PO.IM01.11 · 免疫学
基因内重排负荷：预测TMB低癌症中免疫检查点阻断应答的一种新型生物标志物
Intragenic rearrangement burden: A novel biomarker to predict immune checkpoint blockade response in TMB-low cancers
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摘要 Abstract
中文摘要
背景：免疫检查点阻断（ICB）的疗效有限，而像肿瘤突变负荷（TMB）这样的生物标志物在TMB低的癌症（如乳腺癌、卵巢癌）中失效，尽管其中许多在免疫学上属于"热"肿瘤。这一悖论提示存在一种尚未表征的新抗原来源。我们研究了基因内重排（IGR）——一种隐匿的结构性突变——作为这一来源，假设IGR负荷在这些肿瘤中是T细胞炎症和ICB获益的更优生物标志物。
方法：我们进行了泛癌全基因组测序（WGS）分析（ICGC，n=1,033），将IGR负荷与T细胞炎症特征相关联。我们使用多变量回归比较IGR与TMB、插入缺失、融合和SCNA对免疫浸润的影响，并在TNBC（n=513）、HGSC（n=33）和ESAD队列中进行验证。通过Kaplan-Meier、Cox回归和ROC分析，在ESAD（durvalumab）、HGSC（NACT + pembrolizumab）和mTNBC试验中评估对ICB应答的预测能力。我们还分析了一个乳腺癌免疫肽组学数据集（n=26），以将IGR负荷与呈递的新肽相关联。
结果：泛癌分析显示IGR高和TMB高是不同的T细胞炎症亚群。在TMB低的癌症中，IGR负荷是T细胞炎症最显著的协变量（p=0.0098），而非TMB（p=0.224）。在TNBC中，IGR负荷是T细胞炎症特征唯一显著的基因组标志物（p=0.008）。在机制上，IGR负荷与呈递的IGR衍生新肽强相关（Pearson R=0.54），并显示出免疫编辑的证据。在临床试验中，IGR负荷预测了ICB获益。在HGSC（NACT+Pembro）中，高IGR负荷预测更优的OS（AUROC=0.80；5年OS约85% vs 约30%，HR=0.17，p=0.009），优于PD-L1（HR=0.77，p=0.65）。在ESAD（durvalumab）中，IGR负荷（AUROC=0.74）也优于PD-L1（AUROC=0.46）。至关重要的是，IGR负荷具有预测性，而不仅仅是预后性。在接受化疗-免疫治疗（chemo-IO）的mTNBC中，高IGR负荷预测改善的OS（HR=0.18，p=0.074），但在仅化疗中则预测较差的OS（HR=4.29，p=0.032）。
结论：在TMB和PD-L1失效的TMB低恶性肿瘤中，IGR负荷是ICB应答的一种强有力的预测性生物标志物。在新抗原呈递的免疫肽组学证据支持下，它优于现有标志物，能够将真正的ICB获益与预后区分开来，并解决了"热"TMB低肿瘤的悖论。IGR负荷代表了患者选择的一项关键新工具。
查看英文原文 English abstract
Background: Immune checkpoint blockade (ICB) efficacy is limited, and biomarkers like Tumor Mutation Burden (TMB) fail in TMB-low cancers (e.g., breast, ovarian) despite many being immunologically "hot". This paradox suggests an uncharacterized neoantigen source. We investigated intragenic rearrangements (IGRs)-cryptic structural mutations-as this source, hypothesizing IGR burden is a superior biomarker for T-cell inflammation and ICB benefit in these tumors.
Methods: We performed a pan-cancer WGS analysis (ICGC, n=1,033) correlating IGR burden with T-inflamed signatures. We used multivariate regression to compare IGRs against TMB, indels, fusions, and SCNA on immune infiltration, validating in TNBC (n=513), HGSC (n=33), and ESAD cohorts. Predictive power for ICB response was assessed by Kaplan-Meier, Cox regression, and ROC analysis in ESAD (durvalumab), HGSC (NACT + pembrolizumab), and mTNBC trials. We also analyzed a breast cancer immunopeptidomic dataset (n=26) to correlate IGR burden with presented neopeptides.
Results: Pan-cancer analysis showed IGR-high and TMB-high are distinct T-inflamed subsets. In TMB-low cancers, IGR burden was the most significant covariate for T-cell inflammation (p=0.0098), not TMB (p=0.224). In TNBC, IGR burden was the only significant genomic marker for the T-inflamed signature (p=0.008). Mechanistically, IGR burden strongly correlated with presented IGR-derived neopeptides (Pearson R=0.54) and showed evidence of immunoediting.In clinical trials, IGR burden predicted ICB benefit. In HGSC (NACT+Pembro), high IGR burden predicted superior OS (AUROC=0.80; 5-yr OS ~85% vs ~30%, HR=0.17, p=0.009), outperforming PD-L1 (HR=0.77, p=0.65). In ESAD (durvalumab), IGR burden (AUROC=0.74) also outperformed PD-L1 (AUROC=0.46). Critically, IGR burden was predictive, not just prognostic. High IGR burden predicted improved OS in mTNBC with chemo-IO (HR=0.18, p=0.074) but poorer OS with chemo-only (HR=4.29, p=0.032).
Conclusions: IGR burden is a powerful predictive biomarker for ICB response in TMB-low malignancies where TMB and PD-L1 fail. Supported by immunopeptidomic evidence of neoantigen presentation, it outperforms existing markers, distinguishes true ICB benefit from prognosis, and resolves the "hot" TMB-low tumor paradox. IGR burden represents a critical new tool for patient selection.
利益披露 Disclosure
A. Gupta, None..
S. Xiao, None..
H. Wang, None..
R. Bhargava, None..
A. V. Lee, None..
A. M. Brufsky, None..
X. Wang, None.