Miyashita Hirotaka, Kurzrock Razelle, Bevins Nicholas J, Thangathurai Kartheeswaran, Lee Suzanna, Pabla Sarabjot, Nesline Mary, Glenn Sean T, Conroy Jeffrey M, DePietro Paul, Rubin Eitan, Sicklick Jason K, Kato Shumei
Department of Hematology and Oncology, Dartmouth Cancer Center, Lebanon, NH, USA.
Worldwide Innovative Network (WIN) for Personalized Cancer Therapy, Paris, France.
NPJ Genom Med. 2023 Aug 8;8(1):19. doi: 10.1038/s41525-023-00359-8.
Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.
免疫检查点阻断仅对一部分癌症有效。靶向T细胞启动标志物(TPMs)可能会增强活性,但由于免疫复杂性和异质性,这些药物在临床上的合理应用具有挑战性。我们在一个泛癌队列(N = 514例患者,30种癌症类型)中研究了15种TPMs(CD137、CD27、CD28、CD80、CD86、CD40、CD40LG、GITR、ICOS、ICOSLG、OX40、OX40LG、GZMB、IFNG和TBX21)的转录组学。分析了TPM表达与组织学类型、微卫星高度不稳定(MSI-H)、肿瘤突变负荷(TMB)和程序性死亡配体1(PD-L1)表达的相关性。在514例患者中,最常见的组织学类型是结直肠癌(27%)、胰腺癌(11%)和乳腺癌(10%)。未发现组织学类型与TPM表达之间存在统计学显著关联。相比之下,在MSI-H、TMB≥10个突变/mb且PD-L1≥1%的肿瘤中,颗粒酶B(GZMB,一种储存在活化T细胞和NK细胞中诱导癌细胞凋亡的丝氨酸蛋白酶)和IFNG(激活细胞毒性T细胞)的表达显著更高。PD-L1≥1%也与CD137、GITR和ICOS的显著更高表达相关。使用层次聚类根据TPM表达将患者的肿瘤分为“热”、“混合”或“冷”簇。冷簇中PD-L1≥1%的肿瘤比例显著更低。总体而言,502例患者(98%)具有各自独特的TPM表达模式。观察到TPMs的不同表达模式,其独立于组织学类型,但与其他免疫治疗生物标志物(PD-L1≥1%、MSI-H和TMB≥10个突变/mb)相关。基于TPM免疫组学图谱对患者进行个体化选择可能有助于优化免疫治疗。