LBPO.CL02 · 临床研究 · Late-Breaking
晚期癌症中TP53改变的精准分析：将突变类别与基因组不稳定性及共存可靶向驱动因素相联系的真实世界证据
Precision profiling of TP53 alterations in advanced cancers: Real-world evidence linking mutation class to genomic instability and cooccurring actionable drivers
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：TP53是癌症中最常发生改变的肿瘤抑制基因，然而其多样突变类别的分布、功能后果和基因组相关性在不同肿瘤类型和疾病阶段间各不相同。在真实世界检测环境中分析的晚期癌症为晚期基因组演化压力提供了独特见解。在本研究中，我们利用血浆和组织衍生的联合测序队列，表征了在乳腺癌（BC）、结直肠癌（CRC）和肺癌（LC）中检测到的TP53突变（mTP53）的患病率、功能特征和基因组背景。
方法：对1187例晚期实体瘤患者（827例ctDNA；360例tDNA）进行了全面基因组分析（BC=358，CRC=300，LC=529）。测序采用杂交捕获OncoIndx 1080基因NGS检测，检测SNV、小indel、结构变异以及全基因组肿瘤突变负荷（TMB）和同源重组缺陷（HRD）评分。mTP53按变异类型（错义（MS）、无义（NS）、移码（FS）、剪接变异（SPlv）和短indel（IND））以及预测功能（功能缺失：LOF和功能获得：GOF）进行分类。评估了与经典致癌驱动因素的共突变模式在各谱系间的情况。
结果：在ctDNA中，mTP53在所有病例的50.5%（600/1187）中被检出，在CRC中患病率最高（57.33%），其次为BC（53%）和LC（45%）。错义变异占所有mTP53的65.8%，包括R175、R248、R273和G245处的复发性GOF热点，其中后者在CRC中最为突出。GOF突变占所有mTP53的33.3%。NS、FS、Splv和indel分别占16.6%、7.5%、7.0%、3.1%。在整个队列中，mTP53肿瘤表现出显著高于wtTP53对应者的TMB（P<0.0001，OR= 3.3，CI= 1.9-5.6）。在mTP53中，GOF变异与高TMB相关。然而，在BC中，mTP53与低HRD评分相关（P= 0.0017，OR= 0.28，CI=0.13-0.6），显示出谱系特异性的基因组行为。GOF mTP53肿瘤相比LOF mTP53肿瘤显示出高PD-L1表达（P=0.001）。共突变分析揭示了谱系特异性关联，包括CRC中的TP53-KRAS共改变、LC中的TP53-EGFR/TP53-KRAS以及BC中的TP53-PIK3CA配对。GOF mTP53在具有肝或脑转移的肿瘤中富集，并在LC中显示出较差的预后。
结论：这一大型真实世界数据集揭示了肿瘤类型特异性的mTP53模式，并提示TP53功能障碍，尤其是GOF变异，与基因组不稳定性特征（如晚期疾病中升高的TMB）显著相关。谱系特异性的共突变网络和GOF mTP53的富集凸显了不同的演化压力，并将进一步支持旨在界定mTP53在实体瘤中治疗和预后意义的机制及临床研究。
查看英文原文 English abstract
Background: TP53 is the most frequently altered tumor suppressor gene in cancer, yet the distribution, functional consequences, and genomic correlates of its diverse mutation classes vary across tumor types and disease stages. Advanced cancers profiled in real-world testing environments offer unique insight into late-stage genomic evolution pressures. In this study we characterized the prevalence, functional features[AP1] , and genomic context of TP53 mutations (mTP53) detected across breast (BC), colorectal (CRC), and lung (LC) cancers using a combined plasma- and tissue-derived sequencing cohort.
Methods: Comprehensive genomic profiling was performed on 1187 patients (827 ctDNA; 360 tDNA) with advanced solid tumors (BC=358, CRC=300, LC=529). Sequencing was conducted using a hybrid-capture OncoIndx 1080-gene NGS assay interrogating SNVs, small indels, structural variations and genomwwide tumor mutation burden (TMB) and homologous recombination deficiency (HRD) scores. mTP53 were classified by variant type (missense (MS), nonsense (NS), frameshift (FS), splice variants (SPlv) and short indels (IND) and predicted function (loss-of-function: LOF and gain-of-function: GOF). Co-mutation patterns with canonical oncogenic drivers were assessed across lineages.
Results: In ctDNA, mTP53 were detected in 50.5% (600/1187) of all cases, with highest prevalence in CRC (57.33%), followed by BC (53%), and LC (45%). Missense variants accounted for 65.8% of all mTP53, including recurrent GOF hotspots at R175, R248, R273, and G245, the latter being most prominent in CRC. GOF mutations accounted for 33.3% of all mTP53. NS, FS, Splv and indels comprised 16.6%, 7.5%, 7.0%, 3.1%, respectively. Across the cohort, mTP53 tumors exhibited significantly higher TMB than wtTP53 counterparts (P<0.0001, OR= 3.3, CI= 1.9-5.6). Within mTP53, GOF variants were associated with high TMB. However, In BC, mTP53 was associated with low HRD scores (P= 0.0017, OR= 0.28, CI=0.13-0.6), demonstrating lineage specific genomic behavior. GOF mTP53 tumors showed high PD-L1 expression compared to LOF mTP53 tumors (P=0.001). Co-mutation analysis revealed lineage-specific associations, including TP53-KRAS co-alteration in CRC, TP53-EGFR/ TP53-KRAS in LC and TP53-PIK3CA pairing in BC. GOF mTP53 were enriched in tumors with liver or brain metastasis and showed worse prognosis in LC.
Conclusion: This large real-world dataset reveals tumor-type-specific mTP53 patterns and suggests that TP53 dysfunction, particularly GOF variants, is significantly associated with genomic instability signatures, such as elevated TMB in advanced disease. Lineage-specific co-mutation networks and enrichment of GOF mTP53 highlight distinct evolutionary pressures and will further support mechanistic and clinical studies to define the therapeutic and prognostic implications of mTP53 in solid tumors. [AP1]Not too sure what you mean by functional features here.
利益披露 Disclosure
A. Bharde, None..
D. Deshmukh, None..
P. Sant, None..
H. Kothavade, None..
S. Iyer, None..
S. Halder, None..
A. Pandita, None..
M. Uttarwar, None..
G. Shafi, None..
K. Prabhash, None.