Evidence map›Paper›PMID 42786656›Full record

ReviewClinical and translational medicine2026

Circulating tumour cells for guiding antibody‒drug conjugate therapy: Role of artificial intelligence.

Vahid Yaghoubi Naei, Mehran Dabiri, Lihua Chen, Jiajia Li, I-Han Wang, Gungun Lin, Majid Ebrahimi Warkiani

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Vahid Yaghoubi NaeiInstitute for Biomedical Materials & Devices, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia.
Mehran DabiriSchool of Biomedical Engineering, University of Technology Sydney, Sydney, New South Wales, Australia.
Lihua ChenDepartment of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.
Jiajia LiDepartment of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.
I-Han WangDepartment of Clinical Medicine, Suzhou Labyrinth Biotech Co., Ltd, Suzhou, China.
Gungun LinInstitute for Biomedical Materials & Devices, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0001-9880-8478
Majid Ebrahimi WarkianiDepartment of Mechanical Engineering, College of Engineering, American University of Sharjah, Sharjah, United Arab Emirates.

Funding

American University of SharjahFudan University Shanghai Cancer CenterLabyrinth BiotechUniversity of Technology Sydney
6 · The paper itself

Abstract

Antibody‒drug conjugates (ADCs) represent a major advance in precision oncology, yet their effectiveness depends critically on adequate target antigen expression. Tumour heterogeneity and dynamic antigen expression during treatment pose major challenges for conventional tissue biopsies used in patient selection. Liquid biopsy components such as circulating tumour cells (CTCs) enable real-time, minimally invasive monitoring of tumour burden, molecular characteristics and target antigen status. This review evaluates the potential of CTC analysis to overcome the key challenges in ADC therapy, including real-time target profiling, enhanced patient stratification and longitudinal monitoring of treatment response. While acknowledging that direct clinical evidence for CTC-guided ADC selection remains limited and prospective validation is still needed, we integrate clinical evidence from CTC-guided trials across different cancer types and propose pragmatic decision-making frameworks to incorporate CTC testing into ADC treatment strategies. We also examine how artificial intelligence (AI) has improved CTC detection accuracy and discuss exploratory AI models for multi-omics integration and hypothetical AI-guided ADC recommendation systems, clearly distinguishing these by their current level of clinical evidence. Liquid biopsy-guided ADC selection has the potential to enable more personalised cancer treatment as CTC technologies advance and standardisation improves.

Indexed as

Artificial IntelligenceImmunoconjugatesNeoplasmsNeoplastic Cells, CirculatingHumansLiquid BiopsyImmunoconjugatesantibody‒drug conjugatesartificial intelligencecirculating tumour cellsepithelial‒mesenchymal transitionliquid biopsyprecision oncologytumour heterogeneity

Identifiers

PMID42786656
PMCPMC13612861

What Socratic holds

Textmetadata
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.