MicroRNAs 24 and 27 Suppress Allergic Inflammation and Target a Network of Regulators of T Helper 2 Cell-Associated Cytokine Production.

MicroRNAs (miRNAs) are important regulators of cell fate decisions in immune responses. They act by coordinate repression of multiple target genes, a property that we exploited to uncover regulatory networks that govern T helper-2 (Th2) cells. A functional screen of individual miRNAs in primary T cells uncovered multiple miRNAs that inhibited Th2 cell differentiation. Among these were miR-24 and miR-27, miRNAs coexpressed from two genomic clusters, which each functioned independently to limit interleukin-4 (IL-4) production. Mice lacking both clusters in T cells displayed increased Th2 cell responses and tissue pathology in a mouse model of asthma. Gene expression and pathway analyses placed miR-27 upstream of genes known to regulate Th2 cells. They also identified targets not previously associated with Th2 cell biology which regulated IL-4 production in unbiased functional testing. Thus, elucidating the biological function and target repertoire of miR-24 and miR-27 reveals regulators of Th2 cell biology.

Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

Prospective molecular classification of endometrial carcinomas: institutional implementation, practice, and clinical experience.

The comprehensive genomic analysis of endometrial carcinoma (EC) by The Cancer Genome Atlas (TCGA) led to the discovery of four distinct and prognostically significant molecular subgroups. Molecular classification has the potential to improve risk-stratification when integrated with clinicopathologic features and has recently been included in national and international patient management EC guidelines. Thus, the adoption of molecular classification into routine pathologic and clinical practice is likely to grow significantly in the upcoming years. Establishing an efficient and standardized workflow for performing molecular classification on ECs, and reporting both the molecular and histologic findings in an integrative manner, is imperative. Here we describe our effort to implement rapid and routine molecular classification on all ECs diagnosed at our institution. To this effect, we performed immunohistochemistry as a surrogate marker for identifying genetic and/or epigenetic alterations in DNA mismatch repair (e.g., MLH1, PMS2, MSH6, MSH2), and TP53 genes. In addition, we have developed and employed a single-gene POLE SNaPshot assay, which is a rapid and analytically sensitive method for detecting select POLE exonuclease domain mutations (EDMs). We report our molecular testing workflow and integrative reporting system as well as the clinicopathologic and molecular features of 310 ECs that underwent routine molecular classification at our institution. The 310 ECs were molecularly classified as follows: 15 (5%) POLE mutant (POLEmut), 79 (25%) mismatch repair-deficient (MMRd), 135 (44%) no specific molecular profile (NSMP), and 81 (26%) p53 abnormal (p53abnl). This work provides an initial framework for implementing routine molecular classification of ECs.

A Multiplex SNaPshot Assay is a Rapid and Cost-Effective Method for Detecting POLE Exonuclease Domain Mutations in Endometrial Carcinoma.

Determining the replicative DNA polymerase epsilon ( POLE) mutation status in endometrial carcinomas (ECs) has important clinical implications given that the majority of "ultramutated" tumors harboring pathogenic exonuclease domain mutations in POLE ( POLE mut) have a favorable prognosis, even among high-grade histotypes. Currently, there are no specific morphologic or immunophenotypic features that allow accurate detection of POLE mut tumors without molecular testing. Consequently, identifying POLE mut tumors has been challenging without employing costly and/or time-consuming DNA sequencing approaches. Here we developed a novel SNaPshot assay to facilitate routine and efficient POLE mutation testing in EC. The SNaPshot assay interrogates 15 nucleotide sites within exons 9, 11, 13, and 14 encoding the POLE exonuclease domain. The variant sites were selected based on recurrence, evidence of functional impact, association with high tumor mutation burden and/or detection in EC clinical outcome studies. Based on the pathogenic somatic variants reported in the literature, the assay is predicted to have a clinical sensitivity of 90% to 95% for ECs. Validation studies showed 100% specificity and sensitivity for the variants covered, with expected genotypic results for both the positive (n=11) and negative (n=20) patient controls on multiple repeat tests and dilution series. Analytic sensitivity was conservatively approximated at a 10% variant allele fraction (VAF), with documented detection as low as 5% VAF. As expected, the SNaPshot assay demonstrated greater sensitivity than Sanger sequencing for VAFs below 20%, an important characteristic for somatic mutation detection. Here we have developed and validated the first SNaPshot assay to detect hotspot POLE mutations. While next-generation sequencing and Sanger sequencing-based approaches have also been used to detect POLE mutations, a SNaPshot approach provides useful balance of analytical sensitivity, cost-effectiveness, and efficiency in a high-volume case load setting.

Assessing the Performance of a Novel Point-of-Care Qualitative Assay for Early Diagnosis of Acute Coronary Syndrome.

BACKGROUND: Early and accurate diagnosis of acute coronary syndrome (ACS) is essential for initiating lifesaving interventions. In this article, the diagnostic performance of a novel point-of-care rapid assay (SensAheart©) is analyzed. This assay qualitatively determines the presence of 2 cardiac biomarkers troponin I and heart-type fatty acid-binding protein that are present soon after onset of myocardial injury. METHODS: We conducted a prospective observational study of consecutive patients who presented to the emergency department with typical chest pain. Simultaneous high-sensitive cardiac troponin T (hs-cTnT) and SensAheart testing was performed upon hospital admission. Diagnostic accuracy was computed using SensAheart or hs-cTnT levels versus the final diagnosis defined as positive/negative. RESULTS: Of 225 patients analyzed, a final diagnosis of ACS was established in 138 patients, 87 individuals diagnosed with nonischemic chest pain. In the overall population, as compared to hs-cTnT, the sensitivity of the initial SensAheart assay was significantly higher (80.4 vs. 63.8%, p = 0.002) whereas specificity was lower (78.6 vs. 95.4%, p = 0.036). The overall diagnostic accuracy of SensAheart assay was similar to the hs-cTnT (82.7% compared to 76.0%, p = 0.08). CONCLUSIONS: Upon first medical contact, the novel point-of-care rapid SensAheart assay shows a diagnostic performance similar to hs-cTnT. The combination of 2 cardiac biomarkers in the same kit allows for very early detection of myocardial damage. The SensAheart assay is a reliable and practical tool for ruling-in the diagnosis of ACS.

Challenges and future directions in LC-MS-based multiclass method development for the quantification of food contaminants.

Monitoring of food contaminants and residues has undergone a significant improvement in recent years and is now performed in an intensive manner. Achievements in the area of chromatography-mass spectrometry coupling techniques enabled the development of quantitative multi-target approaches covering several hundred analytes. Although the majority of methods are focusing on the analysis of one specific group of substances, such as pesticides, mycotoxins, or veterinary drugs, current trends are going towards the simultaneous determination of multiclass compounds from several families of contaminants and residues. This work provides an overview of relevant multiclass concepts based on LC-MS/MS and LC-HRMS instruments. Merits and shortcomings will be critically discussed based on current performance characteristics of the EU legislation system. In addition, the discussion of a recently developed multiclass approach covering >1000 substances is presented as a case study to illustrate the current developments in this area.

Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation.

BackgroundDeep learning has the potential to augment the use of chest radiography in clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty comparing across studies.PurposeTo develop and evaluate deep learning models for chest radiograph interpretation by using radiologist-adjudicated reference standards.Materials and MethodsDeep learning models were developed to detect four findings (pneumothorax, opacity, nodule or mass, and fracture) on frontal chest radiographs. This retrospective study used two data sets. Data set 1 (DS1) consisted of 759 611 images from a multicity hospital network and ChestX-ray14 is a publicly available data set with 112 120 images. Natural language processing and expert review of a subset of images provided labels for 657 954 training images. Test sets consisted of 1818 and 1962 images from DS1 and ChestX-ray14, respectively. Reference standards were defined by radiologist-adjudicated image review. Performance was evaluated by area under the receiver operating characteristic curve analysis, sensitivity, specificity, and positive predictive value. Four radiologists reviewed test set images for performance comparison. Inverse probability weighting was applied to DS1 to account for positive radiograph enrichment and estimate population-level performance.ResultsIn DS1, population-adjusted areas under the receiver operating characteristic curve for pneumothorax, nodule or mass, airspace opacity, and fracture were, respectively, 0.95 (95% confidence interval [CI]: 0.91, 0.99), 0.72 (95% CI: 0.66, 0.77), 0.91 (95% CI: 0.88, 0.93), and 0.86 (95% CI: 0.79, 0.92). With ChestX-ray14, areas under the receiver operating characteristic curve were 0.94 (95% CI: 0.93, 0.96), 0.91 (95% CI: 0.89, 0.93), 0.94 (95% CI: 0.93, 0.95), and 0.81 (95% CI: 0.75, 0.86), respectively.ConclusionExpert-level models for detecting clinically relevant chest radiograph findings were developed for this study by using adjudicated reference standards and with population-level performance estimation. Radiologist-adjudicated labels for 2412 ChestX-ray14 validation set images and 1962 test set images are provided.© RSNA, 2019Online supplemental material is available for this article.See also the editorial by Chang in this issue.

Morphological, immunophenotypical and molecular features of hypermutation in colorectal carcinomas with mutations in DNA polymerase ε (POLE).

AIMS: Colorectal carcinomas (CRC) with mismatch repair (MMR) deficiency have increased tumour mutation burden and respond to immune check-point inhibitor therapy. The Cancer Genome Atlas identified hypermutated CRCs with somatic mutations in DNA polymerase ε (POLE) with mutation burdens exceeding that of MMR-deficient CRCs. METHODS AND RESULTS: To identify the morphological, immunophenotypical and molecular features of POLE-mutated CRCs, 63 consecutive MMR-intact CRCs were evaluated by Sanger sequencing for POLE exonuclease domain mutations in exons 9, 11, 13 and 14 and confirmed by next-generation sequencing. Tumour immune microenvironment and IMMUNOSCORE®1 were assessed in POLE-mutated CRCs using immunohistochemistry to detect CD3+ /CD8+ tumour-infiltrating lymphocytes and compared to 59 non-POLE mutated MMR-intact CRC, 10 non-POLE mutated MMR-deficient CRCs and 223 normal colonic mucosa. CONCLUSIONS: A total of 4.8% CRC (four MMR-intact primary and one MMR-intact metastasis) harboured POLE mutations in amino acid 286 in exon 9 (p.P286R) or exon 13 (p.V411L). POLE-mutated CRCs arose in the transverse colon and rectum, were male-predominant, younger and showed increased tumour-infiltrating lymphocytes and immune cells at the tumour-stromal interface. The patient with metastatic POLE-mutated CRC was placed on PD-1 inhibitor treatment with marked and sustained response. These data indicate that POLE-mutated CRCs have hypermutated phenotypes despite MMR-intact status, with mutation burdens higher than that in microsatellite-unstable CRCs. Given the recent approval for treatment of microsatellite-unstable cancer with immune check-point inhibitors, assessment of POLE status may help to guide therapeutic decisions for hypermutated tumours with intact MMR that would otherwise be missed by routine testing.

MicroRNA-29 regulates T-box transcription factors and interferon-γ production in helper T cells.

MicroRNA (miRNA)-deficient helper T cells exhibit abnormal IFN-γ production and decreased proliferation. However, the contributions of individual miRNAs to this phenotype remain poorly understood. We conducted a screen for miRNA function in primary T cells and identified individual miRNAs that rescue the defects associated with miRNA deficiency. Multiple members of the miR-17 and miR-92 families enhanced miRNA-deficient T cell proliferation whereas miR-29 largely corrected their aberrant interferon-γ (IFN-γ) expression. Repression of IFN-γ production by miR-29 involved direct targeting of both T-bet and Eomes, two transcription factors known to induce IFN-γ production. Although not usually expressed at functionally relevant amounts in helper T cells, Eomes was abundant in miRNA-deficient cells and was upregulated after miR-29 inhibition in wild-type cells. These results demonstrate that miR-29 regulates helper T cell differentiation by repressing multiple target genes, including at least two that are independently capable of inducing the T helper 1 (Th1) cell gene expression program.

Towards a dietary-exposome assessment of chemicals in food: An update on the chronic health risks for the European consumer.

An informed opinion to a hugely important question, whether the food on the Europeans' plate is safe to eat, is provided. Today, the Europeans face food-borne health risks from non-communicable diseases induced by excess body weight, outbreaks caused by pathogens, antimicrobial resistance and exposures to chemical contaminants. In this review, these risks are first put in an order of importance. Then, not only potentially injurious dietary chemicals are discussed but also beneficial factors of the food. This review can be regarded as an attempt towards a dietary-exposome evaluation of the chemicals, the average European adult consumers could chronically expose to during their life-times. Risk ranking reveals that currently the European adults are chronically exposed to a mixture of potentially genotoxic-carcinogenic contaminants, particularly food process contaminants, at the potential risk levels. Furthermore, several of the contaminants whose dietary exposures pose risks appear to be carcinogens operating with a genotoxic mode of action targeting the liver. This suggests that combined health risks from the exposure to a mixture of the chemical contaminants poses a greater potential risk than the risks assessed for single compounds. Over 100 European-level risk assessments are examined. Finally, the importance of a diversified and balanced diet is emphasized.

Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions.

This paper describes the validation of an LC-MS/MS-based method for the quantification of > 500 secondary microbial metabolites. Analytical performance parameters have been determined for seven food matrices using seven individual samples per matrix for spiking. Apparent recoveries ranged from 70 to 120% for 53-83% of all investigated analytes (depending on the matrix). This number increased to 84-94% if the recovery of extraction was considered. The comparison of the fraction of analytes for which the precision criterion of RSD ≤ 20% under repeatability conditions (for 7 replicates derived from different individual samples) and intermediate precision conditions (for 7 technical replicates from one sample), respectively, was met (85-97% vs. 93-94%) highlights the contribution of relative matrix effects to the method uncertainty. Statistical testing of apparent recoveries between pairs of matrices exhibited a significant difference for more than half of the analytes, while recoveries of the extraction showed a much better agreement. Apparent recoveries and matrix effects were found to be constant over 2-3 orders of magnitude of analyte concentrations in figs and maize, whereas the LOQs differed less than by a factor of 2 for 90% of the investigated compounds. Based on these findings, this paper discusses the applicability and practicability of current guidelines for multi-analyte method validation. Investigation of (apparent) recoveries near the LOQ seems to be insufficiently relevant to justify the enormous time-effort for manual inspection of the peaks of hundreds of analytes. Instead, more emphasis should be put on the investigation of relative matrix effects in the validation procedure. Graphical abstract.

Material coherence from trajectories via Burau eigenanalysis of braids.

In this paper, we provide a numerical tool to study a material's coherence from a set of 2D Lagrangian trajectories sampling a dynamical system, i.e., from the motion of passive tracers. We show that eigenvectors of the Burau representation of a topological braid derived from the trajectories have levelsets corresponding to components of the Nielsen-Thurston decomposition of the dynamical system. One can thus detect and identify clusters of space-time trajectories corresponding to coherent regions of the dynamical system by solving an eigenvalue problem. Unlike previous methods, the scalable computational complexity of our braid-based approach allows the analysis of large amounts of trajectories.

Coexistence of BRAF V600E and TERT Promoter Mutations in Low-grade Serous Carcinoma of Ovary Recurring as Carcinosarcoma in a Lymph Node: Report of a Case.

Low-grade serous carcinomas only rarely coexist with or progress to high-grade tumors. We present a case of low-grade serous carcinoma with transformation to carcinosarcoma on recurrence in the lymph node. Identical BRAF V600E and telomerase reverse transcriptase promoter mutations were identified in both the original and recurrent tumor. Given that telomerase reverse transcriptase promotor mutations are thought to play a role in progression of other tumor types, the function of telomerase reverse transcriptase mutations in BRAF mutated low-grade serous carcinoma deserves investigation.

Pharma-Oncogenomics in the Era of Personal Genomics: A Quick Guide to Online Resources and Tools.

The past two decades have seen unprecedented advances in the field of oncogenomics. The ongoing characterization of neoplastic tissues through genomic techniques has transformed many aspects of cancer research, diagnosis, and treatment. However, identifying sequence variants with biological and clinical significance is a challenging endeavor. In order to accomplish this task, variants must be annotated and interpreted using various online resources. Data on protein structure, functional prediction, variant frequency in relevant populations, and multiple other factors have been compiled in useful databases for this purpose. Thus, understanding the available online resources for the annotation and interpretation of sequence variants is critical to aid molecular pathologists and researchers working in this space.

Pathologist Validation of a Machine Learning-Derived Feature for Colon Cancer Risk Stratification.

Importance: Identifying new prognostic features in colon cancer has the potential to refine histopathologic review and inform patient care. Although prognostic artificial intelligence systems have recently demonstrated significant risk stratification for several cancer types, studies have not yet shown that the machine learning-derived features associated with these prognostic artificial intelligence systems are both interpretable and usable by pathologists. Objective: To evaluate whether pathologist scoring of a histopathologic feature previously identified by machine learning is associated with survival among patients with colon cancer. Design, Setting, and Participants: This prognostic study used deidentified, archived colorectal cancer cases from January 2013 to December 2015 from the University of Milano-Bicocca. All available histologic slides from 258 consecutive colon adenocarcinoma cases were reviewed from December 2021 to February 2022 by 2 pathologists, who conducted semiquantitative scoring for tumor adipose feature (TAF), which was previously identified via a prognostic deep learning model developed with an independent colorectal cancer cohort. Main Outcomes and Measures: Prognostic value of TAF for overall survival and disease-specific survival as measured by univariable and multivariable regression analyses. Interpathologist agreement in TAF scoring was also evaluated. Results: A total of 258 colon adenocarcinoma histopathologic cases from 258 patients (138 men [53%]; median age, 67 years [IQR, 65-81 years]) with stage II (n = 119) or stage III (n = 139) cancer were included. Tumor adipose feature was identified in 120 cases (widespread in 63 cases, multifocal in 31, and unifocal in 26). For overall survival analysis after adjustment for tumor stage, TAF was independently prognostic in 2 ways: TAF as a binary feature (presence vs absence: hazard ratio [HR] for presence of TAF, 1.55 [95% CI, 1.07-2.25]; P = .02) and TAF as a semiquantitative categorical feature (HR for widespread TAF, 1.87 [95% CI, 1.23-2.85]; P = .004). Interpathologist agreement for widespread TAF vs lower categories (absent, unifocal, or multifocal) was 90%, corresponding to a κ metric at this threshold of 0.69 (95% CI, 0.58-0.80). Conclusions and Relevance: In this prognostic study, pathologists were able to learn and reproducibly score for TAF, providing significant risk stratification on this independent data set. Although additional work is warranted to understand the biological significance of this feature and to establish broadly reproducible TAF scoring, this work represents the first validation to date of human expert learning from machine learning in pathology. Specifically, this validation demonstrates that a computationally identified histologic feature can represent a human-identifiable, prognostic feature with the potential for integration into pathology practice.

Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning.

BACKGROUND: Presence of lymph node metastasis (LNM) influences prognosis and clinical decision-making in colorectal cancer. However, detection of LNM is variable and depends on a number of external factors. Deep learning has shown success in computational pathology, but has struggled to boost performance when combined with known predictors. METHODS: Machine-learned features are created by clustering deep learning embeddings of small patches of tumor in colorectal cancer via k-means, and then selecting the top clusters that add predictive value to a logistic regression model when combined with known baseline clinicopathological variables. We then analyze performance of logistic regression models trained with and without these machine-learned features in combination with the baseline variables. RESULTS: The machine-learned extracted features provide independent signal for the presence of LNM (AUROC: 0.638, 95% CI: [0.590, 0.683]). Furthermore, the machine-learned features add predictive value to the set of 6 clinicopathologic variables in an external validation set (likelihood ratio test, p < 0.00032; AUROC: 0.740, 95% CI: [0.701, 0.780]). A model incorporating these features can also further risk-stratify patients with and without identified metastasis (p < 0.001 for both stage II and stage III). CONCLUSION: This work demonstrates an effective approach to combine deep learning with established clinicopathologic factors in order to identify independently informative features associated with LNM. Further work building on these specific results may have important impact in prognostication and therapeutic decision making for LNM. Additionally, this general computational approach may prove useful in other contexts.

When colorectal cancers spread to the lymph nodes, it can indicate a poorer prognosis. However, detecting lymph node metastasis (spread) can be difficult and depends on a number of factors such as how samples are taken and processed. Here, we show that machine learning, which involves computer software learning from patterns in data, can predict lymph node metastasis in patients with colorectal cancer from the microscopic appearance of their primary tumor and the clinical characteristics of the patients. We also show that the same approach can predict patient survival. With further work, our approach may help clinicians to inform patients about their prognosis and decide on appropriate treatments.

Distinct requirements of microRNAs in NK cell activation, survival, and function.

MicroRNAs (miRNAs) are small noncoding RNAs that have recently emerged as critical regulators of gene expression within the immune system. In this study, we used mice with conditional deletion of Dicer and DiGeorge syndrome critical region 8 (Dgcr8) to dissect the roles of miRNAs in NK cell activation, survival, and function during viral infection. We developed a system for deletion of either Dicer or Dgcr8 in peripheral NK cells via drug-induced Cre activity. We found that Dicer- and Dgcr8-deficient NK cells were significantly impaired in survival and turnover, and had impaired function of the ITAM-containing activating NK cell receptors. We further demonstrated that both Dicer- and Dgcr8-dependent pathways were indispensable for the expansion of Ly49H(+) NK cells during mouse cytomegalovirus infection. Our data indicate similar phenotypes for Dicer- and Dgcr8-deficient NK cells, which strongly suggest that these processes are regulated by miRNAs. Thus, our findings indicate a critical role for miRNAs in controlling NK cell homeostasis and effector function, with implications for miRNAs regulating diverse aspects of NK cell biology.

An Interlaboratory Comparison Study of Regulated and Emerging Mycotoxins Using Liquid Chromatography Mass Spectrometry: Challenges and Future Directions of Routine Multi-Mycotoxin Analysis including Emerging Mycotoxins.

The present interlaboratory comparison study involved nine laboratories located throughout the world that tested for 24 regulated and non-regulated mycotoxins by applying their in-house LC-MS/MS multi-toxin method to 10 individual lots of 4 matrix commodities, including complex chicken and swine feed, soy and corn gluten. In total, more than 6000 data points were collected and analyzed statistically by calculating a consensus value in combination with a target standard deviation following a modified Horwitz equation. The performance of each participant was evaluated by a z-score assessment with a satisfying range of ±2, leading to an overall success rate of 70% for all tested compounds. Equal performance for both regulated and emerging mycotoxins indicates that participating routine laboratories have successfully expanded their analytical portfolio in view of potentially new regulations. In addition, the study design proved to be fit for the purpose of providing future certified reference materials, which surpass current analyte matrix combinations and exceed the typical scope of the regulatory framework.