Exploiting metabolic vulnerabilities after anti-VEGF antibody therapy in ovarian cancer

Glassman, Deanna; Kim, Mark S.; Spradlin, Meredith; Badal, Sunil; Taki, Mana; Bhattacharya, Pratip K.; Dutta, Prasanta; Kingsley, Charles V.; Foster, Katherine; Animasahun, Olamide; Jeon, Jin Heon; Achreja, Abhinav; Jayaraman, Anusha; Kumar, Praveen; Nenwani, Minal; Wuchu, Fulei; Bayraktar, Emine; Wu, Yangjun; Stur, Elaine; Mangala, Lingegowda S.; Lee, Sanghoon; Yap, Timothy A.; Westin, Shannon N.; Eberlin, Lívia S.; Nagrath, Deepak; Sood, Anil K.

doi:10.1016/j.isci.2023.106020

Cited by 5 publications

(1 citation statement)

References 29 publications

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“…Animal protocols were approved by the MD Anderson Institutional Animal Care and Use Committee and experiments were performed with 6-to 8-week-old female athymic nude mice (NCr-nude) obtained from Taconic Biosciences. Luciferase-labeled SKOV3ip1 ovarian cancer cells were used to establish xenograft models for all mouse experiments as described before 42 . Cells were cultured to 70-90% confluence and then trypsinized, washed twice with phosphate-buffered saline, and resuspended in ice-cold Hank's Balanced Salt Solution (cat.…”

Section: In Vivo Models Of Ovarian Cancermentioning

confidence: 99%

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

Corvigno,

Badal,

Spradlin

et al. 2023

npj Precis. Onc.

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In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients’ tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

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Section: In Vivo Models Of Ovarian Cancermentioning

confidence: 99%

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

Corvigno,

Badal,

Spradlin

et al. 2023

npj Precis. Onc.

Self Cite

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Exploring Metabolic Approaches for Epithelial Ovarian Cancer Therapy

Kumari,

Gupta,

Jamil

et al. 2024

Journal Cellular Physiology

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Epithelial ovarian cancer (EOC) has the highest mortality rate among malignant tumors of the female reproductive system and the lowest survival rate. This poor prognosis is due to the aggressive nature of EOC, its late‐stage diagnosis, and the tumor's ability to adapt to stressors through metabolic reprogramming. EOC cells sustain their rapid proliferation by altering the uptake, utilization, and regulation of carbohydrates, lipids, and amino acids. These metabolic changes support tumor growth and contribute to metastasis, chemotherapy resistance, and immune evasion. Targeting these metabolic vulnerabilities has shown promise in preclinical studies, with some therapies advancing to clinical trials. However, challenges remain due to tumor heterogeneity, adaptive resistance mechanisms, and the influence of the tumor microenvironment. This review provides a comprehensive summary of metabolic targets for EOC treatment and offers an overview of the current landscape of clinical trials focusing on ovarian cancer metabolism. Future efforts should prioritize combination therapies that integrate metabolic inhibitors with immunotherapies or chemotherapy. Advances in precision medicine and multi‐omics approaches will be crucial for identifying patient‐specific metabolic dependencies and improving outcomes. By addressing these challenges, metabolism‐based therapies can significantly transform the treatment of this devastating disease.

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