Evidence map›Paper›PMID 41063141›Full record

ReviewGenome medicine2025

Cell-cell interactions as predictive and prognostic markers for drug responses in cancer.

Xuehan Lu, Xiao Tan, Eun Ju Kim, Xinnan Jin, Meg L Donovan, Jazmina L Gonzalez Cruz, Zherui Xiong, Maria Reyes Becerra de Los Reyes Becerra Perez, Jialei Gong, James Monkman and 5 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

15 authors.

Xuehan Lu *Frazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
Xiao Tan *Institute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4067, Australia.
Eun Ju Kim *Institute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4067, Australia.
Xinnan JinInstitute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4067, Australia.
Meg L DonovanQueensland Spatial Biology Centre, Wesley Research Institute, The Wesley Hospital, Level 8 East Wing, Auchenflower, QLD, 4066, Australia.
Jazmina L Gonzalez CruzFrazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
Zherui XiongQIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia.
Maria Reyes Becerra de Los Reyes Becerra PerezFrazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
Jialei GongFrazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
James MonkmanFrazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
Divya AgrawalAustralian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, 4067, Australia.
Arutha KulasingheFrazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia.
U. Q. CellOmics Innovation Forum
Quan Nguyen *Institute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4067, Australia. quan.ngyuen@qimrberghofer.edu.au.
Zewen Kelvin Tuong *Frazer Institute, Faculty of Health, Medicine and Behavourial Sciences, The University of Queensland, Brisbane, QLD, 4102, Australia. z.tuong@uq.edu.au.

Funding

National Health and Medical Research Council (NHMRC) Investigator Grant GNT2008928
6 · The paper itself

Abstract

The tumor microenvironment (TME) is composed of a diverse and dynamic spectrum of cell types, cellular activities, and cell-cell interactions (CCI). Understanding the complex CCI within the TME is critical for advancing cancer treatment strategies, including modulating or predicting drug responses. Recent advances in omics technologies, including spatial transcriptomics and proteomics, have allowed improved mapping of CCI within the TME. The integration of omics insights from different platforms may facilitate the identification of novel biomarkers and therapeutic targets. This review discusses the latest computational methods for inferring CCIs from different omics data and various CCI and drug databases, emphasizing their applications in predicting drug responses. We also comprehensively summarize recent patents, clinical trials, and publications that leverage these cellular interactions to refine cancer treatment approaches. We believe that the integration of these CCI-focused technologies can improve personalized therapy for cancer patients, thereby optimizing treatment outcomes and paving the way for next-generation precision oncology.

Indexed as

Antineoplastic AgentsBiomarkers, TumorCell CommunicationNeoplasmsComputational BiologyHumansPrecision MedicinePrognosisTumor MicroenvironmentAntineoplastic AgentsBiomarkers, TumorCancerCell–cell colocalizationCell–cell interactionsDrug responsesPersonalized therapyPrecision treatmentSingle cell-omicsSpatial-omicsTumor microenvironment

Identifiers

PMID41063141
PMCPMC12506067

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.