Differences in arm-level copy number gains and losses by source data set (CBCS vs TCGA)

Oncogenic pathway level alterations and associations with subtype

Complete tabulation of mutational frequency and proportion by self-reported race [either Black vs non-Black or Non-Hispanic white vs Non-Hispanic Black only] and age at diagnosis.

Flow diagram of sample and patient selection for study

BACKGROUND:Treatment approaches differ for isolated in-breast tumor recurrence (representing treatment failure) and new primary breast tumors (representing high etiologic risk). However, methods for distinguishing recurrences from second primaries (based on radiographic and histologic criteria) are subject to error. Gold-standard genomic datasets for assessing classification accuracy have been lacking. METHODS:To identify the scope of misclassification, we performed DNA sequencing of 1,200 genes in 108 participants with synchronous or metachronous second breast cancer in the Carolina Breast Cancer Study (CBCS3). DNA sequencing data included 87 second tumors and 42 paired first and second breast cancers in the same patient (14 contralateral and 28 ipsilateral). Recurrence status was classified based on mutations and copy number, accounting for site-specific mutation probabilities. DNA-based recurrence versus second primary classifications were compared with clinical and Surveillance, Epidemiology and End Results (SEER) classifications based on laterality, histology, quadrant, and latency. RESULTS:Twenty-two of 28 ipsilateral tumor pairs (79%) shared at least one mutation and were classified as recurrences. Pathologist classifications of ipsilateral second tumors were 79% accurate [95% confidence interval (CI), 60%-90%) with higher sensitivity (95%, 95% CI = CI, 78%-99%) and lower specificity (17%, 95% CI, 3%-56%). SEER classifications were 82% accurate (95% CI, 64%-92%) with lower sensitivity (77%, 95% CI, 57%-90%) and higher specificity (100%, 95% CI, 61%-100%). CONCLUSIONS:Although most genomically defined recurrences are captured by clinical recurrence definitions, new primaries are frequently misclassified. IMPACT:Given overtreatment harms, genomic methods may support treatment de-escalation for second breast cancers.

Association between RNA-based TP53 pathway dysfunction and DNA-based TP53 defects

Boxplot showing differences in predicted probability of recurrence by weighting schema

Differences in proportions of samples with detected mutations by stage at diagnosis (Stage I/II vs. Stage III/IV)

Enrichments for arm-level alterations by self reported race

Arm level amplification and deletion prevalence differences by age at diagnosis

Association between socioeconomic variables in CBCS and mutations or copy number alterations. All estimates are stratified by self reported race

Summary or different schema to classify IBTR vs second primary tumors

Accuracy and test metrics of genomic vs clinical schema stratified by prior treatment.

Differences in recurrent copy number alterations of mutations by self-reported race or age after stratifying on estrogen receptor (ER) status

Oncogenic pathway dysfunction differences by race and age at diagnosis

Differences in proportions of samples with detected mutations to each gene of target panel by pipeline [paired tumor/normal or tumor only].

Comparison of tamoxifen and control treated epithelial subpopulations from normal samples

Background: The immune cell component of the tumor microenvironment is an important modulator of tumor progression and suppression. In patients with breast cancer, tumor-infiltrating lymphocytes (TILs) represent a large part of antitumor immunity along with tertiary lymphoid structure (TLS), as they predict favorable prognosis and good treatment response. In this study, we scored for immune-related histology features using whole slide H&E images of the TCGA-BRCA dataset and analyzed these distinct features relative to gene expression patterns and molecular intrinsic subtypes. Method: A total of 1035 cases from TCGA-BRCA dataset were evaluated for TILs, plasma cells, high-endothelial venule associated lymphoid aggregate (HALA) and TLS. For HALA and TLS, location relative to tumor (non-tumor, peritumor, and intratumoral area) and number was determined. For each pathologically defined immune feature (i.e., no TLS vs TLS+), we then searched for associated gene expression features and used the top 100 significantly upregulated genes to make signatures for tumor group-based analyses. Upregulated immune modules in high-TIL tumors using a 10% TIL level cutoff were compared based on PAM50 molecular subtype (luminal A/B, HER2-enriched, basal-like). The clinical significance of histology-based gene signatures and high-TIL related immune modules was validated using bulk RNAseq and survival data from the SCAN-B cohort (N=6329). Results: HER2-enriched (HER2E) and basal-like breast tumors exhibited the highest mean TILs, with plasma cells more frequently observed in these subtypes. HALAs were present in 36.4% of cases and TLS were found in 6.5% of cases, also predominantly in HER2E and basal-like tumors. Gene signatures related to intratumoral HALA and intratumoral TLS correlated with better survival outcomes, while peritumoral HALA correlated with worse outcomes on the overall TCGA data set. In addition to TILs- and plasma cell-associated gene signatures, intratumoral HALA and intratumoral TLS correlated with HER2E and basal like tumors. High-TIL tumors revealed 164 enriched immune modules, with unique upregulated modules in each molecular subtype. For example, in luminal tumors, immune modules had little relation to favorable prognosis. High-TIL HER2E and basal-like tumors had distinct immune gene signatures linked to improved survival, with HER2E being more associated with B-cell prognostic features and basal-like subtype more associated with T-cell prognostic features. Conclusion: Different subtypes of breast cancer exhibit distinct tumor immune microenvironments, both histologically and molecularly. These differences in immune properties and biological characteristics should be considered when developing precise treatment strategies to achieve the best therapeutic efficacy for patients. Citation Format: Yoon Jin, Constandina E. O’Connell, Benjamin C. Calhoun, Christian Brueffer, Christer Larsson, Åke Borg, Lao H. Saal, and Charles M. Perou. Genomic characteristics related to histology-based immune features in breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr PS1-05.

Effect of time in suspension on cell population abundance and gene expression.