Tumor cell-intrinsic phenotypic plasticity facilitates adaptive cellular reprogramming driving acquired drug
Heinz Hammerlindl1, Helmut Schaider2
1The University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent Street, Brisbane, QLD, 4102, Australia.
Abstract:
The enthusiasm about successful novel therapeutic strategies in cancer is often quickly dampened by the development of drug resistance. This is true for targeted therapies using tyrosine kinase inhibitors for EGFR or BRAF mutant cancers, but is also an increasingly recognized problem for immunotherapies. One of the major obstacles of successful cancer therapy is tumor heterogeneity of genotypic and phenotypic features. Historically, drivers for drug resistance have been suspected and found on the genetic level, with mutations either being pre-existing in a subset of cancer cells or emerging de novo to mediate drug resistance. In contrast to that, our group and others identified a non-mutational adaptive response, resulting in a reversible, drug tolerant, slow cycling phenotype that precedes the emergence of permanent drug resistance and is triggered by prolonged drug exposure. More recently, studies described the importance of initially reversible transcriptional reprogramming for the development of acquired drug resistance, identified factors important for the survival of the slow cycling phenotype and investigated the relationship of mutational and non-mutational resistance mechanisms. However, the connection and relative importance of mutational and adaptive drug resistance in relation to the in vitro models at hand and the clinically observed response patterns remains poorly defined. In this review we focus on adaptive intrinsic phenotypic plasticity in cancer cells that leads to the drug tolerant slow cycling state, which eventually transitions to permanent resistance, and propose a general model based on current literature, to describe the development of acquired drug resistance.
Insights
Cancer drug resistance is a major challenge, often driven by genetic mutations or adaptive cellular changes. This review explores how non-mutational adaptive plasticity leads to drug tolerance and eventual resistance, proposing a model for acquired resistance.
Area of Science:
- Oncology
- Cancer Biology
- Drug Resistance Mechanisms
Background:
- Drug resistance, both to targeted therapies and immunotherapies, significantly hinders cancer treatment success.
- Tumor heterogeneity, encompassing genotypic and phenotypic variations, is a key obstacle in achieving effective cancer therapy.
- While genetic mutations have been historically recognized as drivers of drug resistance, non-mutational adaptive responses are increasingly implicated.
Purpose of the Study:
- To review and synthesize current literature on adaptive intrinsic phenotypic plasticity in cancer cells.
- To elucidate the development of drug-tolerant, slow-cycling phenotypes preceding permanent drug resistance.
- To propose a generalized model for acquired drug resistance, integrating mutational and non-mutational mechanisms.
Main Methods:
- Literature review and synthesis of existing research on cancer drug resistance.
- Analysis of studies investigating non-mutational adaptive responses and transcriptional reprogramming.
- Examination of the relationship between in vitro models and clinical observations of resistance patterns.
Main Results:
- Non-mutational adaptive responses, including reversible transcriptional reprogramming, contribute to a drug-tolerant, slow-cycling state.
- This adaptive state can precede and potentially transition into permanent, mutation-driven drug resistance.
- The interplay and relative importance of mutational versus adaptive resistance mechanisms require further definition.
Conclusions:
- Adaptive phenotypic plasticity is a critical, often reversible, mechanism contributing to acquired cancer drug resistance.
- Understanding this plasticity is essential for developing novel therapeutic strategies to overcome or prevent resistance.
- A comprehensive model integrating genetic and adaptive resistance is needed to better predict and manage clinical treatment outcomes.
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