Integrating mutational and nonmutational mechanisms of acquired therapy resistance within the Darwinian paradigm

Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies

Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Clonal differences underlie variable responses to sequential and prolonged treatment

Cancer cells exhibit dramatic differences in gene expression at the single-cell level, which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor. A record of this paper's transparent peer review process is included in the supplemental information.

Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy in pancreatic ductal adenocarcinoma

Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (Irf6), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.

Adaptive therapy: a tumor therapy strategy based on Darwinian evolution theory

Cancer progression is a dynamic process of continuous evolution, in which genetic diversity and heterogeneity are generated by clonal and subclonal amplification based on random mutations. Traditional cancer treatment strategies have a great challenge, which often leads to treatment failure due to drug resistance. Integrating evolutionary dynamics into treatment regimens may be an effective way to overcome the problem of drug resistance. In particular, a potential treatment is adaptive therapy, which strategy advocates containment strategies that adjust the treatment cycles according to tumor evolution to control the growth of treatment-resistant cells. In this review, we first summarize the shortcomings of traditional tumor treatment methods in evolution and then introduce the theoretical basis and research status of adaptive therapy. By analyzing the limitations of adaptive therapy and exploring possible solutions, we can broaden people's understanding of adaptive therapy and provide new insights and strategies for tumor treatment.

Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy

Acquired resistance to immune checkpoint immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we found that tumors underwent an epithelial-to-mesenchymal transition (EMT) that resulted in reduced sensitivity to T cell-mediated killing. EMT-transcription factors (EMT-TFs) ZEB1 and SNAIL function as master genetic and epigenetic regulators of this tumor-intrinsic effect. Acquired resistance was not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, EMT was associated with epigenetic and transcriptional silencing of interferon regulatory factor 6 (Irf6), which renders tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings show how resistance to immunotherapy in PDAC can be acquired through plasticity programs that render tumor cells impervious to T cell killing.

Clonal differences underlie variable responses to sequential and prolonged treatment

Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.