ABSTRACT
A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.
Subject(s)
Breast Neoplasms , Humans , Female , Pathologists , Lymphocytes, Tumor-Infiltrating , Artificial Intelligence , PrognosisABSTRACT
Background: Differential diagnosis of rhabdomyosarcoma (RMS) is challenging. Sineoculis homeobox homolog 1 (SIX1) is an oncogene involved in skeletal muscle differentiation. We compared protein expression patterns of SIX1 in RMS and its most common differential diagnoses. Methods: SIX1 immunohistochemistry in 36 RMS and in 33 tumors from seven differential diagnostic subtypes were evaluated. The fraction of SIX1 positive tumor cells was scored by three independent observers. Results: A majority (75%) of the evaluated RMS expressed SIX1 in at least 50% of tumor cells and all except one RMS had more than 25% positive tumor cells. Neuroblastoma had less than 1% SIX1 positive tumor cells. Gonadoblastoma, malignant rhabdoid tumor, and Ewing sarcoma had 10% or less positive tumor cells. Pleuropulmonary blastoma exhibited 26-50% positive tumor cells and synovial sarcoma >50% positive cells. Conclusion: SIX1 immunohistochemistry is positive in most RMS, and occasionally in some tumors within the differential diagnoses of RMS.
Subject(s)
Biomarkers, Tumor , Rhabdomyosarcoma , Humans , Diagnosis, Differential , Biomarkers, Tumor/metabolism , Rhabdomyosarcoma/diagnosis , Rhabdomyosarcoma/pathology , Immunohistochemistry , Cell Differentiation , Homeodomain ProteinsABSTRACT
Septic shock, a serious consequence of disseminated infection that has a high mortality, is due to a dysregulated, severe immune response triggered by the infection. Acute phase reactants play key roles in sepsis, for example, hepcidin regulating iron metabolism. Reticulocyte haemoglobin (Ret-He) depends on available iron in blood, indirectly regulated by hepcidin. This study aimed at exploring rapid changes in hepcidin and Ret-He in patients with septic shock receiving adequate antibiotic treatment. Fifteen patients, included within an hour of admission to the intensive care unit, were evaluated by microbiological tests and cultures, Sequential Organ Failure Assessment score, and plasma levels of hepcidin, Ret-He, heparin-binding protein (HBP), leucocytes, C-reactive protein, procalcitonin (PCT), and lactate. Samples were taken every morning for 7 consecutive days. Maximal levels of hepcidin (median 61 nmol/L; reference 1-12 nmol/L) were seen at the time of inclusion, then declining steadily similar to PCT and lactate levels. Ret-He values decreased transiently in response to increased hepcidin, normalization occurred at 96 h upon decrease of hepcidin levels. Maximal levels of HBP were noted 24 h after inclusion. In conclusion, hepcidin promptly declined within the first 24 h in patients with septic shock receiving adequate antibiotic treatment in contrast to Ret-He and HBP.