Evidence map›Paper›PMID 39498855›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

CITMIC: Comprehensive Estimation of Cell Infiltration in Tumor Microenvironment based on Individualized Intercellular Crosstalk.

Xilong Zhao, Jiashuo Wu, Jiyin Lai, Bingyue Pan, Miao Ji, Xiangmei Li, Yalan He, Junwei Han

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Xilong ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Jiashuo WuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Jiyin LaiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Bingyue PanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Miao JiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xiangmei LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yalan HeCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Junwei HanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.ORCID 0000-0002-3276-0819

Funding

National Natural Science Foundation of China 62072145National Natural Science Foundation of China 62372143
6 · The paper itself

Abstract

The tumor microenvironment (TME) cells interact with each other and play a pivotal role in tumor progression and treatment response. A comprehensive characterization of cell and intercellular crosstalk in the TME is essential for understanding tumor biology and developing effective therapies. However, current cell infiltration analysis methods only partially describe the TME's cellular landscape and overlook cell-cell crosstalk. Here, this approach, CITMIC, can infer the cell infiltration of TME by simultaneously measuring 86 different cell types, constructing an individualized cell-cell crosstalk network based on functional similarities between cells, and using only gene transcription data. This is a novel approach to estimating the relative cell infiltration levels, which are shown to be superior to the current methods. The TME cell-based features generated by analyzing melanoma data are effective in predicting prognosis and treatment response. Interestingly, these features are found to be particularly effective in assessing the prognosis of high-stage patients, and this method is applied to multiple high-stage adenocarcinomas, where more significant prognostic performance is also observed. In conclusion, CITMIC offers a more comprehensive description of TME cell composition by considering cell-cell crosstalk, providing an important reference for the discovery of predictive biomarkers and the development of new therapeutic strategies.

Indexed as

Cell CommunicationTumor MicroenvironmentBiomarkers, TumorHumansMelanomaNeoplasmsPrognosisBiomarkers, Tumorcell‐cell crosstalkcell infiltrationindividualized analysisnetwork analysistumor microenvironment

Identifiers

PMID39498855
PMCPMC11714168

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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.