Identification and validation of PANoptosis-based HNSCPAN-index as a prognostic model for head and neck squamous cell carcinoma DOI Creative Commons
Yun Feng,

Qinglai Tang,

Xiaojun Tang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Abstract PANoptosis, a recently characterized form of programmed cell death, remains incompletely understood in the context Head and Neck Squamous Cell Carcinoma (HNSCC). In this study, we identified prognostically relevant set PANoptosis genes within The Cancer Genome Atlas (TCGA) database for HNSCC uncovered three molecular subtypes based on their expression profiles. Each subtype exhibited distinct prognostic outcomes immune infiltration patterns. To further elucidate clinical relevance, constructed risk score model, termed HNSCPAN-index, using least absolute shrinkage selection operator (LASSO) Cox regression differentially expressed across subtypes. Patients were stratified into high-risk low-risk groups according to HNSCPAN-index. predictive power model was evaluated Kaplan-Meier analysis, ROC, nomogram validated an external dataset. A lower HNSCPAN-index correlated with longer overall survival enhanced immunotherapy responses, whereas higher indicated increased sensitivity small-molecule targeted therapies. Moreover, demonstrated strong correlation chemotherapeutic drug sensitivity. Finally, DSCAM as key regulator HNSCC, where silencing death mediated by pyroptosis inducers. conclusion, revealed its potential role prognosis, TME, chemotherapy. These findings may provide deeper understanding pave way development more personalized therapeutic strategies.

Language: Английский

PANoptosis: bridging apoptosis, pyroptosis, and necroptosis in cancer progression and treatment DOI Creative Commons
Jie Gao,

Anying Xiong,

Jiliu Liu

et al.

Cancer Gene Therapy, Journal Year: 2024, Volume and Issue: 31(7), P. 970 - 983

Published: March 29, 2024

Abstract This comprehensive review explores the intricate mechanisms of PANoptosis and its implications in cancer. PANoptosis, a convergence apoptosis, pyroptosis, necroptosis, plays crucial role cell death immune response regulation. The study delves into molecular pathways each mechanism their crosstalk within emphasizing shared components like caspases PANoptosome complex. It highlights significant various cancers, including respiratory, digestive, genitourinary, gliomas, breast showing impact on tumorigenesis patient survival rates. We further discuss interwoven relationship between tumor microenvironment (TME), illustrating how influences behavior progression. underscores dynamic interplay tumors microenvironments, focusing roles different cells interactions with cancer cells. Moreover, presents new breakthroughs therapy, potential targeting to enhance anti-tumor immunity. outlines strategies manipulate for therapeutic purposes, such as key signaling molecules caspases, NLRP3, RIPK1, RIPK3. novel treatments immunogenic PANoptosis-initiated therapies nanoparticle-based is also explored.

Language: Английский

Citations

35
Exploring the role of LOX family in glioma progression and immune modulation DOI Creative Commons
Chen Liu, Huilian Qiao, Hongqi Li

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 9, 2025

Glioma is a major cause of mortality among central nervous system tumors, with generally poor prognosis. The lysyl oxidase (LOX) family, group copper-dependent amine oxidases, has been implicated in the progression various cancers, but its specific role glioma and relationship immune infiltration remains insufficiently explored. This study aims to investigate LOX family's expression, prognostic significance, dynamics identify potential therapeutic targets. A comprehensive analysis was conducted using public databases assess gene mutation frequency, patterns related family glioma. results were validated through survival immunohistochemistry. Functional assays, including EdU, Transwell, flow cytometry, used evaluate cell proliferation, migration, invasion, apoptosis. Co-culture experiments cells, ELISA, transplantation model employed immune-modulatory effects family. Gene protein expression levels further analyzed qRT-PCR Western blotting. significantly upregulated low-grade gliomas strongly associated clinical outcomes. Although frequencies low, contributed pathways involving metastasis, hypoxia response, angiogenesis, infiltration. correlated increased macrophages eosinophils decreased presence Treg CD8+ T cells. Knockdown genes impaired functions, induced apoptosis, altered behavior by reducing M2 macrophage polarization enhancing activity. overexpressed prognosis patterns. These findings highlight as promising marker target, particularly for effectiveness immunotherapy treatment.

Language: Английский

Citations

0
Opportunities and Challenges of Machine Learning in Anticaner Drug Therapies DOI Creative Commons

M.I.A.O. Chunlei,

H.U.A.N.G.F.U. rui,

Chao Yuan

et al.

Intelligent Pharmacy, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Predicting survival and immune status of breast cancer patients based on prognostic features related to PANoptosis DOI Creative Commons
Jing Cui, Dapeng Wu, Da Lv

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 15, 2025

Breast cancer (BRCA) is a prevalent female malignancy. PANoptosis, integrating diverse cell death traits, pivotal in BRCA, thus necessitating deeper study. Data from Gene Expression Omnibus (GEO, GSE180286 and GSE20685) The Cancer Genome Atlas (TCGA) were analyzed. Weighted gene co-expression network analysis (WGCNA) identified PANoptosis-related genes BRCA patients TCGA. Further refinement of these module was conducted through univariate Cox regression, LASSO regression (glmnet package), stepwise multivariate to derive the final biomarkers. Based on biomarkers, risk model established, in-vitro experiments (wound healing assay, Transwell qRT-PCR) carried out validate accuracy MCPcounter package oncoPredict used assess immune infiltration sensitivity drugs patients, respectively. This study 8 biomarkers (ACY3, CD83, CXCL13, KLHDC7B, NR1H3, SMCO4, TRPM2, UPP1) established model. In-vitro revealed significant differences biomarker expression between cells control group, with TRPM2 knockdown inhibiting migration invasion. Enrichment showed metabolic pathways activated high-risk group. Additionally, lower enrichment fibroblasts Drug linked 13 RiskScore. Finally, single-cell six types (including stem cells, fibroblasts, T-cells, macrophages, B/Plasma endothelial cells) for found that macrophages had higher PANoptosis activity. current research introduces novel prognosis but also provides fresh perspective treatment strategies.

Language: Английский

Citations

0
Identification of PANoptosis-relevant subgroups and predicting signature to evaluate the prognosis and immune landscape of patients with biliary tract cancer DOI Creative Commons
Dongming Liu, Wenshuai Chen, Zhiqiang Han

et al.

Hepatology International, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 10, 2024

This study conducted molecular subtyping of biliary tract cancer patients based on 19 PANoptosis-related gene signatures.

Language: Английский

Citations

3
PANoptosis: A new era for anti-cancer strategies DOI
Zilian Cui, Yuan Li,

Yao Bi

et al.

Life Sciences, Journal Year: 2024, Volume and Issue: unknown, P. 123241 - 123241

Published: Nov. 1, 2024

Language: Английский

Citations

1
PANoptosis-based molecular subtype and prognostic model predict survival and immune landscape in esophageal cancer DOI Creative Commons
Zheming Liu, Jiahui Liu, Fuben Liao

et al.

Clinical Cancer Bulletin, Journal Year: 2024, Volume and Issue: 3(1)

Published: July 4, 2024

Abstract Purpose To establish a prognostic model to predict the survival of patients with esophageal cancer (EC). Methods We extracted expression profiles prognostic-related genes and clinicopathological data from TCGA GEO databases. Subsequently, comprehensive bioinformatics analysis was conducted construct utilizing LASSO multivariate Cox regression. The stability risk signature validated through Kaplan-Meier ROC curve analyses on training, internal testing, external testing sets. Furthermore, we developed nomogram that incorporates score clinical features suvival. Additionally, incorporating relevant parameters enhance survivorship prediction. delved into exploring correlation between immune cell abundance, checkpoints, as well responses immunotherapy chemotherapeutic agents. Results In this study, successfully identified 19 prognosis-related out pool 65 PANoptosis-related (PRGs) sourced existing literature. Through consensus clustering analysis, classified two distinct groups PANcluster A B. derived five signatures emerged an independent factor among EC. accuracy, devised integrating characteristics, enabling prediction 1-year, 2-year, 3-year overall (OS) rates. Notably, individuals in high-risk group demonstrated poorer prognoses compared their low-risk counterparts. displayed substantial correlations levels These pivotal findings underscore significance considering patterns improving assessment predicting treatment diagnosed cancer. Conclusion constructed reliable for EC PRGs. serves valuable tool patient outcomes, offering crucial insights can inform guide decisions

Language: Английский

Citations

1
A novel PANoptosis-related lncRNA model for forecasting prognosis and therapeutic response in hepatocellular carcinoma DOI Creative Commons

Chenlu Lan,

Haifei Qin,

Zaida Huang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 19, 2024

Abstract Some studies have shown PANoptosis-related genes were related to the prognosis for hepatocellular carcinoma (HCC), but efforts lncRNAs are scarce. Data of The Cancer Genome Atlas (TCGA) was used identify prognostic lncRNAs, risk model and nomogram constructed predicting HCC. clinical characteristic, mutation landscape, immune response, drug sensitivity, enriched biological process pathway between low high groups analyzed. Polymerase Chain Reaction (PCR) performed verify expression lncRNAs. Risk models displayed good predictive performance in TCGA, train test cohorts with area under receiver operator characteristic curves (AUC) 1- 3- year OS > 0.7. Notably, better than TNM stage (AUC: 0.717 0.673 vs 0.660). group proved be an independent factor (p < 0.05). Furthermore, we found that patients had a larger tumor size, higher AFP level advanced functional enrichment analysis suggested upregulated molecular characteristics cell division, proliferation, cycle p53 signaling pathway, downregulated metabolic pathway. revealed obvious difference TP53 CTNNB1 groups. Immune response sensitivity discovered likely benefit from immunotherapy some targeted drugs. In conclusion, lncRNA may predict therapeutic

Language: Английский

Citations

0
Comprehensive pancancer analysis reveals that LPCAT1 is a novel predictive biomarker for prognosis and immunotherapy response DOI
Hongyu Gao, Jinfeng Zhu, Tong Wu

et al.

APOPTOSIS, Journal Year: 2024, Volume and Issue: 29(11-12), P. 2128 - 2146

Published: Aug. 4, 2024

Language: Английский

Citations

0
Immunotherapy and pan-apoptotic characterization of the tumor microenvironment in gastric cancer (STAD): a single-cell multidimensional analysis DOI Creative Commons
Sheng Zhang, Jianhong Wang, Huan Zhang

et al.

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: Oct. 13, 2024

The aim of this study was to elucidate the critical role autophagy-related gene aggregation in gastric cancer tumor microenvironment cells and investigate their major roles cellular functions. In particular, expression these genes tumor-associated fibroblast subtypes scrutinized an attempt explain cell-subpopulation-specific cell–cell communication regulation study, single-cell RNA sequencing data were first analyzed multiple steps, including preprocessing, cell clustering, classification. Cell subpopulations patterns identified using unsupervised non-negative matrix factorization (NMF) techniques. dynamic aggregates various types deciphered by pseudotime trajectory analysis (PTA). Intercellular performed CellChat R software package, revealing intricate exchange key signaling molecules between subpopulations, SCENIC used identify regulatory networks reveal mechanisms behind heterogeneity. associated with pan-apoptosis NMF decomposition analysis. Cell–cell revealed subpopulations. Dynamic aggregated pseudotemporal STAD observed PTA. subtype, different ligand-receptor interactions immunomodulation observed. By deeply analyzing comparing within intercellular communication, provides new insights into pan-apoptosis-related regulating immune responses functions cancer. These findings pave way for further exploration tumorigenesis regulation, as well laying foundation potential therapeutic strategies.

Language: Английский

Citations

0