The Mitochondrial Transacylase, Tafazzin, Regulates AML Stemness by Modulating Intracellular Levels of Phospholipids

Seneviratne, Ayesh K.; Xu, Mingjing; Henao, Juan J. Aristizabal; Fajardo, Val A.; Zhou, Hao; Voisin, Véronique; Xu, Gang; Hurren, Rose; Kim, S.; MacLean, Neil; Wang, Xiaoming; Gronda, Marcela; Jeyaraju, Danny V.; Jitkova, Yulia; Ketela, Troy; Mullokandov, Michael; Sharon, David; Thomas, Geethu Emily; Chouinard‐Watkins, Raphaël; Hawley, James R.; Schafer, Caitlin; Yau, Helen Loo; Khuchua, Zaza; Aman, Ahmed; Al‐awar, Rima; Gross, Atan; Claypool, Steven M.; Bazinet, Richard P.; Lupien, Mathieu; Chan, Steven M.; Carvalho, Daniel D. De; Minden, Mark D.; Bader, Gary D.; Stark, Ken D.; LeBlanc, Paul J.; Schimmer, Aaron D.

doi:10.1016/j.stem.2019.02.020

Cited by 37 publications

(38 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stemness signatures were already identi ed in several malignancies and had different prognostic value in AML, breast cancer, lung cancer or colon cancers (32)(33)(34). In our screening in multiple cohorts, the 13gene signature was never been reported in other previous studies that could predict the PFS outcomes, which was convenient to implement in clinical practice.…”

Section: Discussionmentioning

confidence: 89%

Systematical assessment of cancer stemness traits via one-class logistic regression (OCLR) algorithm and associations with tumor immune infiltrates in prostate cancer based on seven cohorts

Chen¹,

Xie²,

Peng³

2020

Preprint

View full text Add to dashboard Cite

Background: Prostate cancer stemness (PCS) cells have been reported to drive tumor progression, recurrence and drug resistance. However, there is lacking systematical assessment of stemness traits and associations with immunological properties in prostate adenocarcinoma (PRAD). Methods We collected 7 PRAD cohorts with 1465 men and calculated the stemness indices for each sample using the innovative one-class logistic regression (OCLR) machine learning algorithm. We selected the mRNAsi to quantify the stemness traits that correlated significantly with prognosis and accordingly identified 21 PCS-related CpG loci and 13 pivotal signature. Meanwhile, we conducted consensus clustering and classified the total cohorts into 5 PCS clusters with distinct outcomes based on the 13-gene panel. Additionally, we implemented the CIBERSORT algorithm to infer the differential abundance across 5 PCS clusters. Lastly, we used the Connectivity Map (CMap) resource to screen potential compounds for targeting PRAD stemness. Results: The 13-gene based PCS model possessed high predictive significance for progression-free survival (PFS) that was trained and validated in 7 independent cohorts. We found that PCScluster5 possessed the highest stemness fractions and suffered from the worst prognosis. Immune infiltration analysis shows that the activated immune cells (CD8+ T cell and dendritic cells) infiltrated significantly less in PCScluster5 than other clusters, especially PCScluster1, supporting the negative regulations between stemness and anticancer immunity. High mRNAsi was also found to be associated with up-regulation of immunosuppressive checkpoints, like PDL1. Finally, several potential compounds, including the top hits of cell cycle inhibitor and FOXM1 inhibitor, were identified for targeting PRAD stemness. Conclusion: Our study comprehensively evaluated the PRAD stemness traits based on large cohorts and established a 13-gene based classifier for predicting prognosis or potential strategies for stemness treatment.

show abstract

Section: Discussionmentioning

confidence: 89%

Systematical assessment of cancer stemness traits via one-class logistic regression (OCLR) algorithm and associations with tumor immune infiltrates in prostate cancer based on seven cohorts

Chen¹,

Xie²,

Peng³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Taz inhibition induces phospholipid remodelling by decreasing cardiolipin levels in leukaemic stem cells and, consequently, increasing the abundance of PS. 107 Of note, this remodelling did not affect mitochondrial integrity, but rather increasing PS abundance promoted Toll-like receptor (TLR) activity, thereby inducing a shift from stemness to differentiation. Further phospholipid remodelling has been observed in various cancer cell lines, including leukaemia, demonstrated by an increase in ether lipid content, implicating them in carcinogenesis.…”

Section: Lipid Metabolism and Leukaemiamentioning

confidence: 98%

“…This tightly regulated network can also affect leukaemic stemness. Taz inhibition induces phospholipid remodelling by decreasing cardiolipin levels in leukaemic stem cells and, consequently, increasing the abundance of PS . Of note, this remodelling did not affect mitochondrial integrity, but rather increasing PS abundance promoted Toll‐like receptor (TLR) activity, thereby inducing a shift from stemness to differentiation.…”

Section: Lipid Metabolism and Leukaemiamentioning

confidence: 99%

Fat for fuel: lipid metabolism in haematopoiesis

et al. 2019

View full text Add to dashboard Cite

The importance of metabolic regulation in the immune system has launched back into the limelight in recent years. Various metabolic pathways have been examined in the context of their contribution to maintaining immune cell homeostasis and function. Moreover, this regulation is also important in the immune cell precursors, where metabolism controls their maintenance and cell fate. This review will discuss lipid metabolism in the context of haematopoiesis, that is blood cell development. We specifically focus on nonoxidative lipid metabolism which encapsulates the synthesis and degradation of the major lipid classes such as phospholipids, sphingolipids and sterols. We will also discuss how these metabolic processes are affected by haematological malignancies such as leukaemia and lymphoma, which are known to have altered metabolism, and how these different pathways contribute to the pathology.

show abstract

“…A brief outline for the preparation of the concentrated virus is provided below. The reader is also referred to ( Seneviratne et al., 2019 ) for more details. Proper institutional approvals for biosafety, use of animals, and human samples should be obtained before starting this protocol.…”

Section: Before You Beginmentioning

confidence: 99%

Transduction of Primary AML Cells with Lentiviral Vector for In Vitro Study or In Vivo Engraftment

et al. 2020

Self Cite

View full text Add to dashboard Cite

Summary We describe a method to silence genes in primary acute myeloid leukemia cells by transducing them with shRNA in lentiviral vectors. The transduction of primary non-adherent cells is particularly challenging. The protocol will aid in performing such experiments and is particularly helpful to prepare cells for in vivo engraftment studies. Use of a special medium supplemented with cytokines preserves the viability of the leukemic stem cells and their ability to engraft the marrow of immune-deficient mice. For complete details on the use and execution of this protocol, please refer to Singh et al. (2020 ).

show abstract

The Mitochondrial Transacylase, Tafazzin, Regulates AML Stemness by Modulating Intracellular Levels of Phospholipids

Abstract: Highlights d Inhibiting TAZ leads to increased levels of PS in AML cells d TAZ and PS regulate AML stemness d Reducing TAZ or increasing PS decreases AML stemness and activates TLR signaling d Increasing PS is a potential therapeutic strategy for AML

Cited by 37 publications

References 67 publications

Systematical assessment of cancer stemness traits via one-class logistic regression (OCLR) algorithm and associations with tumor immune infiltrates in prostate cancer based on seven cohorts

Systematical assessment of cancer stemness traits via one-class logistic regression (OCLR) algorithm and associations with tumor immune infiltrates in prostate cancer based on seven cohorts

Fat for fuel: lipid metabolism in haematopoiesis

Transduction of Primary AML Cells with Lentiviral Vector for In Vitro Study or In Vivo Engraftment

Contact Info

Product

Resources

About