Evidence map›Paper›PMID 41915288›Full record

ReviewMolecular biology reports2026

Spatial omics insights into tumor myeloid cells: roles in tumorigenesis, prognosis, and therapy.

Bugi Ratno Budiarto, Pimpin Utama Pohan

Abstract readReview
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In one paragraph

Review in Molecular biology reports, 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

2 authors.

Bugi Ratno BudiartoCenter for Biomedical Research, National Research and Innovation Agency (BRIN), Kawasan Sains dan Teknologi (KST) Soekarno, Gedung Meatpro, Jalan Raya Jakarta-Bogor KM 46, Cibinong, Jawa Barat, Indonesia. bugi002@brin.go.id.
Pimpin Utama PohanFaculty of Medicine, University of North Sumatra, Jalan Dr. T. Mansyur No.5, Padang Bulan, Medan Baru, Kota Medan, Sumatera Utara, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor-associated myeloid cells form a highly plastic and spatially organized immune compartment that plays a central role in tumor evolution, clinical outcome, and therapeutic response. Single-cell RNA sequencing has revealed extensive heterogeneity among macrophages, monocytes, neutrophils, dendritic cells, and related lineages, uncovering transcriptional programs linked to tumor promotion or immune activation. However, the dissociative nature of single-cell approaches disrupts tissue architecture, limiting insight into how myeloid cells interact with malignant, stromal, and lymphoid populations within intact tumors. Recent advances in spatial omics technologies address this limitation by preserving tissue context while enabling high-dimensional profiling of RNA and protein expression in situ. In this review, we synthesize emerging spatial proteomic and transcriptomic studies of tumor-associated myeloid cells, identify recurrent spatial architectures that govern tumorigenesis, prognosis, and treatment response, and examine analytical frameworks that translate spatial patterns into mechanistic understanding. By moving beyond descriptive spatial maps, we highlight unifying biological principles and translational opportunities that position myeloid spatial organization as a critical determinant of cancer progression and precision oncology.

Indexed as

CarcinogenesisMyeloid CellsNeoplasmsAnimalsGene Expression Regulation, NeoplasticHumansMultiomicsPrognosisProteomicsSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsTumor MicroenvironmentClinical implicationSpatial-omicsTumor-associated myeloid cellsTumorigenesis

Identifiers

PMID41915288

What OpenQuestion holds

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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.