Macroscopic inelastic scattering imaging using a hyperspectral line-scanning system identifies invasive breast cancer in lumpectomy and mastectomy specimens.

Significance: Of patients with early-stage breast cancer, 60% to 75% undergo breast-conserving surgery. Of those, 20% or more need a second surgery because of an incomplete tumor resection only discovered days after surgery. An intraoperative imaging technology allowing cancer detection on the margins of breast specimens could reduce re-excision procedure rates and improve patient survival. Aim: We aimed to develop an experimental protocol using hyperspectral line-scanning Raman spectroscopy to image fresh breast specimens from cancer patients. Our objective was to determine whether macroscopic specimen images could be produced to distinguish invasive breast cancer from normal tissue structures. Approach: A hyperspectral inelastic scattering imaging instrument was used to interrogate eight specimens from six patients undergoing breast cancer surgery. Machine learning models trained with a different system to distinguish cancer from normal breast structures were used to produce tissue maps with a field-of-view of 1 cm 2 classifying each pixel as either cancer, adipose, or other normal tissues. The predictive model results were compared with spatially correlated histology maps of the specimens. Results: A total of eight specimens from six patients were imaged. Four of the hyperspectral images were associated with specimens containing cancer cells that were correctly identified by the new ex vivo pathology technique. The images associated with the remaining four specimens had no histologically detectable cancer cells, and this was also correctly predicted by the instrument. Conclusions: We showed the potential of hyperspectral Raman imaging as an intraoperative breast cancer margin assessment technique that could help surgeons improve cosmesis and reduce the number of repeat procedures in breast cancer surgery.

The NF-κB Transcription Factor c-Rel Modulates Group 2 Innate Lymphoid Cell Effector Functions and Drives Allergic Airway Inflammation.

Group 2 innate lymphoid cells (ILC2s) play a key role in the initiation and orchestration of early type 2 immune responses. Upon tissue damage, ILC2s are activated by alarmins such as IL-33 and rapidly secrete large amounts of type 2 signature cytokines. ILC2 activation is governed by a network of transcriptional regulators including nuclear factor (NF)-κB family transcription factors. While it is known that activating IL-33 receptor signaling results in downstream NF-κB activation, the underlying molecular mechanisms remain elusive. Here, we found that the NF-κB subunit c-Rel is required to mount effective innate pulmonary type 2 immune responses. IL-33-mediated activation of ILC2s in vitro as well as in vivo was found to induce c-Rel mRNA and protein expression. In addition, we demonstrate that IL-33-mediated activation of ILC2s leads to nuclear translocation of c-Rel in pulmonary ILC2s. Although c-Rel was found to be a critical mediator of innate pulmonary type 2 immune responses, ILC2-intrinsic deficiency of c-Rel did not have an impact on the developmental capacity of ILC2s nor affected homeostatic numbers of lung-resident ILC2s at steady state. Moreover, we demonstrate that ILC2-intrinsic deficiency of c-Rel alters the capacity of ILC2s to upregulate the expression of ICOSL and OX40L, key stimulatory receptors, and the expression of type 2 signature cytokines IL-5, IL-9, IL-13, and granulocyte-macrophage colony-stimulating factor (GM-CSF). Collectively, our data using Rel-/- mice suggest that c-Rel promotes acute ILC2-driven allergic airway inflammation and suggest that c-Rel may contribute to the pathophysiology of ILC2-mediated allergic airway disease. It thereby represents a promising target for the treatment of allergic asthma, and evaluating the effect of established c-Rel inhibitors in this context would be of great clinical interest.

Biological data annotation via a human-augmenting AI-based labeling system.

Biology has become a prime area for the deployment of deep learning and artificial intelligence (AI), enabled largely by the massive data sets that the field can generate. Key to most AI tasks is the availability of a sufficiently large, labeled data set with which to train AI models. In the context of microscopy, it is easy to generate image data sets containing millions of cells and structures. However, it is challenging to obtain large-scale high-quality annotations for AI models. Here, we present HALS (Human-Augmenting Labeling System), a human-in-the-loop data labeling AI, which begins uninitialized and learns annotations from a human, in real-time. Using a multi-part AI composed of three deep learning models, HALS learns from just a few examples and immediately decreases the workload of the annotator, while increasing the quality of their annotations. Using a highly repetitive use-case-annotating cell types-and running experiments with seven pathologists-experts at the microscopic analysis of biological specimens-we demonstrate a manual work reduction of 90.60%, and an average data-quality boost of 4.34%, measured across four use-cases and two tissue stain types.

Mismatch Repair Universal Screening of Endometrial Cancers (MUSE) in a Canadian Cohort.

BACKGROUND: Approximately 2-6% of endometrial cancers (ECs) are due to Lynch Syndrome (LS), a cancer predisposition syndrome caused by germline pathogenic variants (PVs) affecting the DNA mismatch repair (MMR) pathway. Increasingly, universal tissue-based screening of ECs has been proposed as an efficient and cost-effective way to identify families with LS, though few studies have been published on Canadian cohorts. The purpose of this study was to evaluate the feasibility and overall performance of a universal immunohistochemistry (IHC) screening program for women with EC within a single Canadian university hospital centre. METHODS AND RESULTS: From 1 October 2015 to 31 December 2017, all newly diagnosed ECs (n = 261) at our centre were screened for MMR protein deficiency by IHC. MMR deficiency was noted in 69 tumours (26.4%), among which 53 had somatic MLH1 promoter hypermethylation and were considered "screen-negative". The remaining MMR-deficient cases (n = 16) were considered "screen-positive" and were referred for genetic counselling and testing. Germline PVs were identified in 12/16 (75%). One additional PV was identified in a screen-negative individual who was independently referred to the Genetics service. This corresponds to an overall LS frequency of 5.0% among unselected women with EC, and 6.4% among women diagnosed under age 70 years. Our algorithm detected MMR gene pathogenic variants in 4.6% and 6.2% of unselected individuals and individuals under age 70 years, respectively. Four germline PVs (30.8%) were identified in individuals who did not meet any traditional LS screening criteria. CONCLUSIONS: Universal IHC screening for women with EC is an effective and feasible method of identifying individuals with LS in a Canadian context.

Clinical significance of isolated tumor cells and micrometastasis in low-grade, stage I endometrial cancer.

INTRODUCTION: Ultrastaging in endometrial cancer (EC) led to increased detection of isolated tumor cells (ITC, ≤0.2 mm) and micrometastases (MM, 0.2-2 mm), with unclear effect on prognosis. Our aim was to characterize the impact of ITC and MM on the outcome of these patients. METHODS: Grade 1 to 2 stage I endometrioid EC patients with nodal ITC (n = 11) or MM (n = 12) between 2012 and 2018 were retrospectively compared to a matched group of lymph node negative (n = 18) patients based on age, body mass index, grade, myometrial invasion, and lymphovascular space invasion (LVI) status using propensity score analysis (1:1). Mann-Whitney U tests were performed on continuous variables and χ2 tests on categorical variables. Progression-free survival (PFS) was the main endpoint. RESULTS: All MM and 81% of ITC had LVI. More ITC/MM patients received RT and chemotherapy (91.7% vs 18.4%; 70.8% vs 4.5%, respectively; P < 0.01) without significant difference in treatment-related toxicities (25% vs 27.3% grade 1%-2% and 20.8% vs 9.1% grade 2-3; P = 0.538) or PFS (29.2 vs 25 months; P = 0.828). Two distant recurrences occurred in MM patients after 2.5 years; one lung and one para-aortic lymph node. CONCLUSION: With adjuvant treatment, ITC/MM in otherwise well-differentiated stage I endometrial cancer have similar outcomes to matched LN- patients.

Nonhomogeneous transfer reveals specificity in speech motor learning.

Does motor learning generalize to new situations that are not experienced during training, or is motor learning essentially specific to the training situation? In the present experiments, we use speech production as a model to investigate generalization in motor learning. We tested for generalization from training to transfer utterances by varying the acoustical similarity between these two sets of utterances. During the training phase of the experiment, subjects received auditory feedback that was altered in real time as they repeated a single consonant-vowel-consonant utterance. Different groups of subjects were trained with different consonant-vowel-consonant utterances, which differed from a subsequent transfer utterance in terms of the initial consonant or vowel. During the adaptation phase of the experiment, we observed that subjects in all groups progressively changed their speech output to compensate for the perturbation (altered auditory feedback). After learning, we tested for generalization by having all subjects produce the same single transfer utterance while receiving unaltered auditory feedback. We observed limited transfer of learning, which depended on the acoustical similarity between the training and the transfer utterances. The gradients of generalization observed here are comparable to those observed in limb movement. The present findings are consistent with the conclusion that speech learning remains specific to individual instances of learning.