Xu George J, Loberg Matthew A, Gallant Jean-Nicolas, Sheng Quanhu, Chen Sheau-Chiann, Lehmann Brian D, Shaddy Sophia M, Tigue Megan L, Phifer Courtney J, Wang Li, Saab-Chalhoub Mario W, Dehan Lauren M, Wei Qiang, Chen Rui, Li Bingshan, Kim Christine Y, Ferguson Donna C, Netterville James L, Rohde Sarah L, Solórzano Carmen C, Bischoff Lindsay A, Baregamian Naira, Shaver Aaron C, Mehrad Mitra, Ely Kim A, Byrne Daniel W, Stricker Thomas P, Murphy Barbara A, Choe Jennifer H, Kagohara Luciane T, Jaffee Elizabeth M, Huang Eric C, Ye Fei, Lee Ethan, Weiss Vivian L
Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.
Cell Genom. 2023 Sep 14;3(10):100409. doi: 10.1016/j.xgen.2023.100409. eCollection 2023 Oct 11.
Genomic and transcriptomic analysis has furthered our understanding of many tumors. Yet, thyroid cancer management is largely guided by staging and histology, with few molecular prognostic and treatment biomarkers. Here, we utilize a large cohort of 251 patients with 312 samples from two tertiary medical centers and perform DNA/RNA sequencing, spatial transcriptomics, and multiplex immunofluorescence to identify biomarkers of aggressive thyroid malignancy. We identify high-risk mutations and discover a unique molecular signature of aggressive disease, the Molecular Aggression and Prediction (MAP) score, which provides improved prognostication over high-risk mutations alone. The MAP score is enriched for genes involved in epithelial de-differentiation, cellular division, and the tumor microenvironment. The MAP score also identifies aggressive tumors with lymphocyte-rich stroma that may benefit from immunotherapy. Future clinical profiling of the stromal microenvironment of thyroid cancer could improve prognostication, inform immunotherapy, and support development of novel therapeutics for thyroid cancer and other stroma-rich tumors.
基因组和转录组分析加深了我们对许多肿瘤的理解。然而,甲状腺癌的管理很大程度上由分期和组织学指导,几乎没有分子预后和治疗生物标志物。在此,我们利用来自两个三级医疗中心的251名患者的312个样本组成的大型队列,进行DNA/RNA测序、空间转录组学和多重免疫荧光,以识别侵袭性甲状腺恶性肿瘤的生物标志物。我们识别出高风险突变,并发现侵袭性疾病的独特分子特征,即分子侵袭与预测(MAP)评分,与单独的高风险突变相比,该评分能提供更好的预后。MAP评分在参与上皮去分化、细胞分裂和肿瘤微环境的基因中富集。MAP评分还能识别出具有富含淋巴细胞的基质的侵袭性肿瘤,这些肿瘤可能从免疫治疗中获益。未来对甲状腺癌基质微环境的临床分析可能会改善预后、为免疫治疗提供依据,并支持开发针对甲状腺癌和其他富含基质肿瘤的新型疗法。