Evidence map›Paper›PMID 39122893›Full record

Trial reportOncogene2024

Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma.

Chao Wu, Guoqing Zhang, Lin Wang, Jinlong Hu, Zhongjian Ju, Haitao Tao, Qing Li, Jian Li, Wei Zhang, Jianpeng Sheng and 2 more

Abstract readClinical Trial, Phase II
PubMed Publisher
In one paragraph

Trial report in Oncogene, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

  1. Trial
  2. Identification of a distinct cluster of LY6EBritish journal of cancer · 2026
    Article
  3. Odon: an ultra-fast viewer for spatial proteomics.Bioinformatics (Oxford, England) · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Chao Wu *Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China.
Guoqing Zhang *Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China.
Lin Wang *College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Jinlong Hu *Department of Oncology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Zhongjian JuDepartment of Radiation Oncology, Chinese PLA General Hospital, The First Medical Center, Beijing, China.
Haitao TaoDepartment of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China.
Qing LiThe Shapingba Affiliated Hospital, Chongqing University, Chongqing, China.
Jian LiChengdu Medical College, Chengdu, China.
Wei ZhangDepartment of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China. zhangwei850603@163.com.
Jianpeng ShengCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China. shengjp@zju.edu.cn.ORCID 0000-0002-5535-5541
Xiaobin HouDepartment of Thoracic Surgery, Chinese PLA General Hospital, The First Medical Center, Beijing, China. drhouxb@163.com.
Yi HuDepartment of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China. huyi301zlxb@sina.com.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82173078National Natural Science Foundation of China (National Science Foundation of China) 82271404
6 · The paper itself

Abstract

Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaNeoadjuvant TherapyProteomicsTumor MicroenvironmentAdultAgedAlbuminsAntineoplastic Combined Chemotherapy ProtocolsDrug CombinationsFemaleHumansImmunotherapyMaleMiddle AgedOxonic Acid130-nm albumin-bound paclitaxelAlbuminsDrug CombinationsOxonic AcidPaclitaxelS 1 (combination)Tegafur

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.