Evidence map›Paper›PMID 41874895›Full record

ArticleDiscover oncology2026

Development and prognostic evaluation of an integrative programmed cell death index in pancreatic cancer based on multiple cell death modalities.

Junqian Zhang, Lei Ni, Shuoguo Li, Ruinuo Jia

Abstract read
In one paragraph

Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Junqian Zhang *Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Luoyang Cancer Hospital, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, 471023, China.
Lei Ni *Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Luoyang Cancer Hospital, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, 471023, China.
Shuoguo Li *Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Luoyang Cancer Hospital, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, 471023, China.
Ruinuo JiaHenan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Luoyang Cancer Hospital, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, 471023, China. jiaruinuo@163.com.

Funding

Henan Provincial Medical Science and Technology Research Project No. LHGJ20230478
6 · The paper itself

Abstract

Pancreatic cancer has exceptionally high mortality and is often clinically silent early on, with outcomes remaining poor; however, reliable tools that substantially refine prognostic stratification are still scarce. Programmed cell death (PCD) is intimately involved in tumor progression and treatment response and may provide clinically informative biomarkers. In this study, we systematically integrated genes related to 14 PCD modalities to develop a cell death index (CDI) in the TCGA cohort, followed by external validation in three independent GEO cohorts (GSE62452, GSE28735, and GSE57495). We further characterized associations between CDI-defined risk groups and the tumor microenvironment as well as predicted drug sensitivity. An eight-gene CDI signature was established and enabled effective risk stratification: patients in the high-CDI group exhibited significantly worse overall survival, and principal component analysis demonstrated clear separation between high- and low-CDI groups. Immune profiling indicated that the high-CDI group displayed an immune-cold phenotype with globally reduced immune infiltration, and drug sensitivity prediction suggested lower responsiveness to commonly used chemotherapeutic agents, including oxaliplatin and gemcitabine. Collectively, the CDI provides a practical framework for prognostic assessment and potential therapeutic stratification in pancreatic cancer, and may facilitate subsequent mechanistic studies and the development of individualized treatment strategies.

Identifiers

PMID41874895
PMCPMC13136472

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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.