Scientific Reports (Nov 2023)

Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy

  • Darcy L. Welch,
  • Brooke L. Fridley,
  • Ling Cen,
  • Jamie K. Teer,
  • Sean J. Yoder,
  • Fredrik Pettersson,
  • Liping Xu,
  • Chia-Ho Cheng,
  • Yonghong Zhang,
  • Mark G. Alexandrow,
  • Shengyan Xiang,
  • Mark Robertson-Tessi,
  • Joel S. Brown,
  • Jonathan Metts,
  • Andrew S. Brohl,
  • Damon R. Reed

DOI
https://doi.org/10.1038/s41598-023-47412-1
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

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Abstract Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.