A dynamic microRNA profile that tracks a chemotherapy resistance phenotype in osteosarcoma. Implications for novel therapeutics.

Osteosarcoma is a rare primary bone tumor for which no significant therapeutic advancement has been made since the late 1980s despite ongoing efforts. Overall, the five-year survival rate remains about 65%, and is much lower in patients with tumors unresponsive to methotrexate, doxorubicin, and cisplatin therapy. Genetic studies have not revealed actionable drug targets, but our group, and others, have reported that epigenomic biomarkers, including regulatory RNAs, may be useful prognostic tools for osteosarcoma. We tested if microRNA (miRNA) transcriptional patterns mark the transition from a chemotherapy sensitive to resistant tumor phenotype. Small RNA sequencing was performed using 14 patient matched pre-chemotherapy biopsy and post-chemotherapy resection high-grade osteosarcoma frozen tumor samples. Independently, small RNA sequencing was performed using 14 patient matched biopsy and resection samples from untreated tumors. Separately, miRNA specific Illumina DASL arrays were used to assay an independent cohort of 65 pre-chemotherapy biopsy and 26 patient matched post-chemotherapy resection formalin fixed paraffin embedded (FFPE) tumor samples. mRNA specific Illumina DASL arrays were used to profile 37 pre-chemotherapy biopsy and five post-chemotherapy resection FFPE samples, all of which were also used for Illumina DASL miRNA profiling. The National Cancer Institute Therapeutically Applicable Research to Generate Effective Treatments dataset, including PCR based miRNA profiling and RNA-seq data for 86 and 93 pre-chemotherapy tumor samples, respectively, was also used. Paired differential expression testing revealed a profile of 17 miRNAs with significantly different transcriptional levels following chemotherapy. Genes targeted by the miRNAs were differentially expressed following chemotherapy, suggesting the miRNAs may regulate transcriptional networks. Finally, an in vitro pharmacogenomic screen using miRNAs and their target transcripts predicted response to a set of candidate small molecule therapeutics which potentially reverse the chemotherapy resistance phenotype and synergize with chemotherapy in otherwise treatment resistant tumors. Importantly, these novel therapeutic targets are distinct from targets identified by a similar pharmacogenomic analysis of previously published prognostic miRNA profiles from pre chemotherapy biopsy specimens.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci.

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3' untranslated region (3'-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3'-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3'-UTR eQTLs in immune-related genes. Our approach identifies numerous 3'-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

The potential use of artificial intelligence for venous thromboembolism prophylaxis and management: clinician and healthcare informatician perspectives.

Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis. We conducted electronic surveys asking clinician and healthcare informaticians about their perspectives on AI/ML for VTE prevention and management. Of 101 respondents to the informatician survey, most were 40 years or older, male, clinicians and data scientists, and had performed research on AI/ML. Of the 607 US-based respondents to the clinician survey, most were 40 years or younger, female, physicians, and had never used AI to inform clinical practice. Most informaticians agreed that AI/ML can be used to manage VTE (56.0%). Over one-third were concerned that clinicians would not use the technology (38.9%), but the majority of clinicians believed that AI/ML probably or definitely can help with VTE prevention (70.1%). The most common concern in both groups was a perceived lack of transparency (informaticians 54.4%; clinicians 25.4%). These two surveys revealed that key stakeholders are interested in AI/ML for VTE prevention and management, and identified potential barriers to address prior to implementation.

Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis.

ABSTRACT: Venous thromboembolism (VTE) is a leading cause of preventable in-hospital mortality. Monitoring VTE cases is limited by the challenges of manual medical record review and diagnosis code interpretation. Natural language processing (NLP) can automate the process. Rule-based NLP methods are effective but time consuming. Machine learning (ML)-NLP methods present a promising solution. We conducted a systematic review and meta-analysis of studies published before May 2023 that use ML-NLP to identify VTE diagnoses in the electronic health records. Four reviewers screened all manuscripts, excluding studies that only used a rule-based method. A meta-analysis evaluated the pooled performance of each study's best performing model that evaluated for pulmonary embolism and/or deep vein thrombosis. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with confidence interval (CI) were calculated by DerSimonian and Laird method using a random-effects model. Study quality was assessed using an adapted TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) tool. Thirteen studies were included in the systematic review and 8 had data available for meta-analysis. Pooled sensitivity was 0.931 (95% CI, 0.881-0.962), specificity 0.984 (95% CI, 0.967-0.992), PPV 0.910 (95% CI, 0.865-0.941) and NPV 0.985 (95% CI, 0.977-0.990). All studies met at least 13 of the 21 NLP-modified TRIPOD items, demonstrating fair quality. The highest performing models used vectorization rather than bag-of-words and deep-learning techniques such as convolutional neural networks. There was significant heterogeneity in the studies, and only 4 validated their model on an external data set. Further standardization of ML studies can help progress this novel technology toward real-world implementation.

Polycomb-mediated silencing of miR-8 is required for maintenance of intestinal stemness in Drosophila melanogaster.

Balancing maintenance of self-renewal and differentiation is a key property of adult stem cells. The epigenetic mechanisms controlling this balance remain largely unknown. Herein, we report that the Polycomb Repressive Complex 2 (PRC2) is required for maintenance of the intestinal stem cell (ISC) pool in the adult female Drosophila melanogaster. We show that loss of PRC2 activity in ISCs by RNAi-mediated knockdown or genetic ablation of the enzymatic subunit Enhancer of zeste, E(z), results in loss of stemness and precocious differentiation of enteroblasts to enterocytes. Mechanistically, we have identified the microRNA miR-8 as a critical target of E(z)/PRC2-mediated tri-methylation of histone H3 at Lys27 (H3K27me3) and uncovered a dynamic relationship between E(z), miR-8 and Notch signaling in controlling stemness versus differentiation of ISCs. Collectively, these findings uncover a hitherto unrecognized epigenetic layer in the regulation of stem cell specification that safeguards intestinal homeostasis.

PanomiR: a systems biology framework for analysis of multi-pathway targeting by miRNAs.

Charting microRNA (miRNA) regulation across pathways is key to characterizing their function. Yet, no method currently exists that can quantify how miRNAs regulate multiple interconnected pathways or prioritize them for their ability to regulate coordinate transcriptional programs. Existing methods primarily infer one-to-one relationships between miRNAs and pathways using differentially expressed genes. We introduce PanomiR, an in silico framework for studying the interplay of miRNAs and disease functions. PanomiR integrates gene expression, mRNA-miRNA interactions and known biological pathways to reveal coordinated multi-pathway targeting by miRNAs. PanomiR utilizes pathway-activity profiling approaches, a pathway co-expression network and network clustering algorithms to prioritize miRNAs that target broad-scale transcriptional disease phenotypes. It directly resolves differential regulation of pathways, irrespective of their differential gene expression, and captures co-activity to establish functional pathway groupings and the miRNAs that may regulate them. PanomiR uses a systems biology approach to provide broad but precise insights into miRNA-regulated functional programs. It is available at https://bioconductor.org/packages/PanomiR.

Artificial intelligence in the prediction of venous thromboembolism: A systematic review and pooled analysis.

BACKGROUND: Accurate diagnostic and prognostic predictions of venous thromboembolism (VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous identification of the most predictive patterns from large complex data. Although evidence regarding its performance in VTE prediction is emerging, a comprehensive analysis of performance is lacking. AIMS: To systematically review the performance of AI in the diagnosis and prediction of VTE and compare it to clinical risk assessment models (RAMs) or logistic regression models. METHODS: A systematic literature search was performed using PubMed, MEDLINE, EMBASE, and Web of Science from inception to April 20, 2021. Search terms included "artificial intelligence" and "venous thromboembolism." Eligible criteria were original studies evaluating AI in the prediction of VTE in adults and reporting one of the following outcomes: sensitivity, specificity, positive predictive value, negative predictive value, or area under receiver operating curve (AUC). Risks of bias were assessed using the PROBAST tool. Unpaired t-test was performed to compare the mean AUC from AI versus conventional methods (RAMs or logistic regression models). RESULTS: A total of 20 studies were included. Number of participants ranged from 31 to 111 888. The AI-based models included artificial neural network (six studies), support vector machines (four studies), Bayesian methods (one study), super learner ensemble (one study), genetic programming (one study), unspecified machine learning models (two studies), and multiple machine learning models (five studies). Twelve studies (60%) had both training and testing cohorts. Among 14 studies (70%) where AUCs were reported, the mean AUC for AI versus conventional methods were 0.79 (95% CI: 0.74-0.85) versus 0.61 (95% CI: 0.54-0.68), respectively (p < .001). However, the good to excellent discriminative performance of AI methods is unlikely to be replicated when used in clinical practice, because most studies had high risk of bias due to missing data handling and outcome determination. CONCLUSION: The use of AI appears to improve the accuracy of diagnostic and prognostic prediction of VTE over conventional risk models; however, there was a high risk of bias observed across studies. Future studies should focus on transparent reporting, external validation, and clinical application of these models.

Venous thromboembolism prophylaxis for hospitalized adult patients: a survey of US health care providers on attitudes and practices.

Background: Venous thromboembolism (VTE) is a leading cause of preventable mortality among hospitalized patients, but appropriate risk assessment and thromboprophylaxis remain underutilized or misapplied. Objectives: We conducted an electronic survey of US health care providers to explore attitudes, practices, and barriers related to thromboprophylaxis in adult hospitalized patients and at discharge. Results: A total of 607 US respondents completed the survey: 63.1% reported working in an academic hospital, 70.7% identified as physicians, and hospital medicine was the most frequent specialty (52.1%). The majority of respondents agreed that VTE prophylaxis is important (98.8%; 95% CI: 97.6%-99.5%) and that current measures are safe (92.6%; 95% CI: 90.2%-94.5%) and effective (93.8%; 95% CI: 91.6%-95.6%), but only half (52.0%; 95% CI: 47.9%-56.0%) believed that hospitalized patients at their institution are on appropriate VTE prophylaxis almost all the time. One-third (35.4%) reported using a risk assessment model (RAM) to determine VTE prophylaxis need; 44.9% reported unfamiliarity with RAMs. The most common recommendation for improving rates of appropriate thromboprophylaxis was to leverage technology. A majority of respondents (84.5%) do not reassess a patient's need for VTE prophylaxis at discharge, and a minority educates patients about the risk (16.2%) or symptoms (18.9%) of VTE at discharge. Conclusion: Despite guideline recommendations to use RAMs, the majority of providers in our survey do not use them. A majority of respondents believed that technology could help improve VTE prophylaxis rates. A majority of respondents do not reassess the risk of VTE at discharge or educate patients about this risk of VTE at discharge.

MicroRNA-22 Is a Key Regulator of Lipid and Metabolic Homeostasis.

Obesity is a growing public health problem associated with increased risk of type 2 diabetes, cardiovascular disease, nonalcoholic fatty liver disease (NAFLD) and cancer. Here, we identify microRNA-22 (miR-22) as an essential rheostat involved in the control of lipid and energy homeostasis as well as the onset and maintenance of obesity. We demonstrate through knockout and transgenic mouse models that miR-22 loss-of-function protects against obesity and hepatic steatosis, while its overexpression promotes both phenotypes even when mice are fed a regular chow diet. Mechanistically, we show that miR-22 controls multiple pathways related to lipid biogenesis and differentiation. Importantly, genetic ablation of miR-22 favors metabolic rewiring towards higher energy expenditure and browning of white adipose tissue, suggesting that modulation of miR-22 could represent a viable therapeutic strategy for treatment of obesity and other metabolic disorders.

Identifying and profiling structural similarities between Spike of SARS-CoV-2 and other viral or host proteins with Machaon.

Using protein structure to predict function, interactions, and evolutionary history is still an open challenge, with existing approaches relying extensively on protein homology and families. Here, we present Machaon, a data-driven method combining orientation invariant metrics on phi-psi angles, inter-residue contacts and surface complexity. It can be readily applied on whole structures or segments-such as domains and binding sites. Machaon was applied on SARS-CoV-2 Spike monomers of native, Delta and Omicron variants and identified correlations with a wide range of viral proteins from close to distant taxonomy ranks, as well as host proteins, such as ACE2 receptor. Machaon's meta-analysis of the results highlights structural, chemical and transcriptional similarities between the Spike monomer and human proteins, indicating a multi-level viral mimicry. This extended analysis also revealed relationships of the Spike protein with biological processes such as ubiquitination and angiogenesis and highlighted different patterns in virus attachment among the studied variants. Available at: https://machaonweb.com .

Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging.

Multiplexed antibody-based imaging enables the detailed characterization of molecular and cellular organization in tissues. Advances in the field now allow high-parameter data collection (>60 targets); however, considerable expertise and capital are needed to construct the antibody panels employed by these methods. Organ mapping antibody panels are community-validated resources that save time and money, increase reproducibility, accelerate discovery and support the construction of a Human Reference Atlas.

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP).

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.

Randomized Phase II Trial of Dendritic Cell/Myeloma Fusion Vaccine with Lenalidomide Maintenance after Upfront Autologous Hematopoietic Cell Transplantation for Multiple Myeloma: BMT CTN 1401.

PURPOSE: Vaccination with dendritic cell (DC)/multiple myeloma (MM) fusions has been shown to induce the expansion of circulating multiple myeloma-reactive lymphocytes and consolidation of clinical response following autologous hematopoietic cell transplant (auto-HCT). PATIENTS AND METHODS: In this randomized phase II trial (NCT02728102), we assessed the effect of DC/MM fusion vaccination, GM-CSF, and lenalidomide maintenance as compared with control arms of GM-CSF and lenalidomide or lenalidomide maintenance alone on clinical response rates and induction of multiple myeloma-specific immunity at 1-year posttransplant. RESULTS: The study enrolled 203 patients, with 140 randomized posttransplantation. Vaccine production was successful in 63 of 68 patients. At 1 year, rates of CR were 52.9% (vaccine) and 50% (control; P = 0.37, 80% CI 44.5%, 61.3%, and 41.6%, 58.4%, respectively), and rates of VGPR or better were 85.3% (vaccine) and 77.8% (control; P = 0.2). Conversion to CR at 1 year was 34.8% (vaccine) and 27.3% (control; P = 0.4). Vaccination induced a statistically significant expansion of multiple myeloma-reactive T cells at 1 year compared with before vaccination (P = 0.024) and in contrast to the nonvaccine arm (P = 0.026). Single-cell transcriptomics revealed clonotypic expansion of activated CD8 cells and shared dominant clonotypes between patients at 1-year posttransplant. CONCLUSIONS: DC/MM fusion vaccination with lenalidomide did not result in a statistically significant increase in CR rates at 1 year posttransplant but was associated with a significant increase in circulating multiple myeloma-reactive lymphocytes indicative of tumor-specific immunity. Site-specific production of a personalized cell therapy with centralized product characterization was effectively accomplished in the context of a multicenter cooperative group study. See related commentary by Qazilbash and Kwak, p. 4703.

Targeting of microRNA-22 Suppresses Tumor Spread in a Mouse Model of Triple-Negative Breast Cancer.

microRNA-22 (miR-22) is an oncogenic miRNA whose up-regulation promotes epithelial-mesenchymal transition (EMT), tumor invasion, and metastasis in hormone-responsive breast cancer. Here we show that miR-22 plays a key role in triple negative breast cancer (TNBC) by promoting EMT and aggressiveness in 2D and 3D cell models and a mouse xenograft model of human TNBC, respectively. Furthermore, we report that miR-22 inhibition using an LNA-modified antimiR-22 compound is effective in reducing EMT both in vitro and in vivo. Importantly, pharmacologic inhibition of miR-22 suppressed metastatic spread and markedly prolonged survival in mouse xenograft models of metastatic TNBC highlighting the potential of miR-22 silencing as a new therapeutic strategy for the treatment of TNBC.

Toker Cell Hyperplasia in the Nipple-Areolar Complex of Transmasculine Individuals.

We previously reported breast histopathologic features associated with testosterone therapy in transmasculine chest-contouring surgical specimens. During that study, we observed a high frequency of intraepidermal glands in the nipple-areolar complex (NAC) formed by Toker cells. This study reports Toker cell hyperplasia (TCH)-the presence of clusters of Toker cells consisting of at least 3 contiguous cells and/or glands with lumen formation-in the transmasculine population. Increased numbers of singly dispersed Toker cells were not considered TCH. Among the 444 transmasculine individuals, 82 (18.5%) had a portion of their NAC excised and available for evaluation. We also reviewed the NACs from 55 cisgender women who were aged <50 years old and had full mastectomies. The proportion of transmasculine cases with TCH (20/82; 24.4%) was 1.7-fold higher than cisgender women (8/55; 14.5%) but did not achieve significance (P = .20). However, in cases with TCH, the rate of gland formation is 2.4-fold higher in transmasculine cases, achieving borderline significance (18/82 vs 5/55; P = .06). Among transmasculine individuals, TCH was significantly more likely to be present in those with higher body mass index (P = .03). A subset of 5 transmasculine and 5 cisgender cases were stained for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), androgen receptor (AR), cytokeratin 7, and Ki67. All 10 cases were cytokeratin 7+ and Ki67-; 9 out of 10 cases were AR+. Toker cells in transmasculine cases demonstrated variable expression of ER, PR, and HER2. For cisgender cases, Toker cells were consistently ER+, PR-, and HER2-. In conclusion, there is a higher rate of TCH in the transmasculine than cisgender population, particularly among transmasculine individuals with high body mass index and taking testosterone. To our knowledge, this is the first study to demonstrate that Toker cells are AR+. Toker cell features display variable ER, PR, and HER2 immunoreactivity. The clinical significance of TCH in the transmasculine population remains to be elucidated.

SHP-2 and PD-1-SHP-2 signaling regulate myeloid cell differentiation and antitumor responses.

The inhibitory receptor PD-1 suppresses T cell activation by recruiting the phosphatase SHP-2. However, mice with a T-cell-specific deletion of SHP-2 do not have improved antitumor immunity. Here we showed that mice with conditional targeting of SHP-2 in myeloid cells, but not in T cells, had diminished tumor growth. RNA sequencing (RNA-seq) followed by gene set enrichment analysis indicated the presence of polymorphonuclear myeloid-derived suppressor cells and tumor-associated macrophages (TAMs) with enriched gene expression profiles of enhanced differentiation, activation and expression of immunostimulatory molecules. In mice with conditional targeting of PD-1 in myeloid cells, which also displayed diminished tumor growth, TAMs had gene expression profiles enriched for myeloid differentiation, activation and leukocyte-mediated immunity displaying >50% overlap with enriched profiles of SHP-2-deficient TAMs. In bone marrow, GM-CSF induced the phosphorylation of PD-1 and recruitment of PD-1-SHP-2 to the GM-CSF receptor. Deletion of SHP-2 or PD-1 enhanced GM-CSF-mediated phosphorylation of the transcription factors HOXA10 and IRF8, which regulate myeloid differentiation and monocytic-moDC lineage commitment, respectively. Thus, SHP-2 and PD-1-SHP-2 signaling restrained myelocyte differentiation resulting in a myeloid landscape that suppressed antitumor immunity.

Neutrophil extracellular traps contribute to liver damage and increase defective low-density neutrophils in alcohol-associated hepatitis.

BACKGROUND & AIMS: In alcohol-associated hepatitis (AH), inflammation and neutrophil counts correlate with poor clinical outcomes. Here, we investigated how neutrophils contribute to liver damage in AH. METHODS: We isolated blood neutrophils from individuals with AH to examine neutrophil extracellular traps (NETs) and performed RNA sequencing to explore their unique characteristics. RESULTS: We observed a significant increase in NET production in AH. We also observed a unique low-density neutrophil (LDN) population in individuals with AH and alcohol-fed mice that was not present in healthy controls. Transcriptome analysis of peripheral LDNs and high-density neutrophils (HDNs) from individuals with AH revealed that LDNs exhibit a functionally exhausted phenotype, while HDNs are activated. Indeed, AH HDNs exhibited increased resting reactive oxygen species (ROS) production and produced more ROS upon lipopolysaccharide stimulation than control HDNs, whereas AH LDNs failed to respond to lipopolysaccharide. We show that LDNs are generated from HDNs after alcohol-induced NET release in vitro, and this LDN subset has decreased functionality, including reduced phagocytic capacity. Moreover, LDNs showed reduced homing capacity and clearance by macrophage efferocytosis; therefore, dysfunctional neutrophils could remain in the circulation and liver. Depletion of both HDNs and LDNs in vivo prevented alcohol-induced NET production and liver damage in mice. Granulocyte-colony stimulating factor treatment also ameliorated alcohol-induced liver injury in mice. CONCLUSION: Neutrophils contribute to liver damage through increased NET formation which increases defective LDNs in AH. Alcohol induces phenotypic changes in neutrophils; HDNs are activated whereas LDNs are defective. Our findings provide mechanistic insights that could guide the development of therapeutic interventions for AH. IMPACT AND IMPLICATIONS: In this study we discovered heterogeneity of neutrophils in alcohol-associated hepatitis, including high-density and low-density neutrophils that show hyper-activated or exhausted transcriptomic profiles, respectively. We found that alcohol induces neutrophil extracellular trap (NET) formation, which contributes to liver damage. NET release by high-density neutrophils resulted in low-density neutrophils that reside in the liver and escape clean-up by macrophages. Our findings help to understand the opposing neutrophil phenotypes observed in individuals with alcohol-associated hepatitis and provide mechanistic insights that could guide therapeutic strategies targeting neutrophils.

Tissue-Specific Human Extracellular Matrix Scaffolds Promote Pancreatic Tumour Progression and Chemotherapy Resistance.

Over 80% of patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed at a late stage and are locally advanced or with concurrent metastases. The aggressive phenotype and relative chemo- and radiotherapeutic resistance of PDAC is thought to be mediated largely by its prominent stroma, which is supported by an extracellular matrix (ECM). Therefore, we investigated the impact of tissue-matched human ECM in driving PDAC and the role of the ECM in promoting chemotherapy resistance. Decellularized human pancreata and livers were recellularized with PANC-1 and MIA PaCa-2 (PDAC cell lines), as well as PK-1 cells (liver-derived metastatic PDAC cell line). PANC-1 cells migrated into the pancreatic scaffolds, MIA PaCa-2 cells were able to migrate into both scaffolds, whereas PK-1 cells were able to migrate into the liver scaffolds only. These differences were supported by significant deregulations in gene and protein expression between the pancreas scaffolds, liver scaffolds, and 2D culture. Moreover, these cell lines were significantly more resistant to gemcitabine and doxorubicin chemotherapy treatments in the 3D models compared to 2D cultures, even after confirmed uptake by confocal microscopy. These results suggest that tissue-specific ECM provides the preserved native cues for primary and metastatic PDAC cells necessary for a more reliable in vitro cell culture.