Systemic spread is an early step in breast cancer.

It is widely accepted that metastasis is a late event in cancer progression. Here, however, we show that tumor cells can disseminate systemically from earliest epithelial alterations in HER-2 and PyMT transgenic mice and from ductal carcinoma in situ in women. Wild-type mice transplanted with single premalignant HER-2 transgenic glands displayed disseminated tumor cells and micrometastasis in bone marrow and lungs. The number of disseminated cancer cells and their karyotypic abnormalities were similar for small and large tumors in patients and mouse models. When activated by bone marrow transplantation into wild-type recipients, 80 early-disseminated cancer cells sufficed to induce lethal carcinosis. Therefore, release from dormancy of early-disseminated cancer cells may frequently account for metachronous metastasis.

Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer.

Chromosomal instability in human breast cancer is known to take place before mammary neoplasias display morphological signs of invasion. We describe here the unexpected finding of a tumor cell population with normal karyotypes isolated from bone marrow of breast cancer patients. By analyzing the same single cells for chromosomal aberrations, subchromosomal allelic losses, and gene amplifications, we confirmed their malignant origin and delineated the sequence of genomic events during breast cancer progression. On this trajectory of genomic progression, we identified a subpopulation of patients with very early HER2 amplification. Because early changes have the highest probability of being shared by genetically unstable tumor cells, the genetic characterization of disseminated tumor cells provides a novel rationale for selecting patients for targeted therapies.

TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images.

Purpose: To present a deep learning segmentation model that can automatically and robustly segment all major anatomic structures on body CT images. Materials and Methods: In this retrospective study, 1204 CT examinations (from 2012, 2016, and 2020) were used to segment 104 anatomic structures (27 organs, 59 bones, 10 muscles, and eight vessels) relevant for use cases such as organ volumetry, disease characterization, and surgical or radiation therapy planning. The CT images were randomly sampled from routine clinical studies and thus represent a real-world dataset (different ages, abnormalities, scanners, body parts, sequences, and sites). The authors trained an nnU-Net segmentation algorithm on this dataset and calculated Dice similarity coefficients to evaluate the model's performance. The trained algorithm was applied to a second dataset of 4004 whole-body CT examinations to investigate age-dependent volume and attenuation changes. Results: The proposed model showed a high Dice score (0.943) on the test set, which included a wide range of clinical data with major abnormalities. The model significantly outperformed another publicly available segmentation model on a separate dataset (Dice score, 0.932 vs 0.871; P < .001). The aging study demonstrated significant correlations between age and volume and mean attenuation for a variety of organ groups (eg, age and aortic volume [rs = 0.64; P < .001]; age and mean attenuation of the autochthonous dorsal musculature [rs = -0.74; P < .001]). Conclusion: The developed model enables robust and accurate segmentation of 104 anatomic structures. The annotated dataset (https://doi.org/10.5281/zenodo.6802613) and toolkit (https://www.github.com/wasserth/TotalSegmentator) are publicly available.Keywords: CT, Segmentation, Neural Networks Supplemental material is available for this article. © RSNA, 2023See also commentary by Sebro and Mongan in this issue.

Fast purification of thioredoxin reductases and of thioredoxins with an unusual redox-active centre from anaerobic, amino-acid-utilizing bacteria.

Thioredoxin reductase and thioredoxin are primarily involved in catabolic metabolism as important electron carriers in anaerobic, amino-acid-degrading bacteria. A general and fast procedure was developed for the purification of thioredoxin reductase and thioredoxin from Eubacterium acidaminophilum, Clostridium litorale, C. sticklandii, C. sporogenes, C. cylindrosporum and 'Tissierella creatinophila' based upon their properties: the binding to 2',5'-AMP-Sepharose by thioredoxin reductase and the inability of thioredoxins to bind to a DEAE-Sephacel column. The consensus sequence at the active site of thioredoxins (-WCGPC-) was found to be modified in all of these anaerobes: Trp-31 (Escherichia coli nomenclature) was replaced by Gly or Ser, Gly-33 by Val or Glu. None of these thioredoxins reacted with thioredoxin reductase of E. coli or vice versa, but they did interact with the thioredoxin reductases obtained from the other anaerobes studied. Based upon their distinguishing features it is suggested that these thioredoxins might form an evolutionarily separate group.