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Home NEWS Science News Health

NSUN2 Drives Glycolysis, Immune Evasion in Kidney Cancer

Bioengineer by Bioengineer
May 24, 2025
in Health
Reading Time: 4 mins read
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In the relentless fight against kidney cancer, clear cell renal cell carcinoma (ccRCC) stands as one of the most formidable adversaries. Characterized by its aggressive nature and high prevalence, ccRCC continues to challenge clinicians and researchers alike. However, a groundbreaking study published in Genes & Immunity offers fresh insights into this malignancy’s intricate biology, specifically unraveling a novel metabolic and epigenetic axis that fuels tumor progression and immune evasion. This comprehensive investigation leverages cutting-edge multi-omics technologies alongside robust machine learning methods to spotlight mitochondrial metabolism as a critical player and introduces an extraordinary molecular target in ccRCC: the RNA methyltransferase NSUN2.

The current therapeutic landscape for ccRCC underscores the urgency to identify new strategies that go beyond conventional targeted therapies and immunotherapies. Metabolic reprogramming, a hallmark of cancer, attracts considerable attention given its capacity to support unchecked tumor growth and foster resistance mechanisms. The study in focus embarked on a meticulous mining of ccRCC patient data, compiling extensive bulk and single-cell RNA sequencing profiles across multiple clinical cohorts. Their ambitious aim: to delineate mitochondrial gene signatures that could serve both as predictive prognostic markers and as entry points for therapeutic intervention.

To extract meaningful patterns from such voluminous datasets, the research team ingeniously integrated ten distinct machine learning algorithms, constructing a total of 117 predictive models. Among them emerged a superior model, denoted as the “Mitoscore,” which demonstrated remarkable stratification power in forecasting patient outcomes and potentially guiding treatment decisions. This model did not merely rely on conventional gene expression metrics but painstakingly emphasized mitochondrial metabolic genes, shedding light on how cancer cells rewire their energy machinery.

Central to the Mitoscore’s predictive prowess was the gene NSUN2, an RNA 5-methylcytosine (m5C) methyltransferase that catalyzes the methylation of cytosine residues on RNA molecules. While NSUN2’s functions have been implicated in other cancer types, its specific role in ccRCC biology remained obscure until this pivotal analysis. By homing in on NSUN2, the researchers embarked on exhaustive functional studies involving both cultured cell lines and animal models to decode its influence on tumor behavior.

Experimental manipulations revealed that NSUN2 significantly enhanced ccRCC cell proliferation, migration, and invasion—hallmark traits of malignancy. Intriguingly, this oncogenic effect was mediated via metabolic rewiring, particularly by sustaining enhanced glycolytic flux within mitochondria. The glycolytic shift was not isolated; it extended its influence into the nuclear realm by modulating histone lactylation levels, thereby integrating metabolic status with epigenetic regulation. This interplay effectively reprogrammed chromatin landscapes to favor tumor progression.

Digging deeper into the molecular underpinnings, the team uncovered that NSUN2 preserved the stability of NEO1 mRNA through m5C modifications. NEO1, a neuroepithelial cell transforming gene, emerged as a critical mediator linking NSUN2’s enzymatic activity to downstream metabolic and epigenetic outcomes. This regulatory axis exemplifies how post-transcriptional RNA modifications can orchestrate complex oncogenic circuits, tying together metabolism, gene expression, and epigenetic adaptations.

Perhaps most compelling was the discovery that NSUN2 orchestrates immune escape mechanisms by upregulating PD-L1 expression on tumor cells. This process was mediated by a sophisticated signaling cascade involving MYC, POM121, and CD274, where histone lactylation played a pivotal role. By linking metabolic reprogramming to immune checkpoint regulation, NSUN2 effectively enables ccRCC cells to evade immune surveillance, dampening T cell-mediated antitumor responses.

This immunomodulatory facet was further validated experimentally: knocking down NSUN2 not only impaired tumor cell proliferation but also enhanced cytotoxic CD8+ T cell killing in vitro. Moreover, animal studies demonstrated increased infiltration of TNF-α-positive T cells within the tumor microenvironment following NSUN2 silencing, underscoring its potential as a target to restore antitumor immunity in vivo.

These groundbreaking findings collectively unveil mitochondrial genes, and NSUN2 in particular, as dual-purpose targets that hold promise for both prognostic assessment and therapeutic intervention. The study’s integration of multi-layered omic data with machine learning to construct the Mitoscore offers a formidable blueprint for future precision oncology approaches. By elucidating NSUN2’s role in maintaining mitochondrial glycolysis and regulating histone lactylation in an m5C-dependent manner, it reveals an unprecedented mechanism of metabolic-epigenetic crosstalk driving immune escape.

The implications extend beyond ccRCC, suggesting that RNA methylation enzymes like NSUN2 could represent a broader paradigm in cancer biology where metabolism, epigenetics, and immune evasion converge. Targeting such nodal points may permit synergistic therapies that disrupt tumor energy metabolism while reinvigorating antitumor immunity, potentially overcoming the limitations of current treatments.

Moving forward, clinical validation of the Mitoscore in larger patient cohorts and across diverse populations is crucial to establish its utility as a prognostic tool. Additionally, the development of specific inhibitors targeting NSUN2’s methyltransferase activity could pave the way for novel ccRCC therapeutics aimed at intercepting tumor metabolism and immune suppression simultaneously.

Beyond NSUN2, the study’s methodological framework sets a precedent for future research endeavors employing integrative multi-omics and artificial intelligence to unravel cancer’s complexity. As technological sophistication in sequencing and computational analysis continues to advance, the capacity to decode the intricate interplay between tumor biology facets will only grow stronger, heralding a new era in personalized oncology.

In summary, this landmark research demystifies the intricate mechanisms by which mitochondrial metabolic alterations and epigenetic modifications sustain ccRCC aggressiveness and immune evasion. NSUN2 emerges as a multifaceted oncogenic driver, linking glycolysis to histone lactylation and checkpoint regulation, thereby offering new vistas for intervention. These insights not only deepen our understanding of ccRCC pathophysiology but also invigorate efforts against this challenging malignancy with innovative molecular strategies.

The convergence of metabolism and immunity, bridged by epigenetic modulation as illuminated by NSUN2 function, exemplifies the complexity of tumor ecosystems. It underscores an essential principle: effective cancer therapies must address the multifactorial nature of tumor survival tactics, combining metabolic, epigenetic, and immune-targeted strategies. This work propels the field forward, inspiring hope that defeating ccRCC may soon become an attainable goal through precision molecular medicine.

Subject of Research:
Investigation of mitochondrial metabolic genes and RNA methyltransferase NSUN2’s role in clear cell renal cell carcinoma (ccRCC), focusing on metabolic reprogramming, epigenetic histone modifications, and immune evasion mechanisms.

Article Title:
Integrative multi-omics reveal NSUN2 facilitates glycolysis and histone lactylation-driven immune evasion in renal carcinoma

Article References:
Wang, K., Kong, F., Han, X. et al. Integrative multi-omics reveal NSUN2 facilitates glycolysis and histone lactylation-driven immune evasion in renal carcinoma. Genes Immun (2025). https://doi.org/10.1038/s41435-025-00336-4

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41435-025-00336-4

Tags: clear cell renal cell carcinomaglycolysis and immune evasionimmune resistance in renal cancermachine learning in cancer researchmetabolic reprogramming in cancermitochondrial metabolism in ccRCCmulti-omics technologies in oncologynovel treatment strategies for ccRCCNSUN2 in kidney cancerprognostic markers in kidney cancerRNA methyltransferase as therapeutic targettumor progression mechanisms

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