Radon concentration in seawater as a geochemical indicator of submarine fault activity in the Yatsushiro Sea, Japan.

This study examined the relationship between radon (222Rn) concentrations in seawater and crustal activity in the Yatsushiro Sea by investigating the submarine fault zone situated at the southern end of the Futagawa-Hinagu fault zone, activated by the 2016 Kumamoto earthquake (M7.3). We conducted an analysis of 222Rn concentration in samples of bottom water just above the seafloor and pore water in sediments, utilizing multiple and piston cores from the Hakuho Maru Expedition KH18-3. The findings revealed significantly elevated 222Rn concentrations in the central sites of the Yatsushiro Sea, coinciding with a high-stress field exhibiting dense active faults. Seismicity analysis revealed heightened moment release and a low b-value post the 2016 Kumamoto earthquake, indicative of increased seismic activity and the potential for substantial earthquakes in the Yatsushiro Sea vicinity. Our results indicate that heightened concentrations of 222Rn in seawater can serve as an effective tracer for identifying and estimating submarine fault activities. Moreover, our research highlights the utility of 222Rn concentrations in detecting active submarine faults and assessing their activity. It contributes to a comprehensive understanding of the potential for significant earthquakes in the Yatsushiro Sea in the future.

Structural and surface characterizations of 2D ß-In2Se3/3D ß-Ga2O3 heterostructures grown on c-Sapphire substrates by molecular beam epitaxy.

Integrating two-dimensional (2D) layered materials with wide bandgap ß-Ga2O3 has unveiled impressive opportunities for exploring novel physics and device concepts. This study presents the epitaxial growth of 2D ß-In2Se3/3D ß-Ga2O3 heterostructures on c-Sapphire substrates by plasma-assisted molecular beam epitaxy. Firstly, we employed a temperature-dependent two-step growth process to deposit Ga2O3 and obtained a phase-pure ( 2 ¯ 01 ) ß-Ga2O3 film on c-Sapphire. Interestingly, the in-situ reflective high-energy electron diffraction (RHEED) patterns observed from this heterostructure revealed the in-plane 'b' lattice constant of ß-Ga2O3 ~ 3.038Å. In the next stage, for the first time, 2D In2Se3 layers were epitaxially realized on 3D ß-Ga2O3 under varying substrate temperatures (Tsub) and Se/In flux ratios (RVI/III). The deposited layers exhibited (00l) oriented ß-In2Se3 on ( 2 ¯ 01 ) ß-Ga2O3/c-Sapphire with the epitaxial relationship of [ 11 2 ¯ 0 ] ß-In2Se3 || [010] ß-Ga2O3 and [ 10 1 ¯ 0 ] ß-In2Se3 || [102] ß-Ga2O3 as observed from the RHEED patterns. Also, the in-plane 'a' lattice constant of ß-In2Se3 was determined to be ~ 4.027Å. The single-phase ß-In2Se3 layers with improved structural and surface quality were achieved at a Tsub ~ 280 °C and RVI/III ~ 18. The microstructural and detailed elemental analysis further confirmed the epitaxy of 2D layered ß-In2Se3 on 3D ß-Ga2O3, a consequence of the quasi-van der Waals epitaxy. Furthermore, the ß-Ga2O3 with an optical bandgap (Eg) of ~ 5.04 eV (deep ultraviolet) when integrated with 2D ß-In2Se3, Eg ~ 1.43eV (near infra-red) can reveal potential applications in the optoelectronic field.

Development and Validation of a 3D Resnet Model for Prediction of Lymph Node Metastasis in Head and Neck Cancer Patients.

The accurate diagnosis and staging of lymph node metastasis (LNM) are crucial for determining the optimal treatment strategy for head and neck cancer patients. We aimed to develop a 3D Resnet model and investigate its prediction value in detecting LNM. This study enrolled 156 head and neck cancer patients and analyzed 342 lymph nodes segmented from surgical pathologic reports. The patients' clinical and pathological data related to the primary tumor site and clinical and pathology T and N stages were collected. To predict LNM, we developed a dual-pathway 3D Resnet model incorporating two Resnet models with different depths to extract features from the input data. To assess the model's performance, we compared its predictions with those of radiologists in a test dataset comprising 38 patients. The study found that the dimensions and volume of LNM + were significantly larger than those of LNM-. Specifically, the Y and Z dimensions showed the highest sensitivity of 84.6% and specificity of 72.2%, respectively, in predicting LNM + . The analysis of various variations of the proposed 3D Resnet model demonstrated that Dual-3D-Resnet models with a depth of 34 achieved the highest AUC values of 0.9294. In the validation test of 38 patients and 86 lymph nodes dataset, the 3D Resnet model outperformed both physical examination and radiologists in terms of sensitivity (80.8% compared to 50.0% and 91.7%, respectively), specificity(90.0% compared to 88.5% and 65.4%, respectively), and positive predictive value (77.8% compared to 66.7% and 55.0%, respectively) in detecting individual LNM + . These results suggest that the 3D Resnet model can be valuable for accurately identifying LNM + in head and neck cancer patients. A prospective trial is needed to evaluate further the role of the 3D Resnet model in determining LNM + in head and neck cancer patients and its impact on treatment strategies and patient outcomes.

Heterogeneity of cancer stem cell-related marker expression is associated with three-dimensional structures in malignant pleural effusion produced by lung adenocarcinoma.

INTRODUCTION: Cancer stem cells have been described in lung adenocarcinoma-associated malignant pleural effusion. They show clinically important features, including the ability to initiate new tumours and resistance to treatments. However, their correlation with the three-dimensional tumour structures in the effusion is not well understood. METHODS: Cell blocks produced from lung adenocarcinoma patients' pleural effusion were examined for cancer stem cell-related markers Nanog and CD133 using immunocytochemistry. The three-dimensional cancer cell structures and CD133 expression patterns were visualized with tissue-clearing technology. The expression patterns were correlated with tumour cell structures, genetic variants and clinical outcomes. RESULTS: Thirty-nine patients were analysed. Moderate-to-strong Nanog expression was detected in 27 cases (69%), while CD133 was expressed by more than 1% of cancer cells in 11 cases (28%). Nanog expression was more homogenous within individual specimens, while CD133 expression was detected in single tumour cells or cells within small clusters instead of larger structures in 8 of the 11 positive cases (73%). Although no statistically significant correlation between the markers and tumour genetic variants or patient survival was observed, we recorded seven cases with follow-up specimens after cancer treatment, and four (57%) showed a change in stem cell-related marker expression corresponding to treatment response. CONCLUSIONS: Lung adenocarcinoma cells in the pleural effusion show variable expression of cancer stem cell-related markers, some showing a correlation with the size of cell clusters. Their expression level is potentially correlated with cancer treatment effects.

Haematopoietic cell-derived exosomes in cancer development and therapeutics: From basic science to clinical practice.

BACKGROUND: The tumour microenvironment (TME) is a specialised niche involving intercellular communication among cancer cells and various host cells. Among the host cells, the quantity and quality of immune cells within the TME play essential roles in cancer development and management. The immunologically suppressive, so-called 'cold' TME established by a series of tumour-host interactions, including generating immunosuppressive cytokines and recruiting regulatory host immune cells, is associated with resistance to therapies and worse clinical outcomes. MAIN BODY: Various therapeutic approaches have been used to target the cold TME, including immune checkpoint blockade therapy and adoptive T-cell transfer. A promising, less explored therapeutic strategy involves targeting TME-associated exosomes. Exosomes are nanometer-sized, extracellular vesicles that transfer material from donor to recipient cells. These particles can reprogram the recipient cells and modulate the TME. In particular, exosomes from haematopoietic cells are known to promote or suppress cancer progression under specific conditions. Understanding the effects of haematopoietic cell-secreted exosomes may foster the development of therapeutic exosomes (tExos) for personalised cancer treatment. However, the development of exosome-based therapies has unique challenges, including scalable production, purification, storage and delivery of exosomes and controlling batch variations. Clinical trials are being conducted to verify the safety, feasibility, availability and efficacy of tExos. CONCLUSION: This review summarises our understanding of how haematopoietic cell-secreted exosomes regulate the TME and antitumour immunity and highlights present challenges and solutions for haematopoietic cell-derived exosome-based therapies.

Genomic Profiling With Large-Scale Next-Generation Sequencing Panels Distinguishes Separate Primary Lung Adenocarcinomas From Intrapulmonary Metastases.

The distinction between different separate primary lung cancers (SPLCs) and intrapulmonary metastases (IPMs) is a challenging but clinically significant issue. Histopathology-based classification is the current practice; however, it is subjective and affected by interobserver variability. Recently, next-generation sequencing (NGS) panels have been used in lung cancer diagnostics. This study aimed to investigate the value of large-scale NGS panels for distinguishing between SPLCs and IPMs. A total of 32 patients with 69 lung adenocarcinomas were included. Comprehensive histopathologic assessments of multiple pulmonary adenocarcinomas were performed independently by 3 pathologists. The consensus of histopathologic classification was determined by a majority vote. Genomic analysis was performed using an amplicon-based large-scale NGS panel, targeting single-nucleotide variants and short insertions and deletions in 409 genes. Tumor pairs were classified as SPLCs or IPMs according to a predefined molecular classification algorithm. Using NGS and our molecular classification algorithm, 97.6% of the tumor pairs can be unambiguously classified as SPLCs or IPMs. The molecular classification was predictive of postoperative clinical outcomes in terms of overall survival (P = .015) and recurrence-free interval (P = .0012). There was a moderate interobserver agreement regarding histopathologic classification (κ = 0.524 at the tumor pair level). The concordance between histopathologic and molecular classification was 100% in cases where pathologists reached a complete agreement but only 53.3% where they did not. This study showed that large-scale NGS panels are a powerful modality that can help distinguish SPLCs from IPMs in patients with multiple lung adenocarcinomas and objectively provide accurate risk stratification.

Stereotactic radiosurgery for pituitary and cavernous sinus metastases.

PURPOSE: Metastases extending to the pituitary gland and cavernous sinus are extremely rare; however, advances in neuroimaging have increased the reported incidence. Stereotactic radiosurgery (SRS) affords the precise delivery of focused radiation to minimize adverse radiation effects. This study assessed the efficacy and safety of SRS in the treatment of pituitary and cavernous sinus metastases. METHODS: Analysis was performed on 23 patients with pituitary and cavernous sinus metastases who underwent treatment using SRS between 1996 and 2021. The cohort was categorized into 2 groups in terms of metastasis location: pituitary involvement (Group 1, n = 11) and cavernous sinus involvement (Group 2, n = 12). Overall survival, local tumor control, and distal tumor control rates were compared between the two groups using Kaplan-Meier analysis. RESULTS: The median age of the cohort was 52.2 years and the median tumor volume was 4.5 mL. Overall survival rates were as follows: 1 year (72.9%), 2 years (51.8%), and 3 years (45.3%). Local tumor control rates were as follows: 1 year (82.3%), 2 years (82.3%), and 3 years (65.9%). Visual deficit and hypopituitarism were the most common presentations in Group 1, whereas cranial nerve deficit was the most common presentation in Group 2. CONCLUSIONS: SRS appears to be a safe and effective therapy for the treatment of pituitary and cavernous sinus metastases. GKRS is a relatively simple procedure, which places minimal stress on the patient, thereby facilitating further anti-cancer treatment. Considering the limited survival duration in cases of metastasis, it is very likely that post-GKRS complications (e.g., new onset cranial nerve deficit and hypopituitarism) would not become an issue before patient passes away.

Application of artificial intelligence to stereotactic radiosurgery for intracranial lesions: detection, segmentation, and outcome prediction.

BACKGROUND: Rapid evolution of artificial intelligence (AI) prompted its wide application in healthcare systems. Stereotactic radiosurgery served as a good candidate for AI model development and achieved encouraging result in recent years. This article aimed at demonstrating current AI application in radiosurgery. METHODS: Literatures published in PubMed during 2010-2022, discussing AI application in stereotactic radiosurgery were reviewed. RESULTS: AI algorithms, especially machine learning/deep learning models, have been administered to different aspect of stereotactic radiosurgery. Spontaneous tumor detection and automated lesion delineation or segmentation were two of the promising application, which could be further extended to longitudinal treatment follow-up. Outcome prediction utilized machine learning algorithms with radiomic-based analysis was another well-established application. CONCLUSIONS: Stereotactic radiosurgery has taken a lead role in AI development. Current achievement, limitation, and further investigation was summarized in this article.

Genomic profiling with whole-exome sequencing revealed distinct mutations and novel pathways in Asian melanoma.

The clinical characteristics of malignant melanoma are highly variable between patient populations of different ethnicities. To explore the underlining genetic variations, we reviewed the clinical data of 242 malignant melanoma cases from Taiwan and among them submitted formalin-fixed paraffin-embedded tissue samples from 37 patients for whole-exome sequencing to identify the mutational signatures, tumor mutation burden and specific gene mutations. The genomic profiles and clinical outcomes were compared with the information derived from the publicly available TCGA and TGEN databases. Mutation signature 12 was the dominant signature in Taiwanese patients and represented approximately 45% of the mutation signatures observed. In contrast, mutation signature 7 was the most prominent among cases available in the TCGA database. Common gene mutations found in the TCGA melanoma dataset were not frequently found in melanomas from Taiwanese patients. There were a significant number of specific gene mutations that exclusively occurred in acral subtype but not in non-acral subtype melanomas, and vice versa. While certain common mutations form a shared core of genetic features, there appear to be specific genetic pathways that are involved in the occurrence of melanomas that grow in non-UV-exposed areas. Our findings have shed light on the tumorigenesis pathways involved in malignant melanoma.

BANet: A Blur-Aware Attention Network for Dynamic Scene Deblurring.

Image motion blur results from a combination of object motions and camera shakes, and such blurring effect is generally directional and non-uniform. Previous research attempted to solve non-uniform blurs using self-recurrent multi-scale, multi-patch, or multi-temporal architectures with self-attention to obtain decent results. However, using self-recurrent frameworks typically leads to a longer inference time, while inter-pixel or inter-channel self-attention may cause excessive memory usage. This paper proposes a Blur-aware Attention Network (BANet), that accomplishes accurate and efficient deblurring via a single forward pass. Our BANet utilizes region-based self-attention with multi-kernel strip pooling to disentangle blur patterns of different magnitudes and orientations and cascaded parallel dilated convolution to aggregate multi-scale content features. Extensive experimental results on the GoPro and RealBlur benchmarks demonstrate that the proposed BANet performs favorably against the state-of-the-arts in blurred image restoration and can provide deblurred results in real-time.

Molecular actions of exosomes and their theragnostics in colorectal cancer: current findings and limitations.

Extracellular vesicles (EVs) are cell-released, membranous structures essential for intercellular communication. The biochemical compositions and physiological impacts of exosomes, lipid-bound, endosomal origin EVs, have been focused on, especially on the tumor-host interactions in a defined tumor microenvironment (TME). Despite recent progress in targeted therapy and cancer immunotherapy in colorectal cancer (CRC), cancer patients still suffer from distal metastasis and tumor relapse, suggesting unmet needs for biomarkers directing therapeutic interventions and predicting treatment responsiveness. As exosomes are indispensable for intercellular communication and high exosome abundance makes them feasible biomarker molecules, this review discusses exosome heterogeneity and how exosomes orchestrate the interplay among tumor cells, cancer stem cells (CSCs) and host cells, including stromal cells, endothelial cells and immunocytes, in the CRC TME. This review also discusses mechanisms for loading exosomal contents and potential exosomal DNA, RNA and protein biomarkers for early CRC detection. Finally, we summarize the diagnostic and therapeutic exosomes in clinical trials. We envision that detecting and targeting cancer-specific exosomes could provide therapeutic advances in developing personalized cancer medicine.

A Promiscuity Locus Confers Lotus burttii Nodulation with Rhizobia from Five Different Genera.

Legumes acquire access to atmospheric nitrogen through nitrogen fixation by rhizobia in root nodules. Rhizobia are soil-dwelling bacteria and there is a tremendous diversity of rhizobial species in different habitats. From the legume perspective, host range is a compromise between the ability to colonize new habitats, in which the preferred symbiotic partner may be absent, and guarding against infection by suboptimal nitrogen fixers. Here, we investigate natural variation in rhizobial host range across Lotus species. We find that Lotus burttii is considerably more promiscuous than Lotus japonicus, represented by the Gifu accession, in its interactions with rhizobia. This promiscuity allows Lotus burttii to form nodules with Mesorhizobium, Rhizobium, Sinorhizobium, Bradyrhizobium, and Allorhizobium species that represent five distinct genera. Using recombinant inbred lines, we have mapped the Gifu/burttii promiscuity quantitative trait loci (QTL) to the same genetic locus regardless of rhizobial genus, suggesting a general genetic mechanism for symbiont-range expansion. The Gifu/burttii QTL now provides an opportunity for genetic and mechanistic understanding of promiscuous legume-rhizobia interactions. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

CFD Numerical Simulation in Building Drainage Stacks as an Infection Pathway of COVID-19.

Being aware of global pandemics, this research focused on the potential infection routes in building drainage systems. Case studies have found that dysfunctional building drainage systems not only failed to block contaminants but also potentially became a route for the spreading of viruses. Several fluid simulations in pipelines were conducted in this research using COMSOL Multiphysics. In particular, virus transmission from one patient's room to other uninfected residential units through pipelines was visualized. A 12-story building, which is commonly seen in the local area, was designed as a simulation model to visualize the transmission and analyze its hazards. Furthermore, five environmental factors were filtered out for discussion: distance, time span, pressure, initial concentration, and environment temperature. By manipulating these factors, the relationship between the factors and the behavior of the contaminant could be explored. In addition, a simulation with a different pipeline arrangement was included to observe the virus diffusion behavior under different scenarios. The visualized simulation concluded that the contaminant would spread through the drainage system and arrive at the neighboring four floors within an hour under the circumstances of a 12-story building with broken seals and constant pressure and contaminant supply on the seventh floor. Meanwhile, the whole building would be exposed to infection risks by the continuous virus spreading through a drainage system. Distance, time span, and pressure were considered critical factors that affected indoor contamination in the system. On the other hand, initial concentration and environmental temperature did not have significant roles. Visualizing the behavior of viruses provides a glimpse of what happens behind walls, paving the way for recognizing the importance of maintaining functional drainage systems for individuals' health.

Computer-assisted three-dimensional quantitation of programmed death-ligand 1 in non-small cell lung cancer using tissue clearing technology.

Immune checkpoint blockade therapy has revolutionized non-small cell lung cancer treatment. However, not all patients respond to this therapy. Assessing the tumor expression of immune checkpoint molecules, including programmed death-ligand 1 (PD-L1), is the current standard in predicting treatment response. However, the correlation between PD-L1 expression and anti-PD-1/PD-L1 treatment response is not perfect. This is partly caused by tumor heterogeneity and the common practice of assessing PD-L1 expression based on limited biopsy material. To overcome this problem, we developed a novel method that can make formalin-fixed, paraffin-embedded tissue translucent, allowing three-dimensional (3D) imaging. Our protocol can process tissues up to 150 µm in thickness, allowing anti-PD-L1 staining of the entire tissue and producing high resolution 3D images. Compared to a traditional 4 µm section, our 3D image provides 30 times more coverage of the specimen, assessing PD-L1 expression of approximately 10 times more cells. We further developed a computer-assisted PD-L1 quantitation method to analyze these images, and we found marked variation of PD-L1 expression in 3D. In 5 of 33 needle-biopsy-sized specimens (15.2%), the PD-L1 tumor proportion score (TPS) varied by greater than 10% at different depth levels. In 14 cases (42.4%), the TPS at different depth levels fell into different categories (< 1%, 1-49%, or ≥ 50%), which can potentially influence treatment decisions. Importantly, our technology permits recovery of the processed tissue for subsequent analysis, including histology examination, immunohistochemistry, and mutation analysis. In conclusion, our novel method has the potential to increase the accuracy of tumor PD-L1 expression assessment and enable precise deployment of cancer immunotherapy.

Gene Expression Profile in Primary Tumor Is Associated with Brain-Tropism of Metastasis from Lung Adenocarcinoma.

Lung adenocarcinoma has a strong propensity to metastasize to the brain. The brain metastases are difficult to treat and can cause significant morbidity and mortality. Identifying patients with increased risk of developing brain metastasis can assist medical decision-making, facilitating a closer surveillance or justifying a preventive treatment. We analyzed 27 lung adenocarcinoma patients who received a primary lung tumor resection and developed metastases within 5 years after the surgery. Among these patients, 16 developed brain metastases and 11 developed non-brain metastases only. We performed targeted DNA sequencing, RNA sequencing and immunohistochemistry to characterize the difference between the primary tumors. We also compared our findings to the published data of brain-tropic and non-brain-tropic lung adenocarcinoma cell lines. The results demonstrated that the targeted tumor DNA sequencing did not reveal a significant difference between the groups, but the RNA sequencing identified 390 differentially expressed genes. A gene expression signature including CDKN2A could identify 100% of brain-metastasizing tumors with a 91% specificity. However, when compared to the differentially expressed genes between brain-tropic and non-brain-tropic lung cancer cell lines, a different set of genes was shared between the patient data and the cell line data, which include many genes implicated in the cancer-glia/neuron interaction. Our findings indicate that it is possible to identify lung adenocarcinoma patients at the highest risk for brain metastasis by analyzing the primary tumor. Further investigation is required to elucidate the mechanism behind these associations and to identify potential treatment targets.

Establishing diagnostic algorithms for SARS-CoV-2 nucleic acid testing in clinical practice.

BACKGROUND: Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic. Our laboratory initially used a two-step molecular assay, first reported by Corman et al, for SARS-CoV-2 identification (the Taiwan Center for Disease Control [T-CDC] method). As rapid and accurate diagnosis of COVID-19 is required to control the spread of this infectious disease, the current study evaluated three commercially available assays, including the TaqPath COVID-19 Combo kit, the cobas SARS-CoV-2 test, and the Rendu 2019-nCoV Assay kit, to establish diagnostic algorithms for clinical laboratories. METHODS: A total of 790 clinical specimens, including nasopharyngeal swabs, throat swabs, sputum, saliva, stool, endotracheal aspirate, and serum were obtained from patients who were suspected or already confirmed to have COVID-19 at the Taipei Veterans General Hospital from February to May 2020. These specimens were tested for SARS-CoV-2 using the different assays and the performance variance between the assays was analyzed. RESULTS: Of the assays we evaluated, the T-CDC method and the TaqPath COVID-19 Combo kit require lots of hands-on practical laboratory work, while the cobas SARS-CoV-2 test and the Rendu 2019-nCoV Assay kit are fully automated detection systems. The T-CDC method and the TaqPath COVID-19 Combo kit showed similar detection sensitivity; however, the T-CDC method frequently delivered false-positive signals for envelope (E) and/or RNA-dependent RNA polymerase (RdRP) gene detection, thus increasing the risk of reporting false-positive results. A manual test-based testing strategy combining the T-CDC method and the TaqPath COVID-19 Combo kit was developed, which demonstrated excellent concordance rates (>99%) with the cobas and Rendu automatic systems. There were a few cases showing discrepant results, which may be due to the varied detection sensitivities as well as targets among the different platforms. Moreover, the concordance rate between the cobas and Rendu assays was 100%. CONCLUSION: Based on our evaluation, two SARS-CoV-2 diagnostic algorithms, one focusing on the manual assays and the other on the automatic platforms, were proposed. Our results provide valuable information that allows clinical laboratories to implement optimal diagnostic strategies for SARS-CoV-2 testing based on their clinical needs, such as test volume, turn-around time, and staff/resource limitations.

Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-Segmentation.

We present an approach for jointly matching and segmenting object instances of the same category within a collection of images. In contrast to existing algorithms that tackle the tasks of semantic matching and object co-segmentation in isolation, our method exploits the complementary nature of the two tasks. The key insights of our method are two-fold. First, the estimated dense correspondence fields from semantic matching provide supervision for object co-segmentation by enforcing consistency between the predicted masks from a pair of images. Second, the predicted object masks from object co-segmentation in turn allow us to reduce the adverse effects due to background clutters for improving semantic matching. Our model is end-to-end trainable and does not require supervision from manually annotated correspondences and object masks. We validate the efficacy of our approach on five benchmark datasets: TSS, Internet, PF-PASCAL, PF-WILLOW, and SPair-71k, and show that our algorithm performs favorably against the state-of-the-art methods on both semantic matching and object co-segmentation tasks.

Diffuse Intratumoral Stromal Inflammation in Ovarian Clear Cell Carcinoma is Associated With Loss of Mismatch Repair Protein and High PD-L1 Expression.

Ovarian clear cell carcinoma (OCCC) is an aggressive chemotherapy-resistant cancer with limited treatment options, and some OCCCs have mismatch repair (MMR) deficiency (MMRD). Emerging evidence has revealed that various cancers with MMRD are susceptible to anti-programmed death-1/programmed death ligand-1 (anti-PD-1/PD-L1) immunotherapy, and certain histologic features are associated with MMRD. However, few studies have addressed this in OCCC. We reviewed 76 OCCCs for tumor-associated inflammation (intratumoral stromal inflammation and peritumoral lymphocytes) and performed immunohistochemistry for 4 MMR proteins and PD-L1. MMR-deficient OCCCs were analyzed for microsatellite instability (MSI), and those with MLH1 loss were tested for MLH1 promoter methylation. No patients fulfilled the Amsterdam II criteria for the diagnosis of Lynch syndrome. Four (5.3%) tumors showed diffuse intratumoral stromal inflammation obliterating the tumor-stroma interfaces, and none had peritumoral lymphoid aggregates. MMRD was found in 2 (2.6%) tumors; one had MLH1/PMS2 loss (MSI-high and MLH1 promoter methylation was detected) and the other had MSH2/MSH6 loss (MSI-low). Twenty (26.3%) tumors showed tumoral PD-L1 expression ≥1%. Both MMR-deficient tumors showed diffuse intratumoral stromal inflammation and tumoral PD-L1 expression ≥50%. Three of the 4 (75%) tumors with diffuse intratumoral stromal inflammation also showed tumoral PD-L1 expression ≥50%. None of the tumors without diffuse intratumoral stromal inflammation showed MMRD (P=0.021) or tumoral PD-L1 expression ≥50% (P=0.0001). We identified a strong correlation among diffuse intratumoral stromal inflammation, MMRD, and high tumoral PD-L1 expression in a small but significant subset of OCCCs. Histologic evaluation can facilitate patient selection for subsequent anti-PD-1/PD-L1 immunotherapy.

Programmed death-ligand 1 (PD-L1)/thyroid transcription factor-1 double immunohistochemical staining facilitates scoring of tumor PD-L1 expression in cytopathology specimens from lung adenocarcinoma patients.

BACKGROUND: Immune checkpoint inhibitor therapy has revolutionized lung adenocarcinoma therapy. Treatment with antibodies against the immune checkpoint molecules programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) can induce a durable response in a subset of patients. Immunohistochemistry characterization of tumor PD-L1 expression using either a histopathology specimen or a cytopathology specimen has been shown to correlate with treatment response. However, the current practice relies on pathologists' visual estimation of tumor PD-L1 staining, which can be variable in certain conditions. Highlighting tumor cells via double immunostaining with PD-L1 and thyroid transcription factor-1 (TTF-1) may improve estimation accuracy. METHODS: We performed PD-L1 single staining and PD-L1/TTF-1 double staining in 42 pairs of cytopathology and histopathology specimens from lung adenocarcinoma patients. An experienced pathologist visually estimated PD-L1 expression in each case and placed tumor PD-L1 expression into 1 of 3 categories: <1%, 1%-49%, or ≥50%. A medical technologist also performed estimations of the same cases based on a count of 200 tumor cells, and the results were compared. RESULTS: PD-L1/TTF-1 double immunohistochemistry could better identify the PD-L1-positive tumor cells in cytopathology specimens compared with PD-L1 single staining. The concordance of PD-L1 expression categorization between the pathologist's visual estimation and the medical technologist's counting was increased by double staining in cytopathology specimens (Cohen's weighted kappa: single stain, 0.784; double stain, 0.880). Double staining reduced possible error in the pathologist's visual estimation of PD-L1 expression from 9.5% to 4.8%. The benefit was not observed in histopathology specimens. CONCLUSION: A simple PD-L1/TTF-1 double immunohistochemistry technique can be applied successfully to cytopathology specimens in better identifying patients who can potentially benefit from immune checkpoint blockade treatment.

A mosaic analysis system with Cre or Tomato expression in the mouse.

Somatic mutations are major genetic contributors to cancers and many other age-related diseases. Many disease-causing somatic mutations can initiate clonal growth prior to the appearance of any disease symptoms, yet experimental models that can be used to examine clonal abnormalities are limited. We describe a mosaic analysis system with Cre or Tomato (MASCOT) for tracking mutant cells and demonstrate its utility for modeling clonal hematopoiesis. MASCOT can be induced to constitutively express either Cre-GFP or Tomato for lineage tracing of a mutant and a reference group of cells simultaneously. We conducted mosaic analysis to assess functions of the Id3 and/or Tet2 gene in hematopoietic cell development and clonal hematopoiesis. Using Tomato-positive cells as a reference population, we demonstrated the high sensitivity of this system for detecting cell-intrinsic phenotypes during short-term or long-term tracking of hematopoietic cells. Long-term tracking of Tet2 mutant or Tet2/Id3 double-mutant cells in our MASCOT model revealed a dynamic shift from myeloid expansion to lymphoid expansion and subsequent development of lymphoma. This work demonstrates the utility of the MASCOT method in mosaic analysis of single or combined mutations, making the system suitable for modeling somatic mutations identified in humans.