Evidence map›Paper›PMID 41799193›Full record

ArticleTheranostics2026

Identification of programmed cell death-related subtypes reveals immune heterogeneity and therapeutic divergence in colon cancer.

Peng Xia, Ying Qu, Quanzhong Liu, Mengyan Zhu, Bin Huang, Wei Wu, Kening Li, Lingxiang Wu, Ruohan Zhang, Yingli Lv and 1 more

Abstract read
In one paragraph

Article in Theranostics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

11 authors.

Peng XiaSchool of Biological Science & Medical Engineering, Southeast University, Nanjing 211189, China.
Ying QuDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Quanzhong LiuDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Mengyan ZhuDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Bin HuangSchool of Biological Science & Medical Engineering, Southeast University, Nanjing 211189, China.
Wei WuSchool of Biological Science & Medical Engineering, Southeast University, Nanjing 211189, China.
Kening LiDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Lingxiang WuDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Ruohan ZhangDepartment of Bioinformatics, Nanjing Medical University, Nanjing 211166, China.
Yingli LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Qianghu WangSchool of Biological Science & Medical Engineering, Southeast University, Nanjing 211189, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale: Therapy resistance remains a critical challenge in colon adenocarcinoma (COAD). The dysregulation of programmed cell death (PCD) pathways significantly influences therapeutic response, but its integrated role in shaping the tumor microenvironment (TME) and driving clinical heterogeneity in COAD is poorly defined. Methods: We established a Programmed Cell Death-related Subtype (PCDS) classification by integrating 12 PCD pathways across transcriptomic data from 1,140 COAD patients using non-negative matrix factorization (NMF). The subtypes were validated in independent RNA-sequencing cohorts. We characterized the genomic, TME, and therapeutic features of each PCDS using multi-omics data analysis, and computational drug repositioning. Molecular docking and in silico drug sensitivity analyses were employed to evaluate candidate drugs. Results: We identified three robust subtypes, including PCDS1 (immune-activated), PCDS2 (WNT and TP53 signaling activation), and PCDS3 (mesenchymal and T-cell dysfunction/exclusion). PCDS3, enriched with inflammatory cancer-associated fibroblasts (iCAFs), exhibited the poorest prognosis and dual resistance to both chemotherapy and immunotherapy (>80% non-response). Analysis of single-cell and spatial transcriptomics data revealed the activation of MDK-SDC2 ligand-receptor axis between tumor cells and fibroblasts in PCDS3, spatially associated with T-cell dysfunction and exclusion. Computational drug repositioning identified the sunitinib as having selective potency against PCDS3 tumors, showing significantly lower IC50 values and high-affinity binding to SDC2 in molecular docking. Conclusions: This study defines a novel molecular subtype for COAD, linking PCD dysregulation to distinct TME remodeling and therapeutic outcomes. Targeting the MDK-SDC2 axis with agents such as sunitinib may offer a promising strategy to overcome stromal-mediated immunotherapy resistance in the most lethal PCDS3 tumors.

Indexed as

AdenocarcinomaApoptosisColonic NeoplasmsAntineoplastic AgentsDrug RepositioningDrug Resistance, NeoplasmGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyMolecular Docking SimulationTranscriptomeTumor MicroenvironmentAntineoplastic Agentscolon adenocarcinomamolecular subtypestherapy resistancetumor microenvironment

Identifiers

PMID41799193
PMCPMC12964230

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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.