Dataset Information

Alvarez2019 - A nonlinear mathematical model of cell-mediated immune response for tumor phenotypic heterogeneity

ABSTRACT: This is a non-linear mathematical model of cancer immunosurveillance that takes into account intratumoral phenotypic heterogeneity, such as differential expression of cell surface receptors and growth factors, according to cell-mediated immune responses. The model describes phenomena that have also been observed in vivo, such as tumor dormancy, cancer immunoediting, and a strong sensitivity to initial conditions.

SUBMITTER: Johannes Meyer

PROVIDER: BIOMD0000000790 | BioModels | 2019-08-12

REPOSITORIES: BioModels

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Publications

A nonlinear mathematical model of cell-mediated immune response for tumor phenotypic heterogeneity.

Alvarez Robinson F RF Barbuto José A M JAM Venegeroles Roberto R

Journal of theoretical biology 20190329

Human cancers display intra-tumor heterogeneity in many phenotypic features, such as expression of cell surface receptors, growth, and angiogenic, proliferative, and immunogenic factors, which represent obstacles to a successful immune response. In this paper, we propose a nonlinear mathematical model of cancer immunosurveillance that takes into account some of these features based on cell-mediated immune responses. The model describes phenomena that are seen in vivo, such as tumor dormancy, rob ...[more]

PMID: 30930063

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Project description:Intra-tumor heterogeneity (ITH) results from coexistence of genetically distinct cancer cell (sub)populations, their phenotypic plasticity, and the presence of heterotypic components of the tumor microenvironment (TME). Here we addressed potential association between phenotypic ITH revealed by mass spectrometry imaging (MSI) and the prognosis of breast cancer. Tissue specimens resected from 59 patients treated radically due to the locally advanced HER2-positive invasive ductal carcinoma were included in the study. After on-tissue trypsin digestion of cellu-lar proteins, peptide maps of all cancer regions (about 380,000 spectra in total) were segmented by an unsupervised approach to reveal their intrinsic heterogeneity. A high degree of similarity between spectra was observed, which indicated relative homogeneity of cancer regions. How-ever, when the number and diversity of the detected clusters of spectra were analyzed, differ-ences between patient groups were observed. It is noteworthy that a higher degree of heteroge-neity was found in tumors from patients who remained disease-free during a 5-year follow-up (n=38) compared to tumors from patients with progressive disease (distant metastases detected during follow-up, n=21). Interestingly, such differences were not observed between patients with different status of regional lymph nodes, cancer grade, or expression of estrogen receptor at the time of the primary treatment. Subsequently, spectral components with different abundance in cancer regions were detected in patients with different outcomes, and their hypothetical identity was established by assignment to measured masses of tryptic peptides identified in correspond-ing tissue lysates. Such differentiating components were associated with proteins involved in immune regulation and hemostasis. We postulate that a higher heterogeneity of tumors with a better prognosis could reflect the presence of heterotypic components including the microvas-culature and infiltrating immune cells, that facilitated response to treatment.

Dataset Information

Alvarez2019 - A nonlinear mathematical model of cell-mediated immune response for tumor phenotypic heterogeneity

Publications

A nonlinear mathematical model of cell-mediated immune response for tumor phenotypic heterogeneity.

Similar Datasets

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