Evidence map›Paper›PMID 36281356›Full record

ArticleCommunications medicine2022

Multiplexed imaging mass cytometry reveals distinct tumor-immune microenvironments linked to immunotherapy responses in melanoma.

Xu Xiao, Qian Guo, Chuanliang Cui, Yating Lin, Lei Zhang, Xin Ding, Qiyuan Li, Minshu Wang, Wenxian Yang, Yan Kong and 1 more

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.0field-weighted citation impact, top 7% of its field
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

30 citing papers in PubMed, 31 citations in OpenAlex.

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  3. Role of pyroptosis in melanoma: Molecular mechanisms and therapeutic potentials.Apoptosis : an international journal on programmed cell death · 2026
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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

11 authors at 3 institutions in 1 country.

Xu Xiao *School of Informatics, Xiamen University, Xiamen, China.ORCID 0000-0003-3743-3582
Qian Guo *Peking University Cancer Hospital and Institute, Beijing, China.ORCID 0000-0002-1211-6436
Chuanliang CuiPeking University Cancer Hospital and Institute, Beijing, China.
Yating LinSchool of Informatics, Xiamen University, Xiamen, China.ORCID 0000-0001-5061-5132
Lei ZhangSchool of Life Science, Xiamen University, Xiamen, China.
Xin DingZhongshan Hospital, Xiamen University, Xiamen, China.
Qiyuan LiNational Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China.
Minshu WangNational Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China.
Wenxian YangAginome Scientific, Xiamen, China.ORCID 0000-0002-5349-9680
Yan KongPeking University Cancer Hospital and Institute, Beijing, China.ORCID 0000-0002-2266-7872
Rongshan YuSchool of Informatics, Xiamen University, Xiamen, China.ORCID 0000-0003-2179-173X
Xiamen University · CNPeking University · CNZhongshan Hospital of Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Single-cell technologies have enabled extensive analysis of complex immune composition, phenotype and interactions within tumor, which is crucial in understanding the mechanisms behind cancer progression and treatment resistance. Unfortunately, knowledge on cell phenotypes and their spatial interactions has only had limited impact on the pathological stratification of patients in the clinic so far. We explore the relationship between different tumor environments (TMEs) and response to immunotherapy by deciphering the composition and spatial relationships of different cell types. Methods: Here we used imaging mass cytometry to simultaneously quantify 35 proteins in a spatially resolved manner on tumor tissues from 26 melanoma patients receiving anti-programmed cell death-1 (anti-PD-1) therapy. Using unsupervised clustering, we profiled 662,266 single cells to identify lymphocytes, myeloid derived monocytes, stromal and tumor cells, and characterized TME of different melanomas. Results: Combined single-cell and spatial analysis reveals highly dynamic TMEs that are characterized with variable tumor and immune cell phenotypes and their spatial organizations in melanomas, and many of these multicellular features are associated with response to anti-PD-1 therapy. We further identify six distinct TME archetypes based on their multicellular compositions, and find that patients with different TME archetypes responded differently to anti-PD-1 therapy. Finally, we find that classifying patients based on the gene expression signature derived from TME archetypes predicts anti-PD-1 therapy response across multiple validation cohorts. Conclusions: Our results demonstrate the utility of multiplex proteomic imaging technologies in studying complex molecular events in a spatially resolved manner for the development of new strategies for patient stratification and treatment outcome prediction.

Indexed as

Cancer microenvironmentImmunotherapy

Identifiers

PMID36281356
PMCPMC9587266
OpenAlexW4306986118

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.