Synaptic plasticity in human thalamocortical assembloids.

Synaptic plasticities, such as long-term potentiation (LTP) and depression (LTD), tune synaptic efficacy and are essential for learning and memory. Current studies of synaptic plasticity in humans are limited by a lack of adequate human models. Here, we modeled the thalamocortical system by fusing human induced pluripotent stem cell-derived thalamic and cortical organoids. Single-nucleus RNA-sequencing revealed that most cells in mature thalamic organoids were glutamatergic neurons. When fused to form thalamocortical assembloids, thalamic and cortical organoids formed reciprocal long-range axonal projections and reciprocal synapses detectable by light and electron microscopy, respectively. Using whole-cell patch-clamp electrophysiology and two-photon imaging, we characterized glutamatergic synaptic transmission. Thalamocortical and corticothalamic synapses displayed short-term plasticity analogous to that in animal models. LTP and LTD were reliably induced at both synapses; however, their mechanisms differed from those previously described in rodents. Thus, thalamocortical assembloids provide a model system for exploring synaptic plasticity in human circuits.

Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning.

We demonstrate a convolutional neural network (CNN) for multi-class breast tissue classification as adipose tissue, benign dense tissue, or malignant tissue, using multi-channel optical coherence tomography (OCT) and attenuation images, and a novel Matthews correlation coefficient (MCC)-based loss function that correlates more strongly with performance metrics than the commonly used cross-entropy loss. We hypothesized that using multi-channel images would increase tumor detection performance compared to using OCT alone. 5,804 images from 29 patients were used to fine-tune a pre-trained ResNet-18 network. Adding attenuation images to OCT images yields statistically significant improvements in several performance metrics, including benign dense tissue sensitivity (68.0% versus 59.6%), malignant tissue positive predictive value (PPV) (79.4% versus 75.5%), and total accuracy (85.4% versus 83.3%), indicating that the additional contrast from attenuation imaging is most beneficial for distinguishing between benign dense tissue and malignant tissue.

Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery.

Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld QME probe, designed to interrogate the surgical cavity, can detect residual cancer directly in the breast cavity in vivo during BCS. In a first-in-human study, 21 BCS patients were scanned in vivo with the QME probe by five surgeons. For validation, protocols were developed to coregister in vivo QME with postoperative histopathology of the resected tissue to assess the capability of QME to identify residual cancer. In four cavity aspects presenting cancer and 21 cavity aspects presenting benign tissue, QME detected elevated stiffness in all four cancer cases, in contrast to low stiffness observed in 19 of the 21 benign cases. The results indicate that in vivo QME can identify residual cancer by directly imaging the surgical cavity, potentially providing a reliable intraoperative solution that can enable more complete cancer excision during BCS. SIGNIFICANCE: Optical imaging of microscale tissue stiffness enables the detection of residual breast cancer directly in the surgical cavity during breast-conserving surgery, which could potentially contribute to more complete cancer excision.

Retinoblastoma from human stem cell-derived retinal organoids.

Retinoblastoma is a childhood cancer of the developing retina that initiates with biallelic inactivation of the RB1 gene. Children with germline mutations in RB1 have a high likelihood of developing retinoblastoma and other malignancies later in life. Genetically engineered mouse models of retinoblastoma share some similarities with human retinoblastoma but there are differences in their cellular differentiation. To develop a laboratory model of human retinoblastoma formation, we make induced pluripotent stem cells (iPSCs) from 15 participants with germline RB1 mutations. Each of the stem cell lines is validated, characterized and then differentiated into retina using a 3-dimensional organoid culture system. After 45 days in culture, the retinal organoids are dissociated and injected into the vitreous of eyes of immunocompromised mice to support retinoblastoma tumor growth. Retinoblastomas formed from retinal organoids made from patient-derived iPSCs have molecular, cellular and genomic features indistinguishable from human retinoblastomas. This model of human cancer based on patient-derived iPSCs with germline cancer predisposing mutations provides valuable insights into the cellular origins of this debilitating childhood disease as well as the mechanism of tumorigenesis following RB1 gene inactivation.