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Single-cell landscape of malignant ascites from patients with metastatic colorectal cancer 转移性结直肠癌患者恶性腹水的单细胞图谱。
IF 20.1 1区 医学 Q1 ONCOLOGY Pub Date : 2024-03-26 DOI: 10.1002/cac2.12541
Haiyang Zhou, Jiahui Yin, Anqi Wang, Xiaomao Yin, Taojun Jin, Kai Xu, Lin Zhu, Jiexuan Wang, Wenqiang Wang, Wei Zhang, Xinxiang Li, Zhiqian Hu, Xinxing Li

The presence of malignant ascites in colorectal cancer (CRC) patients is associated with a poor prognosis, a high risk of recurrence, and resistance to chemotherapy and immune therapy [1-3]. Understanding the complex interactions among different kinds of cells and the ecosystem of peritoneal metastasized colorectal cancer (pmCRC) ascites may provide insights into effective treatment strategies.

We profiled the single-cell transcriptomes of 96,065 cells from ascites samples of 12 treatment-naïve patients with pmCRC using the 10× single-cell RNA-sequencing (scRNA-seq) (Supplementary Figure S1A, Supplementary Table S1). Eleven major cell types were identified by characteristic canonical cell markers, including epithelial cells, endothelial cells, fibroblasts, T cells, B cells, monocytes, macrophages, plasma cells, natural killer (NK) cells, dendritic cells (DCs), and mast cells (Figure 1A-B). The main cellular components of pmCRC ascites are T cells (40,095; 41.7%), macrophages (28,487; 29.7%), and fibroblasts (5,932; 6.2%). Compared with primary CRC, which showed 14.8% epithelial cells [4], only 0.3% (291) epithelial cells were found in the ascites. The low percentage of epithelial cells in pmCRC ascites was consistent with the scRNA-seq studies of another tumor ascites [5-7].

We classified the 12 patients into 2 groups according to their treatment response as follows: 8 patients (P02, P03, P04, P07, P08, P09, P11, and P12) had stable disease (SD), while 4 (P01, P05, P06, and P10) had progressive disease (PD). Single-cell transcriptomic analyses have revealed high heterogeneity of cell composition in 12 patients. The SD group exhibited a higher proportion of fibroblasts and epithelial cells (Figure 1B). Remarkably, fibroblasts had significantly different expression characteristics between the 2 groups (Figure 1C), and the top five upregulated/downregulated genes were visualized in 11 cell types (Figure 1D). We also found a significant increase in the frequency of macrophages in pmCRC ascites compared with the primary tumors [4] (Figure 1E). It hinted that significant inter-patient variability in the composition and functional programs of pmCRC ascites cells under different disease states.

To comprehensively study the cellular interactions within the pmCRC ascites ecosystem, we predicted cell-cell communication networks using CellChat. Overall, we identified 44 significant ligand-receptor pair interactions. Although T cells were the most abundant cell population (41.7%) in pmCRC ascites, fibroblasts and macrophages were the core of the cellular interaction network (Figure 1F), suggesting their important roles in recruiting and cross-talking with diverse cells in the pmCRC ascites ecosystem.

The result of cellular communications suggested that there was a complex interplay between various signaling molecule. Macrophage migration inhibitory factor (MIF), annexin, complement

结直肠癌(CRC)患者出现恶性腹水与预后不良、复发风险高以及对化疗和免疫疗法的耐药性有关 [1-3]。我们利用10×单细胞RNA测序技术(scRNA-seq)分析了12名未经治疗的pmCRC患者腹水样本中96,065个细胞的单细胞转录组(补充图S1A,补充表S1)。通过特征性的典型细胞标记鉴定出11种主要细胞类型,包括上皮细胞、内皮细胞、成纤维细胞、T细胞、B细胞、单核细胞、巨噬细胞、浆细胞、自然杀伤(NK)细胞、树突状细胞(DC)和肥大细胞(图1A-B)。pmCRC 腹水的主要细胞成分是 T 细胞(40,095;41.7%)、巨噬细胞(28,487;29.7%)和成纤维细胞(5,932;6.2%)。原发性 CRC 的上皮细胞比例为 14.8%[4],而腹水中的上皮细胞比例仅为 0.3%(291 个)。pmCRC 腹水中上皮细胞的低比例与另一种肿瘤腹水的 scRNA-seq 研究一致[5-7]:根据治疗反应,我们将 12 名患者分为两组:8 名患者(P02、P03、P04、P07、P08、P09、P11 和 P12)病情稳定(SD),4 名患者(P01、P05、P06 和 P10)病情进展(PD)。单细胞转录组分析显示,12 名患者的细胞组成具有高度异质性。SD 组的成纤维细胞和上皮细胞比例较高(图 1B)。值得注意的是,成纤维细胞的表达特征在两组之间存在显著差异(图 1C),前五大上调/下调基因在 11 种细胞类型中均可视化(图 1D)。我们还发现,与原发肿瘤相比,pmCRC 腹水中巨噬细胞的频率明显增加[4](图 1E)。为了全面研究 pmCRC 腹水生态系统中的细胞相互作用,我们使用 CellChat 预测了细胞-细胞通讯网络。总体而言,我们发现了 44 对重要的配体-受体相互作用。虽然T细胞是pmCRC腹水中数量最多的细胞群(41.7%),但成纤维细胞和巨噬细胞是细胞相互作用网络的核心(图1F),这表明它们在pmCRC腹水生态系统中与不同细胞的招募和交叉对话中发挥着重要作用。巨噬细胞迁移抑制因子(MIF)、附件蛋白、补体和C-C趋化因子配体(CCL)是CRC腹水中最活跃的传出/传入信号分子(补充图S1B)。成纤维细胞通过MIF-(CD74 + C-X-C 趋化因子受体4型 [CXCR4])和MIF-(CD74 + CD44)轴的配体-受体相互作用以及C3-(整合素αX [ITGAX] + 整合素亚基β2 [ITGB2])直接与不同类型的细胞接触(图1G)。值得注意的是,巨噬细胞群更有可能通过粘附配体-受体对 galectin-9 (LGALS9)-CD44 和 LGALS9-CD45 与其他细胞群相互作用,而在其他细胞群中没有观察到这种情况(图 1G)。在癌症基因组图谱(TCGA)的 CRC 队列中,CD74、LGALS9 与转移显著相关。我们还发现 CD44 和 ITGAX 具有生存性(图 1H;CD44 和 ITGAX 在转移性和非转移性患者之间没有明显的表达差异,因此数据未显示)。这些结果表明,pmCRC 腹水的整个细胞相互作用网络有助于建立免疫抑制和转移微环境。我们观察到,在 pmCRC 腹水样本中,SD 患者成纤维细胞的丰度明显高于 PD 患者(图 1B)。根据无监督聚类法,成纤维细胞被划分为 7 个不同的集群(C0-C6)(图 1I)。所有癌症相关成纤维细胞(CAfs)亚簇都显示了细胞外基质癌症相关成纤维细胞(eCAFs)特征的高表达(图 1J),而炎症性 CAF(iCAF)、肌成纤维细胞 CAF(myCAF)、基质 CAF(mCAF)和炎症性 CAF(iCAF)的表达都很高、而炎性CAF(iCAF)、肌成纤维细胞CAF(myCAF)和血管CAF(vCAF)只出现在一小部分成纤维细胞中(补充图S1C),这支持了eCAFs在增强pmCRC转移潜能中的作用。在PD队列(n = 310)中观察到的抗原呈递癌症相关成纤维细胞(apCAFs)的丰度高于SD队列(n = 93)(Wilcoxon检验,P = 0.049)。 这些结果表明,pmCRC 腹水中的 CAFs 与免疫调节功能有双向关联,是治疗 CRC 的有利候选者。差异表达基因和基因本体(GO)分析表明,"细胞-细胞粘附"、"炎症反应 "和 "细胞因子产生 "在原发肿瘤和腹水中的富集程度不同(补充图 S1D),这意味着腹水的液态改变了成纤维细胞群的功能。利用之前定义的 "M1 "和 "M2 "特征,C2 显示出 "类 M1 "模式,C5 显示出 "类 M2 "模式。我们还发现 C5 中有一小部分同时表达 "M1 "和 "M2 "基因特征(图 1L),这在之前的实体瘤研究中已有报道[8]。接下来,我们检测了之前报道的一系列免疫抑制基因(白细胞相关免疫球蛋白样受体 1 [LAIR1]、甲型肝炎病毒细胞受体 2 [HAVCR2;又称 T 细胞免疫球蛋白和含粘蛋白结构域蛋白 3]、LGALS9 和 V 集免疫调节受体 [VSIR])在巨噬细胞亚簇中的表达情况。由于 "M2 "标记基因 CD163 的表达模式与 LAIR1 在所有亚簇中的表达模式完全一致(图 1M),我们推测肿瘤相关巨噬细胞(TAMs)的免疫抑制功能可能是通过 LAIR1 发挥的。另外两个免疫抑制基因,即具有 Ig 和 ITIM 结构域的 T 细胞免疫受体(TIGIT)和程序性细胞死亡 1(PDCD1),也在 C5 中高表达。C4 高表达关键的免疫抑制表型标志物--髓系细胞上表达的触发受体 2(TREM2)(图 1N)。总之,pmCRC 腹水中的大多数巨噬细胞表现出高度免疫抑制特征。我们根据其各自标记物的表达确定了 11 个 T 细胞亚群,包括 CD4+ T 细胞(C1、C4、C5 和 C6)和 CD8+ T 细胞(C0、C2、C3、C7、C8、C9 和 C10)(图 1O)。大多数重新表达CD45RA T(Temra/Teff)细胞的CD8+效应记忆细胞(C8)来自患者5(P05),而CD8+效应记忆T(Tem)细胞(C7)主要来自患者8(P08);其余10名患者的11个T细胞亚簇表现出高度异质性(补充图S1E-F)。重要的是,CD8+组织驻留记忆(Trm)细胞(C7)据报道与形成三级淋巴结构(TLS)有关[9],但在SD患者(P03、P08、P09、P11和P12)中含量较少。我们还观察到,所有亚簇均表达铁蛋白轻链(FTL)(补充图 S1G),据报道,铁蛋白轻链可调控 CRC 的化疗耐药性和转移[10]。我们计算了所有 CD8+ T 细胞亚簇的细胞毒性、增殖和衰竭特征(图 1P)。只有一个 CD8+ T 细胞亚簇未显示衰竭特征(C10)。簇 9 和簇 10 的增殖率略高,这可能会招募细胞毒性 T 细胞。C9 和 C10 的丰度较低,这表明 T 细胞在腹水的免疫微环境中可能扮演次要角色,并可能与其他细胞群协同作用。此外,我们还预测了以巨噬细胞为靶点的免疫调节药物,从 pmCRC 腹水数据的巨噬细胞中提取了基因集(图 1Q)。总之,我们发现 T 细胞、成纤维细胞和巨噬细胞在 pmCRC 腹水中表现出免疫抑制特征(图 1R)。pmCRC腹水的细胞图谱对患者的免疫状态
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引用次数: 0
Immune cell pair ratio captured by imaging mass cytometry has superior predictive value for prognosis of non-small cell lung cancer than cell fraction and density 成像质控细胞仪捕获的免疫细胞对比率对非小细胞肺癌预后的预测价值优于细胞分数和密度。
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-26 DOI: 10.1002/cac2.12540
Jian-Rong Li, Chao Cheng

Infiltrating immune cells in the tumor microenvironment (TME) play critical roles in the initiation, progression, and metastasis of cancer [1]. Previous studies have reported that the infiltration levels of various immune cell types are significantly associated with patient prognosis in different cancers [2, 3]. Specifically, in non-small cell lung cancer (NSCLC) the prognostic associations of major immune cell types have been investigated [4-6], however, some of the reported associations are inconsistent and remain debated [7]. Limited by technical issues, most studies focused on a few immune cell lineages or relied on inferred immune cell levels from computational deconvolution. To investigate the prognostic effects of all major immune cell types unbiasedly, more systematic high-quality immune cell profiling data with matched patient survival information are needed.

Recently, Sorin et al. [8] used imaging mass cytometry (IMC) to characterize the immunological landscape of 416 distinct lung adenocarcinoma (LUAD) samples at single-cell resolution. The IMC images provide the counts and spatial distribution of 16 cell types with high precision in each sample. These cell types include cancer and endothelial cells, along with 14 immune cell types, including CD163+ and CD163 macrophages, CD8+, CD4+, regulatory, and other T cells, classical, non-classical, and intermediate monocytes, natural killer cells, dendritic cells, mast cells, neutrophils, and other immune cells. Additionally, the data provide patient survival and other clinical information. Using these data, we investigated the prognostic associations of the cell density (#cells/megapixel) and fractions of the 16 cell types as well as the fraction ratio between each pair of cell types (Supplementary Methods). Our results indicated that the relative abundance between cell types (fraction ratios) was more prognostic than cell fractions and densities.

We calculated the densities of the 16 cell types in each patient's IMC image and applied Cox regression analysis to examine their associations with progression-free survival (PFS) after adjusting for established clinical factors including age, sex, smoking status, and tumor stage. At the significance level of P < 0.05, only the density of non-classical monocytes was found to have a significant association with worse prognosis (hazard ratio [HR] = 1.004, P = 0.040, Figure 1A). After multiple testing corrections, none of the cell types was significant (false discovery rate [FDR] > 0.05). Similar results were obtained when cell fractions among all cells were used for prognostic association analysis (Figure 1B). In addition, we conducted prognostic analysis on 14 immune cell types, focusing on their proportions among immune cells (excluding cancer and endothelial cells), yielding similar results. It has b

这些结果凸显了非经典或中间单核细胞与CD4+或CD8+T细胞的比例在LUAD中的关键预后作用,这与之前的研究显示非经典或中间单核细胞抑制CD8+或CD4+T细胞的增殖和免疫反应[9, 10]是一致的。为了进一步巩固我们的结果,我们进行了100次向下取样分析,每次随机选择80%的样本进行预后分析。就细胞密度和细胞分数而言,与 PFS 显著相关的细胞类型数量(FDR &lt;0.05)平均分别只有 0.01 和 0.02(补充图 S4A)。相比之下,我们平均发现了 9.37 对重要的细胞-细胞对。此外,我们从所有图像中随机抽取了 80% 的细胞,并重新计算细胞分数进行预后分析,重复 100 次。平均每次发现 9.74 个重要的细胞对,而使用细胞分数和细胞密度则没有发现明显的关联(补充图 S4B)。总之,我们的研究证实,在 LUAD 中,预后价值与 TME 中特定细胞类型之间的相对丰度关系更密切,而不是 IMC 图像所显示的绝对细胞密度或细胞分数。这一发现强调了TME中不同免疫细胞之间相互作用的预后意义,尤其是免疫抑制细胞和免疫刺激细胞之间的免疫平衡。基于对免疫细胞相互作用的微妙理解,这些见解对开发靶向疗法和对LUAD患者进行分层具有重要意义。李建荣收集数据集。程超和李建荣进行了分析。李建荣绘制图表。程超和李建荣解释结果并撰写手稿。程超指导了该项目。本研究得到了德克萨斯州癌症预防研究所(CPRIT)(RR180061给CC)和美国国立卫生研究院国家癌症研究所(1R01CA269764给CC)的支持。CC 是 CPRIT 癌症研究学者。
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引用次数: 0
Cover Image, Volume 44, Issue 3 封面图片,第 44 卷第 3 期
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-22 DOI: 10.1002/cac2.12537
Bin Song, Ping Yang, Shuyu Zhang

The cover image is based on the Review Article Cell fate regulation governed by p53: Friends or reversible foes in cancer therapy by Bin Song et al., https://doi.org/10.1002/cac2.12520.

封面图片基于宋斌等人撰写的评论文章《p53调控的细胞命运:癌症治疗中的朋友还是可逆的敌人》(Cell fate regulation governed by p53: Friends or reversible foes in cancer therapy),https://doi.org/10.1002/cac2.12520。
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引用次数: 0
N6-methyladenosine reader hnRNPA2B1 recognizes and stabilizes NEAT1 to confer chemoresistance in gastric cancer. N6-甲基腺苷阅读器 hnRNPA2B1 能识别并稳定 NEAT1,从而赋予胃癌化疗抗性。
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-21 DOI: 10.1002/cac2.12534
Jiayao Wang, Jiehao Zhang, Hao Liu, Lingnan Meng, Xianchun Gao, Yihan Zhao, Chen Wang, Xiaoliang Gao, Ahui Fan, Tianyu Cao, Daiming Fan, Xiaodi Zhao, Yuanyuan Lu

Background: Chemoresistance is a major cause of treatment failure in gastric cancer (GC). Heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is an N6-methyladenosine (m6A)-binding protein involved in a variety of cancers. However, whether m6A modification and hnRNPA2B1 play a role in GC chemoresistance is largely unknown. In this study, we aimed to investigate the role of hnRNPA2B1 and the downstream mechanism in GC chemoresistance.

Methods: The expression of hnRNPA2B1 among public datasets were analyzed and validated by quantitative PCR (qPCR), Western blotting, immunofluorescence, and immunohistochemical staining. The biological functions of hnRNPA2B1 in GC chemoresistance were investigated both in vitro and in vivo. RNA sequencing, methylated RNA immunoprecipitation, RNA immunoprecipitation, and RNA stability assay were performed to assess the association between hnRNPA2B1 and the binding RNA. The role of hnRNPA2B1 in maintenance of GC stemness was evaluated by bioinformatic analysis, qPCR, Western blotting, immunofluorescence, and sphere formation assays. The expression patterns of hnRNPA2B1 and downstream regulators in GC specimens from patients who received adjuvant chemotherapy were analyzed by RNAscope and multiplex immunohistochemistry.

Results: Elevated expression of hnRNPA2B1 was found in GC cells and tissues, especially in multidrug-resistant (MDR) GC cell lines. The expression of hnRNPA2B1 was associated with poor outcomes of GC patients, especially in those who received 5-fluorouracil treatment. Silencing hnRNPA2B1 effectively sensitized GC cells to chemotherapy by inhibiting cell proliferation and inducing apoptosis both in vitro and in vivo. Mechanically, hnRNPA2B1 interacted with and stabilized long noncoding RNA NEAT1 in an m6A-dependent manner. Furthermore, hnRNPA2B1 and NEAT1 worked together to enhance the stemness properties of GC cells via Wnt/β-catenin signaling pathway. In clinical specimens from GC patients subjected to chemotherapy, the expression levels of hnRNPA2B1, NEAT1, CD133, and CD44 were markedly elevated in non-responders compared with responders.

Conclusion: Our findings indicated that hnRNPA2B1 interacts with and stabilizes lncRNA NEAT1, which contribute to the maintenance of stemness property via Wnt/β-catenin pathway and exacerbate chemoresistance in GC.

背景:化疗耐药性是胃癌(GC)治疗失败的主要原因:耐药性是胃癌(GC)治疗失败的主要原因。异构核糖核蛋白 A2B1(hnRNPA2B1)是一种 N6-甲基腺苷(m6A)结合蛋白,与多种癌症有关。然而,m6A修饰和hnRNPA2B1是否在GC化疗耐药性中发挥作用,目前尚不清楚。本研究旨在探讨 hnRNPA2B1 在 GC 化疗耐药性中的作用及其下游机制:方法:通过定量 PCR(qPCR)、Western 印迹、免疫荧光和免疫组化染色等方法分析和验证了 hnRNPA2B1 在公开数据集中的表达情况。在体外和体内研究了 hnRNPA2B1 在 GC 化疗耐药性中的生物学功能。通过RNA测序、甲基化RNA免疫沉淀、RNA免疫沉淀和RNA稳定性检测来评估hnRNPA2B1与结合RNA之间的关联。通过生物信息分析、qPCR、Western 印迹、免疫荧光和球形成实验评估了 hnRNPA2B1 在维持 GC 干性中的作用。通过RNAscope和多重免疫组化分析了辅助化疗患者GC标本中hnRNPA2B1和下游调控因子的表达模式:结果:hnRNPA2B1在GC细胞和组织中的表达升高,尤其是在耐多药(MDR)GC细胞系中。hnRNPA2B1的表达与GC患者的不良预后有关,尤其是接受5-氟尿嘧啶治疗的患者。沉默hnRNPA2B1能在体外和体内抑制细胞增殖并诱导细胞凋亡,从而有效地使GC细胞对化疗敏感。在机制上,hnRNPA2B1与长非编码RNA NEAT1相互作用,并以m6A依赖性的方式稳定NEAT1。此外,hnRNPA2B1和NEAT1通过Wnt/β-catenin信号通路共同增强了GC细胞的干性。在接受化疗的GC患者的临床标本中,非应答者与应答者相比,hnRNPA2B1、NEAT1、CD133和CD44的表达水平明显升高:我们的研究结果表明,hnRNPA2B1与lncRNA NEAT1相互作用并使其稳定,从而通过Wnt/β-catenin通路维持干性特性,并加剧GC的化疗耐药性。
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引用次数: 0
Sexual dimorphism in the antitumor immune responses elicited by the combination of fasting and chemotherapy. 禁食和化疗联合疗法引起的抗肿瘤免疫反应的性别双态性。
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-21 DOI: 10.1002/cac2.12535
Andrés Pastor-Fernández, Manuel Montero Gómez de Las Heras, Jose Ignacio Escrig-Larena, Marta Barradas, Cristina Pantoja, Adrian Plaza, Jose Luis Lopez-Aceituno, Esther Durán, Alejo Efeyan, Maria Mittelbrunn, Lola Martinez, Pablo Jose Fernandez-Marcos
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引用次数: 0
Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade 保守的免疫胶原亚型可预测对免疫检查点阻断剂的反应
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-20 DOI: 10.1002/cac2.12538
Jie Mei, Yun Cai, Rui Xu, Qing Li, Jiahui Chu, Zhiwen Luo, Yaying Sun, Yuxin Shi, Junying Xu, Di Li, Shuai Liang, Ying Jiang, Jiayu Liu, Zhiwen Qian, Jiaofeng Zhou, Mengyun Wan, Yunlong Yang, Yichao Zhu, Yan Zhang, Yongmei Yin

Background

Immune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy.

Methods

We analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes.

Results

Our categorization divided tumors into three subtypes: “soft & hot” (low collagen activity and high immune infiltration), “armored & cold” (high collagen activity and low immune infiltration), and “quiescent” (low collagen activity and immune infiltration). Notably, “soft & hot” tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in “armored & cold” tumors, relating with poor prognosis.

Conclusion

This study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.

免疫检查点阻断(ICB)彻底改变了各种癌症的治疗。尽管在了解机制方面取得了重大的临床前进展,但确定临床 ICB 反应的分子基础和预测性生物标志物仍具有挑战性。最近的临床前和临床证据都强调了细胞外基质(ECM)在调节免疫细胞浸润和行为中的关键作用。这项研究旨在创建一种创新的分类器,利用 ECM 的特征来提高 ICB 治疗的效果。
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引用次数: 0
Positive regulation of cell proliferation by the miR-1290-EHHADH axis in hepatocellular carcinoma 肝细胞癌中 miR-1290-EHHADH 轴对细胞增殖的积极调控。
IF 20.1 1区 医学 Q1 ONCOLOGY Pub Date : 2024-03-18 DOI: 10.1002/cac2.12536
Jinkwon Lee, Gyeonghwa Kim, Tae-Su Han, Eunsun Jung, Taesang Son, Kwangho Kim, Kiyoon Kwon, Yuna Roh, Tae Young Ryu, In Hwan Tae, Yunsang Kang, Byungheon Lee, Yu Rim Lee, Soo Young Park, Won Young Tak, Dae-Soo Kim, Mi-Young Son, Keun Hur, Hyun-Soo Cho

Hepatocellular carcinoma (HCC) is the second most common cancer and the third leading cause of cancer-related death worldwide [1]. Recently, HCC incidence and mortality rates have further increased due to changes in the global social environment and dietary habits [2]. HCC is treated by surgical resection or combination chemotherapy, but the overall survival rate of HCC patients has not improved, and the recurrence rate is still high due to strong invasiveness and resistance to chemotherapy [3]. Therefore, it is necessary to understand the pathogenesis of HCC and identify novel diagnostic biomarkers and therapeutic targets for the treatment of HCC. Recently, microRNA-1290 (miR-1290) has been reported to regulate the progression of many types of malignant cancers, such as colorectal cancer [4], lung cancer [5], and HCC [6]. However, research on the therapeutic targets of miR-1290 is still needed. Thus, in this study, we will use HCC patient samples to assess the potential of miR-1290 as both a diagnostic marker and a therapeutic target, and we will demonstrate its oncogenic properties through functional and mechanistic studies. The methods and materials were described in Supplementary Materials andMethods.

To discover HCC development-specific microRNAs (miRNAs), we performed NanoString-based miRNA expression profiling in 5 steatohepatitis cirrhosis (SHC) tissues and 5 early-stage HCC tissues. Eleven miRNAs were discovered to be differentially expressed between SHC and HCC tissues (Figure 1A). Among them, miR-1290 was upregulated in HCC compared to SHC and was selected based on its cell proliferation and differentiation function in cancers [7, 8]. In a subsequent validation step, the miR-1290 was found to be significantly elevated in HCC tissues compared to either SHC (P = 0.043) or normal healthy liver tissues (NT) (P = 0.019) (Figure 1B). In addition, miR-1290 expression was significantly upregulated as the TNM stage increased in an independent cohort of 111 HCC patients (Figure 1C; ANOVA test P = 0.002). To demonstrate the clinical relevance of miR-1290 expression in patients with HCC, we determined the association between miR-1290 expression and various clinicopathological variables in a cohort of 111 HCC patients (Supplementary Table S1). The expression of miR-1290 was associated with factors reflecting disease progression, such as T stage (P < 0.001), M stage (P = 0.011), TNM stage (P = 0.003), and BCLC stage (P < 0.001). Moreover, the 5-year overall survival rate was significantly lower in high miR-1290-expressing HCC patients (log-rank P < 0.001) (Figure 1D). Next, the Univariate Cox proportional hazards analysis (Supplementary Table S2) revealed that T stage (HR 4.60; 95% CI 2.76 to 7.66; P < 0.001), N stage (HR 3.21; 95% CI 1.52 to 6.78; P = 0.002), M stage (H

为了确定miR-1290的直接靶标,我们关注了miR-1290模拟处理后与模拟-NC处理相比下调的基因,并选择了RNA-seq结果中247个下调基因(截断&gt;2-fold)(图1H)。通过比较 miR-1290 的 TargetScan 结果,我们最终选择了烯酰-CoA、氢化酶/3-羟基乙酰 CoA 脱氢酶(EHHADH)[9] 作为 miR-1290 的直接靶标。在使用 EHHADH 3' 非翻译区(UTR)的野生型(wt)和突变型(mut)miR-1290 结合位点进行的荧光素酶检测中,我们观察到与 wt 相比,EHHADH 3' UTR 的突变不会改变荧光素酶的活性(图 1I)。利用癌症基因组图谱(TCGA)门户网站的RNA-seq结果进行预后分析发现,EHHADH在HCC中的低表达表明预后较差(图1J)。此外,通过 siEHHADH 下调 EHHADH 会诱导 HCC 细胞系的细胞生长(图 1K)。因此,我们的研究结果清楚地表明,EHHADH可能是miR-1290在HCC中的直接靶点。GO分析表明,经miR-1290模拟物处理后,JUN激酶活性正向调节这一术语富集(补充图S1A)。此外,用 miR-1290 mimic 或 siEHHADH 处理后的磷酸化阵列清楚地显示,与 mimic-NC 或 siCont(siControl RNA)组相比,c-JUN 的丝氨酸 63 磷酸化增加了(补充图 S1B)。因此,我们认为 miR-1290 诱导细胞生长与通过下调 EHHADH 激活 c-JUN 有关。为了证实磷酸化 c-JUN 的诱导,我们发现 miR-1290 mimic 或 siEHHADH 与 mimic-NC 或 siCont 相比,分别诱导了丝氨酸 63 磷酸化(图 1L)。此外,为了评估miR-1290-EHHADH轴如何激活c-JUN,我们利用miR-1290 mimic或siEHHADH处理后的RNA-seq结果确定了一个下调靶标,最后我们选择了高迁移率组AT-钩1(HMGA1)[10],并在qRT-PCR结果中观察到HMGA1上调(图1M)。此外,利用 HCC TCGA 结果(n = 374)进行的相关性分析表明,EHHADH 与 HMGA1 的表达呈负相关(R2 = -0.56)(图 1N)。为了验证 EHHADH 和 HMGA1 在细胞生长中的关系,我们在 siEHHADH 和 siHMGA1 共处理后进行了恢复分析,发现 siEHHADH 单次处理会诱导 c-JUN 磷酸化的增加,而共处理组会降低 c-JUN 磷酸化(补充图 S2A 和 B)。在三维小球模型和体内异种移植小鼠模型中,我们观察到用 miR-1290 模拟物处理后三维小球和肿瘤的体积增大(图 1O 和 1P,补充图 S3)。此外,在三维球状模型中,miR-1290 嵌体处理显著促进了 c-JUN 的磷酸化(图 1Q)。这项研究证明了 miR-1290 作为预测 HCC 进展和远处转移的生物标记物的潜在作用。我们通过比较肝硬化和HCC组织样本,发现了HCC特异性的miR-1290上调。通过使用几个大型独立 HCC 患者队列进行验证,我们确定与正常肝脏相比,miR-1290 在 HCC 中上调,而且其水平随着 HCC 的进展以 TNM 分期依赖性的方式升高。此外,我们研究的独特优势之一是成功阐明了 miR-1290 表达作为新型 HCC 生物标记物的潜在作用。在 5 年的随访分析中,miR-1290 高表达的患者生存率较低。值得注意的是,HCC中miR-1290的高表达是HCC预后和转移的一个重要指标,其表现优于甲胎蛋白。此外,miR-1290 对 EHHADH 的负调控通过 HMGA1 的上调诱导了 c-JUN 的活化。因此,我们认为miR-1290-EHHADH-c-JUN激活轴在HCC细胞增殖中起着重要作用,而且miR-1290是HCC预后和转移风险的新标志物(补充图S4):构思与设计:Mi-Young Son、Dae-Soo Kim、Keun Hur、Hyun-Soo Cho。方法开发:Jinkwon Lee, Tae-Soo Kim, Keun Hur, Hyun-Soo Cho:Jinkwon Lee、Tae-Su Han、Eunsun Jung、Kwangho Kim、Tae Young Ryu、In Hwan Tae、Yunsang Kang、Taesang Son、Kiyoon Kwon、Yuna Roh。数据分析和解释以及临床数据:Gyeonghwa Kim、Byungheon Lee、Yu Rim Lee、Soo Young Park、Won Young Tak。撰写和审阅手稿Mi-Young Son、Dae-Soo Kim、Keun Hur、Hyun-Soo Cho。研究监督:研究监督:Mi-Young Son、Dae-Soo Kim、Keun Hur、Hyun-Soo Cho。作者声明不存在竞争利益。
{"title":"Positive regulation of cell proliferation by the miR-1290-EHHADH axis in hepatocellular carcinoma","authors":"Jinkwon Lee,&nbsp;Gyeonghwa Kim,&nbsp;Tae-Su Han,&nbsp;Eunsun Jung,&nbsp;Taesang Son,&nbsp;Kwangho Kim,&nbsp;Kiyoon Kwon,&nbsp;Yuna Roh,&nbsp;Tae Young Ryu,&nbsp;In Hwan Tae,&nbsp;Yunsang Kang,&nbsp;Byungheon Lee,&nbsp;Yu Rim Lee,&nbsp;Soo Young Park,&nbsp;Won Young Tak,&nbsp;Dae-Soo Kim,&nbsp;Mi-Young Son,&nbsp;Keun Hur,&nbsp;Hyun-Soo Cho","doi":"10.1002/cac2.12536","DOIUrl":"10.1002/cac2.12536","url":null,"abstract":"<p>Hepatocellular carcinoma (HCC) is the second most common cancer and the third leading cause of cancer-related death worldwide [<span>1</span>]. Recently, HCC incidence and mortality rates have further increased due to changes in the global social environment and dietary habits [<span>2</span>]. HCC is treated by surgical resection or combination chemotherapy, but the overall survival rate of HCC patients has not improved, and the recurrence rate is still high due to strong invasiveness and resistance to chemotherapy [<span>3</span>]. Therefore, it is necessary to understand the pathogenesis of HCC and identify novel diagnostic biomarkers and therapeutic targets for the treatment of HCC. Recently, microRNA-1290 (miR-1290) has been reported to regulate the progression of many types of malignant cancers, such as colorectal cancer [<span>4</span>], lung cancer [<span>5</span>], and HCC [<span>6</span>]. However, research on the therapeutic targets of miR-1290 is still needed. Thus, in this study, we will use HCC patient samples to assess the potential of miR-1290 as both a diagnostic marker and a therapeutic target, and we will demonstrate its oncogenic properties through functional and mechanistic studies. The methods and materials were described in Supplementary Materials andMethods.</p><p>To discover HCC development-specific microRNAs (miRNAs), we performed NanoString-based miRNA expression profiling in 5 steatohepatitis cirrhosis (SHC) tissues and 5 early-stage HCC tissues. Eleven miRNAs were discovered to be differentially expressed between SHC and HCC tissues (Figure 1A). Among them, miR-1290 was upregulated in HCC compared to SHC and was selected based on its cell proliferation and differentiation function in cancers [<span>7, 8</span>]. In a subsequent validation step, the miR-1290 was found to be significantly elevated in HCC tissues compared to either SHC (<i>P</i> = 0.043) or normal healthy liver tissues (NT) (<i>P</i> = 0.019) (Figure 1B). In addition, miR-1290 expression was significantly upregulated as the TNM stage increased in an independent cohort of 111 HCC patients (Figure 1C; ANOVA test <i>P</i> = 0.002). To demonstrate the clinical relevance of miR-1290 expression in patients with HCC, we determined the association between miR-1290 expression and various clinicopathological variables in a cohort of 111 HCC patients (Supplementary Table S1). The expression of miR-1290 was associated with factors reflecting disease progression, such as T stage (<i>P</i> &lt; 0.001), M stage (<i>P</i> = 0.011), TNM stage (<i>P</i> = 0.003), and BCLC stage (<i>P</i> &lt; 0.001). Moreover, the 5-year overall survival rate was significantly lower in high miR-1290-expressing HCC patients (log-rank <i>P</i> &lt; 0.001) (Figure 1D). Next, the Univariate Cox proportional hazards analysis (Supplementary Table S2) revealed that T stage (HR 4.60; 95% CI 2.76 to 7.66; <i>P</i> &lt; 0.001), N stage (HR 3.21; 95% CI 1.52 to 6.78; <i>P</i> = 0.002), M stage (H","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":null,"pages":null},"PeriodicalIF":20.1,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194445/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140157621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Disclosing the true impact of screening endoscopy in colorectal cancer prevention. 揭示内窥镜筛查对大肠癌预防的真正影响。
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-18 DOI: 10.1002/cac2.12531
Thomas Heisser, Carlo Senore, Michael Hoffmeister, Lina Jansen, Hermann Brenner
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引用次数: 0
Deciphering metastatic route-specific signals and their microenvironment interactions in peritoneal metastasis of gastric cancer 解密胃癌腹膜转移的转移途径特异性信号及其微环境相互作用
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-18 DOI: 10.1002/cac2.12533
Ki Tae Kim, Jae Eun Lee, Jae-Ho Cheong, In Cho, Yoon Young Choi

Gastric cancer (GC) is a pervasive global malignancy with high mortality rates due to distant metastasis [1]. GC metastasis can occur via hematogenous route, peritoneal route, and specifically through ovarian spread in females [2]. Among these, peritoneal metastasis is the most prevalent and challenging condition to treat [3]. The Cancer Genome Atlas (TCGA) has uncovered four molecular subtypes of GC: microsatellite instability, Epstein-Barr virus-related, chromosomal instability, and genomically stable [4]. These subtypes exhibit unique features and metastatic behaviors [5], providing valuable insights into the molecular characteristics of GC. Nevertheless, there remains a gap in understanding gene expression feature in metastatic GC compared to corresponding primary tumors, particularly regarding its biological and clinical relevance in different metastatic patterns.

A whole-transcriptome sequencing analysis was conducted to investigate the characteristics of metastatic GC. We examined 66 paired primary and metastatic tumors, categorized according to their sites (38 primary, 9 hematogenous, 6 peritoneal, and 13 ovarian metastases), collected from 14 patients with GC metastasis (Supplementary Tables S1-S2 and Supplementary Figure S1). To corroborate the biological and clinical relevance of the identified metastatic GC-specific signals, we utilized publicly available databases containing expression data on primary GC, including TCGA (n = 415) [4], Asian Cancer Research Group (ACRG, n = 300) [6], and Yonsei Cancer Center (YCC, n = 433) cohorts [7]. For in-depth analysis at the single-cell resolution, we accessed a public dataset comprising 5 primary GC samples [8] and performed a single-cell RNA sequencing (scRNA-seq) analysis on ascites obtained from 4 patients with GC (Supplementary Tables S3-S4). The flow of analysis is summarized in Supplementary Figure S2. Details of the patient demographics, samples, and data analysis methods used are outlined in the Supplementary Methods.

Through a differential expression analysis of the 66 paired primary and metastatic tumors, we identified 949 genes uniquely associated with metastatic GC tumors (Supplementary Figure S3). Subsequent over-representation analysis of these metastatic GC-specific genes indicated that hematogenous metastatic tumors exhibited an up-regulation of receptor tyrosine kinase-related signals, while simultaneously showing a down-regulation of pathways associated with epithelial-mesenchymal transition (EMT) (Supplementary Figure S4). Conversely, peritoneal/ovarian metastatic tumors demonstrated an upregulation of the Hedgehog pathway, a key player in EMT signaling. These findings suggest that the mechanisms underlying GC metastasis vary by route [5], thus underscoring the need for route-specific clinical considerations.

胃癌(GC)是一种普遍存在的全球性恶性肿瘤,其远处转移导致的死亡率很高[1]。胃癌转移可通过血源性途径、腹膜途径,特别是通过女性卵巢转移[2]。其中,腹膜转移最为常见,治疗起来也最具挑战性[3]。癌症基因组图谱(TCGA)发现了 GC 的四种分子亚型:微卫星不稳定型、Epstein-Barr 病毒相关型、染色体不稳定型和基因组稳定型 [4]。这些亚型表现出独特的特征和转移行为[5],为了解 GC 的分子特征提供了宝贵的信息。然而,与相应的原发肿瘤相比,人们对转移性 GC 基因表达特征的了解仍然存在差距,尤其是在不同转移模式下的生物学和临床相关性方面。我们研究了从 14 例 GC 转移患者中收集的 66 例配对原发和转移肿瘤,并根据其部位进行了分类(38 例原发、9 例血行转移、6 例腹膜转移和 13 例卵巢转移)(补充表 S1-S2 和补充图 S1)。为了证实所发现的转移性 GC 特异性信号的生物学和临床相关性,我们利用了包含原发性 GC 表达数据的公开数据库,包括 TCGA(n = 415)[4]、亚洲癌症研究组(ACRG,n = 300)[6]和延世癌症中心(YCC,n = 433)队列[7]。为了在单细胞分辨率上进行深入分析,我们访问了由 5 个原发性 GC 样本组成的公开数据集[8],并对 4 名 GC 患者的腹水进行了单细胞 RNA 测序(scRNA-seq)分析(补充表 S3-S4)。分析流程见补充图 S2。通过对 66 个配对的原发性和转移性肿瘤进行差异表达分析,我们确定了 949 个与转移性 GC 肿瘤独特相关的基因(补充图 S3)。随后对这些转移性 GC 特异性基因的过度表达分析表明,血源性转移性肿瘤表现出受体酪氨酸激酶相关信号的上调,同时表现出上皮-间质转化(EMT)相关通路的下调(补充图 S4)。相反,腹膜/卵巢转移性肿瘤则表现出刺猬(Hedgehog)通路的上调,而刺猬通路是 EMT 信号转导的关键参与者。这些研究结果表明,GC 转移的机制因途径而异[5],因此强调了临床上需要考虑特定途径。非负因式分解(NMF)算法根据GC特异性基因的表达将TCGA队列分为两个亚型,分别称为NMF-G1和NMF-G2。NMF-G2 亚型的特点是 GC 特异性基因表达上调,与基因组稳定亚型相关。该亚型经常出现粘连蛋白 1(CDH1)的体细胞突变,而且无论哪种分子亚型,其预后都较差(补充图 S5)。通过加权基因共表达网络分析,我们发现了一个由 122 个基因组成的模块,这些基因在 NMF-G1 和 NMF-G2 之间具有不同的表达模式。值得注意的是,这些基因表现出 EMT 相关信号的上调,因此被称为转移特异性 EMT(msEMT)基因(附图 S6)。这些 msEMT 基因是独特的,因为它们不同于 GC 生物学中的既定基因集和共识癌症驱动基因 [6,9]。此外,大多数 msEMT 基因在血行转移中表现出下调。为了验证msEMT基因在GC中的临床意义,我们分析了ACRG[6]和YCC[7]两个独立的原发性GC队列中这些基因的表达水平,这两个队列都有复发数据。通过对 msEMT 基因表达谱的评估,我们将每个队列分为两个不同的亚型,其中高表达组被指定为 msEMT 亚型。重要的是,在两个队列中,即使调整了临床因素,msEMT 亚型也与明显较差的预后相关(补充图 S7A-D)。此外,原发性肿瘤中的 msEMT 亚型与腹膜/卵巢复发的关系更为密切。机器学习分析表明,msEMT 基因对腹膜/卵巢转移有很强的预测能力,准确率很高(&gt;0.
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引用次数: 0
Impact of pre-existing cardiometabolic diseases on metastatic cancer stage at diagnosis: a prospective multinational cohort study 原有心脏代谢疾病对诊断时转移性癌症分期的影响:一项前瞻性多国队列研究。
IF 16.2 1区 医学 Q1 Medicine Pub Date : 2024-03-15 DOI: 10.1002/cac2.12526
Anna Jansana, Aviane Auguste, Marina Kvaskoff, Agnès Fournier, Emma Fontvieille, Laia Peruchet-Noray, Carine Biessy, Reynalda Cordova, Kristina Elin Nielsen Petersen, Anne Tjønneland, Verena Katzke, Rudolf Kaaks, Fulvio Ricceri, Salvatore Panico, Paolo Contiero, Maria-Jose Sánchez, Jesus Castilla, Marta Crous-Bou, Alicia Heath, Elom Kouassivi Aglago, Elisabete Weiderpass, Marc James Gunter, Pietro Ferrari, Elio Riboli, Vivian Viallon, Heinz Freisling

Owing to shared risk factors between cardiometabolic diseases (CMDs) and cancer, coupled with population aging, the lifetime risk of an individual developing cancer after a CMD is increasing. Furthermore, biological mechanisms such as insulin resistance or inflammation may not only predispose individuals with CMD to an elevated risk of certain types of cancer but also to a diagnosis of cancer at an advanced stage [1, 2].

Cancer stage at diagnosis strongly correlates with cancer survival rates and impacts treatment decisions. Early cancer detection is key to improving cancer outcomes, especially for cancers with poor prognosis. Factors associated with a higher risk of an advanced-stage diagnosis may differ from those associated with cancer incidence. Previous studies support an association between advanced-stage cancer at diagnosis and certain patient characteristics, such as higher body mass index (BMI), older age, smoking, comorbidities, and cancer type. Studies examining the influence of comorbidities on cancer stage at diagnosis have suggested that a CMD requiring regular medical follow-up is associated with earlier cancer detection [3, 4]. However, studies have also suggested that overall participation rates in cancer screening programs may be lower among individuals with type 2 diabetes (T2D) or cardiovascular diseases (CVD), which may lead to later cancer detection and a more advanced stage at diagnosis [5].

A better understanding of how CMDs prior to cancer are associated with stage at cancer diagnosis may inform cancer screening recommendations. This study aimed to investigate whether having a pre-existing CMD is associated with late-stage cancer diagnosis and to identify potential modifiers of this association in the European Prospective Investigation into Cancer and Nutrition study (EPIC).

This multinational prospective cohort study included 11,945 individuals diagnosed with first primary cancer between 1992 and 2012. Of all the diagnosed cancers, 64.9% were localized, 35.1% were metastatic, 53.6% were diagnosed in women, and 4.8%, a, 7.1%, and 1.3% had a history of CVD, of T2D, and of both CVD and T2D, respectively (Supplementary Figure S1, Supplementary Table S1). In addition to overall cancer, breast and colorectal cancers (38.1% of all cancers) were also investigated separately because of the well-established population-based cancer screening programs for these two cancers at the time of cancer diagnosis in the countries included in this study (i.e., Denmark, Germany, Italy, Spain, Sweden, and the UK). Detailed methods are described in Supplementary Materials.

We found that the adjusted odds ratios (ORs) of developing metastatic cancer (vs. localized) comparing individuals with pre-existing CVD, T2D or both to those without a CMD prior to cancer were 0.92 (95% confidence interval [CI] = 0.65-1.01), 1.04 (95% CI = 0.83-1.18) and 1.06 (95% CI = 0.60-1.36), respectively

首先,T2D与晚期诊断之间的正相关仅限于人群筛查计划未涵盖的癌症。此外,在不对癌症类型进行调整的情况下,这种关联变得更强,这一观察结果表明,患有 T2D 的成年人患上更常在转移阶段确诊的癌症的风险更高。与此相反,心血管疾病与晚期诊断之间的提示性反向关联仅限于进行全民筛查的癌症(即我们研究中的乳腺癌和结直肠癌)。其次,有证据表明,年龄组和吸烟状况会改变这些关联的效应。慢性疾病可能会干扰癌症及时诊断的机制包括竞争性需求,即具有高护理复杂性的慢性疾病可能会因症状被掩盖或未被发现而延误癌症诊断。也有观点认为,频繁就医的患者可能不愿意接受医疗专业人员的额外诊断检测。最后,影响癌症进展的生物机制,如高胰岛素血症、炎症途径或共同风险因素,可能解释了 CMD 与晚期癌症诊断之间的关系[1, 8]。与此相反,促进癌症及时诊断的机制包括:更频繁地接触医疗服务,从而提供监测机会以讨论可能的癌症症状;其次,一些慢性疾病的治疗方法可降低进展为转移性疾病的风险(如阿司匹林与结直肠癌)[1,9]。然而,新诊断出的 T2D 或高胰岛素血症患者已被推荐进行胰腺癌和肝癌筛查,因为原有疾病的存在可能会掩盖其他疾病,从而导致癌症晚期发病[10]。我们的研究结果支持这些筛查建议。对于其他部位的癌症,如呼吸系统癌症或血液系统癌症,研究并未显示原有 CMD 对诊断时癌症分期的影响[7]。此外,我们还获得了有关各种饮食和生活方式变量的数据,因此能够对混杂因素进行全面调整。我们研究的局限性包括缺乏心血管疾病/T2D管理数据、缺乏对混杂因素(如生活方式因素)的重复评估,以及样本量有限,无法对不太常见的癌症进行分析(补充表S3)。除了意大利和西班牙的一些研究中心(献血者)、乌得勒支和佛罗伦萨的一些研究中心(受邀参加当地人群乳腺癌筛查项目的妇女)以及牛津的一些研究中心(半数受试者不吃肉)外,大多数研究中心的受试者都来自普通成年人。在这项前瞻性多国队列研究中,患有心血管疾病、糖尿病或同时患有这两种疾病的癌症患者被确诊为晚期癌症的可能性总体上并不大。在这项前瞻性多国队列研究中,患有心血管疾病的癌症患者或同时患有心血管疾病的癌症患者被确诊为晚期癌症的几率总体上并不高。还需要进一步的研究来证实,在未纳入人群筛查的癌症患者中,T2D与无心血管疾病和晚期癌症之间存在提示性的正相关:海因茨-弗雷斯林(Heinz Freisling)。分析数据:Anna Jansana.支持数据分析:Carine Biessy、Vivian Viallon。撰写手稿Anna Jansana、Heinz Freisling。对手稿的最终内容负主要责任:Heinz Freisling。严格审阅手稿的重要思想内容并批准最终版本:Anna Jansana、Aviane Auguste、Marina Kvaskoff、Carine Biessy、Agnès Fournier、Emma Fontvieille、Laia Peruchet-Noray、Reynalda Cordova、Kristina Elin Nielsen Petersen、Anne Tjønneland、Verena Katzke、Rudolf Kaaks、Fulvio Riccieri、Salvatore Panico、Paolo Contiero、Maria-Jose Sánchez、Jesus Castilla、Marta Crous-Bou、Alicia Heath、Elom Kouassivi Aglago、Elisabete Weiderpass、Marc James Gunter、Pietro Ferrari、Elio Riboli、Vivian Viallon、Heinz Freisling。本研究由法国国家癌症研究所(INCA_N°2018-123)资助,并得到法兰西岛癌症协会(N°2018-1-PL SHS-06-CIRC-1)的支持。EPIC的协调工作得到了国际癌症研究机构(IARC)和伦敦帝国学院公共卫生学院流行病学与生物统计学系的资助,该系还得到了NIHR帝国生物医学研究中心(BRC)提供的基础设施支持。
{"title":"Impact of pre-existing cardiometabolic diseases on metastatic cancer stage at diagnosis: a prospective multinational cohort study","authors":"Anna Jansana,&nbsp;Aviane Auguste,&nbsp;Marina Kvaskoff,&nbsp;Agnès Fournier,&nbsp;Emma Fontvieille,&nbsp;Laia Peruchet-Noray,&nbsp;Carine Biessy,&nbsp;Reynalda Cordova,&nbsp;Kristina Elin Nielsen Petersen,&nbsp;Anne Tjønneland,&nbsp;Verena Katzke,&nbsp;Rudolf Kaaks,&nbsp;Fulvio Ricceri,&nbsp;Salvatore Panico,&nbsp;Paolo Contiero,&nbsp;Maria-Jose Sánchez,&nbsp;Jesus Castilla,&nbsp;Marta Crous-Bou,&nbsp;Alicia Heath,&nbsp;Elom Kouassivi Aglago,&nbsp;Elisabete Weiderpass,&nbsp;Marc James Gunter,&nbsp;Pietro Ferrari,&nbsp;Elio Riboli,&nbsp;Vivian Viallon,&nbsp;Heinz Freisling","doi":"10.1002/cac2.12526","DOIUrl":"10.1002/cac2.12526","url":null,"abstract":"<p>Owing to shared risk factors between cardiometabolic diseases (CMDs) and cancer, coupled with population aging, the lifetime risk of an individual developing cancer after a CMD is increasing. Furthermore, biological mechanisms such as insulin resistance or inflammation may not only predispose individuals with CMD to an elevated risk of certain types of cancer but also to a diagnosis of cancer at an advanced stage [<span>1, 2</span>].</p><p>Cancer stage at diagnosis strongly correlates with cancer survival rates and impacts treatment decisions. Early cancer detection is key to improving cancer outcomes, especially for cancers with poor prognosis. Factors associated with a higher risk of an advanced-stage diagnosis may differ from those associated with cancer incidence. Previous studies support an association between advanced-stage cancer at diagnosis and certain patient characteristics, such as higher body mass index (BMI), older age, smoking, comorbidities, and cancer type. Studies examining the influence of comorbidities on cancer stage at diagnosis have suggested that a CMD requiring regular medical follow-up is associated with earlier cancer detection [<span>3, 4</span>]. However, studies have also suggested that overall participation rates in cancer screening programs may be lower among individuals with type 2 diabetes (T2D) or cardiovascular diseases (CVD), which may lead to later cancer detection and a more advanced stage at diagnosis [<span>5</span>].</p><p>A better understanding of how CMDs prior to cancer are associated with stage at cancer diagnosis may inform cancer screening recommendations. This study aimed to investigate whether having a pre-existing CMD is associated with late-stage cancer diagnosis and to identify potential modifiers of this association in the European Prospective Investigation into Cancer and Nutrition study (EPIC).</p><p>This multinational prospective cohort study included 11,945 individuals diagnosed with first primary cancer between 1992 and 2012. Of all the diagnosed cancers, 64.9% were localized, 35.1% were metastatic, 53.6% were diagnosed in women, and 4.8%, a, 7.1%, and 1.3% had a history of CVD, of T2D, and of both CVD and T2D, respectively (Supplementary Figure S1, Supplementary Table S1). In addition to overall cancer, breast and colorectal cancers (38.1% of all cancers) were also investigated separately because of the well-established population-based cancer screening programs for these two cancers at the time of cancer diagnosis in the countries included in this study (i.e., Denmark, Germany, Italy, Spain, Sweden, and the UK). Detailed methods are described in Supplementary Materials.</p><p>We found that the adjusted odds ratios (ORs) of developing metastatic cancer (vs. localized) comparing individuals with pre-existing CVD, T2D or both to those without a CMD prior to cancer were 0.92 (95% confidence interval [CI] = 0.65-1.01), 1.04 (95% CI = 0.83-1.18) and 1.06 (95% CI = 0.60-1.36), respectively ","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":null,"pages":null},"PeriodicalIF":16.2,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140130795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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Cancer Communications
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