LBPO.CL02 · 临床研究 · Late-Breaking

Precision profiling of TP53 alterations in advanced cancers: Real-world evidence linking mutation class to genomic instability and cooccurring actionable drivers

海报缩略图:Precision profiling of TP53 alterations in advanced cancers: Real-world evidence linking mutation class to genomic instability and cooccurring actionable drivers
编号 LB118 展板 5 时间 4/20 09:00–12:00 区域 Section 52 主讲 Atul Bharde, PhD
分会场 Late-Breaking Research: Clinical Research 2
查看完整资料 下载 PDF 登录后可访问当前开放资料 AACR 官方页面 ↗

作者与单位

Atul Bharde1, Devika Deshmukh1, Pooja Sant1, Hrishita Kothavade1, Sandhya Iyer2, Sumit Halder2, Ajay Pandita3, Mohan Uttarwar3, Gowhar Shafi2, Kumar Prabhash4

11Cell.Ai, Pune, India,21Cell.Ai, Mumbai, India,31Cell.Ai, Foster city, CA,4Tata Memorial Hospital, Mumbai, India

摘要 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.

在会议检索中打开