摘要
For decades,the central dogma of oncology has been that a cancer’s identity is inextricably linked to its anatomical origin.This principle underpins the entire diagnostic and therapeutic framework,from histology-based classification to site-specific treatment guidelines.Yet,this framework catastrophically fails for a substantial population of patients diagnosed with cancer of unknown primary(CUP).These patients present metastatic disease,yet their primary tumors remain elusive despite exhaustive clinical workup1.CUP,accounting for 1%-3%of all cancer diagnoses,is an enigma with devastating consequences;the median overall survival is only 2-12 months2-4.The inability to pinpoint an origin forces clinicians to rely on broad-spectrum empirical chemotherapy,such as taxane-carboplatin regimens,which have limited efficacy and exclude patients from the promise of targeted therapies and clinical trials5.CUP is not only a diagnostic challenge but also an indictment of the siloed approach to understanding malignancy:this cancer highlights the limitations of origin-based diagnostic frameworks.However,the confluence of high-dimensional biological data and advanced artificial intelligence(AI)is now poised to address this long-standing diagnostic limitation and to herald a new era for not only CUP but also oncology as a whole(Figure 1).
基金
supported by the National Natural Science Foundation of China(Grant Nos.32270688,31801117,and 82430107 to X.L.,and 32500589 to H.S.)
the China Postdoctoral Science Foundation(Grant Nos.BX20240253 and 2024M762384 to H.S.)
the Natural Science Foundation of Tianjin(Grant No.24JCQNJC01280 to H.S.)
Tianjin Key Medical Discipline(Specialty)Construction Project(Grant No.TJYXZDXK-3-003A).
