Malignancy following solid organ transplantation: Current techniques for determination of donor versus recipient origin.

Among the post-transplantation complications that patients may encounter, the transmission of a donor-derived malignant neoplasm is uncommon but potentially life threatening. The determination of donor versus recipient origin is essential particularly in the setting of multiple transplant recipients from the donor. Advances in molecular biology now allow accurate discrimination utilizing routine tissue samples in a timely and cost-effective manner. The techniques are routinely performed in hospital molecular biology laboratories and are also available in commercial labs. The current methodologies are discussed and future possibilities are presented for clinicians caring for solid organ recipients.

A pathologist-AI collaboration framework for enhancing diagnostic accuracies and efficiencies.

In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by limitations in data collection and in model transparency and interpretability. Here we describe a digital pathology framework, nuclei.io, that incorporates active learning and human-in-the-loop real-time feedback for the rapid creation of diverse datasets and models. We validate the effectiveness of the framework via two crossover user studies that leveraged collaboration between the AI and the pathologist, including the identification of plasma cells in endometrial biopsies and the detection of colorectal cancer metastasis in lymph nodes. In both studies, nuclei.io yielded considerable diagnostic performance improvements. Collaboration between clinicians and AI will aid digital pathology by enhancing accuracies and efficiencies.

Rapid Deployment of Whole Slide Imaging for Primary Diagnosis in Surgical Pathology at Stanford Medicine: Responding to Challenges of the COVID-19 Pandemic.

CONTEXT.­: Stanford Pathology began stepwise subspecialty implementation of whole slide imaging (WSI) in 2018 soon after the first US Food and Drug Administration approval. In 2020, during the COVID-19 pandemic, the Centers for Medicare & Medicaid Services waived the requirement for pathologists to perform diagnostic tests in Clinical Laboratory Improvement Amendments (CLIA)-licensed facilities. This encouraged rapid implementation of WSI across all surgical pathology subspecialties. OBJECTIVE.­: To present our experience with validation and implementation of WSI at a large academic medical center encompassing a caseload of more than 50 000 cases per year. DESIGN.­: Validation was performed independently for 3 subspecialty services with a diagnostic concordance threshold above 95%. Analysis of user experience, staffing, infrastructure, and information technology was performed after department-wide expansion. RESULTS.­: Diagnostic concordance was achieved in 96% of neuropathology cases, 100% of gynecologic pathology cases, and 98% of immunohistochemistry cases. After full implementation, 8 high-capacity scanners were operational, with whole slide images generated on greater than 2000 slides per weekday, accounting for approximately 80% of histologic slides at Stanford Medicine. Multiple modifications in workflow and information technology were needed to improve performance. Within months of full implementation, most attending pathologists and trainees had adopted WSI for primary diagnosis. CONCLUSIONS.­: WSI across all surgical subspecialities is achievable at scale at an academic medical center; however, adoption required flexibility to adjust workflows and develop tailored solutions. WSI at scale supported the health and safety of medical staff while facilitating high-quality patient care and education during COVID-19 restrictions.

Pathology Education Powered by Virtual and Digital Transformation: Now and the Future.

CONTEXT.­: Myriad forces are changing teaching and learning strategies throughout all stages and types of pathology education. Pathology educators and learners face the challenge of adapting to and adopting new methods and tools. The digital pathology transformation and the associated educational ecosystem are major factors in this setting of change. OBJECTIVE.­: To identify and collect resources, tools, and examples of educational innovations involving digital pathology that are valuable to pathology learners and teachers at each phase of professional development. DATA SOURCES.­: Sources were a literature review and the personal experience of authors and educators. CONCLUSIONS.­: High-quality digital pathology tools and resources have permeated all the major niches within anatomic pathology and are increasingly well applied to clinical pathology for learners at all levels. Coupled with other virtual tools, the training landscape in pathology is highly enriched and much more accessible than in the past. Digital pathology is well suited to the demands of peer-to-peer education, such as in the introduction of new testing, grading, or other standardized practices. We found that digital pathology was well adapted to apply our current understanding of optimal teaching strategies and was effective at the undergraduate, graduate, postgraduate, and peer-to-peer levels. We curated and tabulated many existing resources within some segments of pathology. We identified several best practices for each training or educational stage based on current materials and proposed high-priority areas for potential future development.

Digital Image Analysis and Quantitative Bead Standards in Root Cause Analysis of Immunohistochemical Staining Variability: A Real-world Example.

Assessment of automated immunohistochemical staining platform performance is largely limited to the visual evaluation of individual slides by trained personnel. Quantitative assessment of stain intensity is not typically performed. Here we describe our experience with 2 quantitative strategies that were instrumental in root cause investigations performed to identify the sources of suboptimal staining quality (decreased stain intensity and increased variability). In addition, these tools were utilized as adjuncts in validation of a new immunohistochemical staining instrument. The novel methods utilized in the investigation include quantitative assessment of whole slide images (WSI) and commercially available quantitative calibrators. Over the course of ~13 months, these methods helped to identify and verify correction of 2 sources of suboptimal staining. One root cause of suboptimal staining was insufficient/variable power delivery from our building's electrical circuit. This led us to use uninterruptible power managers for all automated immunostainer instruments, which restored expected stain intensity and consistency. Later, we encountered one instrument that, despite passing all vendor quality control checks and not showing error alerts was suspected of yielding suboptimal stain quality. WSI analysis and quantitative calibrators provided a clear evidence that proved critical in confirming the pathologists' visual impressions. This led to the replacement of the instrument, which was then validated using a combination of standard validation metrics supplemented by WSI analysis and quantitative calibrators. These root cause analyses document 2 variables that are critical in producing optimal immunohistochemical stain results and also provide real-world examples of how the application of quantitative tools to measure automated immunohistochemical stain output can provide a greater objectivity when assessing immunohistochemical stain quality.

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.

Pitfalls in the Diagnosis of Nodular Lymphocyte Predominant Hodgkin Lymphoma: Variant Patterns, Borderlines and Mimics.

Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) represents approximately 5% of Hodgkin lymphoma and typically affects children and young adults. Although the overall prognosis is favorable, variant growth patterns in NLPHL correlate with disease recurrence and progression to T-cell/histiocyte-rich large B-cell lymphoma or frank diffuse large B-cell lymphoma (DLBCL). The diagnostic boundary between NLPHL and DLBCL can be difficult to discern, especially in the presence of variant histologies. Both diagnoses are established using morphology and immunophenotype and share similarities, including the infrequent large tumor B-cells and the lymphocyte and histiocyte-rich microenvironment. NLPHL also shows overlap with other lymphomas, particularly, classic Hodgkin lymphoma and T-cell lymphomas. Similarly, there is overlap with non-neoplastic conditions, such as the progressive transformation of germinal centers. Given the significant clinical differences among these entities, it is imperative that NLPHL and its variants are carefully separated from other lymphomas and their mimics. In this article, the characteristic features of NLPHL and its diagnostic boundaries and pitfalls are discussed. The current understanding of genetic features and immune microenvironment will be addressed, such that a framework to better understand biological behavior and customize patient care is provided.

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set.

Diffuse Large B-Cell Lymphoma (DLBCL) is the most common non-Hodgkin lymphoma. Though histologically DLBCL shows varying morphologies, no morphologic features have been consistently demonstrated to correlate with prognosis. We present a morphologic analysis of histology sections from 209 DLBCL cases with associated clinical and cytogenetic data. Duplicate tissue core sections were arranged in tissue microarrays (TMAs), and replicate sections were stained with H&E and immunohistochemical stains for CD10, BCL6, MUM1, BCL2, and MYC. The TMAs are accompanied by pathologist-annotated regions-of-interest (ROIs) that identify areas of tissue representative of DLBCL. We used a deep learning model to segment all tumor nuclei in the ROIs, and computed several geometric features for each segmented nucleus. We fit a Cox proportional hazards model to demonstrate the utility of these geometric features in predicting survival outcome, and found that it achieved a C-index (95% CI) of 0.635 (0.574,0.691). Our finding suggests that geometric features computed from tumor nuclei are of prognostic importance, and should be validated in prospective studies.

Mitochondrial fission factor (Mff) is required for organization of the mitochondrial sheath in spermatids.

BACKGROUND: Mitochondrial fission counterbalances fusion to maintain organelle morphology, but its role during development remains poorly characterized. Mammalian spermatogenesis is a complex developmental process involving several drastic changes to mitochondrial shape and organization. Mitochondria are generally small and spherical in spermatogonia, elongate during meiosis, and fragment in haploid round spermatids. Near the end of spermatid maturation, small mitochondrial spheres line the axoneme, elongate, and tightly wrap around the midpiece to form the mitochondrial sheath, which is critical for fueling flagellar movements. It remains unclear how these changes in mitochondrial morphology are regulated and how they affect sperm development. METHODS: We used genetic ablation of Mff (mitochondrial fission factor) in mice to investigate the role of mitochondrial fission during mammalian spermatogenesis. RESULTS: Our analysis indicates that Mff is required for mitochondrial fragmentation in haploid round spermatids and for organizing mitochondria in the midpiece in elongating spermatids. In Mff mutant mice, round spermatids have aberrantly elongated mitochondria that often show central constrictions, suggestive of failed fission events. In elongating spermatids and spermatozoa, mitochondrial sheaths are disjointed, containing swollen mitochondria with large gaps between organelles. These mitochondrial abnormalities in Mff mutant sperm are associated with reduced respiratory chain Complex IV activity, aberrant sperm morphology and motility, and reduced fertility. CONCLUSIONS: Mff is required for organization of the mitochondrial sheath in mouse sperm. GENERAL SIGNIFICANCE: Mitochondrial fission plays an important role in regulating mitochondrial organization during a complex developmental process.

Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

Advancing diagnostic testing capabilities such as clinical next generation sequencing methods offer the potential to diagnose, risk stratify, and guide specialized treatment, but must be balanced against the escalating costs of healthcare to identify patient cases most likely to benefit from them. Heme-STAMP (Stanford Actionable Mutation Panel for Hematopoietic and Lymphoid Malignancies) is one such next generation sequencing test. Our objective is to assess how well Heme-STAMP pathological variants can be predicted given electronic health records data available at the time of test ordering. The model demonstrated AUROC 0.74 (95% CI: [0.72, 0.76]) with 99% negative predictive value at 6% specificity. A benchmark for comparison is the prevalence of positive results in the dataset at 58.7%. Identifying patients with very low or very high predicted probabilities of finding actionable mutations (positive result) could guide more precise high-value selection of patient cases to test.

Dysphagia and Dysphonia, a Pairing of Symptoms Caused by an Unusual Pair of Diseases: Castleman's Disease and Myasthenia Gravis.

OBJECTIVES: To describe a case of coincident Castleman's disease and myasthenia gravis that initially presented as rapidly progressive dysphagia and dysphonia and to review the unique pathophysiology of these two uncommon diagnoses. METHODS: Case report and literature review. RESULTS: Castleman's disease, angiofollicular or giant lymph node hyperplasia, is a rare benign lymphoid proliferation. Traditionally, the disease is classified based on histologic and clinical characteristics. Fewer than 10 cases with concurrent myasthenia gravis have been reported. Myasthenia gravis and thymic epithelial tumors are both associated with acetylcholine receptor antibody. While patients with isolated Castleman's disease are usually asymptomatic, those who have concurrent myasthenia gravis and undergo surgical treatment are at increased risk of postoperative myasthenic crisis. Both pre- and postoperative plasmapheresis are suggested to improve muscle strength and prevent severe postoperative complications. CONCLUSIONS: In the setting of multiple cranial neuropathies including velopalatal insufficiency and bilateral ptosis it is important to consider myasthenia gravis. Castleman's disease occurs rarely in conjunction with myasthenia gravis but may increase the risk of myasthenic crisis.

Cutaneous T-cell lymphomas with pathogenic somatic mutations and absence of detectable clonal T-cell receptor gene rearrangement: two case reports.

BACKGROUND: Cutaneous T-cell lymphomas (CTCL) are a heterogeneous group of extranodal non-Hodgkin lymphomas for which diagnosis can be challenging given the potential for overlap with inflammatory dermatoses. Current diagnostic criteria for CTCL incorporate clinical and histopathologic findings as well as results of T-cell receptor (TCR) gene sequencing. Molecular interrogation of TCR genes, TRG and TRB, has proven to be a critical tool for confirming diagnoses of CTCL and for disease tracking after initiation of therapy or after stem cell transplant. Methods for confirming a diagnosis of lymphoma in the absence of TCR gene clonality are lacking. We present two patients with CTCL with pathogenic somatic mutations in the absence of TRG and TRB clonality. CASE PRESENTATIONS: Case 1: A 38-year-old male had a 19-year history of a diffuse skin rash with papulosquamous, granulomatous, and verrucous features and progressive ulcerated plaques and tumors demonstrating an atypical CD4+ T-cell infiltrate with expression of cytotoxic markers CD56, TIA-1, granzyme, and perforin on histopathology. No definitive evidence for T-cell clonality was detected by conventional PCR of 6 biopsies or by next-generation sequencing (NGS) of 14 biopsies. Somatic mutational profiling of a skin biopsy revealed pathogenic mutations in PIKC3D and TERT promoter hotspots, confirming the presence of a clonal process. Case 2: A 69-year-old male with a 13-year history of progressive, diffuse hypertrophic and eroded plaques showed an atypical CD4+ T-cell infiltrate with subset expression of TIA-1 and granzyme on histopathology. No TCR clonality was detected by TCR-NGS of 6 biopsies. Somatic mutational profiling of a skin biopsy detected a pathogenic mutation in TP53, confirming the presence of a clonal process. CONCLUSIONS: These cases highlight how detection of pathogenic somatic mutations can confirm a diagnosis of lymphoma in a clinically and histopathologically suspicious cutaneous lymphoid proliferation without detectable TCR clonality.

Mitochondrial fusion is required for spermatogonial differentiation and meiosis.

Differentiating cells tailor their metabolism to fulfill their specialized functions. We examined whether mitochondrial fusion is important for metabolic tailoring during spermatogenesis. Acutely after depletion of mitofusins Mfn1 and Mfn2, spermatogenesis arrests due to failure to accomplish a metabolic shift during meiosis. This metabolic shift includes increased mitochondrial content, mitochondrial elongation, and upregulation of oxidative phosphorylation (OXPHOS). With long-term mitofusin loss, all differentiating germ cell types are depleted, but proliferation of stem-like undifferentiated spermatogonia remains unaffected. Thus, compared with undifferentiated spermatogonia, differentiating spermatogonia and meiotic spermatocytes have cell physiologies that require high levels of mitochondrial fusion. Proteomics in fibroblasts reveals that mitofusin-null cells downregulate respiratory chain complexes and mitochondrial ribosomal subunits. Similarly, mitofusin depletion in immortalized spermatocytes or germ cells in vivo results in reduced OXPHOS subunits and activity. We reveal that by promoting OXPHOS, mitofusins enable spermatogonial differentiation and a metabolic shift during meiosis.

Pancreatic cancer 'mismatch' in Lynch syndrome.

OBJECTIVE: Immune therapy with the PD1 inhibitor pembrolizumab has been approved to treat unresectable/metastatic solid tumours exhibiting mismatch repair (MMR) deficiency. Lynch syndrome (LS), caused by autosomal dominant germline mutations of a MMR gene, predisposes to the development of MMR-deficient cancers. We report a case of MSH2-LS with an MMR-intact pancreatic ductal adenocarcinoma (PDAC) ineligible for treatment with pembrolizumab. DESIGN: Immunohistochemistry of MMR proteins was performed in each malignancy developed in a MSH2-LS patient to determine MMR status. RESULTS: The patient carried a pathogenic MSH2 germline mutation and had a history of LS-type cancers, including endometrial carcinoma, colorectal adenocarcinoma, urothelial carcinoma of the bladder and PDAC. Three malignancies (endometrial, colorectal, urothelial) lacked MSH2 and MSH6 expression, consistent with MSH2-associated tumorigenesis. However, MSH2 and MSH6 expression were intact in the PDAC, suggesting the sporadic occurrence of the pancreatic tumour unrelated to the germline MSH2 mutation. These inconsistent MMR statuses among the tumours rendered the patient ineligible for the immunotherapy pembrolizumab. CONCLUSION: Testing for MMR protein expression is recommended for each tumour in patients with LS, especially pancreatic, as discordant results may have profound effects on treatment opportunities. To our knowledge, this is the first documented case of MMR-intact PDAC in a patient with MSH2-LS.

Elimination of paternal mitochondria in mouse embryos occurs through autophagic degradation dependent on PARKIN and MUL1.

A defining feature of mitochondria is their maternal mode of inheritance. However, little is understood about the cellular mechanism through which paternal mitochondria, delivered from sperm, are eliminated from early mammalian embryos. Autophagy has been implicated in nematodes, but whether this mechanism is conserved in mammals has been disputed. Here, we show that cultured mouse fibroblasts and pre-implantation embryos use a common pathway for elimination of mitochondria. Both situations utilize mitophagy, in which mitochondria are sequestered by autophagosomes and delivered to lysosomes for degradation. The E3 ubiquitin ligases PARKIN and MUL1 play redundant roles in elimination of paternal mitochondria. The process is associated with depolarization of paternal mitochondria and additionally requires the mitochondrial outer membrane protein FIS1, the autophagy adaptor P62, and PINK1 kinase. Our results indicate that strict maternal transmission of mitochondria relies on mitophagy and uncover a collaboration between MUL1 and PARKIN in this process.