Relationships between LDH-A, lactate, and metastases in 4T1 breast tumors

Asif Rizwan1, Inna Serganova, Raya Khanin

  • 1Authors' Affiliations: Departments of Medical Physics, Neurology, Radiology, and Medicine, Bioinformatics Core, Molecular Pharmacology and Chemistry Program, Memorial Sloan-Kettering Cancer Center; and Department of Physiology and Biophysics, Weill Cornell Graduate School of Medical Sciences, New York, New York.

Abstract

Insights

Inhibiting lactate dehydrogenase A (LDH-A) in breast cancer cells reduced metastasis and altered tumor cell metabolism. Lactate magnetic resonance spectroscopic imaging (MRSI) can monitor this targeted therapy and identify high-risk patients.

Area of Science:

  • Oncology
  • Molecular Biology
  • Biochemistry

Background:

  • Lactate dehydrogenase A (LDH-A) plays a role in cancer cell metabolism.
  • Understanding LDH-A's role in metastasis is crucial for developing targeted therapies.

Purpose of the Study:

  • To investigate the link between LDH-A expression, lactate levels, cell metabolism, and metastasis in 4T1 breast tumors.
  • To assess the potential of lactate magnetic resonance spectroscopic imaging (MRSI) in monitoring LDH-A inhibition.

Main Methods:

  • LDH-A expression was inhibited in 4T1 cells using short hairpin RNA (shRNA).
  • Lactate concentration was measured using MRSI.
  • In vitro and in vivo studies assessed cell migration, invasion, proliferation, and tumor growth.

Main Results:

  • LDH-A knockdown significantly reduced LDH activity, acid production, migration, invasion, proliferation, and glucose consumption.
  • Knockdown cells showed increased oxygen consumption, ROS, and ATP levels.
  • In vivo, LDH-A knockdown tumors had lower lactate levels, delayed metastasis, and decreased primary tumor growth.

Conclusions:

  • LDH-A inhibition suppresses metastasis and alters tumor cell metabolism.
  • Lactate MRSI serves as a noninvasive imaging strategy to monitor LDH-A targeted therapy in preclinical models.
  • This imaging approach can be translated to clinical settings for patient monitoring.

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