Evidence map›Paper›PMID 40180058›Full record

ArticleInternational journal of radiation oncology, biology, physics2025

Differentiation Stage Predicts Radiosensitivity in Mesenchymal-Like Pancreatic Cancer.

Tingshi Su, Xinjian Yu, Mojtaba Hoseini-Ghahfarokhi, David B Flint, Scott J Bright, Joana I D S Antunes, David K J Martinus, Mandira Manandhar, Mariam Ben Kacem, Poliana C Marinello and 9 more

Abstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2025. 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. 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

19 authors.

Tingshi SuDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Xinjian YuDepartment of Pediatrics, Texas Children's Cancer Center, Baylor College of Medicine, Houston, Texas.
Mojtaba Hoseini-GhahfarokhiDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
David B FlintDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Scott J BrightDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Joana I D S AntunesDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Physics, Faculty of Science, University of Lisbon, Lisbon, Portugal; Laboratory of Instrumentation and Experimental Particle Physics, Lisbon, Portugal.
David K J MartinusDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Mandira ManandharDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Mariam Ben KacemDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Poliana C MarinelloDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Eurico J G PereiraDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Univ Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) area of Environment Genetics and Oncobiology (CIMAGO), Institute of Biophysics, Faculty of Medicine, Coimbra, Portugal; Univ Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal; Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal.
Hua-Sheng ChiuDepartment of Pediatrics, Texas Children's Cancer Center, Baylor College of Medicine, Houston, Texas.
Uwe TittDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
David R GrosshansDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jan SchuemannDepartment of Radiation Oncology, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts.
Henning WillersDepartment of Radiation Oncology, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts.
Harald PaganettiDepartment of Radiation Oncology, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts.
Pavel SumazinDepartment of Pediatrics, Texas Children's Cancer Center, Baylor College of Medicine, Houston, Texas. Electronic address: sumazin@bcm.edu.
Gabriel O SawakuchiDepartment of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: gsawakuchi@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
Project 3: Enhanced Sensitivity of Tumors to Proton Beam Therapy: Mechanisms and Biomarkers.P01CA261669 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI TITT, UWE · 2021 to 2025
$14.0M
Alpha particles combined with ATR inhibition to activate the immune system: mechanisms and pre-clinical translationR01CA279119 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Gabriel Oliveira Sawakuchi · 2023 to 2026
$2.1M
Discovery of chemoresistant tumor subclones in pediatric liver cancersR21CA286257 · NCI · BAYLOR COLLEGE OF MEDICINE · PI SUMAZIN, PAVEL · 2024 to 2025
$413k
Diagnostic biomarkers for hepatoblastomas with hepatocellular carcinoma featuresR21CA223140 · NCI · BAYLOR COLLEGE OF MEDICINE · PI SUMAZIN, PAVEL · 2019 to 2020
$383k
NCI NIH HHS P01 CA261669NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA279119NCI NIH HHS R21 CA223140NCI NIH HHS R21 CA286257
6 · The paper itself

Abstract

purposeTo derive a genomic classifier to predict radiosensitivity of pancreatic cancer cell lines and patients with pancreatic cancer to allow genomic-guided radiation therapy. METHODS AND MATERIALS: We collected a comprehensive data set of full clonogenic cell survival curves of 45 pancreatic cancer cell lines irradiated with clinical photon and proton beams. We derived classifiers based on data from human embryonic and fetal pancreas single-cell RNA-sequencing to distinguish between epithelial and mesenchymal cells and to predict pancreas cell-line differentiation stage. Independent testing was done with an embryonic mouse pancreas single-cell RNA-sequencing data set. We then used bulk RNA-seq profiles from the Cancer Cell Line Encyclopedia to classify our pancreatic cancer cell lines using our epithelial-mesenchymal and differentiation stage classifiers. We then correlated the differentiation stage classifier with the radiosensitivity of the pancreatic cancer cell lines as well as with pancreatic cancer patient data from The Cancer Genome Atlas.

resultsWe found wide variability in radiosensitivity to both photons and protons among pancreatic cancer cell lines. We showed that the differentiation stage is predictive of radiosensitivity of mesenchymal pancreatic cancer cell lines but not epithelial pancreatic cancer cell lines. We found that chromatin compaction is associated with the differentiation stage and showed that the less differentiated mesenchymal pancreatic cancer cell lines tend to be radioresistant and with more compact chromatin than the radiosensitive differentiated cell lines. Patients with more differentiated tumors exhibit better overall survival.

conclusionsWe found that mesenchymal-like undifferentiated pancreatic cancer cell lines are more radioresistant than mesenchymal-like differentiated ones and that patients with pancreatic cancer with mesenchymal-like undifferentiated tumors treated with radiation therapy tend to have lower overall survival compared with patients with mesenchymal-like differentiated tumors. We show that it is feasibility to use the differentiation stage of mesenchymal pancreatic cancer cells to predict tumor specific radiosensitivity.

Indexed as

Cell DifferentiationPancreatic NeoplasmsRadiation ToleranceAnimalsCell Line, TumorCell SurvivalEpithelial-Mesenchymal TransitionHumansMicePancreas

Identifiers

PMID40180058
PMCPMC12333838

What Socratic holds

Textmetadata
LicenceTDM
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.