The Na⁺/K⁺ATPase Regulates Glycolysis and Modifies Immune Metabolism in Tumors

Abstract

Cancer therapies targeting metabolism have been limited due to toxicity, compound availability, and efficacy. Therefore, strategies for targeting tumor-specific vulnerabilities remain highly desired. Digoxin, a widely used cardiac glycoside in humans, has been shown to exhibit antineoplastic properties. Using metabolomic approaches, we show that a primary consequence of digoxin treatment in tumor cells is disruption of central carbon metabolism via inhibition of the Na + /K + ATPase, an enzyme that consumes a large portion of cellular ATP leading to globally altered energy demands when its activity is disrupted. Furthermore, in an immunocompetent mouse model of sarcoma, we show that digoxin targets these metabolic processes in both malignant and healthy tissue, particularly within cardiac tissue, while exhibiting tumor-specific cytotoxic activity. Single-cell RNA sequencing of 31,611 cells within the mouse sarcoma model demonstrates that acute digoxin treatment induces a shift in the tumor microenvironment, leading to transcriptional reprogramming of energy-generating processes in both tumor and immune cells. These results suggest that digoxin suppresses tumor growth by targeting central carbon in both tumor cells and the immune compartment, rendering it promising as an antitumor agent for metabolic therapeutic and immunomodulatory applications.

Tumor-induced reshuffling of lipid composition on the endoplasmic reticulum membrane sustains macrophage survival and pro-tumorigenic activity

“…1j-l ). By computationally weighting ER stress responses of individual TAMs from the published single cell RNA sequencing results of several human cancers, including colorectal cancer (CRC) 25 , lung adenocarcinoma without chronic obstructive pulmonary disease (LUAD-No COPD) and Non-small cell lung carcinoma (NSCLC) 26 , 27 , and a cohort of murine sarcoma 28 , we observed that pro-tumorigenic TAMs displayed higher ER stress scores compared to anti-tumorigenic TAMs ( Fig. 2e ).…”

“…The processed single-cell gene expression datasets for different tumors including human colorectal cancer 25 , lung tumors 26 , 27 , and mouse sarcoma 28 were collected from Gene Expression Omnibus ( https://www.ncbi.nlm.nih.gov/geo/ ) and single cell portal ( https://singlecell.broadinstitute.org/ ) using their public accessions. The lung tumor subtypes were defined according to sample origins (tumor subtype and disease type) 26 .…”

Review of single-cell RNA-seq data clustering for cell-type identification and characterization

“…In this section, we performed comparison experiments to evaluate the performances of those single-cell RNA-seq clustering methods on five publicly available data sets. Those data sets are from Mouse embryo stem (GSE65525; 2717 cells) ( Klein et al 2015 ), Mouse brain (GSE74672; 2881 cells) ( Romanov et al 2016 ), Human blood (SCP345; 13316 cells) ( Tran et al 2021 ), Mouse tissues (SCP916; 12648 cells) ( Sanderson et al 2020 ), and Human T Cell (GSE162086; 104417 cells) ( Bacher et al 2020 ). Supplemental Table S2 summarizes the statistics of the above five single-cell RNA-seq data sets with varying degrees of number of genes, number of cells (varying from 2k to 100k), and number of cell types.…”