Evidence map›Paper›PMID 41687601›Full record

ArticleCell reports methods2026

An integrative spatial multi-omic workflow for unified analysis of tumor tissue.

Jurgen Kriel, Joel J D Moffet, Tianyao Lu, Oluwaseun E Fatunla, Vinod K Narayana, Adam Valkovic, Ana Maluenda, Malcolm J McConville, Ellen Tsui, James R Whittle and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. 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

12 authors.

Jurgen KrielPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
Joel J D MoffetPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
Tianyao LuPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
Oluwaseun E FatunlaPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
Vinod K NarayanaMetabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC, Australia.
Adam ValkovicPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
Ana MaluendaAdvanced Histotechnology Facility, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.
Malcolm J McConvilleMetabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC, Australia.
Ellen TsuiAdvanced Histotechnology Facility, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.
James R WhittlePersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Sarah A BestPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia. Electronic address: best@wehi.edu.au.
Saskia FreytagPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia. Electronic address: freytag.s@wehi.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combining molecular profiling with imaging techniques has advanced the field of spatial biology, offering new insights into complex biological processes. Focusing on diffuse IDH-mutated glioma, this study presents a workflow for spatial multi-omics integration (SMINT) specifically combining spatial transcriptomics and spatial metabolomics. Our workflow incorporates both existing and custom-developed computational tools to enable cell segmentation and registration of spatial coordinates from both modalities to a common coordinate framework. During our investigation of cell segmentation strategies, we found that nuclei-only segmentation, while containing only 40% of segmented cell transcripts, enables accurate cell-type annotation but does not account for scenarios including delineation of multinucleated cells. Our integrative workflow including cell-morphology segmentation identified distinct cellular neighborhoods at the infiltrating edge of IDH-mutated gliomas, which were enriched in multinucleated and oligodendrocyte-lineage tumor cells and associated with differentially abundant metabolites.

Indexed as

Brain NeoplasmsGliomaMetabolomicsHumansMultiomicsSpatial TranscriptomicsWorkflowalignmentcell segmentationCosMxCP: cancer biologyCP: systems biologygliomaMALDI-TOFMERSCOPEspatial metabolomicsspatial multi-omicsspatial transcriptomicsXenium

Identifiers

PMID41687601
PMCPMC12946760

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.