Abstract 3353: Predicting the prognosis of ductal carcinoma in situ through chemical analysis of breast microcalcifications and soft tissue using infrared and Raman spectroscopy
Authors: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Ihssane Bouybayoune, Rachel Factor, Sarah Pinder, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Alastair Thompson, Elinor Sawyer, Jelle Wesseling, Shelley Hwang, Keith Rogers, Nick Stone
Journal: Cancer Research (2025)

Abstract Introduction: Ductal carcinoma in situ (DCIS) is a potential precursor to invasive breast cancer (IBC). The trajectory of an individual’s DCIS, if it will progress to IBC or remain as DCIS is difficult to predict. Currently &amp;gt;80% of DCIS is detected through mammographic screening of breast calcifications. Despite the close association of calcifications with DCIS, their role in the development of DCIS and/or its progression to IBC remains largely unexplored. In this study, we present a spectroscopy based analytical approach to probe chemical compositional changes of both DCIS associated breast calcifications and surrounding soft tissue aiming to identify a cohort at increased risk for invasive progression. Experimental Procedures: Tissue samples from 316 DCIS patients without invasive cancer were obtained from multiple centres as part of the PRECISION consortium (The Netherlands, UK and USA). Three consecutive tissue sections were obtained each of the tissue biopsies. Mid-infrared (mid-IR) and Raman hyperspectral imaging was performed independently on two sections that were left unstained. The third H&amp;E-stained section was used to annotate calcifications and histopathological features. All DCIS samples had known outcome (i) ‘pure DCIS as controls’ (DCIS without progression to invasion) (n=193), (ii) ‘DCIS with progression to invasion as cases’ (DCIS from patients who subsequently developed invasive disease after initial treatment) (n=123). Spectral features of DCIS calcifications and surrounding soft tissue were used as inputs for analysis. Data was divided into a discovery and a validation set. Cluster analysis followed by Principal component analysis fed linear discriminant analysis was carried out on the discovery set to develop DCIS prediction models. Results: For the Raman data, a mean area under the receiver operating characteristic curve (AUROC) value of 0.85 was obtained using calcification spectral features, and 0.75 using soft tissue spectral features in distinguishing controls from cases (N=118 vs 52). Similar analysis on the IR data showed a mean AUROC value of 0.68 for calcification, 0.78 for epithelial and 0.80 for stromal components (N=97 vs 61). Preliminary analysis shows changes in phosphate to carbonate ratio and variations in magnesium whitlockite content in calcifications, and protein secondary structural changes in soft tissue, between the two groups. The models will be tested independently on the validation set and the outcomes will be presented at the AACR conference. Conclusion: Spectroscopic chemical analysis of breast calcifications and soft tissue show promise in predicting the likely progression of DCIS to IBC. Pending further independent validation, these techniques appear to be novel image-based risk assessment tools that can potentially be utilised to inform DCIS prognosis and treatment options. Citation Format: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Ihssane Bouybayoune, Rachel Factor, Sarah Pinder, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Alastair Thompson, Elinor Sawyer, Jelle Wesseling, Shelley Hwang, Keith Rogers, Nick Stone, Grand Challenge PRECISION consortium. Predicting the prognosis of ductal carcinoma in situ through chemical analysis of breast microcalcifications and soft tissue using infrared and Raman spectroscopy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3353.