Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer

Sep 21, 2026

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Crosstalk among distinct cell death programs has emerged as a key determinant of cancer biology, yet its contribution to colorectal cancer heterogeneity remains insufficiently defined. This study built an interaction-perturbation network spanning 11 cell death pathways and identified four cell-death-network subtypes (CDN1–4) with distinct molecular features and clinical outcomes. The CDN4 subtype showed high autophagy activity and the worst prognosis. AOC3 was then established as an autophagy-associated biomarker with strong predictive power for CDN4 and significant prognostic value in colorectal cancer.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Background

Cell death pathways and colorectal cancer

Methods

Interaction-perturbation network construction

Identification of cell death network subtypes

Results

CDN4: high autophagy activity and poor prognosis

AOC3 as an autophagy-related prognostic biomarker

Conclusion

communications biology Article |
[https://doi.org/10.1038/s42003-024-05980-6](https://doi.org/10.1038/s42003-024-05980-6) | | | --- | --- | | Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer
Check for updates | | | Hui Xu1,2,3,8, Haiyang Cui4,8, Siyuan Weng1,2,3,8, Yuyuan Zhang1, Libo Wang5, ZheXing6, Xinwei Han 1,2,3 & Zaoqu Liu 1,2,3,7 | | | The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression proﬁles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Speciﬁcally, we identiﬁed a subtype (CDN4) endowedwith high autophagy activity andthe worst prognosis. Furthermore, AOC3wasidentiﬁed asa potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and signiﬁcant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC. | | | As the second most deadly worldwide, colorectal cancer (CRC) is featured by dramatical heterogeneity and invasiveness1. By2030, the global burden of CRC is expected to increase by 60%, with more than 1.1 million deaths and 2.2 million new cases2, demonstrating the imperative to improve the diagnosis and treatment of CRC patients. With advances in high-throughput sequencing and experimental techniques, numerous molecular biomarkers and taxonomies have been developed to facilitate the clinical management of CRC. A multicenter study of 13 countries internationally validated an Immunoscore measured by the abundance of CD3+ and CD8 + Tcells in the center and invasive margin of tumors, which could accurately estimate the recurrence risk of CRC patients3. Our study previously integrated ten machine-learning algorithms to construct a multi-gene panel for improving outcomes in CRC4. Moreover, molecular subtypes based on snapshot gene | expression or multi-omics data have represented a tremendous stride forward in deciphering intertumoral heterogeneity and optimizing individual treatments of CRC5–9, such as Consensus Molecular Subtypes (CMS)5 and CRC Intrinsic Subtypes (CRIS)6. Nonetheless, existing tools were commonly developed based on the expression proﬁles of multiple genes, obviously ignoring the biological interactions across various genes within adeﬁned pathway10–12.
Recently, various patterns of cell death have been investigated with each profoundly impacting the initiation and development of cancers13. In CRC, unbalanced or defective cell death signaling is involved in the pathogenesis of colorectal diseases ranging from chronic bowel disease to colorectal cancer14. Additionally, cell death pathways are essential targets for current therapies against CRC. For example, inhibition of the autophagy | 1Department of Interventional Radiology, The First Afﬁliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China. 2Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China. 3Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China. 4Department of Radiology, The First Afﬁliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China. 5Department of Hepatobiliary and Pancreatic Surgery, The First Afﬁliated Hospital of Zhengzhou University, Zhengzhou, Hen

FAQs

What does the study focus on regarding colorectal cancer?

It examines how interactions (crosstalk) among different cell death pathways relate to colorectal cancer heterogeneity, subtype formation, and patient outcomes.

How were the cell death network (CDN) subtypes determined?

The authors constructed an interaction-perturbation network using 11 cell death pathways and derived four CDN subtypes from the perturbation structure.

What is AOC3’s role in this research?

AOC3 is identified as an autophagy-related biomarker, with exceptional predictive performance for the CDN4 subtype and significant prognostic value in colorectal cancer.

Sep 21, 2026

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