PET-CT-based host metabolic (PETMet) features are associated with pathologic response in gastroesophageal adenocarcinoma Journal Article


Authors: White, C.; Jayaprakasam, V. S.; Tenet, M.; Tang, L. H.; Schattner, M. A.; Janjigian, Y. Y.; Maron, S. B.; Schöder, H.; Larson, S. M.; Gönen, M.; Datta, J.; Coit, D. G.; Mauguen, A.; Strong, V. E.; Vitiello, G. A.
Article Title: PET-CT-based host metabolic (PETMet) features are associated with pathologic response in gastroesophageal adenocarcinoma
Abstract: Background: 18F-FDG PET-CT-based host metabolic (PETMet) profiling of non-tumor tissue is a novel approach to incorporate the patient-specific response to cancer into clinical algorithms. Materials and methods: A prospectively maintained institutional database of gastroesophageal cancer patients was queried for pretreatment PET-CTs, demographics, and clinicopathologic variables. 18F-FDG PET avidity was measured in 9 non-tumor tissue types (liver, spleen, 4 muscles, 3 fat locations). Logistic and Cox regression were used to model pathologic response (PR) and overall survival (OS) respectively. Classification and regression tree (CART) and random forest modeling were employed to create decision trees and identify PETMet features associated with outcome. Results: Two-hundred and one patients with distal gastroesophageal (48 %) or gastric (52 %) adenocarcinoma were included. PET-CT-derived scores were independently associated with PR after adjusting for clinical variables. CART and Random Forest methods identified critical split points of non-tumor tissue 18F-FDG avidity that can classify patients and predict PR. PET-CT risk groups created from decision trees predicted PR significantly better than the clinical model (p < 0.001). Specifically, an elevated erector spinae-to-gluteal fat 18F-FDG avidity ratio (≥2.7) combined with low 18F-FDG avidity in the spleen (<2.9) and rectus femoris (<0.52) predict PR. No advantage of PET-CT risk groups was seen for predicting OS (p = 0.155). Conclusions: Pretreatment host PETMet features may be useful for predicting PR after neoadjuvant therapy in gastroesophageal cancer. Unsupervised decision trees indicate that low 18F-FDG avidity in visceral fat, subcutaneous fat, and muscle result in the most favorable PR, suggesting that systemic hypermetabolism adversely impacts prognosis. © 2025 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology
Keywords: adult; aged; major clinical study; overall survival; fluorouracil; systemic therapy; paclitaxel; cancer staging; prospective study; carboplatin; spleen; prediction; docetaxel; folinic acid; fluorodeoxyglucose f 18; patient coding; trastuzumab; oxaliplatin; esophageal adenocarcinoma; stomach adenocarcinoma; gastric cancer; pathological complete response; demographics; gastroesophageal junction; pet-ct; decision tree; pathologic response; cancer prognosis; human; male; female; article; random forest; positron emission tomography-computed tomography; metabolic fingerprinting; patient metabolic profiling; rectus femoris muscle; petmet; erector spinae muscle; gluteal fat
Journal Title: European Journal of Surgical Oncology
Volume: 51
Issue: 5
ISSN: 0748-7983
Publisher: Elsevier Inc.  
Date Published: 2025-05-01
Start Page: 109589
Language: English
DOI: 10.1016/j.ejso.2025.109589
PROVIDER: scopus
PUBMED: 39808889
PMCID: PMC12068993
DOI/URL:
Notes: The MSK Cancer Center Support Grant (P30 CA008748) is acknowledge in the PDF -- Corresponding authors is MSK author: Gerardo A. Vitiello -- Source: Scopus
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MSK Authors
  1. Mithat Gonen
    1029 Gonen
  2. Heiko Schoder
    544 Schoder
  3. Yelena Yuriy Janjigian
    395 Janjigian
  4. Laura Hong Tang
    447 Tang
  5. Vivian Strong
    265 Strong
  6. Daniel Coit
    542 Coit
  7. Steven M Larson
    959 Larson
  8. Mark Schattner
    169 Schattner
  9. Audrey   Mauguen
    156 Mauguen
  10. Steven Maron
    103 Maron
  11. Charlie White
    41 White