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1.

001-es BibID:BIBFORM131917
035-os BibID:(Scopus)105013581473 (WoS)001551735100001
Első szerző:Huang, Xufeng (Bioinformatics, Oncology, Dentistry)
Cím:Space Dentistry Combined With Remote and AI Technologies, a Necessity for Long-Term Stays : Thoughts of US Astronauts' Unexpected Stay / Xufeng Huang, Zhengrui Li, Qi Wang, Ji'an Liu, Ge Zhang, Runzhi Chen, Xuefan Bu, Yixi Wang, Peng Luo, Ling Zhang, Andras Hajdu
Dátum:2025
ISSN:1354-523X
Tárgyszavak:Orvostudományok Klinikai orvostudományok levél
folyóiratcikk
Space dentistry
Microgravity
Remote dental care
AI robotics
clinical science
medicine
Megjelenés:Oral Diseases. - 31 : 8 (2025), p. 1-2. -
További szerzők:Li, Zhengrui Wang, Qi Liu, Ji'an Zhang, Ge Chen, Runzhi Bu, Xuefan Wang, Yixi Luo, Peng Zhang, Ling Hajdu András (1973-) (matematikus, informatikus)
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2.

001-es BibID:BIBFORM103045
035-os BibID:(WoS)001023055700001 (Scopus)85137659869
Első szerző:Huang, Xufeng (Bioinformatics, Oncology, Dentistry)
Cím:Cuproptosis-related gene index: a predictor for pancreatic cancer prognosis, immunotherapy efficacy, and chemosensitivity / Xufeng Huang, Shujing Zhou, Tóth János, Hajdu András
Dátum:2022
ISSN:1664-3224
Megjegyzések:Aim: The term "Cuproptosis" was coined to describe a novel type of cell death triggered by intracellular copper buildup that is fundamentally distinct from other recognized types such as autophagy, ferroptosis, and pyroptosis in recent days. As the underlying mechanism was newly identified, its potential connection to pancreatic adenocarcinoma (PAAD) is still an open issue. Methods: A set of machine learning algorithms was used to develop a Cuproptosis-related gene index (CRGI). Its immunological characteristics were studied by exploring its implications on the expression of the immunological checkpoints, prospective immunotherapy responses, etc. Moreover, the sensitivity to chemotherapeutic drugs was predicted. Unsupervised consensus clustering was performed to more precisely identify different CRGI-based molecular subtypes and investigate the immunotherapy and chemotherapy efficacy. The expression of DLAT, LIPT1 and LIAS were also investigated, through real-time quantitative polymerase chain reaction (RT-qPCR), western blot, and immunofluorescence staining (IFS). Results: A novel CRGI was identified and validated. Additionally, correlation analysis revealed major changes in tumor immunology across the high- and low-CRGI groups. Through an in-depth study of each medication, it was determined that the predictive chemotherapeutic efficacy of 32 regularly used anticancer drugs differed between high- and low-CRGI groups. The results of the molecular subtyping provided more support for such theories. Expressional assays performed at transcriptomic and proteomic levels suggested that the aforementioned Cuproptosis-related genes might serve as reliable diagnostic biomarkers in PAAD. Significance: This is, to the best of our knowledge, the first study to examine prognostic prediction in PAAD from the standpoint of Cuproptosis. These findings may benefit future immunotherapy and chemotherapeutic therapies.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
cuproptosis
machine learning
pancreatic cancer
tumor microenvironment
immunotherapy
chemotherapy
gene signature
Megjelenés:Frontiers in Immunology. - 13 (2022), p. 1-31. -
További szerzők:Zhou, Shujing (1997-) Tóth János (1984-) (programtervező matematikus) Hajdu András (1973-) (matematikus, informatikus)
Pályázati támogatás:TKP2021-NKTA-34
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3.

001-es BibID:BIBFORM132135
Első szerző:Lin, Anqi
Cím:The microbiome in cancer / Anqi Lin, Minying Xiong, Aimin Jiang, Lihaoyun Huang, Hank Z. H. Wong, Suyin Feng, Chunyan Zhang, Yu Li, Li Chen, Hao Chi, Pengpeng Zhang, Bicheng Ye, Hengguo Zhang, Nan Zhang, Lingxuan Zhu, Weiming Mou, Junyi Shen, Kailai Li, Wentao Xu, Haoxuan Ying, Cangang Zhang, Dongqiang Zeng, Jindong Xie, Xinpei Deng, Qi Wang, Jianying Xu, Wenjie Shi, Chang Qi, Chunrun Qu, Xufeng Huang, András Hajdu, Chaoqun Li, Changmin Peng, Xuanye Cao, Guangsheng Pei, Lin Zhang, Yujia Huo, Jiabao Xu, Antonino Glaviano, Attila Gábor Szöllősi, Sicheng Bian, Zhengrui Li, Hailin Tang, Bufu Tang, Zaoqu Liu, Jian Zhang, Kai Miao, Quan Cheng, Ting Wei, Shuofeng Yuan, Peng Luo
Dátum:2025
ISSN:2770-5986 2770-596X
Megjegyzések:The human microbiome is now recognized as a central regulator of cancer biology, intricately shaping tumor development, immune dynamics, and therapeutic response. This comprehensive review delineates the multifaceted roles of bacteria, viruses, and fungi in modulating the tumor microenvironment and systemic immunity across diverse cancer types. We synthesize current evidence on how microbial dysbiosis promotes carcinogenesis via chronic inflammation, metabolic reprogramming, genotoxic stress, immune evasion, and epigenetic remodeling. This review emphasizes organ?specific microbiome signatures and highlights their potential as non?invasive biomarkers for early detection, treatment stratification, and prognosis. Furthermore, we explore the impact of intratumoral microbiota on cancer therapies, uncovering how microbial metabolites and host-microbe interactions shape therapeutic efficacy and resistance. Finally, advances in microbiome?targeted strategies, such as probiotics, fecal microbiota transplantation, and engineered microbes offer new avenues for adjunctive cancer therapy. This review provides a roadmap for future investigation and underscores the transformative promise of microbiome modulation in cancer prevention and treatment.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
cancer
microbiome
precision
oncology treatment
tumor microenvironment
Megjelenés:iMeta. - e70070 (2025), p. 1-104. -
További szerzők:Xiong, Minying Jiang, Aimin Huang, Lihaoyun Wong, Hank Z. H. Feng, Suyin Zhang, Chunyan Li, Yu Chen, Li Chi, Hao Zhang, Pengpeng Ye, Bicheng Zhang, Hengguo Zhang, Nan Zhu, Lingxuan Mou, Weiming Shen, Junyi Li, Kailai Xu, Wentao Ying, Haoxuan Zhang, Cangang Zeng, Dongqiang Xie, Jindong Deng, Xinpei Wang, Qi Xu, Jianying Shi, Wenjie Qi, Chang Qu, Chunrun Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Hajdu András (1973-) (matematikus, informatikus) Li, Chaoqun Peng, Changmin Cao, Xuanye Pei, Guangsheng Zhang, Lin Huo, Yujia Xu, Jiabao Glaviano, Antonino Szöllősi Attila Gábor (1982-) (élettanász) Bian, Sicheng Li, Zhengrui Tang, Hailin Tang, Bufu Liu, Zaoqu Zhang, Jian Miao, Kai Cheng, Quan Wei, Ting Yuan, Shuofeng Luo, Peng
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4.

001-es BibID:BIBFORM131913
Első szerző:Lin, Anqi
Cím:The Evolving Landscape of Immunotoxicity : Charting Mechanisms and Future Strategies for Immune Checkpoint Inhibitor Adverse Events / Anqi Lin, Keyin Zheng, Aimin Jiang, Xufeng Huang, Qi Wang, András Hajdu, Zhengrui Li, Jian Zhang, Peng Luo
Dátum:2025
ISSN:2998-4963 2998-4971
Megjegyzések:The use of immune checkpoint inhibitors (ICIs) has significantly improved the efficacy of cancer therapy, but their associated immune-related adverse events (irAEs) can severely compromise treatment safety. This review systematically summarizes the core mechanisms underlying irAEs, which include multi-organ damage resulting from T-cell dysfunction, B-cell-mediated autoantibody abnormalities, cytokine network dysregulation, and monocyte-driven inflammatory cascades. Identified risk factors encompass a range of elements, including host clinical characteristics and underlying diseases, gut microbiota dysbiosis, characteristics of the treatment regimen, tumor type and its histological features, genetic factors and immunogenetic polymorphisms, pre-existing autoimmune conditions or a history of autoimmunity, and a history of previous exposures alongside various environmental factors. The grading criteria, their clinical context and incidence rates, and clinical management strategies for irAEs affecting various organ systems are detailed herein. Future research should aim to deeply analyze the shared mechanisms and temporal dynamics between irAEs and anti-tumor effects, develop targeted irAE prediction and monitoring systems, and optimize strategies for irAE prevention and treatment.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Med Research. - 1 : 1 (2025), p. 1-37. -
További szerzők:Zheng, Keyin Jiang, Aimin Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Wang, Qi Hajdu András (1973-) (matematikus, informatikus) Li, Zhengrui Zhang, Jian Luo, Peng
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5.

001-es BibID:BIBFORM110398
035-os BibID:(WoS)000969255200001 (Scopus)85152639331
Első szerző:Liu, Ying
Cím:Machine learning approach combined with causal relationship inferring unlocks the shared pathomechanism between COVID-19 and acute myocardial infarction / Ying Liu, Shujing Zhou, Longbin Wang, Ming Xu, Xufeng Huang, Zhengrui Li, Andras Hajdu, Ling Zhang
Dátum:2023
ISSN:1664-302X
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Frontiers in Microbiology. - 14 (2023), p. 1-10. -
További szerzők:Zhou, Shujing (1997-) Wang, Longbin Xu, Ming Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Li, Zhengrui Hajdu András (1973-) (matematikus, informatikus) Zhang, Ling
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6.

001-es BibID:BIBFORM134581
Első szerző:Miao, Pengyu
Cím:Novel common target genes for breast cancer and colorectal cancer : a Mendelian randomization and spatial transcriptomics study / Pengyu Miao, Zhaokai Zhou, Ling Zhang, Xufeng Huang, Zhengrui Li, Shouxin Wei, András Hajdu
Dátum:2025
ISSN:2730-6011
Megjegyzések:Introduction Breast and colorectal cancer are a major global public health problem. Breast cancer is one of the most common cancers worldwide. Colorectal cancer is the third most common cancer and the second most common cause of tumor death worldwide. Central memory T (TCM) cells are closely related to the development of tumors and important targets for immunotherapy. Therefore, identifying the common signaling molecules of these two diseases in TCM cells can improve our understanding of these diseases and lead to the development of therapies that can be effective for treating both. Methods Single-cell RNA (scRNA) data of breast cancer (GSE161529) and colorectal cancer (GSE222300) patients was downloaded from the GEO database. The data were normalized and dimension reduced, then different T cell subsets were identified and differential gene expression analysis of central memory CD8 + T cells was conducted. Mendelian randomization analysis, reverse causality detection, and co-localization analysis was performed to explore the relationship between differentially-expressed genes and the disease. Quasi-temporal analysis and metabolic analysis was done using scRNA sequencing technology and further analysis of gene expression and metabolism in spatial transcriptomes. Finally, the degree of association between drug target genes was analyzed by protein-protein interaction (PPI) analysis. Results Our analysis identified four genes (ZFP36L2, CKS1B, PTTG1, and ITGAE) that were associated with risk of both breast and colorectal cancer. In the pseudotime analysis, we found that the expression levels of CKS1B and PTTG1 decreased over time (p < 0.05) while ZFP36L2 and ITGAE increased over time (p < 0.05). In the metabolic analysis, these four genes were closely associated with the cysteine and methionine metabolism pathways, which was corroborated in the spatial transcription analysis. Finally, the PPI analysis among the drug target genes identified an interaction between PTTG1 and CKS1B genes. Conclusion This study reports that the ZFP36L2, CKS1B, PTTG1, and ITGAE genes could potentially influence breast cancer and colorectal cancer development via TCM CD8 + T cells. These four genes are putative common markers for diagnosis, treatment, and monitoring tumor response to therapies.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Mendelian randomization
Breast cancer
Colorectal cancer
Single-cell RNA sequencing
Spatial transcriptomics
Megjelenés:Discover Oncology. - 12 (2025), p. 1-23. -
További szerzők:Zhou, Zhaokai Zhang, Ling Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Li, Zhengrui Wei, Shouxin Hajdu András (1973-) (matematikus, informatikus)
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7.

001-es BibID:BIBFORM135265
035-os BibID:(Scopus)105026463118
Első szerző:Su, Yang
Cím:Applications of artificial intelligence and large language models in cancer immunotherapy / Su Yang, Liu Ji'An, Li Jing, Huang Xufeng, Hajdu András, Fu Rao, Xu Bo, Wang Yufeng, Liu Xue, Li Zhengrui, Wang, Qi
Dátum:2025
ISSN:1570-1646
Megjegyzések:With the rapid advancement of artificial intelligence (AI) technologies, particularly the widespread adoption of large language models (LLMs), the field of cancer immunotherapy is experiencing unprecedented opportunities for progress. As an innovative therapeutic approach, cancer immunotherapy has markedly improved patient outcomes, yet it continues to face challenges such as substantial inter individual variability in therapeutic response, difficulties in identifying novel targets, and limited accuracy in biomarker prediction. In recent years, AI and LLMs have provided powerful support for target identification, personalized treatment design, and precise prediction of immune related biomarkers through data mining, multi-dimensional information integration, and intelligent analysis. This letter highlights emerging advances in the application of AI and LLMs in cancer immunotherapy, summarizes current research progress and their potential for clinical translation, and discusses existing technical barriers and future directions, aiming to promote greater precision and intelligence in cancer immunotherapy.
Tárgyszavak:idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Artificial intelligence
Large language models
Cancer immunotherapy
Personalized medicine
Biomarkers
Megjelenés:Current Proteomics. - 22 : 5 (2025), p. 1-5. -
További szerzők:Liu, Ji'an Li, Jing Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Hajdu András (1973-) (matematikus, informatikus) Fu, Rao Xu, Bo Wang, Yufeng Liu, Xue Li, Zhengrui Wang, Qi
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8.

001-es BibID:BIBFORM131981
Első szerző:Yan, Xinrong
Cím:Immunotherapy-induced cholestasis in cancer : insights from the two real-world pharmacovigilance databases of FAERS and VigiBase / Xinrong Yan, Zhengrui Li, Aimin Jiang, Jinghong Chen, Xufeng Huang, András Hajdu, Hank Z.H. Wong, Quan Cheng, Jian Zhang, Anqi Lin, Peng Luo
Dátum:2025
ISSN:1743-9191 1743-9159
Megjegyzések:Background: The US Food and Drug Administration (FDA) recently issued a safety alert regarding cholestasis as a potential adverse reaction to immune checkpoint inhibitor (ICI) therapy. However, the underlying mechanisms of ICI-induced cholestasis remain poorly elucidated. Methods: This study analyzed adverse event reports of cancer patients treated with ICIs, extracted from the FAERS (2013-2023) andVigiBase (1968-2023) databases. The reporting odds ratio (ROR) and information component (IC) methods were employed to evaluate the association between cholestasis and ICIs therapy, while time-to-onset (TTO) analysis was conducted. Clinical data from hospitals and results from mouse experiments were integrated to validate the analysis findings. Results: Both ROR and IC analyses demonstrated a statistically significant elevation in cholestasis risk among ICI-treated patients compared to those receiving conventional chemotherapy. A heightened risk was observed in the 0-65 age cohort, with no significant gender-specific disparities noted. The TTO analysis revealed a delayed onset of cholestasis in both ICI-treated patients and female subjects compared to their respective counterparts. Gene expression profiling elucidated multiple cholestasis-associated signaling pathways, encompassing biliary inflammation, bile acid metabolic disorders, and impairment of hepatocellular drug metabolism. Conclusion: ICI-treated patients exhibit a higher cholestasis risk compared to conventional chemotherapy. Long-term liver function monitoring is crucial for patient safety. ICI-related cholestasis may result from immune-mediated bile duct injury or metabolic disorders, potentially influenced by baseline liver function. This comprehensive article provides crucial evidence for the risk assessment and management of ICI-related cholestasis, thereby contributing to safe medication use and enhanced patient care in clinical practice.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
cholestasis
data mining
FAERS and VigiBase
ICI
mechanism
Megjelenés:International Journal of Surgery. - 111 : 8 (2025), p. 5105-5121. -
További szerzők:Li, Zhengrui Jiang, Aimin Chen, Jinghong Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Hajdu András (1973-) (matematikus, informatikus) Wong, Hank Z. H. Cheng, Quan Zhang, Jian Lin, Anqi Luo, Peng
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9.

001-es BibID:BIBFORM104630
035-os BibID:(WOS)000887058400001 (Scopus)85142514473
Első szerző:Zhou, Shujing
Cím:A Novel Immune-Related Gene Prognostic Index (IRGPI) in Pancreatic Adenocarcinoma (PAAD) and Its Implications in the Tumor Microenvironment / Shujing Zhou, Szöllősi Attila Gábor, Xufeng Huang, Yi Che Chang Chien, András Hajdu
Dátum:2022
ISSN:2072-6694
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Cancers. - 14 : 22 (2022), p. 1-25. -
További szerzők:Szöllősi Attila Gábor (1982-) (élettanász) Huang, Xufeng (1997-) (Bioinformatics, Oncology, Dentistry) Chang Chien, Yi-Che (1975-) (pathológus) Hajdu András (1973-) (matematikus, informatikus)
Pályázati támogatás:TKP2021-NKTA-34
Egyéb
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