Evidence map›Paper›PMID 42059481›Full record

ArticleBriefings in bioinformatics2026

Reconstructing 3D transcriptional organization from spatial transcriptomics reveals consistent oncogenic translocations and developmental dynamics.

Yifei Sheng, Shiying Li, Zhengyang Xue, Miaozhe Huo, Yiqi Jiang, Shuai Cheng Li

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 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
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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

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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

6 authors.

Yifei ShengDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.
Shiying LiDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.
Zhengyang XueDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.
Miaozhe HuoDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.
Yiqi JiangDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.
Shuai Cheng LiDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.

Funding

National Key R&D Program of China 2023YFC3403200National Natural Science Foundation of China 32270687
6 · The paper itself

Abstract

Reconstructing the 3D spatial organization of transcription from 2D spatial data is a fundamental challenge in genomics. Here, we introduce Cytocraft, a computational framework that addresses this problem by inferring a shared, cell-type-specific 3D configuration of transcription centers from subcellular spatial transcriptomics profiles. After validating Cytocraft's robust accuracy in simulations (median relative error: 0.0346), we applied it to diverse datasets to explore spatial patterns that may reflect underlying transcriptional organization. In human nonsmall cell lung cancer, we observed consistent spatial repositioning patterns, suggesting that the marker MALAT1 may undergo directional translocation during malignant transformation across eight patient samples. In the developing axolotl brain, we found that transcription center reorganization exhibits conserved developmental dynamics across distinct cell types, suggesting coordinated developmental dynamics. By enabling 3D reconstruction of transcription center configurations from 2D data, Cytocraft provides a powerful tool to explore the spatial organization of transcription in development and disease.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsTranscription, GeneticTranscriptomeTranslocation, GeneticAnimalsHumansImaging, Three-DimensionalSpatial Transcriptomics3D transcriptional organizationspatial configurationsubcellular spatial transcriptomicstranscription center

Identifiers

PMID42059481
PMCPMC13130073

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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.