Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Ware, Kathryn E.; Gupta, Santosh; Eng, Jared S.; Kemeny, Gabor; Puviindran, Bhairavy; Foo, Wen‐Chi; Crawford, Lorin; Almquist, R. Garland; Runyambo, Daniella; Thomas, Beatrice C.; Sheth, Maya U.; Athiya, Agarwal; Pierobon, Mariaelena; Petricoin, Emanuel F.; Corcoran, David L.; Freedman, Jennifer A.; Patierno, Steven R.; Zhang, Tian; Gregory, Simon; Sychev, Zoi; Drake, Justin M.; Armstrong, Andrew J.; Somarelli, Jason A.

doi:10.1101/2020.04.22.050385

Cited by 9 publications

(24 citation statements)

References 90 publications

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“…Oncoviruses such as EBV and HPV have been associated with increased PD-L1 levels (Farrukh et al 2021). Likewise, EMT is also correlated with upregulation of immune checkpoints (Ware et al 2020; Chakraborty et al 2021). These relationships prompted us to investigate whether oncovirus-positive samples were enriched in PD-L1 activity and/or expression.…”

Section: Resultsmentioning

confidence: 99%

“…Given the relationship between PD-L1 and EMT (Ware et al 2020; Chakraborty et al 2021), we also analyzed the correlations between PD-L1 activity and EMT scores across our entire cohort of datasets. We observed that the PD-L1 activity score was more likely to be positively correlated with a Mes score (22 out of 28 datasets in Fig 4C ) than with an Epi signature (15 out of 28 datasets in Fig 4C ).…”

Section: Resultsmentioning

confidence: 99%

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Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

Sehgal¹,

Ray²,

Vaz

et al. 2022

Preprint

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Oncoviruses exploit diverse host mechanisms to survive and proliferate. These adaptive strategies overlap with mechanisms employed by malignant cells during their adaptation to dynamic micro-environments and for evasion of immune attack. While the role of individual oncoviruses in mediating cancer progression has been extensively characterized, little is known about the common gene regulatory features of oncovirus-induced cancers. Here, we focus on defining the interplay between several cancer hallmarks, including Epithelial- Mesenchymal Transition (EMT), metabolic alterations, and immune evasion across major oncoviruses by examining publicly-available transcriptomics data sets containing both oncovirus-positive and oncovirus-negative samples. We observe that oncovirus-positive samples display varying degrees of EMT and metabolic reprogramming. While the progression of EMT generally associated with an enriched glycolytic metabolic program and suppressed fatty acid oxidation (FAO) and oxidative phosphorylation (OXPHOS), partial EMT correlated well with glycolysis. Furthermore, oncovirus-positive samples had higher activity and/or expression levels of immune checkpoint molecules, such as PD-L1, which was associated with a partial EMT program. These analyses thus decode common pathways in oncovirus-positive samples that may be used in pinpointing new therapeutic vulnerabilities for oncovirus-associated cancer cell plasticity.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

Sehgal¹,

Ray²,

Vaz

et al. 2022

Preprint

Self Cite

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Section: Discussionmentioning

confidence: 99%

A mechanistic modeling framework reveals the key principles underlying tumor metabolism

et al. 2022

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While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.

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“…Our modeling framework predicts that the emergence of enzalutamide resistance must be accompanied by a change in the metabolic profile of tumor cells including an increase in glucose uptake. A recent study has shown that the activities of signaling pathways that regulate cell metabolism, including the p38 pathway, are indeed altered by enzalutamide treatment in prostate cancer cells (57). Multiple studies have shown a tight coupling between cell-type switching and change in the metabolic state of cells, especially in the context of epithelial-mesenchymal plasticity.…”

Section: Discussionmentioning

confidence: 99%

A Mechanistic Modeling Framework Reveals the Key Principles Underlying Tumor Metabolism

Tripathi

Park²,

Pudakalakatti

et al. 2021

Preprint

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While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, utilizing glycolysis, oxidative phosphorylation, or both, and can switch between different metabolic phenotypes. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive metabolic heterogeneity. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. We report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.SignificanceThis study presents an interpretable mathematical framework for analyzing the metabolic heterogeneity and plasticity exhibited by tumor cells.

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Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Cited by 9 publications

References 90 publications

Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

A mechanistic modeling framework reveals the key principles underlying tumor metabolism

A Mechanistic Modeling Framework Reveals the Key Principles Underlying Tumor Metabolism

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