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Denutrition status prevails over a standard AML risk assessment in older adults 在老年人中,营养不良状况比标准AML风险评估更重要
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-02-06 DOI: 10.1016/j.retram.2025.103500
Laura Simon , Alexis Caulier , Céline Berthon , Thomas Boyer , Véronique Harrivel , Magalie Joris , Isabelle Leduc , Nicolas Duployez , Claude Preudhomme , Jean-Pierre Marolleau , Delphine Lebon
Older adults with acute myeloid leukemia (AML) have a poor prognosis because frailty and the characteristics of the disease limit the use of intensive chemotherapy (ICT). Treatment with 5-azacitidine (5-AZA) or low-dose cytarabine (Cytarabine) (LDAC) – with or without venetoclax – is currently recommended in this setting. However, we lack real-life data on response rates and treatment outcomes.
We conducted a retrospective, multicenter registry study of 279 older adults with AML (median [interquartile range (IQR)] age: 76 [70–81]) having undergone first-line treatment with LDAC (n = 87) or 5-AZA (n = 192) between 2009 and 2019 (i.e. mainly before the venetoclax era) in a university medical center in France. The complete remission rate was 27.3 % overall. After a median follow-up period of 6.9 months, the median [IQR] overall survival (OS) time was shorter in the LDAC group (4.8 months [2.13–14.41]) than in the 5-AZA group (8.9 months [3.2–13.5]; p = 0.046). Ultimately, however, the OS rates were similar in the LDAC and 5-AZA groups (hazard ratio [HR]: 95 % confidence interval [CI]: 1.37 [0.92–2.04], p = 0.12).
None of the conventional markers with prognostic value in younger patients receiving ICT (such as those in the European LeukemiaNet classification) appeared to predict the outcome in our population of older patients. Albumin <30 g/L was the only factor that predicted day-30 mortality and OS (adjusted odds ratio [95 %CI]: 6.25 [2.08 – 20.0]; p < 0.001; adjusted HR [95 %CI]: 0.65 [0.44–0.96]; p = 0.030).
老年人急性髓性白血病(AML)预后较差,因为虚弱和疾病的特点限制了强化化疗(ICT)的使用。在这种情况下,目前推荐使用5-阿扎胞苷(5-AZA)或低剂量阿糖胞苷(阿糖胞苷)(LDAC)联合或不联合venetoclax治疗。然而,我们缺乏关于反应率和治疗结果的真实数据。我们对2009年至2019年(即主要在venetoclax时代之前)在法国一所大学医学中心接受LDAC (n = 87)或5-AZA (n = 192)一线治疗的279名老年AML患者(中位[四分位数范围(IQR)]年龄:76[70-81])进行了一项回顾性、多中心注册研究。总体完全缓解率为27.3%。中位随访期为6.9个月后,LDAC组的中位总生存期(IQR)(4.8个月[2.13-14.41])短于5-AZA组(8.9个月[3.2-13.5]);P = 0.046)。然而,最终,LDAC组和5-AZA组的OS率相似(风险比[HR]: 95%可信区间[CI]: 1.37 [0.92-2.04], p = 0.12)。在接受ICT治疗的年轻患者中,没有一种具有预后价值的传统标志物(如欧洲白血病网分类)能够预测老年患者的预后。白蛋白30 g/L是预测第30天死亡率和总生存率的唯一因素(校正比值比[95% CI]: 6.25 [2.08 - 20.0];p & lt;0.001;校正后HR [95% CI]: 0.65 [0.44-0.96];P = 0.030)。
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引用次数: 0
AI-assisted computational screening and docking simulation prioritize marine natural products for small-molecule PCSK9 inhibition 人工智能辅助的计算筛选和对接模拟优先考虑小分子PCSK9抑制的海洋天然产物
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-02-04 DOI: 10.1016/j.retram.2025.103498
Neelakandan Annamalai Ramalakshmi , Muthu Kumar Thirunavukkarasu , Fayaz Shaik , Krishna Navami , Rajanikant Golgodu Krishnamurthy
SARS-CoV-2 infection has been associated with long-term cardiovascular complications including myocarditis and heart failure, as well as central nervous system sequelae such as cognitive dysfunction and neuropathy. Proprotein convertase subtilisin/Kexin type 9 (PCSK9), a hepatic protease involved in cholesterol regulation, has shown associations with a spectrum of diseases potentially relevant to these Covid-19 complications, such as atherosclerosis. To identify novel human PCSK9 inhibitors, a custom virtual screening pipeline was developed employing (1) a convolutional neural network-based deep learning model, (2) molecular docking using Schrödinger with Glide scoring function, and (3) molecular dynamics (MD) simulations with Gibbs Free Energy Landscape analysis. The deep learning model was trained on a dataset of known central nervous system, cardiovascular, and anti-inflammatory acting drugs and used to screen the CMNPD database. Docking simulations were performed on shortlisted candidates, followed by MD simulations and free energy landscape analysis to evaluate binding affinities and identify key interaction residues. This multi-step in-silico approach identified promising PCSK9 inhibitor candidates with favorable binding profiles, suggesting that AI-assisted virtual screening can be a powerful tool for discovering novel therapeutic agents.
SARS-CoV-2感染与心肌炎和心力衰竭等长期心血管并发症以及认知功能障碍和神经病变等中枢神经系统后遗症有关。蛋白转化酶枯草杆菌素/可溶蛋白9型(PCSK9)是一种参与胆固醇调节的肝脏蛋白酶,已显示出与一系列可能与这些Covid-19并发症相关的疾病(如动脉粥样硬化)的关联。为了鉴定新的人类PCSK9抑制剂,开发了一个定制的虚拟筛选管道,使用(1)基于卷积神经网络的深度学习模型,(2)使用Schrödinger与Glide评分函数进行分子对接,以及(3)使用Gibbs自由能景观分析进行分子动力学(MD)模拟。深度学习模型在已知中枢神经系统、心血管和抗炎作用药物的数据集上进行训练,并用于筛选CMNPD数据库。对入围候选分子进行对接模拟,然后进行MD模拟和自由能景观分析,以评估结合亲和性并确定关键相互作用残基。这种多步骤的计算机方法确定了具有良好结合谱的有前途的PCSK9抑制剂候选物,这表明人工智能辅助的虚拟筛选可以成为发现新型治疗药物的有力工具。
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引用次数: 0
Post-transplant cyclophosphamide in matched donor transplantation: are we there yet? 移植后环磷酰胺在匹配供体移植中的应用:我们做到了吗?
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-02-03 DOI: 10.1016/j.retram.2025.103499
Lorenzo Lazzari , Gloria Catalano , Alessandro Bruno , Daniele Sannipoli , Maria Teresa Lupo-Stanghellini , Jacopo Peccatori , Fabio Ciceri , Raffaella Greco
Graft-versus-host disease (GvHD) is a frequent cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (alloHCT) and optimal approaches for its prevention have been recently updated. Post-transplant cyclophosphamide (PTCy) has demonstrated impressive results in the setting of haploidentical donor transplantation, allowing for a more widespread application of alloHCT. For this reason, over the years, several groups have implemented the use of PTCy in the context of transplantation from HLA-matched related and unrelated donors, as a replacement for standard GvHD prophylaxis based on calcineurin inhibitors and methotrexate. With increasing results from retrospective studies and new insights from prospective clinical trials, this comprehensive reevaluation of the literature aims to clarify the precise role of PTCy in this context. This review will summarize and critically discuss the overall results of the use of PTCy in alloHCT from HLA-matched donors, unmet needs, and future perspectives.
移植物抗宿主病(GvHD)是异基因造血干细胞移植(allogenic hematopoietic stem cell transplantation, alloHCT)后发病和死亡的常见原因,其预防的最佳方法最近得到了更新。移植后环磷酰胺(PTCy)在单倍体供体移植中显示出令人印象深刻的结果,允许更广泛地应用同种异体造血干细胞移植。出于这个原因,多年来,一些研究小组已经在hla匹配的相关和非相关供体移植中实施了PTCy的使用,作为基于钙调磷酸酶抑制剂和甲氨蝶呤的标准GvHD预防的替代。随着越来越多的回顾性研究结果和前瞻性临床试验的新见解,本文对文献进行了全面的重新评估,旨在阐明PTCy在这种情况下的确切作用。这篇综述将总结和批判性地讨论PTCy在hla匹配供者的同种异体hct中使用的总体结果、未满足的需求和未来的前景。
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引用次数: 0
Trends in drug repurposing: Advancing cardiovascular disease management in geriatric populations 药物再利用趋势:推进老年人群心血管疾病管理。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-17 DOI: 10.1016/j.retram.2025.103496
Murali Krishna Moka , Melvin George , Deepalaxmi Rathakrishnan , V Jagadeeshwaran , Sriram D K
Drug repurposing is a promising strategy for managing cardiovascular disease (CVD) in geriatric populations, offering efficient and cost-effective solutions. CVDs are prevalent across all age groups, with a significant increase in prevalence among geriatric populations. The middle-age period (40–65 years) is critical due to factors like obesity, sedentary lifestyle, and psychosocial stress. In individuals aged 65 and older, the incidence of CVDs is highest due to age-related physiological changes and prolonged exposure to risk factors. In this review we find that certain drugs, such as non-cardiovascular drugs like anakinra, probenecid, N-acetyl cysteine, quercetin, resveratrol, rapamycin, colchicine, bisphosphonates, hydroxychloroquine, SGLT-2i drugs, GLP-1Ras drugs and sildenafil are recommended for drug repurposing to achieve cardiovascular benefits in geriatric patients. However, agents such as canakinumab, methotrexate, ivermectin, erythromycin, capecitabine, carglumic acid, chloroquine, and furosemide are constrained in their therapeutic use and warrant meticulous consideration, rendering them less favorable for this specific application. This review emphasizes the importance of exploring alternative therapeutic strategies to improve outcomes in geriatric populations and suggests drug repurposing as a promising avenue to enhance treatment efficacy.
药物再利用是管理老年人群心血管疾病(CVD)的一种很有前途的策略,提供了高效和具有成本效益的解决方案。心血管疾病在所有年龄组中普遍存在,其中老年人群的患病率显著增加。由于肥胖、久坐不动的生活方式和社会心理压力等因素,中年时期(40-65岁)是关键时期。在65岁及以上的个体中,由于与年龄相关的生理变化和长期暴露于危险因素,心血管疾病的发病率最高。在这篇综述中,我们发现某些药物,如阿那白、probenecid、n-乙酰半胱氨酸、槲皮素、白藜芦醇、雷帕霉素、秋水仙碱、双膦酸盐、羟氯喹、SGLT-2i药物、GLP-1Ras药物和西地那非等非心血管药物被推荐用于药物再利用,以实现老年患者心血管的益处。然而,canakinumab、甲氨蝶呤、伊维菌素、红霉素、卡培他滨、甘油三酸、氯喹和呋塞米等药物在治疗用途上受到限制,需要仔细考虑,使它们不太适合这种特殊应用。这篇综述强调了探索替代治疗策略以改善老年人群预后的重要性,并建议药物再利用是提高治疗效果的有希望的途径。
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引用次数: 0
Identifying potential prognosis markers in relapsed multiple myeloma via integrated bioinformatics analysis and biological experiments 通过综合生物信息学分析和生物学实验确定复发性多发性骨髓瘤的潜在预后标志物。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-12 DOI: 10.1016/j.retram.2025.103495
Yong Xu , Xinya Cao , He Zhou , Han Xu , Bing Chen , Hua Bai

Background

Almost all multiple myeloma (MM) patients will eventually develop disease that has relapsed with or become refractory to current therapeutic regimes. However, the pervious clinical parameters have been proved inaccurate for defining MM relapse, and molecular targets have become the focuses of interests. Prognostic predictions based on molecular targets have been more effective to this day. Our research was performed to demonstrate hub genes involving relapsed MM by bioinformatics and biological experiments.

Methods and results

The integrated bioinformatics analysis in baseline and relapsed MM patients were executed. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were utilized to analyze biologic functions of up-regulated differentially expressed genes (DEGs). Four hub genes (CENPE, ASPM, TOP2A and FANCI) were adopted for construction of relapsed gene score model (RGS), and RGS model was evaluated in two testing sets. The CENPE inhibitor GSK923295 had anti-myeloma effect, including promoting cell death, cell cycle arrest and DNA damage of MM cell lines.

Conclusion

Through bioinformatics analysis, we found that the four hub genes (CENPE, ASPM, TOP2A and FANCI) were associated to cell cycle, nuclear division, mitosis and spindle. Our research provided proof-of-concept that RGS model could be utilized to estimate recurrence risk and prognosis for patients, and targeting CENPE contributed to developing novel therapeutic pattern for MM.
背景:几乎所有多发性骨髓瘤(MM)患者最终都会发展为复发或对当前治疗方案难以治愈的疾病。然而,以往的临床参数已被证明是不准确的定义MM复发,分子靶点已成为关注的焦点。迄今为止,基于分子靶点的预后预测更为有效。我们的研究是通过生物信息学和生物学实验来证明与复发性MM有关的枢纽基因。方法和结果:对基线和复发MM患者进行综合生物信息学分析。利用基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)通路分析,分析上调的差异表达基因(DEGs)的生物学功能。采用4个中心基因(CENPE、ASPM、TOP2A和FANCI)构建复发基因评分模型(RGS), RGS模型分为2个测试集进行评估。CENPE抑制剂GSK923295具有抗骨髓瘤作用,包括促进MM细胞系细胞死亡、细胞周期阻滞和DNA损伤。结论:通过生物信息学分析,我们发现四个中心基因(CENPE、ASPM、TOP2A和FANCI)与细胞周期、核分裂、有丝分裂和纺锤体相关。我们的研究提供了RGS模型可用于评估患者复发风险和预后的概念证明,并且针对CENPE有助于开发新的MM治疗模式。
{"title":"Identifying potential prognosis markers in relapsed multiple myeloma via integrated bioinformatics analysis and biological experiments","authors":"Yong Xu ,&nbsp;Xinya Cao ,&nbsp;He Zhou ,&nbsp;Han Xu ,&nbsp;Bing Chen ,&nbsp;Hua Bai","doi":"10.1016/j.retram.2025.103495","DOIUrl":"10.1016/j.retram.2025.103495","url":null,"abstract":"<div><h3>Background</h3><div>Almost all multiple myeloma (MM) patients will eventually develop disease that has relapsed with or become refractory to current therapeutic regimes. However, the pervious clinical parameters have been proved inaccurate for defining MM relapse, and molecular targets have become the focuses of interests. Prognostic predictions based on molecular targets have been more effective to this day. Our research was performed to demonstrate hub genes involving relapsed MM by bioinformatics and biological experiments.</div></div><div><h3>Methods and results</h3><div>The integrated bioinformatics analysis in baseline and relapsed MM patients were executed. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were utilized to analyze biologic functions of up-regulated differentially expressed genes (DEGs). Four hub genes (CENPE, ASPM, TOP2A and FANCI) were adopted for construction of relapsed gene score model (RGS), and RGS model was evaluated in two testing sets. The CENPE inhibitor GSK923295 had anti-myeloma effect, including promoting cell death, cell cycle arrest and DNA damage of MM cell lines.</div></div><div><h3>Conclusion</h3><div>Through bioinformatics analysis, we found that the four hub genes (CENPE, ASPM, TOP2A and FANCI) were associated to cell cycle, nuclear division, mitosis and spindle. Our research provided proof-of-concept that RGS model could be utilized to estimate recurrence risk and prognosis for patients, and targeting CENPE contributed to developing novel therapeutic pattern for MM.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103495"},"PeriodicalIF":3.2,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Advances in the relationship of immune checkpoint inhibitors and DNA damage repair 免疫检查点抑制剂与DNA损伤修复关系的研究进展。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-11 DOI: 10.1016/j.retram.2025.103494
Xiaolin Liu , Shan Wang , Hongwei Lv , Enli Chen , Li Yan , Jing Yu
Cancer immunotherapy, alongside surgery, radiation therapy, and chemotherapy, has emerged as a key treatment modality. Immune checkpoint inhibitors (ICIs) represent a promising immunotherapy that plays a critical role in the management of various solid tumors. However, the limited efficacy of ICI monotherapy and the development of primary or secondary resistance to combination therapy remain a challenge. Consequently, identifying molecular markers for predicting ICI efficacy has become an area of active clinical research. Notably, the correlation between DNA damage repair (DDR) mechanisms and the effectiveness of ICI treatment has been established. This review outlines the two primary pathways of DDR, namely, the homologous recombination repair pathway and the mismatch repair pathway. The relationship between these key genes and ICIs has been discussed and the potential of these genes as molecular markers for predicting ICI efficacy summarized.
癌症免疫治疗,与手术、放射治疗和化疗一样,已经成为一种关键的治疗方式。免疫检查点抑制剂(ICIs)是一种很有前途的免疫疗法,在各种实体瘤的治疗中起着关键作用。然而,ICI单药治疗的有限疗效以及对联合治疗的原发性或继发性耐药性的发展仍然是一个挑战。因此,鉴别预测ICI疗效的分子标记已成为一个活跃的临床研究领域。值得注意的是,已经建立了DNA损伤修复(DDR)机制与ICI治疗有效性之间的相关性。本文综述了DDR的两条主要途径,即同源重组修复途径和错配修复途径。本文讨论了这些关键基因与ICI之间的关系,并对这些基因作为预测ICI疗效的分子标记的潜力进行了总结。
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引用次数: 0
The impact of artificial intelligence and machine learning in organ retrieval and transplantation: A comprehensive review 人工智能和机器学习在器官检索和移植中的影响:综述。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-06 DOI: 10.1016/j.retram.2025.103493
David B. Olawade , Sheila Marinze , Nabeel Qureshi , Kusal Weerasinghe , Jennifer Teke
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks. Predictive analytics further enable personalized treatment plans by forecasting organ rejection, infection risks, and patient recovery trajectories, thereby supporting early intervention strategies and long-term patient management. AI also optimizes operational efficiency within transplant centers by predicting organ demand, scheduling surgeries efficiently, and managing inventory to minimize wastage, thus streamlining workflows and enhancing resource allocation. Despite these advancements, several challenges hinder the widespread adoption of AI and ML in organ transplantation. These include data privacy concerns, regulatory compliance issues, interoperability across healthcare systems, and the need for rigorous clinical validation of AI models. Addressing these challenges is essential to ensuring the reliable, safe, and ethical use of AI in clinical settings. Future directions for AI and ML in transplantation medicine include integrating genomic data for precision immunosuppression, advancing robotic surgery for minimally invasive procedures, and developing AI-driven remote monitoring systems for continuous post-transplantation care. Collaborative efforts among clinicians, researchers, and policymakers are crucial to harnessing the full potential of AI and ML, ultimately transforming transplantation medicine and improving patient outcomes while enhancing healthcare delivery efficiency.
本文回顾了人工智能(AI)和机器学习(ML)在器官检索和移植中的变革作用。人工智能和机器学习技术通过整合和分析包括临床、遗传和人口统计信息在内的复杂数据集来增强供体-受体匹配,从而实现更精确的器官分配和更高的移植成功率。在手术计划中,人工智能驱动的图像分析可以自动分割器官,识别关键解剖特征,预测手术结果,帮助术前计划和降低术中风险。预测分析通过预测器官排斥、感染风险和患者康复轨迹,进一步实现个性化治疗计划,从而支持早期干预策略和长期患者管理。人工智能还通过预测器官需求、有效安排手术、管理库存以最大限度地减少浪费,从而简化工作流程和加强资源分配,从而优化移植中心的操作效率。尽管取得了这些进步,但仍有一些挑战阻碍了人工智能和机器学习在器官移植中的广泛应用。这些问题包括数据隐私问题、法规遵从性问题、医疗保健系统之间的互操作性,以及对人工智能模型进行严格临床验证的需求。应对这些挑战对于确保在临床环境中可靠、安全和合乎道德地使用人工智能至关重要。人工智能和机器学习在移植医学中的未来发展方向包括整合精确免疫抑制的基因组数据,推进微创手术的机器人手术,以及开发人工智能驱动的远程监测系统,用于持续的移植后护理。临床医生、研究人员和政策制定者之间的协作努力对于充分利用人工智能和机器学习的潜力,最终改变移植医学,改善患者预后,同时提高医疗保健服务效率至关重要。
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引用次数: 0
Construction of a stromal-related prognostic model in acute myeloid leukemia by comprehensive bioinformatics analysis 基于综合生物信息学分析的急性髓系白血病基质相关预后模型的构建。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-05 DOI: 10.1016/j.retram.2025.103492
Laya Khodayi Hajipirloo , Maryam Nabigol , Reza Khayami , Najibe Karami , Mehdi Allahbakhshian Farsani , Amir Abbas Navidinia

Background

Stromal cells play a pivotal role in the tumor microenvironment (TME), significantly impacting the progression of acute myeloid leukemia (AML). This study sought to develop a stromal-related prognostic model for AML, aiming to uncover novel prognostic markers and therapeutic targets.

Methods

RNA expression data and clinical profiles of AML patients were retrieved from the Cancer Genome Atlas (TCGA). The extent of stromal cell infiltration within the TME was quantified using the ESTIMATE algorithm. Associations between stromal scores and the French-American-British (FAB) classification, overall survival (OS), and the Cancer and Leukemia Group B (CALGB) cytogenetic risk categories were analyzed. Differentially expressed genes (DEGs) were identified, and gene ontology (GO) and protein-protein interaction (PPI) networks were constructed. Prognostic DEGs were selected through LASSO-cox regression analysis. A risk score model was then developed based on these DEGs. A stromal-related prognostic model (SPM) was constructed from the patients' risk scores (RS), and its efficacy was evaluated using Receiver Operating Characteristic (ROC) curves and a nomogram. The association between FAB, CALGB, age, and common mutations and SPM was also assessed. Ultimately, the SPM was validated using an external dataset from 246 patients in the TARGET-AML study.

Results

Kaplan-Meier analysis revealed a significant association between stromal scores and patient survival (p = 0.04). LASSOCox regression identified four genes (MAP7D2, CDRT1, HOXB9, and IRX5) as highly predictive of survival. The prognostic model showed a strong correlation with overall survival, with higher scores indicating poorer outcomes (p = 1.48e-07). Older patients (over 60 years) faced significantly worse prognoses (p = 0.0055). Although no significant association was found between the SPM and the FAB classification (p = 0.063), both poor and intermediate/normal cytogenetic groups had significantly higher SPM risk scores than the favorable group (p = 0.0057 and 0.0026). External validation of the SPM in the TARGET-AML dataset confirmed a significant association with survival (p = 0.00035), with the area under the curve (AUC) for 10-year survival at 75.81 %.

Conclusion

Our research successfully established a stromal-related prognostic model in AML, offering new perspectives for prognostic evaluation and identifying potential targets for therapeutic intervention.
背景:基质细胞在肿瘤微环境(tumor microenvironment, TME)中起关键作用,显著影响急性髓系白血病(acute myeloid leukemia, AML)的进展。本研究旨在建立AML的基质相关预后模型,旨在发现新的预后标志物和治疗靶点。方法:从癌症基因组图谱(TCGA)中检索AML患者的RNA表达数据和临床资料。使用ESTIMATE算法量化TME内基质细胞的浸润程度。分析基质评分与法、美、英(FAB)分级、总生存期(OS)以及癌症和白血病B组(CALGB)细胞遗传学风险分类之间的关系。鉴定差异表达基因(DEGs),构建基因本体(GO)和蛋白-蛋白相互作用(PPI)网络。通过LASSO-cox回归分析选择预后deg。然后基于这些deg建立风险评分模型。根据患者的风险评分(RS)构建基质相关预后模型(SPM),并采用受试者工作特征(ROC)曲线和nomogram评估其疗效。还评估了FAB、CALGB、年龄和常见突变与SPM之间的关系。最终,使用TARGET-AML研究中246名患者的外部数据集验证了SPM。结果:Kaplan-Meier分析显示基质评分与患者生存率有显著相关性(p = 0.04)。LASSOCox回归鉴定出4个基因(MAP7D2、CDRT1、HOXB9和IRX5)高度预测生存率。预后模型显示与总生存率有很强的相关性,评分越高表明预后越差(p = 1.48e-07)。老年患者(60岁以上)的预后明显较差(p = 0.0055)。虽然SPM与FAB分级之间没有显著相关性(p = 0.063),但细胞遗传学差组和中等/正常细胞遗传学组的SPM风险评分均显著高于良好组(p = 0.0057和0.0026)。在TARGET-AML数据集中对SPM进行的外部验证证实了SPM与生存率的显著关联(p = 0.00035), 10年生存率的曲线下面积(AUC)为75.81%。结论:我们的研究成功建立了AML的基质相关预后模型,为预后评估和确定治疗干预的潜在靶点提供了新的视角。
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引用次数: 0
Caspases in PANoptosis PANoptosis中的半胱天冬酶
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-01 DOI: 10.1016/j.retram.2025.103502
Kaiyuan Song , Yongbin Wu , Sipin Tan
Recent studies prove that the three well-established cell death pathways—pyroptosis, apoptosis, and necroptosis—are not isolated but rather engage in extensive crosstalk. PANoptosis, a newly identified pathway of inflammatory regulated cell death (RCD), integrates characteristics of apoptosis, pyroptosis, and necroptosis. Caspases are a family of conserved cysteine proteases that play critical roles in pyroptosis, apoptosis, and necroptosis. Similarly, caspases also play a role in PANoptosis. In this paper, we review the molecular mechanisms of these three RCDs and the crosstalk between them. We also delineate the discovery of PANoptosis and its association with disease. Furthermore, we discuss the caspase function in PANoptosis, mainly focusing on caspase-6 and caspase-8 molecules. This review describes the key molecules, especially caspases, in the context of PANoptosis research, aiming to provide a foundation for targeted interventions in PANoptosis-associated diseases.
最近的研究证明,三种公认的细胞死亡途径——焦亡、凋亡和坏死并不是孤立的,而是相互联系的。PANoptosis是一种新发现的炎症调节细胞死亡(RCD)途径,融合了细胞凋亡、焦亡和坏死的特征。半胱天蛋白酶是一个保守的半胱氨酸蛋白酶家族,在焦亡、凋亡和坏死坏死中起关键作用。同样,caspases也在PANoptosis中发挥作用。本文综述了这三种rcd的分子机制以及它们之间的串扰。我们还描述了PANoptosis的发现及其与疾病的关系。此外,我们讨论了caspase在PANoptosis中的功能,主要集中在caspase-6和caspase-8分子上。本文综述了PANoptosis研究中的关键分子,特别是半胱天冬酶,旨在为PANoptosis相关疾病的靶向干预提供基础。
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引用次数: 0
Non-hematological triggers of VEXAS syndrome: A case report and literature review VEXAS综合征的非血液学诱因:1例报告及文献复习。
IF 3.2 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2025-01-01 DOI: 10.1016/j.retram.2024.103487
Thibaud Loupret, Laurie De Coster, Camille Lemaçon, Emma Gadon, Philippe Bertin, Pascale Vergne-Salle
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Current Research in Translational Medicine
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