Philip L Lorenzi

Dr. Philip L Lorenzi

The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 February 2019 in BMC Bioinformatics
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Journal Article
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DDDi Du
Di Du
TTTan Tan
Tan Tan
YWYumeng Wang
Yumeng Wang
BPBo Peng
Bo Peng
JWJohn N. Weinstein
John N. Weinstein
PLPhilip L Lorenzi
Philip L Lorenzi
The investigation of intracellular metabolism is the mainstay in the biotechnology and physiology settings. Intracellular metabolic rates are commonly evaluated using labeling pattern of the identified metabolites obtained from stable isotope labeling experiments. The labeling pattern or mass distribution vector describes the fractional abundances of all isotopologs with different masses as a result of isotopic labeling, which are typically resolved using mass spectrometry. Because naturally occurring isotopes and isotopic impurity also contribute to measured signals, the measured patterns must be corrected to obtain the labeling patterns. Since contaminant isotopologs with the same nominal mass can be resolved using modern mass spectrometers with high mass resolution, the correction process should be resolution dependent. Here we present a software tool, ElemCor, to perform correction of such data in a resolution-dependent manner. The tool is based on mass difference theory (MDT) and information from unlabeled samples (ULS) to account for resolution effects. MDT is a mathematical theory and only requires chemical formulae to perform correction. ULS is semi-empirical and requires additional measurement of isotopologs from unlabeled samples. We validate both methods and show their improvement in accuracy and comprehensiveness over existing methods using simulated data and experimental data from Saccharomyces cerevisiae. The tool is available at https://github.com/4dsoftware/elemcor . We present a software tool based on two methods, MDT and ULS, to correct LC-MS data from isotopic labeling experiments for natural abundance and isotopic impurity. We recommend MDT for low-mass compounds for cost efficiency in experiments, and ULS for high-mass compounds with relatively large spectral inaccuracy that can be tracked by unlabeled standards.

1 September 2018 in Cancer Discovery
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Journal Article
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LCLimo Chen
Limo Chen
LDLixia Diao
Lixia Diao
YYYongbin Yang
Yongbin Yang
XYXiaohui Yi
Xiaohui Yi
BRB. Leticia Rodriguez
B. Leticia Rodriguez
DGDon L. Gibbons
Don L. Gibbons
Although treatment with immune checkpoint inhibitors provides promising benefit for patients with cancer, optimal use is encumbered by high resistance rates and requires a thorough understanding of resistance mechanisms. We observed that tumors treated with PD-1/PD-L1 blocking antibodies develop resistance through the upregulation of CD38, which is induced by all-trans retinoic acid and IFNβ in the tumor microenvironment. In vitro and in vivo studies demonstrate that CD38 inhibits CD8+ T-cell function via adenosine receptor signaling and that CD38 or adenosine receptor blockade are effective strategies to overcome the resistance. Large data sets of human tumors reveal expression of CD38 in a subset of tumors with high levels of basal or treatment-induced T-cell infiltration, where immune checkpoint therapies are thought to be most effective. These findings provide a novel mechanism of acquired resistance to immune checkpoint therapy and an opportunity to expand their efficacy in cancer treatment. Significance: CD38 is a major mechanism of acquired resistance to PD-1/PD-L1 blockade, causing CD8+ T-cell suppression. Coinhibition of CD38 and PD-L1 improves antitumor immune response. Biomarker assessment in patient cohorts suggests that a combination strategy is applicable to a large percentage of patients in whom PD-1/PD-L1 blockade is currently indicated. Cancer Discov; 8(9); 1156–75. ©2018 AACR. See related commentary by Mittal et al., p. 1066. This article is highlighted in the In This Issue feature, p. 1047

8 May 2019 in Science Translational Medicine
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LZLiang Zhang
Liang Zhang
YYYixin Yao
Yixin Yao
SZShaojun Zhang
Shaojun Zhang
YLYang Liu
Yang Liu
HGHui Guo
Hui Guo
MWMichael Wang
Michael Wang
Targeting oxidative phosphorylation overcomes ibrutinib resistance in mantle cell lymphoma.

15 August 2019 in Blood
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Journal Article
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Yoko TabeYoko Tabe
Yoko Tabe
PLPhilip L Lorenzi
Philip L Lorenzi
MKMarina Konopleva
Marina Konopleva
The authors review the latest knowledge of amino acid metabolism in hematologic malignancies and the clinical relevance and potential of amino acid therapeutic targeting.

2 January 2024 in Nature Communications
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HLHyemin Lee
Hyemin Lee
AHAmber Horbath
Amber Horbath
LKLavanya Kondiparthi
Lavanya Kondiparthi
JMJitendra Kumar Meena
Jitendra Kumar Meena
Guang LeiGuang Lei
Guang Lei
BGBoyi Gan
Boyi Gan
How cells coordinate cell cycling with cell survival and death remains incompletely understood. Here, we show that cell cycle arrest has a potent suppressive effect on ferroptosis, a form of regulated cell death induced by overwhelming lipid peroxidation at cellular membranes. Mechanistically, cell cycle arrest induces diacylglycerol acyltransferase (DGAT)–dependent lipid droplet formation to sequester excessive polyunsaturated fatty acids (PUFAs) that accumulate in arrested cells in triacylglycerols (TAGs), resulting in ferroptosis suppression. Consequently, DGAT inhibition orchestrates a reshuffling of PUFAs from TAGs to phospholipids and re-sensitizes arrested cells to ferroptosis. We show that some slow-cycling antimitotic drug–resistant cancer cells, such as 5-fluorouracil–resistant cells, have accumulation of lipid droplets and that combined treatment with ferroptosis inducers and DGAT inhibitors effectively suppresses the growth of 5-fluorouracil–resistant tumors by inducing ferroptosis. Together, these results reveal a role for cell cycle arrest in driving ferroptosis resistance and suggest a ferroptosis-inducing therapeutic strategy to target slow-cycling therapy-resistant cancers.

5 June 2014 in Blood
Verified
Journal Article
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WCWai Kin Chan
Wai Kin Chan
PLPhilip L Lorenzi
Philip L Lorenzi
AAAndriy Anishkin
Andriy Anishkin
PPPreeti Purwaha
Preeti Purwaha
DRDavid M. Rogers
David M. Rogers
JWJohn N. Weinstein
John N. Weinstein
Key Points: We used molecular dynamics, saturation mutagenesis, and enzymologic screening to develop a glutaminase-free mutant (Q59L) l-ASP. We then used Q59L to show that glutaminase activity is not required for l-ASP activity against ASNS-negative cancer cells.