In a groundbreaking presentation at the 38th Annual Congress of the European Association of Nuclear Medicine (EANM’25), researchers unveiled compelling evidence linking the metabolic activity of visceral fat to the aggressiveness of endometrial cancer. This emerging insight shifts the paradigm beyond the traditional understanding that obesity alone exacerbates cancer risk, spotlighting instead the biological activity within visceral fat as a key driver influencing tumor progression and metastasis.
Obesity has long been recognized as a critical risk factor for endometrial cancer, with epidemiological studies repeatedly demonstrating a correlation between excess body fat and cancer incidence. However, the heterogeneous nature of adipose tissue calls for a deeper exploration into how different fat compartments impact cancer biology. Visceral adipose tissue, which envelops vital internal organs, exerts complex influences on systemic metabolism and inflammatory processes, far surpassing the effects attributed to subcutaneous fat. The nuances of this adipose depot’s metabolic behavior may hold the key to understanding cancer aggressiveness at a molecular level.
The investigative team based at Haukeland University Hospital and the University of Bergen employed positron emission tomography/computed tomography (PET/CT) imaging to quantitatively assess glucose metabolism within the visceral fat of 274 women diagnosed with endometrial cancer. PET/CT serves as a powerful, non-invasive tool for visualizing metabolic activity in vivo by measuring the uptake of radiolabeled glucose analogues, thus providing a functional map of biological processes within tissues. Their analysis revealed that elevated glucose uptake in visceral adipose tissue correlates strongly with more advanced cancer stages and increased incidence of lymph node involvement.
This pioneering research emphasizes that the volume of visceral fat is not the sole determinant of cancer severity; rather, the metabolic intensity within this fat depot plays a crucial, independent role. Lead author Jostein Sæterstøl, a medical physicist and PhD candidate, highlighted the absence of a strong correlation between fat quantity and metabolic activity. This underscores the importance of evaluating the biological characteristics of adipose tissue, particularly its metabolic output and inflammatory status, to better stratify patient risk and tailor clinical interventions.
Mechanistically, the heightened metabolic activity of visceral fat may exacerbate cancer aggressiveness through several interrelated pathways. Chronic inflammation within adipose tissue results in the secretion of proinflammatory cytokines and free fatty acids, both of which can facilitate tumor proliferation and aid in immune system evasion. Additionally, this inflammatory milieu often induces insulin resistance, creating a systemic environment conducive to cancer progression. Adipokines—a diverse group of signaling molecules released by fat cells—further modulate tumor biology through complex crosstalk between adipose tissue and malignant cells, possibly enhancing metastasis, particularly to regional lymph nodes.
Despite the promising potential of PET/CT-based metabolic assessment of visceral fat, routine clinical adoption remains constrained by technical and biological challenges. The inherently low uptake signal of glucose analogues in adipose tissue poses difficulties in imaging precision, compounded by variability between patients and imaging protocols. Advances such as standardized imaging methodologies, sophisticated quantitative PET analysis, and the integration of artificial intelligence for image segmentation and interpretation offer a vision of future diagnostic refinement. These innovations could enable clinicians to identify high-risk patients earlier, optimize personalized treatment strategies, and monitor disease dynamics with unprecedented accuracy.
Looking forward, the research team plans to expand their investigative framework to enhance the robustness of visceral fat metabolic measurements. They aim to integrate AI-driven segmentation techniques to improve the resolution and reproducibility of PET/CT assessments. Furthermore, probing the relationship between visceral fat metabolism and circulating biomarkers—including cytokines and hormones—may illuminate systemic mechanisms linking metabolic dysfunction to tumor biology. Delving into tumor genomic profiles alongside adipose tissue metabolic states could unravel intricate biological interactions dictating cancer progression.
Another promising avenue involves longitudinal analysis of visceral fat activity to evaluate temporal changes during disease evolution and therapeutic response. Tracking these dynamics might reveal valuable biomarkers for early detection of treatment efficacy or relapse, enhancing clinical decision-making. Such comprehensive studies could ultimately reshape our understanding of how metabolic disorders intersect with oncogenesis, driving forward the development of targeted interventions addressing both metabolic health and cancer control.
This research marks a significant advance in the field of nuclear medicine and oncology, underscoring the importance of metabolic imaging as not merely a tool for tumor visualization but as a window into the tumor microenvironment and systemic factors influencing cancer behavior. The implications extend beyond endometrial cancer, offering a conceptual framework applicable to other obesity-related malignancies where metabolic health profoundly impacts disease outcomes.
The confluence of metabolic science, advanced imaging, and cancer biology exemplifies precision medicine’s future—one where nuanced biological activities within seemingly inert tissues determine prognosis and guide therapy. As nuclear medicine pioneers continue to innovate, harnessing the full power of PET/CT coupled with computational analytics promises to revolutionize cancer diagnostics, prognostication, and treatment personalization, ultimately improving patient survival and quality of life.
In sum, this paradigm-shifting study compels the medical community to look beyond traditional measures of obesity and consider the intricate metabolic activity within fat depots as an independent factor influencing the aggressiveness of endometrial cancer. It opens new frontiers for research, clinical practice, and interdisciplinary collaboration aimed at unraveling and targeting the metabolic underpinnings of cancer progression.
Subject of Research: Metabolic activity of visceral fat and its association with endometrial cancer aggressiveness.
Article Title: High Metabolic Activity of Visceral Fat Linked to Aggressive Endometrial Cancer: A Novel Insight from PET/CT Imaging.
News Publication Date: 5 October 2025.
References:
- Sæterstøl J, Lavik J, Lunde LP et al. Is Visceral Adipose Tissue Metabolism Linked to Aggressiveness in Endometrial Cancer? Presented at EANM’25 on Sunday 5 October 2025.
- Fasmer, K.E., Sæterstøl, J., Ljunggren, M.B.S. et al. Abdominal fat distribution in endometrial cancer: from diagnosis to follow-up. BMC Cancer 25, 879 (2025).
- van den Bosch A. A. S., Pijnenborg J. M. A., Romano A., Winkens B., van der Putten L. J. M., Kruitwagen R. F. P. M., & Werner H. M. J. (2023). The impact of adipose tissue distribution on endometrial cancer: a systematic review. Frontiers in Oncology, 13, Article 1182479.
- Fontana L, Eagon JC, Trujillo ME, Scherer PE, Klein S. Visceral fat adipokine secretion is associated with systemic inflammation in obese humans. Diabetes. 2007;56(4):1010-1013.
- Westerterp M, Hooiveld GJ, van der Kallen CJH, et al. Associations of abdominal subcutaneous and visceral fat with insulin resistance and secretion differ between men and women: The Netherlands Epidemiology of Obesity Study. Metab Syndr Relat Disord.
- Britton KA, Massaro JM, Murabito JM, Kreger BE, Hoffmann U, Fox CS. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. Circulation. 2013;128(22):2317-2324.
Keywords: Metabolic disorders, Diabetes, Obesity, Childhood obesity, Cancer, Cancer immunology, Metastasis, Health care
