Clinical Implications of the Phenomenon of Drug Resistance
Nicholas Bruchovsky, James H. Goldie in Drug and Hormone Resistance in Neoplasia, 2019
To attempt to account for this variability by invoking a great range of deterministic effects operating in individual patients is, we believe, unsatisfactory from both a practical and conceptual point of view. As we have seen, random variability is the essence of the Luria-Delbruck fluctuation test. This in turn relates to the fundamental properties of the spontaneous mutation phenomenon itself and that at a still deeper level reflects the variability in expression of biological information that occurs when systems are subdivided and segregated.16 Thus, the inference one would draw from the somatic mutation theory is that variable response is the expected outcome of chemotherapeutic trials and does not require the further postulation of a great range of phenomenological factors. The somatic mutation theory effectively accounts for the two broad types of variability that are observed at the clinical level. The first has to do with the variability of response of equivalent tumor stage which was referred to previously and the second has to do with the periodically observed phenomenon of the patient with a favorable histological type of tumor and in whom treatment is commenced at an early point, but manifests refractoriness early in the treatment course. The converse of this situation is the rare patient with advanced disease and of a type usually considered to be very unresponsive to chemotherapy, who has an excellent response of sustained duration. Both these phenomena would be expected as natural consequences of the somatic mutation process.
Genomic Instability During Aging of Postmitotic Mammalian Cells
Alvaro Macieira-Coelho in Molecular Basis of Aging, 2017
The possibility of using hypervariable minisatellite sequences to track genomic instability in senescent somatic cells has been comprehensively reviewed by Vijg and associates.208–212 Uitterlinden et al.209 have advocated using a two-dimensional DNA typing technique for such studies, and Slagboom et al.212 have employed this approach to study VNTR sequences in rat fibroblasts cloned from primary cultures of young and old rodents. An examination of more than 3,000 DNA fragments indicated a high somatic mutation rate at several loci. Surprisingly, though, no correlation with age was found. In fact, clones from young donor rats (6 months) had somewhat higher sequence variation frequencies than fibroblasts from old donor rats (30 months).212 This might mean that somatic mutations at such loci are occurring at very early stages of development, when enzymes that induce such variability are present or at least more abundant.
Antiviral Drugs as Tools for Nanomedicine
Devarajan Thangadurai, Saher Islam, Charles Oluwaseun Adetunji in Viral and Antiviral Nanomaterials, 2022
Figure 12.3 depicts the various steps of cancer development (Witsch et al. 2011). In brief, cancer is instigated by a somatic mutation conferring considerable survival and growth advantages to the initiated cell (1). GFs like EGF and IGF1 help the resulting expansion of clones having mutations (2), this results in intra-luminal lesions (3), such as carcinoma at the site or neoplasia, which are surrounded by the basal membrane. (4) Next step is migration and penetration by cancer cells into neighbouring tissues called invasion. Loss of epithelial polarity, motility attainment, changing phenotype to mesenchymal-like, and secretion of enzymes like proteases. The various oncogenes and tumour suppressors, with the involvement of different growth factors, control the critical phase of tumour development. The extravasation of transformed cells - cancer cells from the site and intravasation into the lymphatic and blood vessels results in metastasis (5) to distant organs. Extra- and intravasation require the assistance of macrophages, platelets, and endothelial cells. At this stage of resulting micro-metastases, (6) the cells usually are sensitive to chemotherapy and radiotherapy. However, constant accumulation of mutation leads to the acquisition of further mutations and makes the cancer cells proficient to produce growth factors. This leads to autocrine loops that propel the development of resistant clones (7). Angiogenesis (8) is an indispensable factor for the establishment of secondary tumours. In the last phase, large metastases (9) move to a distinct set of target organs leading to metastases.
Unilateral Coats’-like disease and an intragenic deletion in the TERC gene: A case report
Published in Ophthalmic Genetics, 2018
G. Peene, E. Smets, E. Legius, C. Cassiman
Coats’ disease mainly affects subjects in the first and second decades of life. The typical patient with Coats’ disease is male and has unilateral telangiectasia, arterial aneurysms, retinal nonperfusion rarely associated with retinal neovascularization, and exudative retinopathy sometimes leading to retinal detachment (8). Considerable progress has been made over the past century in understanding the incidence, morphology, patient characteristics, and natural history of disease. The exact molecular mechanism underlying Coats’ disease, however, remains unknown. The condition is suspected to be a congenital genetic defect (based on frequent onset during infancy), but there is usually no familial history of Coats’ disease. It is usually not associated with systemic disease. Several candidate gene mutations are described, including the Norrie disease protein (NDP) (9), CRB1 (10), and PANK2 (11). A somatic mutation is a compelling hypothesis given the congenital, nonfamilial, and unilateral features of the disease (9).
A computational prognostic model of lncRNA signature for clear cell renal cell carcinoma with genome instability
Published in Expert Review of Molecular Diagnostics, 2022
Tingting Cui, Jiantao Guo, Zhixia Sun
To assess the prognostic risk in ccRCC patients, a genomic instability–derived lncRNA marker (GILncSig) combining the multivariate Cox coefficient and the expression level of the three independent prognostic lncRNAs was constructed. The following equation was used: GILncSig score = (−0.05 × LINC02471) + (0.15 × LINC01234) + (0.07 × LINC00460). In the prognostic model, the coefficient of lncRNA LINC01234 is positive, suggesting that lncRNA LINC01234 is a potential risk factor. Study subjects were divided into high- and low-risk groups based on the median value of the risk score. Kaplan–Meier survival analysis showed that the outcomes of patients were significantly better in the low-risk group than in the high-risk group (P < 0.05, log-rank test; Figure 2B). The area under curve (AUC) of time-dependent ROC curves for the GILncSigwas 0.727 (Figure 2C). We classified the patients in the training set based on their scores (Figure 2D). As shown in Figure 2E, lncRNA LINC01234 was upregulated and lncRNA LINC02471 was downregulated in patients with high scores, while GILncSig showed opposite patterns in patients with low scores. Comparison analysis showed no significant differences in the somatic mutation patterns between patients in the high-risk and low-risk groups. Moreover, UBQLN4 (one of the driving factors of gene instability) expression was significantly lower in high-risk patients compared with low-risk patients (P = 0.024, Mann–Whitney U test; Figure 2F).
Regulatory perspectives on next-generation sequencing and complementary diagnostics in Japan
Published in Expert Review of Molecular Diagnostics, 2020
Rumiko Shimazawa, Masayuki Ikeda
The number of somatic mutations in cancers differs among cell types and their tumor types. Likewise, the roles played in tumorigenesis differ among driver mutations. Cancer cell heterogeneity is recognized not only between, but also within a tumor. Furthermore, both epigenetic and micro-environmental factors also affect the heterogeneity [65–67]. As we better understand the process of somatic mutation in cancer and move away from the one biomarker/one drug scenario, we must also ensure that diagnostic tools be applied to test for multiple biomarkers, thus reflecting the heterogeneity and complexity of the specific cancer. In such circumstances, NGS can help to confirm a diagnosis and evaluate prognostic predictions in patients with mainly solid tumors for whom no standard treatment has been established.
Related Knowledge Centers
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