Association of Genetic Variants with Postoperative Donor Artery Development in Moyamoya Disease: RNF213 and Other Moyamoya Angiopathy-Related Gene Analysis.

Robust postoperative bypass development is a characteristic of moyamoya disease (MMD); however, genetic factors mediating this phenomenon remain incompletely understood. Therefore, we aimed to elucidate the relationship between postoperative donor artery development and genetic variants. We retrospectively enrolled 63 patients (79 hemispheres) who underwent combined revascularization surgery. Postoperative development of the superficial temporal artery (STA), middle meningeal artery, and deep temporal artery (DTA) was assessed using the caliber-change ratio determined from magnetic resonance angiography measurements. We analyzed RNF213 and 36 other moyamoya angiopathy-related genes by whole-exome sequencing and extracted rare or damaging variants. Thirty-five participants carried RNF213 p.Arg4810Lys (all heterozygotes), whereas 5 had RNF213 rare variants (RVs). p.Arg4810Lys was significantly associated with postoperative DTA development, while age at surgery, hypertension, and hyperlipidemia were inversely associated. Multiple regression analysis revealed that age and p.Arg4810Lys held statistical significance (P = 0.044, coefficient - 0.015, 95% confidence interval (CI) - 0.029 to 0.000 and P = 0.001, coefficient 0.670, 95% CI 0.269 to 1.072, respectively). Those with RNF213 RV without p.Arg4810Lys exhibited a significant trend toward poor DTA development (P = 0.001). Hypertension demonstrated a significant positive association with STA development, which remained significant even after multiple regression analysis (P = 0.001, coefficient 0.303, 95% CI 0.123 to 0.482). Following Bonferroni correction for multiple comparisons, targeted analyses of RNF213 and 36 moyamoya angiopathy-related genes showed a significant association of only RNF213 p.Arg4810Lys with favorable DTA development (P = 0.001). A comprehensive analysis of RNF213, considering both p.Arg4810Lys and RVs, may provide a clearer prediction of postoperative DTA development.

Registered multi-device/staining histology image dataset for domain-agnostic machine learning models.

Variations in color and texture of histopathology images are caused by differences in staining conditions and imaging devices between hospitals. These biases decrease the robustness of machine learning models exposed to out-of-domain data. To address this issue, we introduce a comprehensive histopathology image dataset named PathoLogy Images of Scanners and Mobile phones (PLISM). The dataset consisted of 46 human tissue types stained using 13 hematoxylin and eosin conditions and captured using 13 imaging devices. Precisely aligned image patches from different domains allowed for an accurate evaluation of color and texture properties in each domain. Variation in PLISM was assessed and found to be significantly diverse across various domains, particularly between whole-slide images and smartphones. Furthermore, we assessed the improvement in domain shift using a convolutional neural network pre-trained on PLISM. PLISM is a valuable resource that facilitates the precise evaluation of domain shifts in digital pathology and makes significant contributions towards the development of robust machine learning models that can effectively address challenges of domain shift in histological image analysis.

Stomach encyclopedia: Combined single-cell and spatial transcriptomics reveal cell diversity and homeostatic regulation of human stomach.

The stomach is an important digestive organ with various biological functions. However, because of the complexity of its cellular and glandular composition, its precise cellular biology has yet to be elucidated. In this study, we conducted single-cell RNA sequencing (scRNA-seq) and subcellular-level spatial transcriptomics analysis of the human stomach and constructed the largest dataset to date: a stomach encyclopedia. This dataset consists of approximately 380,000 cells from scRNA-seq and the spatial transcriptome, enabling integrated analyses of transcriptional and spatial information of gastric and metaplastic cells. This analysis identified LEFTY1 as an uncharacterized stem cell marker, which was confirmed through lineage tracing analysis. A wide variety of cell-cell interactions between epithelial and stromal cells, including PDGFRA+BMP4+WNT5A+ fibroblasts, was highlighted in the developmental switch of intestinal metaplasia. Our extensive dataset will function as a fundamental resource in investigations of the stomach, including studies of development, aging, and carcinogenesis.

Meningiomas in patients with neurofibromatosis type 2 predominantly comprise 'immunogenic subtype' tumours characterised by macrophage infiltration.

Although recent molecular analyses revealed that sporadic meningiomas have various genetic, epigenetic, and transcriptomic profiles, meningioma in patients with neurofibromatosis type 2 (NF2) have not been fully elucidated. This study investigated meningiomas' clinical, histological, and molecular characteristics in NF2 patients. A long-term retrospective follow-up (13.5 ± 5.5 years) study involving total 159 meningiomas in 37 patients with NF2 was performed. Their characteristics were assessed using immunohistochemistry (IHC), bulk-RNA sequencing, and copy number analysis. All variables of meningiomas in patients with NF2 were compared with those in 189 sporadic NF2-altered meningiomas in 189 patients. Most meningiomas in NF2 patients were stable, and the mean annual growth rate was 1.0 ± 1.8 cm3/year. Twenty-eight meningiomas (17.6%) in 25 patients (43.1%) were resected during the follow-up period. WHO grade I meningiomas in patients with NF2 were more frequent than in sporadic NF2-altered meningiomas (92.9% vs. 80.9%). Transcriptomic analysis for patients with NF2/sporadic NF2-altered WHO grade I meningiomas (n = 14 vs. 15, respectively) showed that tumours in NF2 patients still had a higher immune response and immune cell infiltration than sporadic NF2-altered meningiomas. Furthermore, RNA-seq/IHC-derived immunophenotyping corroborated this enhanced immune response by identifying myeloid cell infiltration, particularly in macrophages. Clinical, histological, and transcriptomic analyses of meningiomas in patients with NF2 demonstrated that meningiomas in NF2 patients showed less aggressive behaviour than sporadic NF2-altered meningiomas and elicited a marked immune response by identifying myeloid cell infiltration, particularly of macrophages.

Meet the authors: Daisuke Komura and Shumpei Ishikawa.

In this People of Data, Cell Press Community Review Scientific Editor Leia Judge talks to lead author Dr. Daisuke Komura and Principal Investigator Prof. Shumpei Ishikawa about their paper "Restaining-based annotation for cancer histology segmentation to overcome annotation-related limitations among pathologists," which was published in the February issue of Patterns, and their experiences with Cell Press Community Review.

RNF213 p.Arg4810Lys Wild Type is Associated with De Novo Hemorrhage in Asymptomatic Hemispheres with Moyamoya Disease.

Clinical implications of RNF213 genetic variants, other than p.Arg4810Lys, in moyamoya disease (MMD), remain unclear. This study aimed to investigate the association of RNF213 variants with clinical phenotypes in MMD. This retrospective cohort study collected data regarding the clinical characteristics of 139 patients with MMD and evaluated the angioarchitectures of 253 hemispheres using digital subtraction angiography at diagnosis. All RNF213 exons were sequenced, and the associations of clinical characteristics and angiographical findings with p.Arg4810Lys, p.Ala4399Thr, and other rare variants (RVs) were examined. Among 139 patients, 100 (71.9%) had p.Arg4810Lys heterozygote (GA) and 39 (28.1%) had the wild type (GG). Fourteen RVs were identified and detetcted in 15/139 (10.8%) patients, and p.Ala4399Thr was detected in 17/139 (12.2%) patients. Hemispheres with GG and p.Ala4399Thr presented with significantly less ischemic events and more hemorrhagic events at diagnosis (p = 0.001 and p = 0.028, respectively). In asymptomatic hemispheres, those with GG were more susceptible to de novo hemorrhage than those with GA (adjusted hazard ratio [aHR] 5.36) with an increased risk when accompanied by p.Ala4399Thr or RVs (aHR 15.22 and 16.60, respectively). Within the choroidal anastomosis-positive hemispheres, GG exhibited a higher incidence of de novo hemorrhage than GA (p = 0.004). The GG of p. Arg4810Lys was a risk factor for de novo hemorrhage in asymptomatic MMD hemispheres. This risk increased with certain other variants and is observed in choroidal anastomosis-positive hemispheres. A comprehensive evaluation of RNF213 variants and angioarchitectures is essential for predicting the phenotype of asymptomatic hemispheres in MMD.

Restaining-based annotation for cancer histology segmentation to overcome annotation-related limitations among pathologists.

Numerous cancer histopathology specimens have been collected and digitized over the past few decades. A comprehensive evaluation of the distribution of various cells in tumor tissue sections can provide valuable information for understanding cancer. Deep learning is suitable for achieving these goals; however, the collection of extensive, unbiased training data is hindered, thus limiting the production of accurate segmentation models. This study presents SegPath-the largest annotation dataset (>10 times larger than publicly available annotations)-for the segmentation of hematoxylin and eosin (H&E)-stained sections for eight major cell types in cancer tissue. The SegPath generating pipeline used H&E-stained sections that were destained and subsequently immunofluorescence-stained with carefully selected antibodies. We found that SegPath is comparable with, or outperforms, pathologist annotations. Moreover, annotations by pathologists are biased toward typical morphologies. However, the model trained on SegPath can overcome this limitation. Our results provide foundational datasets for machine-learning research in histopathology.

Multiancestry genomic and transcriptomic analysis of gastric cancer.

Gastric cancer is among the most common malignancies worldwide, characterized by geographical, epidemiological and histological heterogeneity. Here, we report an extensive, multiancestral landscape of driver events in gastric cancer, involving 1,335 cases. Seventy-seven significantly mutated genes (SMGs) were identified, including ARHGAP5 and TRIM49C. We also identified subtype-specific drivers, including PIGR and SOX9, which were enriched in the diffuse subtype of the disease. SMGs also varied according to Epstein-Barr virus infection status and ancestry. Non-protein-truncating CDH1 mutations, which are characterized by in-frame splicing alterations, targeted localized extracellular domains and uniquely occurred in sporadic diffuse-type cases. In patients with gastric cancer with East Asian ancestry, our data suggested a link between alcohol consumption or metabolism and the development of RHOA mutations. Moreover, mutations with potential roles in immune evasion were identified. Overall, these data provide comprehensive insights into the molecular landscape of gastric cancer across various subtypes and ancestries.

Deep texture representation analysis for histopathological images.

Deep texture representations (DTRs) produced from a bilinear convolutional neural network allow objective quantification of tumor histopathology images effectively. They can be used for various analyses, including visualization of morphological correlation between histology images, content-based image retrieval (CBIR), and supervised learning. This protocol describes the simplified workflow to analyze DTRs from data preparation, visualization of the histological profile, and CBIR analysis, to supervised learning model development to predict the profile from histological images. For complete details on the use and execution of this protocol, please refer to Komura et al. (2022).1.

Aberrant Cadherin11 expression predicts distant metastasis of gastric cancer.

The prognosis of gastric cancer (GC) is significantly affected by distant metastases and postoperative recurrences. Bone metastasis is one of the worst prognostic metastases in GC; however, its molecular mechanisms and predictive biomarkers remain elusive. In prostate and breast cancers, it has been reported that overexpression of Cadherin 11 (CDH11), a mesenchymal cell-cell contact factor, is known to be correlated with bone metastasis. Overexpression of CDH11 mRNA in bulk GC tissues has also been reported to be associated with a worse prognosis. However, a more precise evaluation of CDH11 expression in GC cells is necessary to establish a robust link between CDH11 and metastatic features of GC. We performed immunohistochemical analysis of CDH11 expression in 342 GC cases, of which specimens were obtained at the time of surgery, with a special focus on its aberrant membranous expression in GC cells. The correlations between aberrant CDH11 expression and distant metastases and the prognosis of GC cases were statistically investigated. Approximately half of the GC cases investigated showed aberrant expression of CDH11 in the GC cells of primary lesions. Aberrant CDH11 expression was statistically associated with bone metastasis of GCs. Moreover, metastases to the liver and distant lymph nodes were also statistically correlated with CDH11 expression. Aberrant CDH11 expression in GC cells in primary tumor lesions was shown to be a predictive biomarker of distant metastases in GC. GCs with CDH11 expression require preventive clinical attention for the detection of metastatic lesions.

Immune repertoire profiling for disease pathobiology.

Lymphocytes consist of highly heterogeneous populations, each expressing a specific cell surface receptor corresponding to a particular antigen. Lymphocytes are both the cause and regulator of various diseases, including autoimmune/allergic diseases, lifestyle diseases, neurodegenerative diseases, and cancers. Recently, immune repertoire sequencing has attracted much attention because it helps obtain global profiles of the immune receptor sequences of infiltrating T and B cells in specimens. Immune repertoire sequencing not only helps deepen our understanding of the molecular mechanisms of immune-related pathology but also assists in discovering novel therapeutic modalities for diseases, thereby shedding colorful light on otherwise tiny monotonous cells when observed under a microscope. In this review article, we introduce and detail the background and methodology of immune repertoire sequencing and summarize recent scientific achievements in association with human diseases. Future perspectives on this genetic technique in the field of histopathological research will also be discussed.

Somatic GJA4 gain-of-function mutation in orbital cavernous venous malformations.

Orbital cavernous venous malformation (OCVM) is a sporadic vascular anomaly of uncertain etiology characterized by abnormally dilated vascular channels. Here, we identify a somatic missense mutation, c.121G > T (p.Gly41Cys) in GJA4, which encodes a transmembrane protein that is a component of gap junctions and hemichannels in the vascular system, in OCVM tissues from 25/26 (96.2%) individuals with OCVM. GJA4 expression was detected in OCVM tissue including endothelial cells and the stroma, through immunohistochemistry. Within OCVM tissue, the mutation allele frequency was higher in endothelial cell-enriched fractions obtained using magnetic-activated cell sorting. Whole-cell voltage clamp analysis in Xenopus oocytes revealed that GJA4 c.121G > T (p.Gly41Cys) is a gain-of-function mutation that leads to the formation of a hyperactive hemichannel. Overexpression of the mutant protein in human umbilical vein endothelial cells led to a loss of cellular integrity, which was rescued by carbenoxolone, a non-specific gap junction/hemichannel inhibitor. Our data suggest that GJA4 c.121G > T (p.Gly41Cys) is a potential driver gene mutation for OCVM. We propose that hyperactive hemichannel plays a role in the development of this vascular phenotype.

Nucleic acid-triggered tumoral immunity propagates pH-selective therapeutic antibodies through tumor-driven epitope spreading.

Important roles of humoral tumor immunity are often pointed out; however, precise profiles of dominant antigens and developmental mechanisms remain elusive. We systematically investigated the humoral antigens of dominant intratumor immunoglobulin clones found in human cancers. We found that approximately half of the corresponding antigens were restricted to strongly and densely negatively charged polymers, resulting in simultaneous reactivities of the antibodies to both densely sulfated glycosaminoglycans (dsGAGs) and nucleic acids (NAs). These anti-dsGAG/NA antibodies matured and expanded via intratumoral immunological driving force of innate immunity via NAs. These human cancer-derived antibodies exhibited acidic pH-selective affinity across both antigens and showed specific reactivity to diverse spectrums of human tumor cells. The antibody-drug conjugate exerted therapeutic effects against multiple cancers in vivo by targeting cell surface dsGAG antigens. This study reveals that intratumoral immunological reactions propagate tumor-oriented immunoglobulin clones and demonstrates a new therapeutic modality for the universal treatment of human malignancies.

Functional genomics screening identifies aspartyl-tRNA synthetase as a novel prognostic marker and a therapeutic target for gastric cancers.

Efficient molecular targeting therapies for most gastric cancers (GCs) are currently lacking, despite GC being one of the most frequent and often devastating malignancies worldwide. Thus, identification of novel therapeutic targets for GC is in high demand. Recent advancements of high-throughput nucleic acid synthesis methods combined with next-generation sequencing (NGS) platforms have made it feasible to conduct functional genomics screening using large-scale pooled lentiviral libraries aimed at discovering novel cancer therapeutic targets. In this study, we performed NGS-based functional genomics screening for human GC cell lines using an originally constructed 6,399 shRNA library targeting all 2,096 human metabolism genes. Our screening identified aspartyl-tRNA synthetase (DARS) as a possible candidate for a therapeutic target for GC. In-house tissue microarrays containing 346 cases of GC combined with public datasets showed that patients with high expression levels of DARS protein exhibited more advanced clinicopathologic parameters and a worse prognosis, specifically among diffuse-type GC patients. Both in vitro and in vivo experiments concretely evidenced that DARS inhibition achieved robust growth suppression of GC cells. Moreover, RNA sequencing of GC cell lines under shRNA-mediated DARS knockdown suggested that DARS inhibition exerts its effect through the inactivation of multiple p-ERK pathways. This MAPK-related growth suppression by DARS inhibition would also be applicable to other cancers; thus, it is warranted to investigate the expression and clinical significance of DARS in a wide spectrum of malignancies. Taken together, NGS-based high-throughput pooled lentiviral screening showed DARS as a novel prognostic marker and a promising therapeutic target for GC. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Clinical significance of NF2 alteration in grade I meningiomas revisited; prognostic impact integrated with extent of resection, tumour location, and Ki-67 index.

NF2 alteration is the most commonly-found genetic abnormality in meningiomas and is known to initiate events for aggressive-type meningiomas. Whereas the prognosis of meningiomas differs depending on their epigenomic/transcriptomic profile, the effect of NF2 alteration on the prognosis of benign meningiomas is not fully elucidated. This study aimed to probe the importance of NF2 alteration in prognosis of WHO grade I meningiomas. A long-term retrospective follow-up (5.3 ± 4.5 years) study involving 281 consecutive WHO grade I meningioma patients was performed. We assessed tumour recurrence in correlation with extent of resection (EOR), histopathological findings, tumour location, and NF2 alteration. "NF2 meningioma" was defined as meningiomas with presence of NF2 mutation and/or 22q loss. Overall, NF2 meningioma per se was not a predictor of prognosis in the whole cohort; however, it was a predictor of recurrence in supratentorial meningiomas, together with EOR and Ki-67. In a striking contrast, NF2 meningioma showed a better prognosis than non-NF2 meningioma in infratentorial lesion. Supratentorial NF2 meningiomas had higher Ki-67 and forkhead box protein M1 expression than those of others, possibly explaining the worse prognosis in this subtype. The combination of NF2 alteration, high Ki-67 and supratentorial location defines subgroup with the worst prognosis among WHO grade I meningiomas. Clinical connotation of NF2 alteration in terms of prognosis of WHO grade I meningioma differs in an opposite way between supratentorial and infratentorial tumors. Integrated anatomical, histopathological, and genomic classifications will provide the best follow-up schedule and proactive measures.

Universal encoding of pan-cancer histology by deep texture representations.

Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the direct comparison and accumulation of large-scale datasets. Here, we show successful universal encoding of cancer histology by deep texture representations (DTRs) produced by a bilinear convolutional neural network. DTR-based, unsupervised histological profiling, which captures the morphological diversity, is applied to cancer biopsies and reveals relationships between histologic characteristics and the response to immune checkpoint inhibitors (ICIs). Content-based image retrieval based on DTRs enables the quick retrieval of histologically similar images using The Cancer Genome Atlas (TCGA) dataset. Furthermore, via comprehensive comparisons with driver and clinically actionable gene mutations, we successfully predict 309 combinations of genomic features and cancer types from hematoxylin-and-eosin-stained images. With its mounting capabilities on accessible devices, such as smartphones, universal encoding for cancer histology has a strong impact on global equalization for cancer diagnosis and therapies.

Viola: a structural variant signature extractor with user-defined classifications.

SUMMARY: Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g. cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data. AVAILABILITY AND IMPLEMENTATION: Viola is available on pip (https://pypi.org/project/Viola-SV/) and the source code is on GitHub (https://github.com/dermasugita/Viola-SV). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic landscape of a mouse model of diffuse-type gastric adenocarcinoma.

BACKGROUND: There is a need for a model of diffuse-type gastric cancer that captures the features of the disease, facilitates the study of its mechanisms, and aids the development of potential therapies. One such model may be Cdh1 and Trp53 double conditional knockout (DCKO) mice, which have histopathological features similar to those of human diffuse-type gastric cancer. However, a genomic profile of this mouse model has yet to be completed. METHODS: Whole-genome sequences of tumors from eight DCKO mice were analyzed and their molecular features were compared with those of human gastric adenocarcinoma. RESULTS: DCKO mice gastric cancers harbored single nucleotide variations and indel patterns comparable to those of human genomically stable gastric cancers, whereas their copy number variation fraction and ploidy were more similar to human chromosomal instability gastric cancers (perhaps due to Trp53 knockout). Copy number variations dominated changes in cancer-related genes in DCKO mice, with typical high-level amplifications observed for oncogenic drivers, e.g., Myc, Ccnd1, and Cdks, as well as gastrointestinal transcription factors, e.g., Gata4, Foxa1, and Sox9. Interestingly, frequent alterations in gastrointestinal transcription factors in DCKO mice indicated their potential role in tumorigenesis. Furthermore, mouse gastric cancer had a reproducible but smaller number of mutational signatures than human gastric cancer, including the potentially acid-related signature 17, indicating shared tumorigenic etiologies in humans and mice. CONCLUSIONS: Cdh1/Trp53 DCKO mice have similar genomic features to those found in human gastric cancer; hence, this is a suitable model for further studies of diffuse-type gastric cancer mechanisms and therapies.

Brainstem intraparenchymal schwannoma with genetic analysis: a case report and literature review.

BACKGROUND: Schwannomas are neoplasms that typically arise from the myelin sheath of peripheral nerves and rarely originate within the brain parenchyma. Some case reports present schwannomas arising from the brainstem, but regrowth of the tumor and the efficacy of postoperative irradiation have not been examined. In addition, the genetic background of schwannomas arising from the brainstem has not been investigated. CASE PRESENTATION: A 21-year-old male presented with diplopia, dysphagia, and left-sided hemiparesis, dysesthesia, and ataxia. Intracranial imaging showed a heterogeneous mass with a cystic lesion in the pontomedullary junction. Since the tumor caused obstructive hydrocephalus, the patient underwent subtotal tumor resection. A histopathologic evaluation aided a diagnosis of brainstem intraparenchymal schwannoma. Gradual postoperative mass regrowth was recognized. Three-dimensional conformal radiotherapy was performed on the residual mass and surgical cavity. No tumor regrowth was observed 4 years after surgery. To investigate the genetic background of the tumor, target sequences for 36 genes, including NF2, SMARCB1, and LZTR1, and microsatellite analysis for loss of 22q did not show any somatic variants or 22q loss. CONCLUSIONS: We suggest that brainstem schwannomas might differ from conventional schwannomas in their genetic background.

Helicobacter pylori CagA elicits BRCAness to induce genome instability that may underlie bacterial gastric carcinogenesis.

Infection with CagA-producing Helicobacter pylori plays a causative role in the development of gastric cancer. Upon delivery into gastric epithelial cells, CagA deregulates prooncogenic phosphatase SHP2 while inhibiting polarity-regulating kinase PAR1b through complex formation. Here, we show that CagA/PAR1b interaction subverts nuclear translocation of BRCA1 by inhibiting PAR1b-mediated BRCA1 phosphorylation. It hereby induces BRCAness that promotes DNA double-strand breaks (DSBs) while disabling error-free homologous recombination-mediated DNA repair. The CagA/PAR1b interaction also stimulates Hippo signaling that circumvents apoptosis of DNA-damaged cells, giving cells time to repair DSBs through error-prone mechanisms. The DSB-activated p53-p21Cip1 axis inhibits proliferation of CagA-delivered cells, but the inhibition can be overcome by p53 inactivation. Indeed, sequential pulses of CagA in TP53-mutant cells drove somatic mutation with BRCAness-associated genetic signatures. Expansion of CagA-delivered cells with BRCAness-mediated genome instability, from which CagA-independent cancer-predisposing cells arise, provides a plausible "hit-and-run mechanism" of H. pylori CagA for gastric carcinogenesis.