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An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.

ABSTRACT: 3D cell cultures are in-vitro models representing a significant improvement with respect to traditional monolayers. Their diffusion and applicability, however, are hampered by the complexity of 3D systems, that add new physical variables for experimental analyses. In order to account for these additional features and improve the study of 3D cultures, we here present SALSA (ScAffoLd SimulAtor), a general purpose computational tool that can simulate the behavior of a population of cells cultured in a 3D scaffold. This software allows for the complete customization of both the polymeric template structure and the cell population behavior and characteristics. In the following the technical description of SALSA will be presented, together with its validation and an example of how it could be used to optimize the experimental analysis of two breast cancer cell lines cultured in collagen scaffolds. This work contributes to the growing field of integrated in-silico/in-vitro analysis of biological systems, which have great potential for the study of complex cell population behaviours and could lead to improve and facilitate the effectiveness and diffusion of 3D cell culture models.

SUBMITTER: Cortesi M

PROVIDER: S-EPMC7395763 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.

Cortesi Marilisa M Liverani Chiara C Mercatali Laura L Ibrahim Toni T Giordano Emanuele E

Scientific reports 20200731 1

3D cell cultures are in-vitro models representing a significant improvement with respect to traditional monolayers. Their diffusion and applicability, however, are hampered by the complexity of 3D systems, that add new physical variables for experimental analyses. In order to account for these additional features and improve the study of 3D cultures, we here present SALSA (ScAffoLd SimulAtor), a general purpose computational tool that can simulate the behavior of a population of cells cultured i ...[more]

PMID: 32737377

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Project description:ImportanceIntratumoral heterogeneity has been recognized as a significant barrier in successfully developing targetable biomarkers for gastroesophageal adenocarcinoma (GEA) and may affect neoadjuvant precision medicine approaches.ObjectiveTo describe intratumoral spatial heterogeneity of tumor cell populations in nonmetastatic GEA and its association with survival.Design, setting, and participantsThis case series retrospectively identified 41 patients with GEA who underwent up-front surgical resection at a tertiary referral cancer center from January 1, 1989, through December 31, 2013. Survival was calculated from date of surgery to date of death through June 1, 2017. Data were analyzed from June 2, 2017, to March 1, 2019.Main outcomes and measuresOverall survival, intratumoral clonal composition determined by genomic single-nucleotide variation array and bioinformatic analysis, and intercellular tumoral distances determined by multiprobe fluorescence in situ hybridization.ResultsAmong the 41 patients included in the analysis (22 men [54%]; mean [SD] age, 63 [12] years), a high proportion (19 [46%]) presented with tumors possessing high intratumoral heterogeneity. Kaplan-Meier analysis demonstrated that cases with an intratumoral clonal composition count of at least 2 exhibited worse survival compared with cases with a clonal composition count of 0 to 1 (univariate hazard ratio, 3.92; 95% CI, 1.27-12.08; P = .02). This finding remained significant on multivariate analysis controlling for stage, Lauren histologic subtype, receipt of adjuvant therapy, and age (multivariate hazard ratio, 4.55; 95% CI, 1.09-19.04; P = .04). Multiprobe fluorescence in situ hybridization demonstrated intratumoral clonal populations coexisting at submillimeter distances with differing relevant oncogenic copy number alterations, such as EGFR, JAK2, FGFR2, MET, CCND1, KRAS, MYC, PIK3CA, CD274, and PDCD1LG2.Conclusions and relevanceThis study found that spatial intratumoral heterogeneity of oncogenic copy number alterations exists before metastatic dissemination, and increased heterogeneity was associated with worse outcomes in resected GEA. Baseline heterogeneity illustrates the challenges in GEA targeted therapy. Further study may offer insight into strategies on combinatorial and/or sequential targeted and immunotherapeutic approaches.

Dataset Information

An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.

Publications

An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.

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