the virus that escape the factors of humoral immunity, as well as to the accelerated development of relevant immunobiological preparations, becomes important. This in turn requires the use of approaches to assess the serological properties of new variants, such as neutralization reactions using live infectious virus or immunochemical methods with limited antigen detection. Immuno-PCR (iPCR) is a method which is lacked majority of virus neutralization reaction and immunochemical methods (ELISA and LFT) disadvantages. The iPCR method has many modifications aimed at increasing specificity while reducing background amplification, simplifying staging, and multiplexing. Taking into account the high sensitivity of iPCR, it is possible not only to measure the exact amount of antigen, but also to use the diagnostics in the minimum quantities available, for example, in clinical samples. This fact makes iPCR method high-promising in personalized medicine field. Key words: SARS-CoV-2, coronavirus evolution, immuno-PCR, humoral immunity

Protein Interaction Domains: Structural Features and Drug Discovery Applications (Part 2).

Proteins present a modular organization made up of several domains. Apart from the domains playing catalytic functions, many others are crucial to recruit interactors. The latter domains can be defined as "PIDs" (Protein Interaction Domains) and are responsible for pivotal outcomes in signal transduction and a certain array of normal physiological and disease-related pathways. Targeting such PIDs with small molecules and peptides able to modulate their interaction networks, may represent a valuable route to discover novel therapeutics. This work represents a continuation of a very recent review describing PIDs able to recognize post-translationally modified peptide segments. On the contrary, the second part concerns with PIDs that interact with simple peptide sequences provided with standard amino acids. Crucial structural information on different domain subfamilies and their interactomes was gained by a wide search in different online available databases (including the PDB (Protein Data Bank), the Pfam (Protein family), and the SMART (Simple Modular Architecture Research Tool)). Pubmed was also searched to explore the most recent literature related to the topic. PIDs are multifaceted: they have all diverse structural features and can recognize several consensus sequences. PIDs can be linked to different diseases onset and progression, like cancer or viral infections and find applications in the personalized medicine field. Many efforts have been centered on peptide/peptidomimetic inhibitors of PIDs mediated interactions but much more work needs to be conducted to improve drug-likeness and interaction affinities of identified compounds.

Cancer-on-a-chip for Drug Screening.

The oncology pharmaceutical research spent a shocking amount of money on target validation and drug optimization in preclinical models because many oncology drugs fail during clinical trial phase III. One of the most important reasons for oncology drug failures in clinical trials may due to the poor predictive tool of existing preclinical models. Therefore, in cancer research and personalized medicine field, it is critical to improve the effectiveness of preclinical predictions of the drug response of patients to therapies and to reduce costly failures in clinical trials. Three dimensional (3D) tumor models combine micro-manufacturing technologies mimic critical physiologic parameters present in vivo, including complex multicellular architecture with multicellular arrangement and extracellular matrix deposition, packed 3D structures with cell-cell interactions, such as tight junctions, barriers to mass transport of drugs, nutrients and other factors, which are similar to in vivo tumor tissues. These systems provide a solution to mimic the physiological environment for improving predictive accuracy in oncology drug discovery. This review gives an overview of the innovations, development and limitations of different types of tumor-like construction techniques such as self-assemble spheroid formation, spheroids formation by micro-manufacturing technologies, micro-dissected tumor tissues and tumor organoid. Combination of 3D tumor-like construction and microfluidic techniques to achieve tumor on a chip for in vitro tumor environment modeling and drug screening were all included. Eventually, developmental directions and technical challenges in the research field are also discussed. We believe tumor on chip models have provided better sufficient clinical predictive power and will bridge the gap between proof-of-concept studies and a wider implementation within the oncology drug development for pathophysiological applications.

Proteomics approaches to investigate cancer radiotherapy outcome: slow train coming

Radiotherapy represents an effective curative strategy that along with surgery and chemotherapy is traditionally used in cancer treatment. An optimal therapy delivers accurate radiation doses to tumour while protecting surrounding normal tissue. Although radiotherapy regimens have improved in recent years, tumour radioresistance and normal tissue toxicity remain major challenges that considerably contribute to the effectiveness of cancer therapy. These factors affect especially radiosensitive individuals in the treatment of whom the balance between effective tumour killing and adverse normal tissue late effects turns out to be problematic. Understanding molecular mechanisms involved in tumour and normal tissue response is essential in order to improve radiotherapy outcome in the field of personalised medicine. Alteration in the global proteome of cells and tissues truthfully reflects the changes in physiology and pathophysiology of biological samples. This makes proteomics analysis a powerful tool principally enabling identification of radioresistance biomarkers in cancer and sensitivity biomarkers in individuals. Yet, the use of proteomics in cancer therapy is still in its infancy and more research is needed to fulfil the great promise of this technique. The present review summarises recent proteomic-based studies searching for biomarkers for more accurate prediction of radiotherapeutic response in tumour and normal tissue.

Drosophila as a Tool for Personalized Medicine: A Primer

The goal of personalized medicine is to treat each patient with the best drug: optimal therapeutic benefit with minimal side effects. The genomic revolution is rapidly identifying the genetic contribution to the diseased state as well as its contribution to drug efficacy and toxicity. The ability to perform genome-wide studies has led to an overwhelming number of candidate genes and/or their associated variants; however, understanding which are of therapeutic importance is becoming the greatest unmet need in the personalized medicine field. A related issue is the need to improve our methods of identifying and characterizing therapeutic drugs in the context of the complex genomic landscape of the intact body. Drosophila have proven to be a powerful tool for understanding the basic biological mechanisms of human development. This article will review Drosophila as a whole animal tool for gene and drug discovery. We will examine how Drosophila can be used to both sort through the myriad of hits coming from human genome-wide scans and to dramatically improve the early steps in pharmaceutical drug development.

L'imagerie oncologique et les règles internationales de l'évaluation: l'imagerie nucléaire

The growing success of isotopic explorations in oncology is related to the number of growing radiotracers and progress in the methods for detection and imaging. Today, the nuclear medicine is able to answer important questions raised by biology and therapeutic progress results from this. The new radiopharmaceutical compounds are able to explore in vivo the metabolism, the proliferation, the hypoxia and the expression of some receptors or antigens in tumor cells. This progress in radiopharmaceuticals design can be combined with the new tools for detection, such as the cameras coupled to a tomodensitometer (TEMP-TDM and TEP-TDM), the new gamma cameras with semiconductors, and the peroperative gamma probes. The nuclear medicine can now be used to determine the initial staging of tumours, the evaluation of residual disease, the detection of recurrence, the evaluation and the prediction of response to treatments, i.e. chemotherapy, radiotherapy and now targeted treatments. This led to very promising prospects in the therapeutic adaptation and in the patient follow-up, as clearly shown in the malignant lymphomas. Standardized international criteria are set up for the therapeutic evaluation in TEP-FDG. Today, the nuclear medicine belongs to the family of "markers of substitution", participating more and more to the personalized medicine field.