Triple negative breast cancer (TNBC) is typically a high-grade breast cancer with poorest clinical outcome despite available treatment modalities with chemo-, immuno- and radiotherapy. The status of tumor-infiltrating lymphocytes (TILs) is a prognostic factor closely related to programmed death ligand 1 (PD-L1) expressed on T lymphocytes modulating antitumor immunity. Immune-checkpoint inhibitors (ICI) are showing promising results in a subset of breast cancer patients in both neo- and adjuvant settings. Pathologic complete response (pCR) after neoadjuvant treatment was found to be associated with better prognosis. We analyzed the prognostic and predictive significance of PD-L1 (SP142 assay) immunohistochemical expression on TNBC patients’ samples as illustrated by pCR with regard to its relation to treatment regimen, stage, BRCA mutational status and outcome. Furthermore, we analyzed a few other clinicopathological parameters such as age, TILs and proliferation index. The study highlighted a positive role of PD-L1 evaluation for personalized pCR probability assessment. Although considerable research was made on comparison of PD-L1 level in TNBC with different patient parameters, to our best knowledge, the relation of PD-L1 status to pCR while taking treatment regimen and stage into consideration was so far not investigated.

Histological analysis is the core of follicular thyroid carcinoma (FTC) classification. The histopathological criteria of capsular and vascular invasion define malignancy and aggressiveness of FTC. Analysis of multiple sections is cumbersome and as only a minute tissue fraction is analyzed during histopathology, under-sampling remains a problem. Application of an efficient tool for complete tissue imaging in 3D would speed-up diagnosis and increase accuracy. We show that X-ray propagation-based imaging (XPBI) of paraffin-embedded tissue blocks is a valuable complementary method for follicular thyroid carcinoma diagnosis and assessment. It enables a fast, non-destructive and accurate 3D virtual histology of the FTC resection specimen. We demonstrate that XPBI virtual slices can reliably evaluate capsular invasions. Then we discuss the accessible morphological information from XPBI and their significance for vascular invasion diagnosis. We show 3D morphological information that allow to discern vascular invasions. The results are validated by comparing XPBI images with clinically accepted histology slides revised by and under supervision of two experienced endocrine pathologists.

Advances in laboratory-based X-ray computed tomography (CT) have enabled X-ray 3D virtual histology. This method shows a great potential as a complementary technique to conventional 2D histology where extensive volumetric sampling is necessary. While formalin-fixed paraffin-embedded (FFPE) tissue blocks are the backbone of clinical histology, there exists no generic optimization, and technical study of the X-ray 3D virtual histology of FFPE blocks. X-ray micro-CT of FFPE blocks is studied and optimized in their native state within the cassette to minimize the interference of X-ray 3D virtual histology with clinical workflows and standards, hence facilitating the technology transfer to the clinics. The optimization is carried on the sample positioning, tungsten tubes acceleration voltage, and artifact reduction. Then propagation-based imaging of FFPE blocks is extensively discussed. Hierarchical (local) tomography and laminography are presented as viable approaches for achieving higher spatial resolutions. In the end, future perspectives are given by considering state-of-the-art micro-CT scanners using liquid-metal-jet sources, large-area detectors, and photon counting detectors. The results achieved here are generic and can be applicable to any laboratory-based scanner with a tungsten target source and cone-beam geometry. This article provides a starting point for anyone new to X-ray 3D virtual histology on FFPE blocks, but also serves as a useful source for more experienced users.

Thyroid nodules are a widespread phenomenon, with follicular cell-derived thyroid tumors being the most prevalent type of endocrine tumor, spanning from benign through low grade malignant to aggressive neoplasms with dismal prognosis. In clinical practice, histopathological criteria are primarily used to determine malignancy and aggressiveness. Therefore, accurate classification may result in surgical procedures for diagnostic reasons, associated with an imbalanced risk/benefit ratio. In recent years, the use of integrated proteomic approaches has proven valuable in expanding the molecular understanding of thyroid neoplasms, with implications in classification, yet remains understudied in divergent thyroid nodules. Here we show the delineation of subtype-specific and malignancy-dependent molecular characteristics through integrative proteomic and phosphoproteomic analysis of 53 human thyroid tissues, encompassing five frequent benign and malignant tumors. We found that the (phospho)-proteomic profiles enable a clear stratification of malignant and benign thyroid tissues. The method also performs well in delineating follicular adenoma (FA) and follicular thyroid carcinoma (FTC) samples. Beside the dysregulation of cell cycle control, apoptosis, and metabolic reprogramming associated with tumor development and malignancy, we further report increased alterations within the well-established oncogenic RAS/BRAF/MAPK and AKT/MTOR signaling pathways, which, contrary to the prevailing paradigm, did not clearly differentiate between FTC and papillary thyroid carcinoma (PTC). In addition, activities of ATM, PLK2-3, and GRK5-6 kinases were predicted to be strongly upregulated in malignant subtypes. Together, this study provides an in-depth insight into molecular changes in different thyroid tumor subtypes. These findings highlight the potential of integrated proteomic approaches to refine our understanding of complex diseases like cancer. As such, they offer a pathway to more precise diagnostic and personalized treatment strategies.

Tumor heterogeneity plays a central role in treatment resistance, disease progression, and diagnostic uncertainty. However, it may be overlooked by traditional 2D histology. Accurate 3D assessment of tumor microarchitecture is therefore essential for capturing its spatial complexity. Micro-CT, an emerging imaging modality that offers high-resolution 3D virtual histology of soft tissues, provides a promising alternative. Combined with radiomics—a computational approach for interpretable quantification of tissue phenotypes—this technique enables a deeper understanding of tumor biology beyond visual inspection. In this study, we analyzed a large cohort of thyroid tumors (418 patients) using micro-CT imaging of next-generation tissue microarrays, from which we extracted radiomics features. We achieved robust classification of (i) neoplastic versus non-neoplastic thyroid tissues, (ii) papillary versus follicular thyroid carcinoma, and (iii) BRAF V600E mutation status. Feature interpretation using Shapley additive explanations revealed key visual traits driving these classification decisions. Preliminary results also indicated radiomic patterns associated with TERT promoter mutations, suggesting the existence of potential surrogate imaging biomarkers. Overall, micro-CT radiomics shows strong potential as a complementary tool for improving diagnostic and prognostic accuracy in thyroid cancer and offers a novel platform for quantitative pathology into the 3D spatial complexity of neoplastic tissues.