Evidence map›Paper›PMID 41118768›Full record

ArticleCell reports. Medicine2025

CANDiT: A machine learning framework for differentiation therapy in colorectal cancer.

Saptarshi Sinha, Joshua Alcantara, Kevin Perry, Vanessa Castillo, Annelies K Ondersma, Satarupa Banerjee, Ella McLaren, Celia R Espinoza, Sahar Taheri, Eleadah Vidales and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports. Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Artificial intelligence virtual bone organoids (AIVBOs).Journal of orthopaedic translation · 2026
    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

17 authors.

Saptarshi SinhaDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Joshua AlcantaraDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Kevin PerryDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Vanessa CastilloDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Annelies K OndersmaDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Satarupa BanerjeeDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Ella McLarenDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Celia R EspinozaDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Sahar TaheriDepartment of Computer Science and Engineering, Jacob's School of Engineering, University of California, San Diego, San Diego, CA 92093, USA.
Eleadah VidalesDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Courtney TindleDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA.
Adel AdelDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Siamak AmirfakhriDepartment of Surgery, University of California, San Diego, San Diego, CA 92093, USA; Department of Surgery, VA San Diego Healthcare System, San Diego, CA, USA.
Joseph R SawiresDepartment of Chemistry and Biochemistry, University of California, San Diego, San Diego, CA 92093, USA.
Jerry YangDepartment of Chemistry and Biochemistry, University of California, San Diego, San Diego, CA 92093, USA.
Michael BouvetDepartment of Surgery, University of California, San Diego, San Diego, CA 92093, USA; Department of Surgery, VA San Diego Healthcare System, San Diego, CA, USA; Moores Cancer Center, University of California, San Diego, San Diego, CA 92093, USA.
Pradipta GhoshDepartment of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; HUMANOID™ Center of Research Excellence, University of California, San Diego, La Jolla, CA 92093, USA; Moores Cancer Center, University of California, San Diego, San Diego, CA 92093, USA; Department of Medicine, University of California, San Diego, San Diego, CA 92093, USA. Electronic address: prghosh@ucsd.edu.

Funding

Integrators of Metastatic PotentialR01CA238042 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GHOSH, PRADIPTA, LUKER, GARY D · 2019 to 2023
$2.3M
Network-Based Novel Therapeutics in Colorectal CancersUG3TR002968 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DAS, SOUMITA, GHOSH, PRADIPTA · 2019 to 2021
$946k
Network-Based Novel Therapeutics in Colorectal CancersUH3TR002968 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DAS, SOUMITA, GHOSH, PRADIPTA · 2022 to 2022
$356k
NCATS NIH HHS UG3 TR002968NCATS NIH HHS UH3 TR002968NCI NIH HHS R01 CA238042
6 · The paper itself

Abstract

Reactivating lineage commitment to differentiate, and hence eliminate, cancer stem cells (CSCs) remains a therapeutic challenge. Here, we present CANDiT (cancer-associated nodes for differentiation targeting), a machine learning framework that identifies transcriptomic vulnerabilities for differentiation therapy in colorectal cancer (CRC). Centering on CDX2-a master intestinal lineage factor lost in high-risk, poorly differentiated CRCs-we identify PRKAB1, a stress polarity sensor, as a top therapeutic target. A clinical-grade PRKAB1 agonist reactivates lineage programs, dismantles Wnt/YAP-driven stemness, and selectively eliminates CDX2-low CSCs across CRC cell lines, xenografts, and patient-derived organoids (PDOs). Multivariate analysis reveals a strong therapeutic index tied to the CDX2-low state. A 50-gene response signature, derived from integrated modeling across all platforms, predicts ∼50% reduction in recurrence and mortality risk. Like immunotherapy, CANDiT resurrects a physiologic program-differentiation-to selectively eliminate CSCs, offering a scalable, precision framework for lineage restoration in solid tumors.

Indexed as

Cell DifferentiationColorectal NeoplasmsMachine LearningAnimalsCDX2 Transcription FactorCell Line, TumorGene Expression Regulation, NeoplasticHumansMiceNeoplastic Stem CellsOrganoidsCDX2 protein, humanCDX2 Transcription Factorcancer stem cellCCDC88ACDX2 restorationdifferentiation therapySPSstress-polarity pathway

Identifiers

PMID41118768
PMCPMC12711679

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.