Lazar Vladimir, Raymond Eric, Magidi Shai, Bresson Catherine, Wunder Fanny, Berindan-Neagoe Ioana, Tijeras-Rabaland Annemilaï, Raynaud Jacques, Onn Amir, Ducreux Michel, Batist Gerald, Lassen Ulrik, Cilius Nielsen Fin, Schilsky Richard L, Rubin Eitan, Kurzrock Razelle
Worldwide Innovative Network Association-WIN Consortium, Villejuif, France.
Groupe Hospitalier Saint Joseph, Oncology Department Paris, France.
Ther Adv Med Oncol. 2024 Oct 17;16:17588359241289200. doi: 10.1177/17588359241289200. eCollection 2024.
Dysregulated pathways in cancer may be hub addicted. Identifying these dysregulated networks for targeting might lead to novel therapeutic options.
Considering the hypothesis that central hubs are associated with increased lethality, identifying key hub targets within central networks could lead to the development of novel drugs with improved efficacy in advanced metastatic solid tumors.
Exploring transcriptomic data (22,000 gene products) from the WINTHER trial ( = 101 patients with various metastatic cancers), in which both tumor and normal organ-matched tissue were available.
A retrospective in silico analysis of all genes in the transcriptome was conducted to identify genes different in expression between tumor and normal tissues (paired -test) and to determine their association with survival outcomes using survival analysis (Cox proportional hazard regression algorithm). Based on the biological relevance of the identified genes, hub targets of interest within central networks were then pinpointed. Patients were grouped based on the expression level of these genes (-mean clustering), and the association of these groups with survival was examined (Cox proportional hazard regression algorithm, Forest plot, and Kaplan-Meier plot).
We identified four key central hub genes-, and , for which high expression in tumor tissue compared to analogous normal tissue had the most significant correlation with worse outcomes. The correlation was independent of tumor or treatment type. The combination of the four genes showed the highest significance and correlation with the poorer outcome: overall survival (hazard ratio (95% confidence interval (CI)) = 10.5 (3.43-31.9) = 9.12E-07 log-rank test in a Cox proportional hazard regression model). Findings were validated in independent cohorts.
The expression of , and constitute, when combined, a prognostic tool, agnostic of tumor type and previous treatments. These genes represent potential targets for intercepting central hub networks in various cancers, offering avenues for novel therapeutic interventions.
癌症中失调的信号通路可能对关键节点存在依赖。识别这些失调的网络以进行靶向治疗可能会带来新的治疗选择。
考虑到核心节点与致死率增加相关的假设，在核心网络中识别关键的节点靶点可能会促使开发出对晚期转移性实体瘤疗效更佳的新型药物。
探索WINTHER试验（n = 101例患有各种转移性癌症的患者）的转录组数据（22,000种基因产物），该试验中可获得肿瘤组织和正常器官匹配组织。
对转录组中的所有基因进行回顾性计算机分析，以识别肿瘤组织和正常组织之间表达不同的基因（配对t检验），并使用生存分析（Cox比例风险回归算法）确定它们与生存结果的关联。基于已识别基因的生物学相关性，然后确定核心网络内感兴趣的节点靶点。根据这些基因的表达水平（-均值聚类）对患者进行分组，并检查这些组与生存的关联（Cox比例风险回归算法、森林图和Kaplan-Meier图）。
我们确定了四个关键的核心节点基因——以及，与类似正常组织相比，肿瘤组织中这些基因的高表达与更差的预后具有最显著的相关性。这种相关性与肿瘤类型或治疗类型无关。这四个基因的组合显示出与更差预后的最高显著性和相关性：总生存期（风险比（95%置信区间（CI））= 10.5（3.43 - 31.9），在Cox比例风险回归模型中的对数秩检验P = 9.12E - 07）。研究结果在独立队列中得到验证。
、和的表达相结合构成了一种预后工具，与肿瘤类型和既往治疗无关。这些基因代表了在各种癌症中拦截核心网络的潜在靶点，为新型治疗干预提供了途径。
