Microbiota prognostic signature in colon cancer.

L Lucía Trilla-Fuertes F Fernando Becerril-Gómez V Victoria Heredia (Translational Oncology and Pathology Group, La Paz University Hospital-IdiPAZ, Madrid, Spain) A Angelo Gámez-Pozo A Ana Custodio (Medical Oncology Department, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain) N Nuria Rodriguez Salas (Department of Medical Oncology, Hospital Universitario La Paz, Madrid, Spain) P Pedro Lalanda Delgado (Molecular Oncology Lab, University Hospital La Paz - IdiPAZ, Madrid, Spain) M Marta Mendiola R Rocío López Vacas (Molecular Oncology Lab, INGEMM, University Hospital La Paz - IdiPAZ, Madrid, Spain) I Ismael Ghanem Canete (Department of Medical Oncology, Hospital Universitario La Paz, Madrid, Spain) M Mariana Díaz-Almirón C Carlo Bressa (Francisco de Vitoria University, Madrid, Spain) J Jonas Grossmann (Proteomics Unit, Functional Genomics Center of Zurich, Zurich, Switzerland) A Antje Dittmann J Juan Angel Fresno-Vara (Molecular Oncology Lab, University Hospital La Paz-IdiPAZ, Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain) J Jaime Feliu

Abstract

e15637 Background: Stage II and III colon cancer (CC) poses a significant challenge due to rising global incidence and mortality rates. Despite advancements in screening and treatment, there is a pressing need for reliable prognostic biomarkers. The objective of this study is to determine the prognostic value of the tumor microbiota in CC patients diagnosed with stage II and III treated with adjuvant chemotherapy. Methods: One hundred and fifty-eight stage II-III CC patients from Hospital Universitario La Paz with FFPE samples and clinical data were included in this study. Proteins were extracted from tumor-rich sections, digested, and analyzed by DIA-MS on an Orbitrap Fusion mass spectrometer. Microbiota proteins related to disease-free survival were defined using Kaplan-Meier and Cox regression. Then, a prognostic signature was built with the selected microbiota proteins and a Cox proportional hazard model. These analyses were done using BRB Array Tools (NIH). Multivariate analysis was performed using SPSS IBM v20. Results: One hundred and fifty-eight CRC patients, with a median age of 67 years, 65 (41%) female, 49 (31%) stage II, 109 (63%) stage III, 59 (37%) right colon, 99 (63%) left colon, 127 (80%) treated with CAPOX, and 31 (20%) treated with FOLFOX, were included. After proteomics analysis, two samples were excluded due to a low amount of protein. Proteomics quantified 341 bacterial proteins, 51 after applying quality criteria. Of those fifty-one bacterial proteins, eleven were related to disease free-survival (p<0.05). A prognostic signature composed by three of these microbiota proteins, from Acinetobacter , Prevotellamassilia , and Staphylococcus , was built. This prognostic signature divides CRC patients into low and high-risk groups (p=0.0019, HR=2.53, 95%CI=1.40-4.36). The DFS at 5 years in the low-risk group is 81.74% whereas in the high-risk group is 59.36%. In a multivariate analysis, including TNM stage, CMS, obstruction, perforation, venous, lymphatic and neural invasion, and differentiation grade; TNM stage, perforation, and the microbiota signature showed prognostic value. Therefore, the microbiota signature provides additional prognostic information to clinical data. Conclusions: Abundance of these three microbiota populations seems to be related to disease-free survival and it should be validated in an independent cohort.

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (16)

L

Lucía Trilla-Fuertes

F

Fernando Becerril-Gómez

V

Victoria Heredia

Translational Oncology and Pathology Group, La Paz University Hospital-IdiPAZ, Madrid, Spain

A

Angelo Gámez-Pozo

A

Ana Custodio

Medical Oncology Department, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain

N

Nuria Rodriguez Salas

Department of Medical Oncology, Hospital Universitario La Paz, Madrid, Spain

P

Pedro Lalanda Delgado

Molecular Oncology Lab, University Hospital La Paz - IdiPAZ, Madrid, Spain

M

Marta Mendiola

R

Rocío López Vacas

Molecular Oncology Lab, INGEMM, University Hospital La Paz - IdiPAZ, Madrid, Spain

I

Ismael Ghanem Canete

Department of Medical Oncology, Hospital Universitario La Paz, Madrid, Spain

M

Mariana Díaz-Almirón

C

Carlo Bressa

Francisco de Vitoria University, Madrid, Spain

J

Jonas Grossmann

Proteomics Unit, Functional Genomics Center of Zurich, Zurich, Switzerland

A

Antje Dittmann

J

Juan Angel Fresno-Vara

Molecular Oncology Lab, University Hospital La Paz-IdiPAZ, Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain

J

Jaime Feliu