Related Experiment Video
Updated: Jan 13, 2026

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
Published on: February 7, 2021
Baseline multi-omics signatures could predict therapeutic response to neoadjuvant anti-PD-1 immunochemotherapy in
Ailing Cao1, Yaobin Lin2,3, Shaoxing Guan1
1Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China.
Background:
Neoadjuvant anti-programmed cell death 1 (PD-1) immunochemotherapy has shown promising efficiency in the treatment of early-stage non-small-cell lung cancer (NSCLC), but it has not consistently yielded durable responses. Biomarkers for the prediction of efficacy are warranted.
Methods:
We performed shotgun metagenomic and plasma/faecal metabolomic studies in 44 NSCLC patients who underwent neoadjuvant tislelizumab plus platinum-based doublet chemotherapy. Samples were collected at baseline and before surgical resection, and the major pathologic response (MPR) was evaluated.
Results:
MPR patients showed a significantly higher gut-microbial alpha diversity, an enrichment of Ruminococcaceae, Lachnospiraceae and Clostridiales species, and an increased plasma level of tryptophan metabolites at baseline. On the contrary, non-MPR patients were characterized by enrichment of Prevotella species in faecal samples and higher plasma levels of linoleic acid metabolites. A high predictive accuracy was achieved using a small panel of differential microbial (Clostridium sp. M62/1 and Eisenbergiella tayi) or metabolomic features (linoleic acid, oxindole-3-acetic acid and quinolinic acid) with AUCs > .85.
Conclusions:
The baseline characteristics of the gut microbiota and plasma metabolites could provide early predictions of the response to neoadjuvant anti-PD-1 immunochemotherapy.
Trial Registration:
NCT05244837.
Key Points:
Baseline metagenomic and metabolomic signatures were significantly associated with the major pathologic response of neoadjuvant anti-PD-1 immunochemotherapy. Integrated microbial model (consists of Clostridium sp. M62/1 and Eisenbergiella tayi) and metabolomic model (consists of linoleic acid, oxindole-3-acetic acid and quinolinic acid) could provide early predictions of the response.
More Related Videos
07:59Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
10:29Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence
Published on: August 14, 2019