Evidence map›Paper›PMID 42351923›Full record

ArticleBioengineering (Basel, Switzerland)2026

A Micro-Quantitative and FFPE-Compatible Workflow for Immunohistochemistry-Guided Spatial Proteomic Analysis of Cellular Subpopulations Within the Tumor Microenvironment.

Junya Peng, Lu Ping, Ruikang Dun, Lulu Liu, Yihong Shi, Ruizhe He, Qing Zhong, Yang Chen, Wenmin Tian, Yupei Zhao

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Junya PengState Key Laboratory of Complex and Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102602, China.
Lu PingState Key Laboratory of Complex and Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102602, China.
Ruikang DunDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China.
Lulu LiuInstitute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China.
Yihong ShiDepartment of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China.
Ruizhe HeState Key Laboratory of Complex and Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102602, China.
Qing ZhongInstitute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China.
Yang ChenCenter for Precision Medicine Multi-Omics Research, Institute of Advanced Clinical Medicine, Peking University, Beijing 100080, China.
Wenmin TianCenter for Precision Medicine Multi-Omics Research, Institute of Advanced Clinical Medicine, Peking University, Beijing 100080, China.
Yupei ZhaoState Key Laboratory of Complex and Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102602, China.

Funding

Beijing High-Level Innovation and Entrepreneurship Talent Support Program Young Backbone Talent Projects G202532187National High level Hospital Clinical Research Funding 2025-PUMCH-C-042National Key Research and Development Program of China 2023YFF0613402National Science and Technology Innovation 2030, Major Project - Research on Cancer, Cardiovascular, Respiratory and Metabolic Diseases 2025ZD0552402Peking Union Medical College Hospital Outstanding Young Talent Development Program UBJ11753
6 · The paper itself

Abstract

Understanding the spatial proteomic landscape of human tumors is essential for dissecting cellular heterogeneity and microenvironmental interactions in cancer biology. Traditional bulk proteomic approaches, however, obscure spatial information and average out signals from distinct cell populations. Here, we present a detailed and reproducible micro-quantitative protocol for spatially resolved proteomic analysis of specific cellular subpopulations isolated from immunohistochemistry (IHC)-labeled formalin-fixed paraffin-embedded (FFPE) tissue sections using laser microdissection (LMD). By combining IHC staining to visually define phenotypically distinct cells within preserved tissue architecture and precise LMD capture, approximately 6000 target cells can be isolated per sample for downstream proteomic quantification. Despite the ultra-low input, optimized lysis and digestion steps ensure consistent peptide recovery and highly reproducible label-free LC-MS/MS data across replicates. Integrating immunohistochemistry staining-guided spatial sampling with ultrasensitive quantitative proteomics, this workflow enables reliable cell-type-specific profiling directly within human tumor tissues. The protocol bridges histopathology and proteomics, offering a practical framework for translational research exploring spatial protein signatures and tumor microenvironmental heterogeneity.

Indexed as

FFPE tissueimmunohistochemistrylaser microdissectiontumor microenvironment

Identifiers

PMID42351923
PMCPMC13296145

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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.