Abstract PD9-01: Comprehensive Genomic Landscape of Invasive Lobular Carcinoma Reveals Distinct Molecular Subtypes
Abstract
Abstract Introduction: Invasive lobular carcinoma (ILC) represents a distinct subtype of breast cancer with unique clinical and molecular features compared to invasive ductal carcinoma (IDC). A hallmark of ILC is the loss of E-cadherin due to CDH1 alterations, yet large-scale genomic profiling of this histology, which is predominantly hormone receptor-positive (HR+)/HER2-negative, remains limited. Here, we comprehensively characterized the somatic mutational landscape of HR+/HER2-negative ILC and explored associations with clinical outcomes using real-world data. Methods: Whole-exome sequencing (WES) was performed as part of the SignateraTM (Natera, Inc.) workflow. WES-derived somatic variants from 1,451 patients with HR+/HER2- ILC in Natera’s large real-world database. Variants were annotated using the Ensembl Variant Effect Predictor (VEP), and only non-synonymous mutations with variant allele frequency (VAF) ≥ 5% were included in the prevalence analysis. Mutational signatures were assessed by comparing 96-trinucleotide mutation contexts with COSMIC single base substitution (SBS) signatures (v3.3). Event dates, including curative-intent surgery and distant relapse, together with treatment information, were sourced from claims data. Subtype was inferred based on treatment received. Associations between gene-level mutation and distant relapse-free survival (DRFS) were evaluated. Results: Among 1,451 HR+/HER2- ILC cases, CDH1 mutations were observed in 68%, with truncating variants accounting for 91% of these alterations. The most frequent CDH1 variants were p.Q23* (6.2%), p.I650Yfs13 (1.03%), p.Q129 (1.03%), and p.Q610* (1.03%). Comparative analysis with HR+/HER2- IDC revealed differential mutation frequencies in key genes, including PIK3CA, TBX3, TP53, and ERBB2 (47.3% vs 37.33%, 11.8% vs 4.0%,6.9% vs 25.2%, and 5.8% vs 2.2% P
Fields of Study & Subjects
Cancer Genomics and Diagnostics
Breast Cancer Treatment Studies
Bioinformatics and Genomic Networks
Publication details
- Journal / source
- Clinical Cancer Research
- Publisher
- American Association for Cancer Research (AACR)
- Volume
- 32
- Issue
- 4_Supplement
- Pages
- PD9–01
- Publication date
- 17 February 2026
- Language
- EN