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Current in vivo Models for Brain Disorders
Published in Carla Vitorino, Andreia Jorge, Alberto Pais, Nanoparticles for Brain Drug Delivery, 2021
Marta Guerra-Rebollo, Cristina Garrido
GEM models are based on specific genetic alterations observed in human tumours. GEM models have been established by regulating gene expression or by altering key signalling pathways known to be disrupted in human GB [19]. Spontaneous tumours recapitulate complex processes which address specific molecular events responsible for tumour initiation and progression [20]. GEM models present a specific dysfunctional cancer-related pathway in a controlled manner and can provide invaluable insights into the efficacy of single- or multiple-drug treatment [21]. However, their use in therapeutic studies is often difficult because of tumour initiation cannot be controlled and they characterised by poor reproducibility [22, 23].
Comparative Anatomy, Physiology, and Biochemistry of Mammalian Skin
Published in David W. Hobson, Dermal and Ocular Toxicology, 2020
The importance of the hair growth cycle to cutaneous toxicology and percutaneous absorption is obvious, in that response to specific agents may be dependent upon the state of hair growth present. If possible, hair growth should be synchronized within animals of a study. In laboratory animals this can be accomplished by clipping all animals a day before treatment, a process which induces a new hair growth cycle in all animals. This is especially important in tumor initiation and promotion protocols.
Mouse to Man: Extrapolation from Animals
Published in Samuel C. Morris, Cancer Risk Assessment, 2020
The multistage model, presumably the most well-based biologically of any model used in regulatory practice, is grounded in the biological understanding of the 1950s. It provides for multiple stages in the development of a tumor, but these stages do not represent specific, known, biological mechanisms. The parameters for each stage must be determined simultaneously from dose and tumor production data, one cannot physically measure each parameter specifically. While a complete understanding of the carcinogenic process remains elusive, biomedical science has advanced considerably in this area since the 1950s. A better appreciation of the many different mechanisms involved in tumor initiation and development has been gained (Chap. 2). Quantitative research models have been developed for many of these precesses (see, e.g., Thompson and Brown, 1987). In addition, the ability to measure quantities previously unheard of has advanced rapidly; this ability allows quantification and verification of mechanistic models. As was the case for pharmacokinetics (Chap. 7), cancer risk modeling is also moving to more biologically based models. The call for such change was made strongly by Wilson (1986) in an editorial in Risk Analysis.
The WHO claims estrogens are ‘carcinogenic’: is this true?
Published in Climacteric, 2023
Nevertheless, 30–35 tumor doublings are required to achieve a tumor size of 1 cm diameter. This corresponds to 109 cells, while a single tumor cell has an approximate volume of 10−6 mm3 [21]. A tumor cell therefore requires 1750–3500 days to develop into a clinically and/or mammographically detectable cell mass [22]. This equates to at least 5–10 years from tumor initiation to cancer diagnosis. Observation of breast cancer after a treatment duration of less than about 5–10 years, as recently reported in the largest meta-analysis on breast cancer risk and HRT [23], can only be able to detect already pre-existing breast cancer, suggesting that these cancers also would have occurred without estrogen therapy as a result of many other proliferating factors exerting endogenous or exogenous actions.
Bone tumors effective therapy through functionalized hydrogels: current developments and future expectations
Published in Drug Delivery, 2022
Ruyi Shao, Yeben Wang, Laifeng Li, Yongqiang Dong, Jiayi Zhao, Wenqing Liang
Sarcomas are primary bone tumors originating from rich cell populations due to close interaction between cancer cells and local microenvironments’ cell types, e.g. mesenchymal stem cells, osteoblasts, cancer-associated fibroblasts, osteocytes, chondrocytes, osteoclasts, or immune infiltrates (Menéndez et al., 2021; Tzanakakis et al., 2021). The most common primary bone cancers are Ewing sarcomas, chondrosarcomas, and osteosarcomas constituting 16, 25, and 35% respectively of malignant primary bone tumors (Cortini et al., 2019; Menéndez et al., 2021). These tumors are rarely occurring and comprise overall <0.2% of all diagnosed cancers with an approximate incidence rate of around 0.9 per 100,000 individuals annually for all joint and bone malignancies (Franchi, 2012; Menéndez et al., 2021). Although they less frequently occur, they are challenging have high mortality rates, and pose an overall burden on healthcare sectors (Cortini et al., 2019; Thanindratarn et al., 2019). Sarcomas consist of diverse cells populations, including cancer stem cells (CSCs). CSCs have certain features of normal stem cells e.g. differentiation capacity and self-renewal. These CSCs can more precisely be termed ‘tumor-initiating cells’ because they can generate nearly all cell types usually present in a tumor (Steinbichler et al., 2018). Thus, CSCs produce a broad range of markers depending on the tissue of origin and cancer type (Fujiwara & Ozaki, 2016; Steinbichler et al., 2018).
The association between body mass index and pathological complete response in neoadjuvant-treated breast cancer patients
Published in Acta Oncologica, 2022
Ida Skarping, Stine Blaabjerg Pedersen, Daniel Förnvik, Sophia Zackrisson, Signe Borgquist
The current understanding is that obesity is mainly associated with the risk of postmenopausal BC, whereas most studies report a null or inverse association of obesity with BC risk in premenopausal women [39,40]. While risk and prognostic/predictive factors are different entities, their underlying biological explanation might share common grounds. The mechanistic links between adiposity and BC, sex hormone metabolism, insulin IGF-signaling, adipokine pathobiology, and subclinical inflammation [41] might also cause a less favorable response to NACT, as investigated in this study. The fostering and fueling factors underlying tumor initiation and growth might prohibit an adequate response to chemotherapy. For example, in the breasts of overweight women, the tumor microenvironment is influenced by a larger adipocyte population, causing different cytokine profiles, a hypoxic environment, and locally enhanced stiffness due to remodeling of the matrix [42,43]. In a recently published exploratory study (N = 62), both obesity and high tumor expression of the adipokine apelin were independently associated with lower pCR rates, indicating that specific adipokines are associated with NACT response [44]. In overweight patients with BC, we hypothesize that the focally stiffer environment, in an otherwise mostly fatty breast, might mechanically hinder the transport of NACT’s active cytotoxic elements.