CD24 negativity reprograms mitochondrial metabolism to PPARα and NF-κB-driven fatty acid ß-oxidation in triple-negative breast cancer.

CD24 is a well-characterized breast cancer (BC) stem cell (BCSC) marker. Primary breast tumor cells having CD24-negativity together with CD44-positivity is known to maintain high metastatic potential. However, the functional role of CD24 gene in triple-negative BC (TNBC), an aggressive subtype of BC, is not well understood. While the significance of CD24 in regulating immune pathways is well recognized in previous studies, the significance of CD24 low expression in onco-signaling and metabolic rewiring is largely unknown. Using CD24 knock-down and over-expression TNBC models, our in vitro and in vivo analysis suggest that CD24 is a tumor suppressor in metastatic TNBC. Comprehensive in silico gene expression analysis of breast tumors followed by lipidomic and metabolomic analyses of CD24-modulated cells revealed that CD24 negativity induces mitochondrial oxidative phosphorylation and reprograms TNBC metabolism toward the fatty acid beta-oxidation (FAO) pathway. CD24 silencing activates PPARα-mediated regulation of FAO in TNBC cells. Further analysis using reverse-phase protein array and its validation using CD24-modulated TNBC cells and xenograft models nominated CD24-NF-κB-CPT1A signaling pathway as the central regulatory mechanism of CD24-mediated FAO activity. Overall, our study proposes a novel role of CD24 in metabolic reprogramming that can open new avenues for the treatment strategies for patients with metastatic TNBC.

Metabolomic Rewiring Promotes Endocrine Therapy Resistance in Breast Cancer.

Approximately one-third of endocrine-treated women with estrogen receptor alpha-positive (ER+) breast cancers are at risk of recurrence due to intrinsic or acquired resistance. Thus, it is vital to understand the mechanisms underlying endocrine therapy resistance in ER+ breast cancer to improve patient treatment. Mitochondrial fatty acid ß-oxidation (FAO) has been shown to be a major metabolic pathway in triple-negative breast cancer (TNBC) that can activate Src signaling. Here, we found metabolic reprogramming that increases FAO in ER+ breast cancer as a mechanism of resistance to endocrine therapy. A metabolically relevant, integrated gene signature was derived from transcriptomic, metabolomic, and lipidomic analyses in TNBC cells following inhibition of the FAO rate-limiting enzyme carnitine palmitoyl transferase 1 (CPT1), and this TNBC-derived signature was significantly associated with endocrine resistance in patients with ER+ breast cancer. Molecular, genetic, and metabolomic experiments identified activation of AMPK-FAO-oxidative phosphorylation (OXPHOS) signaling in endocrine-resistant ER+ breast cancer. CPT1 knockdown or treatment with FAO inhibitors in vitro and in vivo significantly enhanced the response of ER+ breast cancer cells to endocrine therapy. Consistent with the previous findings in TNBC, endocrine therapy-induced FAO activated the Src pathway in ER+ breast cancer. Src inhibitors suppressed the growth of endocrine-resistant tumors, and the efficacy could be further enhanced by metabolic priming with CPT1 inhibition. Collectively, this study developed and applied a TNBC-derived signature to reveal that metabolic reprogramming to FAO activates the Src pathway to drive endocrine resistance in ER+ breast cancer. SIGNIFICANCE: Increased fatty acid oxidation induced by endocrine therapy activates Src signaling to promote endocrine resistance in breast cancer, which can be overcome using clinically approved therapies targeting FAO and Src.

Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulations.

At the molecular level, all the biological processes are exposed to fluctuations emanating from various sources in and around the cellular system. Often these fluctuations dictate the outcome of a cell-fate decision-making event. Thus, having an accurate estimate of these fluctuations for any biological network is extremely important. There are well-established theoretical and numerical methods to quantify the intrinsic fluctuation present within a biological network arising due to the low copy numbers of cellular components. Unfortunately, the extrinsic fluctuations arising due to cell division events, epigenetic regulation, etc. have received very little attention. However, recent studies demonstrate that these extrinsic fluctuations significantly affect the transcriptional heterogeneity of certain important genes. Herein, we propose a new stochastic simulation algorithm to efficiently estimate these extrinsic fluctuations for experimentally constructed bidirectional transcriptional reporter systems along with the intrinsic variability. We use the Nanog transcriptional regulatory network and its variants to illustrate our numerical method. Our method reconciled experimental observations related to Nanog transcription, made exciting predictions, and can be applied to quantify intrinsic and extrinsic fluctuations for any similar transcriptional regulatory network.

Unraveling the origin of glucose mediated disparate proliferation dynamics of cancer stem cells.

Cancer stem cells (CSCs) often switch on their self-renewal programming aggressively to cause a relapse of cancer. Intriguingly, glucose triggers the proliferation propensities in CSCs by controlling the expression of the key transcription factor-like Nanog. However, the factors that critically govern this glucose-stimulated proliferation dynamics of CSCs remain elusive. Herein, by proposing a mathematical model of glucose-mediated Nanog regulation, we showed that the differential proliferation behavior of CSCs and cell-type similar to CSCs can be explained by considering the experimentally observed varied expression levels of key positive (STAT3) and negative (p53) regulators of Nanog. Our model reconciles various experimental observations and predicts ways to fine-tune the proliferation dynamics of these cell types in a context-dependent manner. In future, these modeling insights will be useful in developing improved therapeutic strategies to get rid of harmful CSCs.

Fine-tuning Nanog expression heterogeneity in embryonic stem cells by regulating a Nanog transcript-specific microRNA.

In embryonic stem cells (ESCs), the transcription factor Nanog maintains the stemness of ESCs despite exhibiting heterogeneous expression patterns under varied culture conditions. Efficient fine-tuning of Nanog expression heterogeneity could enable ESC proliferation and differentiation along specific lineages to be regulated. Herein, by employing a stochastic modeling approach, we show that Nanog expression heterogeneity can be controlled by modulating the regulatory features of a Nanog transcript-specific microRNA, mir-296. We demonstrate how and why the extent of origin-dependent fluctuations in Nanog expression level can be altered by varying either the binding efficiency of the microRNA-mRNA complex or the expression level of mir-296. Moreover, our model makes experimentally feasible and insightful predictions to maneuver Nanog expression heterogeneity explicitly to achieve cell-type-specific differentiation of ESCs.

Dynamical Reorganization of Transcriptional Events Governs Robust Nanog Heterogeneity.

Nanog maintains the pluripotency of embryonic stem cells (ESCs), while demonstrating high expression heterogeneity. Intriguingly, the overall heterogeneity at the Nanog mRNA level under various culture conditions gets precisely partitioned into intrinsic and extrinsic fluctuations. However, the dynamical origin of such a robust transcriptional noise regulation still remains illusive. Herein, we propose a new stochastic simulation strategy that efficiently reconciles the strict apportioning of fluctuations observed in Nanog transcription, while predicting possible experimental scenarios to avoid such an exact noise segregation. Importantly, our model analyses reveal that different culture conditions essentially preserve the robust Nanog expression heterogeneity by altering the dynamics of transcriptional events. In the future, these insights will be useful to systematically maneuver cell-fate decision-making events of ESCs.

Decoding the regulatory mechanism of glucose and insulin induced phosphatidylinositol 3,4,5-trisphosphate dynamics in ß-cells.

In MIN6 pancreatic ß-cells, glucose and insulin act in a synergistic manner to regulate the dynamics of Phosphatidylinositol (3,4,5)-trisphosphate (PIP3). However, the precise regulatory mechanism behind such an experimentally observed synergy is poorly understood. In this article, we propose a phenomenological mathematical model for studying the glucose and insulin driven PIP3 activation dynamics under various stimulatory conditions to unfold the mechanism responsible for the observed synergy. The modeling study reveals that the experimentally observed oscillation in PIP3 dynamics with disparate time scales for different external glucose doses is mainly orchestrated by the complex dynamic regulation of cytosolic Ca2+ in ß-cells. The model accounts for the dose-dependent activation of PIP3 as a function of externally added insulin, and further shows that even in the absence of Ca2+ signaling, externally added glucose can still maintain a basal level of endogenous insulin secretion via the fatty acid metabolism pathway. Importantly, the model analysis suggests that the glucose mediated ROS (reactive oxygen species) activation often contributes considerably to the synergistic activation of PIP3 by glucose and insulin in a context dependent manner. Under the physiological conditions that keep ß-cells in an insulin responsive state, the effect of glucose induced ROS signaling plays a moderate role in PIP3 activation. As ß-cells approach an insulin resistant state, the glucose induced ROS signaling significantly affects the PIP3 dynamics. Our findings provide a plausible mechanistic insight into the experimentally observed synergy, and can lead to novel therapeutic strategies.