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Metastatic competency and tumor spheroid formation are independent cell states governed by RB in lung adenocarcinoma.

Nelson F FreeburgNia PetersonDain A RuizAmy C GladsteinDavid M Feldser
Published in: Cancer research communications (2023)
Inactivation of the retinoblastoma (RB) tumor suppressor in lung adenocarcinoma is associated with the rapid acquisition of metastatic ability and the loss of lung cell lineage commitment. We previously showed that restoration of RB in advanced lung adenocarcinomas in the mouse was correlated with a decreased frequency of lineage de-committed tumors and overt metastases. To identify a causal relationship for RB and its role in reprogramming lineage commitment and reducing metastatic competency in lung adenocarcinoma, we developed multiple tumor spheroid forming lines where RB restoration could be achieved after characterization of the degree of each spheroid's lineage commitment and metastatic ability. Surprisingly, we discovered that RB inactivation dramatically promoted tumor spheroid forming potential in tumors that arise in the KrasLSL-G12D/+; p53flox/flox lung adenocarcinoma model. However, RB reactivation had no effect on the maintenance of tumor spheroid lines once established. Additionally, we show that RB-deficient tumor spheroid lines are not uniformly metastatically competent but are equally likely to be non-metastatic. Interestingly, unlike tumor spheroid maintenance, RB restoration could functionally revert metastatic tumor spheroids to a non-metastatic cell state. Thus, strategies to reinstate RB-pathway activity in lung cancer may reverse metastatic ability and have therapeutic potential. Finally, the acquisition of tumor spheroid forming potential reflects underlying cell state plasticity, which is often predictive of, or even conflated with metastatic ability. Our data support that each is a discrete cell state restricted by RB and question the suitability of tumor spheroid models for their predictive potential of advanced metastatic tumor cell states.
Keyphrases
  • squamous cell carcinoma
  • small cell lung cancer
  • single cell
  • cell therapy
  • stem cells
  • mesenchymal stem cells
  • big data
  • data analysis