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Characterization of Biological Resistance and Successful Drug Resistance Control in Medicine.

ABSTRACT: It has now been a century that drug resistance has been getting worse in human infectious diseases medicine. A similar trend is observed in veterinary medicine and agriculture. The successful control of drug resistance requires an understanding of biological resistance in general, as a phenomenon taking place in nature. Once we have understood the main characteristics of biological resistance and how it operates in nature, we can then apply that new understanding to its subset that drug resistance in human medicine is. Possession of such an edge can also lead to the successful control of resistance in veterinary medicine, in agriculture, and in other settings of resistance activity by biological organisms. Based on biological resistance data from human medicine, veterinary medicine, and agriculture, some of the fundamental characteristics of resistance as a natural process displayed by all living organisms are established. The consistent, common features characterizing the data are exploited, as is a mathematical model depicting how biological resistance strengthens in living organisms. It is found that biological resistance in general, and drug resistance in particular, is a phenomenon governed by at least two laws: the First Law of Resistance, requiring a threshold to be met before resistance can be prevented and the Second Law of Resistance, causing resistance to strengthen to infinite levels if unstopped. Inference is thereafter made as to the drug design strategy required for the successful control of resistance in medicine. To that end, the blueprint currently applied in the design of infectious diseases drugs needs revising.

SUBMITTER: Fullybright R

PROVIDER: S-EPMC6631572 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Characterization of Biological Resistance and Successful Drug Resistance Control in Medicine.

Fullybright Rudolf R

Pathogens (Basel, Switzerland) 20190531 2

It has now been a century that drug resistance has been getting worse in human infectious diseases medicine. A similar trend is observed in veterinary medicine and agriculture. The successful control of drug resistance requires an understanding of biological resistance in general, as a phenomenon taking place in nature. Once we have understood the main characteristics of biological resistance and how it operates in nature, we can then apply that new understanding to its subset that drug resistan ...[more]

PMID: 31159292

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Project description:BackgroundAdipose tissue-derived stem cells are considered to be a promising source in the field of cell therapy and regenerative medicine. In addition to direct cell replacement using adipose tissue or purified stem cells, intercellular molecule exchange by the adipose tissue complex, a vast array of bioactive secretory factors, demonstrated beneficial effects by reducing tissue damage and stimulation of endogenous repair. However, for therapeutic purposes, the use of secretome derivatives, such as full conditioned media or purified exosomes generated in vitro, may present considerable disadvantages for cell manufacturing, storage, product safety, and their potential as a ready-to-go therapeutic product.MethodsIn this study, the effect of a liquid fraction of lipoaspirates isolated intraoperatively from 28 healthy donors was evaluated for their protective effect against oxidative stress and senescence, proliferation, and migration in vitro on normal human melanocytes, keratinocytes, and fibroblasts. Immunoenzymatic quantification of several growth factors and important signal molecules was used to define the biological profile of physiological adipose tissue secretome.ResultsAdipose tissue extracellular fraction (AT-Ex), isolated from lipoaspirate, exhibited significant potential for skin repair. AT-Ex augmented dermal and epidermal cell proliferation in a dose-dependent manner without promoting cancer cell growth. Moreover, migration of dermal fibroblasts, an important phenomenon implicated in endogenous repair, was enhanced by AT-Ex treatment. AT-Ex has a positive impact on oxidative stress damage when cells are exposed to extrinsic hostile factors and prevent a fibroblast senescence phenotype including paracrine functions associated with skin aging.ConclusionsCollectively, our findings propose natural systems carrying the physiological balance of in-vivo produced secretome that could improve cutaneous wound healing and tissue repair. This approach, representing an innovative perspective and therapeutic strategy in regenerative medicine, could also be combined with autologous stem cell grafts to treat chronic nonhealing wounds, stable vitiligo, severe burns, and post-oncological scarring.

Project description:Background Development of drug resistance is often dynamic and requires time series experiments to understand these processes. The most abundant source of information regarding such progressive activity is tracking single cell gene expression data. Our understanding of the imminent role of phenotype switching in modifying therapeutic response has considerably increased.The analysis of single cell transcriptomic data along with machine learning models offers a constructive tool to describe dynamic cellular processes to elucidate cell-to-cell variability within the population after drug exposure. Here we studied how genomic and non-genomic basis for transcriptome differences can influence the developing drug resistance and clonal fitness. Results: This study describes the scRNA-seq analysis of untreated, treated and drug holiday PDX transplants of TNBC exposed to platinum. This builds from the materials and findings of our paper by Salehi, Kabeer et al, Nature 2021 (PMID: 3416307), in which we established the measurement of fitness in this time series. In the new work, we have mapped single cell transcription in conjunction, allowing a dissection of copy number driven (in-cis) clonal transcription and non-clonal, ie non-genomic transcription. We developed an experimental and computational platform consisting of four major steps: (1) timeseries sampling of scRNA-seq 126,556 TNBC PDX cells >2.5 years; (2) clustering the tumor cells into groups reflecting their drug sensitivity, resistance and other characteristics; (3) performing trajectory inference to identify lineages of transitional processes along with drug and tumor progression; (4) estimating the longitudinal gene expression of each lineage; and identifying significant genes between-lineage differential expression modules. Interestingly, we identified a small group of genes (18.9%) that display a new cell state that is not towards the untreated (Un-Rx) nor towards treated Rx which are distant from untreated cell states. The pathway results are shared between two different quantitative measurements of clone-aware differential expression and pseudotime analysis.

Dataset Information

Characterization of Biological Resistance and Successful Drug Resistance Control in Medicine.

Publications

Characterization of Biological Resistance and Successful Drug Resistance Control in Medicine.

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