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PDF file, 80K, Supplementary Tables 4-8: 4. LOH patterns in three cohorts, 5A&B. FLOH and chemotherapy resistance in three cohorts, 6. BRCA mutations in the AOCS, 7. Univariate and multivariate analysis of platinum resistantce, 8. PFS in LOH subclusters and patients with BRCA mutations.

XLS file, 509K, supplementary Tables 1-3: 1. Information from the Boston cohort, 2. Information from AOCS cohort, 3. Information from TCGA.

PDF file, 366K, Supplementary Figures 1-9: 1. LOH patterns on different array platforms, 2. Allelic imbalance in LOH clusters, 3. LOH clustering breast cancer, 4. LOH and copy number prevalence in breast cancer, 5. Chemotherapy resistance and FLOH in three cohorts, 6. Chemotherapy resistance and FLOH with or without BRCA mutations, 7. PFS regardless of stage and residual disease, 8. PFS with or without BRCA mutations, 9. BRCA1 expression and FLOH.

Purpose: High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR causes uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers.Experimental Design: We examined LOH and copy number changes using single nucleotide polymorphism array data from three HGSC cohorts and compared results to a cohort of high-grade breast cancers. The LOH profiles in HGSC were matched to chemotherapy resistance and progression-free survival (PFS).Results: LOH-based clustering divided HGSC into two clusters. The major group displayed extensive LOH and was further divided into two subgroups. The second group contained remarkably less LOH. BRCA1 promoter methylation was associated with the major group. LOH clusters were reproducible when validated in two independent HGSC datasets. LOH burden in the major cluster of HGSC was similar to triple-negative, and distinct from other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS.Conclusions: Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors. Clin Cancer Res; 18(20); 5806–15. ©2012 AACR.

ObjectiveTo determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional medical recommendation algorithms in the literature.MethodsDemand for medical expertise far outstrips supply, with tens of millions in the US alone with deficient access to specialty care. Rather than potentially months long delays to initiate diagnostic workup and medical treatment with a specialist, referring primary care supported by an automated recommender algorithm could anticipate and directly initiate patient evaluation that would otherwise be needed at subsequent a specialist appointment. We propose a novel graph representation learning approach with a heterogeneous graph neural network to model structured electronic health records and formulate recommendation/prediction of subsequent specialist orders as a link prediction problem.ResultsModels are trained and assessed in two specialty care sites: endocrinology and hematology. Our experimental results show that our model achieves an 8% improvement in ROC-AUC for endocrinology (ROC-AUC=0.88) and 5% improvement for hematology (ROC-AUC=0.84) personalized procedure recommendations over prior medical recommender systems. These recommender algorithm approaches provide medical procedure recommendations for endocrinology referrals more effectively than manual clinical checklists (recommender: precision=0.60, recall=0.27, F1-score=0.37) vs. (checklist: precision=0.16, recall=0.28, F1-score=0.20), and similarly for hematology referrals (recommender: precision=0.44, recall=0.38, F1-score=0.41) vs. (checklist: precision=0.27, recall=0.71, F1-score=0.39).ConclusionEmbedding graph neural network models into clinical care can improve digital specialty consultation systems and expand the access to medical experience of prior similar cases.

Introduction: Acute myeloid leukemia (AML) has a poor prognosis, despite aggressive therapies and a recent expansion in the array of treatments. Treatment is often determined by mutations, which risk-stratify a patient’s leukemia or can identify mutations that serve as therapeutic targets. Although common mutations in AML have been extensively studied, less research has formally characterized the order by which mutations tend to occur and how this order relates to properties of the disease. Methods: We leveraged published, single-cell DNA sequencing data from three institutions to model the clonal evolution of AML. Sequencing had been performed using targeted sequencing panels covering 19 to 37 genes, and driver mutations were identified using conservative filters. Mutation trees were created using Single Cell Inference of Tumor Evolution (SCITE). Clonal evolution patterns, including across clinical timepoints, were identified and compared to patient characteristics, disease phenotype, and outcomes. The BeatAML dataset was leveraged to explore associations between mutation order and gene expression. Results: Using 835 driver mutations from 276 samples and 209 patients, we identified 223 total unique mutation patterns. Branched evolution primarily involves FLT3 and RAS pathway mutations, whereas certain mutation pairs, such as NPM1 and FLT3, always occurred linearly in the same clone. Although some mutation pairs, such as those related to DNA methylation versus the RAS pathway, tended to occur in a specific order, several cases exhibited atypical orderings. Early signaling gene mutations were associated with younger patient age and increased signaling mutation homozygosity while NRAS-first cases were associated with increased monocyte counts. NRAS-first cases were also associated with distinct gene expression patterns in the BeatAML dataset. Paired diagnosis and relapse samples revealed novel associations between mutations gained at relapse and their clonal context, and these analyses supported a relative fitness advantage for signaling mutations in clones containing mutations in NPM1 or genes affecting DNA methylation. Conclusions: Clonal evolution in AML can be reconstructed at scale using single-cell DNA sequencing data, and different mutation acquisition patterns are associated with distinct leukemia and patient characteristics, despite cases having similar co-mutation patterns. Citation Format: Matthew Schwede, Katharina Jahn, Linde A Miles, Robert L Bowman, Jack Kuipers, Troy M Robinson, Asiri Ediriwickrema, Andrew J Gentles, Ross Levine, Niko Beerenwinkel, Koichi Takahashi, Ravindra Majeti. Characterizing the order of mutation acquisition in acute myeloid leukemia using large-scale single-cell sequencing [abstract]. In: Proceedings of the AACR Special Conference: Acute Myeloid Leukemia and Myelodysplastic Syndrome; 2023 Jan 23-25; Austin, TX. Philadelphia (PA): AACR; Blood Cancer Discov 2023;4(3_Suppl):Abstract nr A49.

OBJECTIVES The acute respiratory distress syndrome is common in critically ill patients. Recognition is crucial because acute respiratory distress syndrome is associated with a high mortality rate, and low tidal volume ventilation improves mortality. However, acute respiratory distress syndrome often goes unrecognized. Risk factors for under-recognition and trends over time have not been fully described. DESIGN Retrospective chart review of patients with acute respiratory distress syndrome from a prospective cohort study of critically ill patients. For each patient's ICU stay, we searched the chart for terms that indicated that acute respiratory distress syndrome was diagnosed, in the differential diagnosis, or treated with low tidal volume ventilation. SETTING ICUs at a tertiary hospital at the University of California, San Francisco between 2008 and 2016. PATIENTS Critically ill patients with acute respiratory distress syndrome. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Acute respiratory distress syndrome was recognized in 70% of patients, and recognition increased from 60% in 2008-2009 to 92% in 2016 (p = 0.004). Use of tidal volumes less than 6.5 mL/kg also increased (p < 0.001) from 20% to 92%. Increased acute respiratory distress syndrome severity (p = 0.01) and vasopressor use (p = 0.04) were associated with greater recognition. Clinician diagnosis of acute respiratory distress syndrome and inclusion of acute respiratory distress syndrome in the differential diagnosis were associated with tidal volumes less than 6.5 mL/kg (51% use of tidal volume ≤ 6.5 mL/kg if acute respiratory distress syndrome recognized vs 15% if not recognized; p = 0.002). Diagnosing acute respiratory distress syndrome was associated with lower tidal volume in multivariate analysis. CONCLUSIONS Although acute respiratory distress syndrome recognition and low tidal volume ventilation use have increased over time, they remain less than universal. Clinician recognition of acute respiratory distress syndrome is associated with both systemic and respiratory severity of illness and is also associated with use of low tidal volume ventilation.

Chronic neutrophilia is commonly seen with persistent infections, inflammatory disorders, smoking, solid tumors, and specific medications. However, after reactive causes have been excluded, a workup for primary (clonal) neutrophilic disorders, such as myeloproliferative neoplasms (MPNs) and myelodysplastic/myeloproliferative overlap syndromes, should be pursued. Except for chronic myeloid leukemia, which is defined by the presence of the Philadelphia (Ph) chromosome, and the classic Ph chromosome-negative MPNs (polycythemia vera, essential thrombocythemia, and primary myelofibrosis), clonal neutrophilic neoplasms historically have been challenging to diagnose and classify. The 2016 revised World Health Organization classification of these disorders has been based mainly on clinicopathologic features. However, recent discoveries of the molecular alterations underlying these disorders have served to supplement our knowledge of their morphologic and clinical features, opening new therapeutic avenues. In this review, we discuss the diagnostic approach, prognostic features, and treatments of neutrophilic myeloid neoplasms, with a focus on chronic neutrophilic leukemia, atypical chronic myeloid leukemia, and chronic myelomonocytic leukemia.

11010 Background: Oncology is a vast and fast-paced field. Fellows must expend significant effort to learn and stay updated. Up-to-date learning tools covering core oncology content in a digestible manner are lacking. Additionally, passive lectures are common in oncology, while constructivist approaches that may improve learning are rare. Therefore, we piloted updatable online modules (“scaffolds”) as a learning tool for oncology fellows. Methods: Author SB, a University of California, San Francisco (UCSF) solid-tumor oncologist, designed 12 scaffolds (breast, non-small cell lung, small cell lung, head/neck, salivary/thyroid, upper gastrointestinal, lower gastrointestinal, germ cell, bladder/renal/adrenal, prostate, melanoma, and sarcoma) using Google Slides between 12/2018 and 6/2019. The scaffolds included bullet points and tables/figures synthesized from the ASCO self-evaluation program textbook’s solid tumor chapters and the National Comprehensive Cancer Network (NCCN) guidelines. We emailed scaffold links to all UCSF and Stanford oncology fellows in 2019-2020, including instructions for fellows to update the scaffolds without exceeding 20 slides per scaffold, 5 lines per slide, or 7 words per line. The scaffolds were reintroduced to new fellows at the beginning of each academic year. SB audited to ensure no erroneous information was added. In December 2021 we reviewed updates tracked in Google Slides and conducted one UCSF and one Stanford focus group with four 1st-3rd year fellows each. Results: Between 7/2019 and 12/2021, fellows made 60 updates to the scaffolds, with a mean of 5 updates per scaffold ranging from new trials to changes in management. During the same period, the auditor made 9 updates and found no erroneous fellow updates. Fellow updates occasionally exceeded specified limits, requiring correction. Content analysis revealed that fellows considered the scaffolds to be accessible and succinct learning tools that 1) addressed a dearth of similar resources, 2) served as effective preparation for clinical work and examinations, 3) provided structured information for rapid review, and 4) made subsequent interactions with complex resources such as NCCN guidelines easier. Barriers to fellows updating the scaffolds included lack of ownership and low confidence in judgment regarding appropriate updates. Conclusions: In this two-institution pilot, oncology fellows used and subsequently updated online scaffolds in a constructivist fashion. This model has the potential to fill a crucial gap in available learning resources and can be applied to other specialties. Assigning scaffolds to fellows with faculty mentorship may facilitate ownership and bolster fellow confidence in updating these tools. Individual institutions may update their own versions of the scaffolds to align with institution-specific needs.

Background: The combination of HMA and venetoclax is now standard of care for patients with AML who are not candidates for intensive chemotherapy. Elderly patients are more likely to have secondary AML (sAML), although the presence of an antecedent hematologic malignancy is often not apparent by history. Lindsley et al (Blood, 2015) showed that a somatic mutation in SRSF2, SF3B1, U2AF1, ZRSR2, ASXL1, EZH2, BCOR, or STAG2 is >95% specific for sAML and associated with worse outcomes. While outcomes with HMA/ven in patients meeting standard criteria for sAML have recently been reported (Pullarkat, ASCO 2021), we set out to conduct a real-world analysis of sAML patients receiving HMA/ven, including those with a secondary mutation profile (SMP) as described by Lindsley et al. We hypothesized that-when treated with HMA/ven-outcomes of patients with SMP may be most similar to those with de novo AML. Methods: Patients diagnosed with AML at Stanford Cancer Institute from 4/2017-3/2021 and treated with front-line HMA/ven were retrospectively reviewed. These included patients previously treated with HMA monotherapy for an antecedent hematologic malignancy and those who had previously received ≤ 3 cycles of HMA monotherapy for AML. Responses were classified per the modified International Working Group response criteria. Overall survival (OS) was assessed for all patients, and for patients who had a complete response (CR) or CR with incomplete hematologic recovery (CRi), duration of response (DoR) was also assessed. Statistical analyses were performed in R using the logrank test, with hazard ratios (HR) computed using the Cox proportional hazards model. For multivariate analyses, p-values for a specific variable were calculated using Cox proportional hazards regression. Results: 82 patients met criteria for inclusion; 78 had valid response assessments and 49 (62.8%) had achieved a CR or CRi at first response assessment. Median age was 72 years, with 3 patients younger than 60. 62 patients were male, median ECOG performance status (PS) was 1, median Charlson Comorbidity Index (CCI) was 6, median time to death or end of follow-up from the start of treatment was 366 days, and 58% of patients had adverse risk AML per ELN guidelines. Fig 1a demonstrates demographics for de novo, sAML (excluding SMP), and patients with SMP AML. 13 patients met criteria for AML-MRC, 23 patients had prior history of antecedent hematologic malignancy (18 with MDS or CMML, 5 with MDS/MPN overlap or MPN), 12 had tAML, and 20 patients possessed a SMP and did not meet criteria for the other three categories of sAML. 14 patients with de novo AML were characterized by the absence of any of the above factors. Patients with de novo AML were less likely to have adverse risk disease (29% vs. 64% in others) and had lower CCI scores (mean 5.1 vs. 6.2) but had no significant differences in age, gender, follow-up time, or PS. There was no statistically significant difference in rates of CR/CRi between the different subgroups or the different types of sAML; 69% of patients with de novo AML, 79% of SMP patients, and 57% of patients with other types of sAML achieved a CR or CRi. However, SMP patients had response durations and OS patterns similar to patients with de novo AML (Fig 1b and 1c), and when grouped with de novo patients, both DoR (HR = 3.5, p = 0.047, Fig 1d) and OS (HR = 2.1, p = 0.042, Fig 1e) were significantly longer than those of the sAML patients. Neither DoR nor OS were significantly longer when the SMP patients were grouped with sAML patients (respectively: HR = 3.3, p = 0.22, Fig 1f; HR = 1.5, p = 0.37, Fig 1g). In multivariate Cox proportional regression adjusting for age, ELN risk category, CCI, and PS, worse OS for sAML patients was maintained relative to the SMP and de novo patients (HR 2.9, p = 0.036), although the difference in DoR was no longer significant (HR 4.4, p= 0.10). Conclusions: Patients meeting standard definitions of sAML had worse outcomes than those with de novo AML when treated with HMA/ven in a retrospective, real-world analysis. Although a secondary mutation profile as described by Lindsley et al may be helpful in identifying patients with sAML, when treated with HMA/ven, patients with this profile have outcomes that align more closely with those of patients with de novo AML. Figure 1 Figure 1. Disclosures Mannis: Astex, Forty Seven Inc/Gilead, Glycomimetics, and Jazz Pharmaceuticals: Research Funding; AbbVie, Agios, Astellas Pharma, Bristol Myers Squibb, Genentech, MacroGenics, Pfizer, and Stemline: Consultancy.

Human mesenchymal stem/stromal cells (hMSCs) are a promising therapy for acute respiratory distress syndrome (ARDS) and other inflammatory conditions. While considerable research has focused on paracrine effects and mitochondrial transfer that improve lung fluid balance, hMSCs are well known to have immunomodulatory properties as well. Some of these immunomodulatory properties have been related to previously reported paracrine effectors such as indoleamine-2,3-dioxygenase (IDO), but these effects cannot fully account for cell-contact dependent immunomodulation. Here, we report that CD40 is upregulated on hMSCs under the same conditions previously reported to induce IDO. Further, CD40 transcription is also upregulated on hMSCs by ARDS pulmonary edema fluid but not by hydrostatic pulmonary edema fluid. Transcription of CD40, as well as paracrine effectors TSG6 and PTGS2 remained significantly upregulated for at least 12 hours after withdrawal of cytokine stimulation. Finally, induction of this immune phenotype altered the transdifferentiation of hMSCs, one of their hallmark properties. CD40 may play an important role in the immunomodulatory effects of hMSCs in ARDS and inflammation.

Background: Recent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures. Methods: Gene signatures of tumor and stroma were developed using paired microdissected tissue from two independent studies. Stromal genes were investigated in two molecular subtype classifications and 61 published gene signatures. Prognostic performance of gene signatures of stromal admixture was evaluated in 2,527 ovarian tumors (16 studies). Computational simulations of increasing stromal cell proportion were performed by mixing gene-expression profiles of paired microdissected ovarian tumor and stroma. Results: Recently described ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations where the percentage of stromal cells increased. Stromal gene expression in bulk tumors was associated with overall survival (hazard ratio, 1.17; 95% confidence interval, 1.11–1.23), and in one data set, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content. Conclusions: Cell admixture affects the interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Elucidating the role of stroma in the tumor microenvironment and in prognosis is important. Impact: Single-cell analyses may be required to refine the molecular subtypes of high-grade serous ovarian cancer.

PurposeRecent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures.Experimental DesignPublic gene expression data, two molecular subtype classifications, and 61 published gene signatures of ovarian cancer were examined. Using microdissected data, we developed gene signatures of ovarian tumor and stroma. Computational simulations of increasing stromal cell proportion were performed by mixing gene expression profiles of paired microdissected ovarian tumor and stroma.ResultsEstablished ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations, when the percentage of stromal cells increased. Stromal gene expression in bulk tumor was weakly prognostic, and in one dataset, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content alone.ConclusionsThe discovery that molecular subtypes of high grade serous ovarian cancer is influenced by cell admixture, and stromal cell gene expression is crucial for interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Single cell analysis may be required to refine the molecular subtypes of high grade serous ovarian cancer. Because stroma proportion was weakly prognostic, elucidating the role of the tumor microenvironment’s components will be important.Translational relevanceOvarian cancer is a leading cause of cancer death in women in the United States. Although the tumor responds to standard therapy for the majority of patients, it frequently recurs and becomes drug-resistant. Recent efforts have focused on identifying molecular subtypes and prognostic gene signatures of ovarian cancer in order to tailor therapy and improve outcomes. This study demonstrates that molecular subtype identification depends on the ratio of tumor to stroma within the specimen. We show that the specific anatomic location of the biopsy may influence the proportion of stromal involvement and potentially the resulting gene expression pattern. It will be crucial for these factors to be taken into consideration when interpreting and reproducing ovarian cancer molecular subtypes and gene signatures derived using bulk tissue and single cells. Furthermore, it will be important to define the relative proportions of stromal cells and model their prognostic importance in the tumor microenvironment.

Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0-HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors.

The Accreditation Council for Graduate Medical Education (ACGME) first established national standards for resident duty hours in 2003 as part of the Common Program Requirements.1 Residents were limited to 30-hour duty periods, with a maximum 80 working hours and 1 day free from clinical responsibilities each week, averaged over a 4-week period.1 In 2008, the Institute of Medicine recommended greater supervision and additional limits on residents' hours.2

Mutations that cause neurological phenotypes are highly informative with regard to mechanisms governing human brain function and disease. We report autosomal recessive mutations in the enzyme glutamate pyruvate transaminase 2 (GPT2) in large kindreds initially ascertained for intellectual and developmental disability (IDD). GPT2 [also known as alanine transaminase 2 (ALT2)] is one of two related transaminases that catalyze the reversible addition of an amino group from glutamate to pyruvate, yielding alanine and α-ketoglutarate. In addition to IDD, all affected individuals show postnatal microcephaly and ∼80% of those followed over time show progressive motor symptoms, a spastic paraplegia. Homozygous nonsense p.Arg404* and missense p.Pro272Leu mutations are shown biochemically to be loss of function. The GPT2 gene demonstrates increasing expression in brain in the early postnatal period, and GPT2 protein localizes to mitochondria. Akin to the human phenotype, Gpt2-null mice exhibit reduced brain growth. Through metabolomics and direct isotope tracing experiments, we find a number of metabolic abnormalities associated with loss of Gpt2. These include defects in amino acid metabolism such as low alanine levels and elevated essential amino acids. Also, we find defects in anaplerosis, the metabolic process involved in replenishing TCA cycle intermediates. Finally, mutant brains demonstrate misregulated metabolites in pathways implicated in neuroprotective mechanisms previously associated with neurodegenerative disorders. Overall, our data reveal an important role for the GPT2 enzyme in mitochondrial metabolism with relevance to developmental as well as potentially to neurodegenerative mechanisms.

Activity-dependent neuroprotective protein (ADNP) is a highly conserved transcription factor comprised of nine-zinc finger domains and a homeobox domain.1 ,2 It is highly expressed prenatally during critical stages of embryonic brain development.3 Knockout (KO) mouse embryos demonstrate severe neurodevelopmental morphological profiles.4 Although the ADNP KO is lethal, heterozygous embryos demonstrate typical embryogenesis yet display a neurodevelopmental delay phenotype including decreased neuronal survival.3 ,5 Exome sequencing in the Simons Simplex Collection autism dataset identified ADNP mutations as a putative autism gene candidate.6 ,7 Helsmoortel et al 8 recently reported 10 individuals with autism spectrum disorder (ASD) and mutations in exon 5 of the ADNP gene, nine of which were confirmed de novo. These patients also exhibited intellectual disability (ID) and dysmorphic features such as a prominent forehead. Mutations in the ADNP gene are estimated to be present in at least 0.17% of ASD cases. The current report further expands the ADNP phenotype to include abnormalities in the developing visual system (such as eye movement abnormalities and cortical visual impairment). We advise appropriate screening of eye movement and visual symptoms by clinicians in patients who have mutations in ADNP . The 6-year-old patient was the first child born to healthy non-consanguineous parents. Pregnancy was notable for placenta previa and early dilation and effacement of the cervix 3 weeks prior to delivery. The patient was born at 40 weeks via C-section secondary to failure to progress and maternal (i.e. maternal hypertension) hypertension weighing 6 pounds 14 ounces. She had a short stay in the neonatal intensive care unit (NICU) for breathe holding and feeding problems. She was also hospitalised at 6 weeks for an acute life-threatening event of multiple cyanotic episodes thought to be due to breath holding. Our patient has been diagnosed with hypotonia and mixed developmental …

The acute respiratory distress syndrome (ARDS) is common in critically ill patients and has a high mortality rate. Mesenchymal stromal cells (MSCs) have demonstrated therapeutic potential in animal models of ARDS, and their benefits occur in part through interactions with alveolar type II (ATII) cells. However, the effects that MSCs have on human ATII cells have not been well studied. Using previously published microarray data, we performed genome‐wide differential gene expression analyses of human ATII cells that were (1) unstimulated, (2) exposed to proinflammatory cytokines (CytoMix), or (3) exposed to proinflammatory cytokines plus MSCs. Findings were validated by qPCR. Alveolar type II cells differentially expressed hundreds of genes when exposed either to proinflammatory cytokines or to proinflammatory cytokines plus MSCs. Stimulation with proinflammatory cytokines increased expression of inflammatory genes and downregulated genes related to surfactant function and alveolar fluid clearance. Some of these changes, including expression of some cytokines and genes related to surfactant, were reversed by exposure to MSCs. In addition, MSCs induced upregulation of other potentially beneficial genes, such as those related to extracellular matrix remodeling. We confirmed several of these gene expression changes by qPCR. Thus, ATII cells downregulate genes associated with surfactant and alveolar fluid clearance when exposed to inflammatory cytokines, and mesenchymal stromal cells partially reverse many of these gene expression changes.

The Association of American Medical Colleges' Entrustable Professional Activity (EPA) 6 states that “the day 1 resident should be able to concisely present a summary of a clinical encounter to one or more members of the health care team (including patients and families) in order to achieve a shared understanding of the patient's current condition.” It further notes that the entrustable student should be able to “provide an accurate, concise, and well-organized oral presentation” and to “adjust the oral presentation to meet the needs of the receiver of the information.” This curriculum focuses specifically on how to adjust the oral presentation according to the needs of the specialty and provides a foundation upon which students can further refine their skills during clerkships. This curriculum is designed to teach second-year medical students the fundamentals of specialty-specific oral presentations just prior to the start of their clinical rotations. The curriculum covers the most common core clerkships at US medical schools: internal medicine, family medicine, pediatrics, surgery, obstetrics and gynecology, psychiatry, neurology, and emergency medicine. The curriculum serves as an extension of the MedEdPORTAL publication “Teaching Oral Presentation Skills to Second-Year Medical Students.” This curriculum was successfully deployed during Brown's Clinical Skills Clerkship (CSC) in 2015. Although there has been a session on specialty-specific OPs for the past 3 years, the current iteration of the curriculum has only been in use for 1 year. In 2015, 121 students completed the CSC. Students ranked the effectiveness of instruction on specialty-specific OPs by the senior medical students on a 1-6 Likert scale (1 = Poor, 6 = Outstanding). The mean of these scores was 4.72 (SD = 0.99). Qualitative comments suggested that students appreciated the opportunity to focus on what they would need to do in the specialty of their first clerkship, while simultaneously gaining a broad perspective of how oral presentation requirements would change during each core rotation. Students appreciated having the resources organized by specialty to access them easily both during the CSC and for future reference.

Autism is a highly heterogeneous neurodevelopmental disorder with impaired language, social communication, and restricted and repetitive interests and behavior. Monogenic developmental brain disorders with autism features such as Rett syndrome, Angelman syndrome, Fragile X syndrome, and others provide important tractable models of relevance to severe autism. In addition to observing autism symptoms in the monogenic condition, if the gene responsible is also significantly misregulated in the brains of people with idiopathic autism, then these data provide substantial independent support for the importance of the gene in autism pathophysiology. Given this logic, we set out to test if there were gene expression changes in postmortem brain tissue from patients with idiopathic autism in the genes of interest that encode the Na+/H+ exchanger family of proteins, with particular interest in the forms of exchangers localized to endosomes, namely, NHE6 and NHE9. Mutations in the X-linked endosomal Na+/H+ Exchanger 6 (NHE6, also known as SLC9A6) represent a novel neurogenetic syndrome with variable expressivity.1 In a systematic, large-scale resequencing screen of X-chromosome coding exons in >200 pedigrees consistent with X-linked intellectual disability, NHE6 was among the top six most recurrently mutated genes.2 The ‘Christianson syndrome', based on the initial clinical description, reported an association with autistic symptoms as has been reported subsequently.3, 4 In parallel to the description of autistic symptoms associated with mutations in NHE6, Morrow et al.5 published mutations in the highly related endosomal protein NHE9 in severe autism with epilepsy. Endosomal processes, such as would be suggested by mutations in NHE6 and NHE9, represent an important cellular mechanism for investigations regarding disorders of cognitive development. Interestingly, of the six top genes implicated in the Tarpey et al.2 study, two of the genes, NHE6 and AP1S2, are known to be involved in endosomal mechanisms. We therefore investigated whether the expression of NHE genes, NHE6 and NHE9, were altered in autism cerebral cortex. We did this by renormalizing and analyzing publically available microarray data. Specifically, we first analyzed data from Voineagu et al.,6 which were previously used to compare autism and control cortex (n=29 of each). We renormalized the data as described in Voineagu et al.,6 except for when we wished to analyze a subset of NHE genes that were excluded from the analysis because of low expression. Among their results, Voineagu et al.6 reported that synapse-associated genes were downregulated in autism cortex,6 and we confirmed this result by performing differential gene expression analysis7 between autism and control cortex (for detailed Methods, please see Supplementary Information). We then performed DAVID functional annotation clustering analysis8, 9 on the 197 genes with at least 1.3-fold reduction in autism cortex and P 0.15). We further hypothesized that changes in these genes were reflective of broader changes in gene expression, such as downregulation of synapse genes. To investigate the functional changes associated with NHE1, NHE6 and NHE9 gene expression, we found Pearson correlation coefficients between each of these genes and the average expression of the 21 synapse-related genes. NHE1 was not significantly correlated with the synapse genes (r=0.15, P=0.28), but NHE6 and NHE9 both were strongly correlated with the synapse genes (r=0.86, P=4.2 × 10−18 for NHE6; r=−0.62, P=2.2 × 10−7 for NHE9—see Figure 1). Furthermore, the sub-population of samples with the lowest NHE6 expression was almost entirely autism cases, as was the sub-population of high NHE9 expression. Additionally, NHE6 and NHE9 were negatively correlated (P=0.00015), and when NHE6 expression was high, NHE9 was tightly regulated. A similar decrease in NHE9 variability could be seen with high synapse gene expression (Figure 1). Thus, a sub-population within autism is not only associated with lower synapse gene expression, but also with lower NHE6 expression and increased and potentially misregulated NHE9 expression. We also studied the correlation of NHE6 and NHE9 with the downregulated synapse gene set during normal brain development. We capitalized on the large mRNA-seq data set from human brain made available by the Allen Brain Institute (http://www.developinghumanbrain.org). We find that NHE6 clusters strongly during development with this synapse gene group (see Supplementary Information). NHE9 expression was far lower embryonically, increased postnatally but did not appreciably cluster with this synapse group in typical brain development (Supplementary Figures 1–3). Figure 1 Expression plots of NHE6 versus synapse genes, NHE9 versus synapse genes and NHE6 versus NHE9 in three independent data sets. We compared the average log base 2 expression of 21 synapse genes with that of NHE6 and NHE9 expression in microarray data sets ... We used two independent microarray data sets for autism and control cerebral cortex to validate both the differential gene expression of NHE6 and NHE9 in autism cases and these genes' associations with synapse genes. The validation data sets were from Chow et al.11 (n=15 autism, n=18 control) and Garbett et al.12 (n=6 of each; data set details in Supplementary Table 4). The Chow et al.11 data were downloaded from GEO ({"type":"entrez-geo","attrs":{"text":"GSE28475","term_id":"28475"}}GSE28475), and the Garbett et al.12 data were provided by the authors. In the Garbett et al.12 data, NHE9 was significantly higher in autism than control cortex (P=0.039), and while NHE6 was lower on average in autism cortex, this was not statistically significant (P=0.22), although this may have been due to low sample size (Figure 1). In the Chow et al.11 data, although NHE6 and NHE9 had lower and higher expression in autism cortex compared with control, respectively, these trends were not significant (P=0.38 and 0.17). However, the mean expression of synapse genes was also not significantly different in the Chow et al.11 data set (P=0.46), suggesting that the Voineagu et al.6 and Chow et al.11 data sets represent different populations. Additionally, NHE6 and NHE9 were negatively correlated across data sets, except for in Garbett et al.,12 in which the correlation was not significant (P=0.56) but suggesting as yet unknown mechanisms of interaction. Despite this lack of significance in the independent data sets, these genes' associations with synapse genes remained strong in both additional data sets: NHE6 is positively associated with synapse genes (r=0.59, P=0.00029 for NHE6 in Chow et al.11 study; and r=0.6, P=0.041 for NHE6 in Garbett et al.12 study—see Figure 1) and NHE9 negatively associated (r=−0.72, P=2.0 × 10−6 for NHE9 in Chow et al.11 study; and r=−0.78, P=0.0029 for NHE9 in Garbett et al.12 study—see Figure 1). Finally, we tested for an association of gene expression for NHE6 and NHE9 and well-established autism-related genes such as SHANK2/3, NLGN4X, NRXN1 and PTEN. Notably, NHE6 and NHE9 each showed a strong association with NRXN1 (P=2 × 10−10 for NHE6, and P=2.9 × 10−8 for NHE9; Supplementary Figures 4 and 5). In summary, we find interesting gene expression changes in endosomal NHE6 and NHE9 in postmortem autism brains. These gene expression changes are largely replicated across data sets or the trends of these changes are maintained given limitations in sample size. We also report a strong correlation of endosomal NHE6 and NHE9 gene expression with the synapse genes across all data sets. The strong correlation of endosomal NHEs with synapse genes suggests that changes in synapse genes in autism involves a cellular mechanism that involves endosomal NHE6 and NHE9 in at least some autism brains. In conclusion, these gene expression studies in postmortem brains from patients with idiopathic autism provide additional support, in addition to the association of autism symptoms with the single-gene mutations, that endosomal NHEs are mechanistically involved in the pathophysiology of autism.

We report on a pedigree with a pair of brothers each with minor anomalies, developmental delay, and autistic-symptoms who share an unbalanced translocation (not detectable by karyotype). The unbalanced translocation involves a 7.1 Mb loss of the terminal portion of 10q, and a 4.2 Mb gain of 11q. One of the brothers also developed a cerebellar juvenile pilocytic astrocytoma. The father was found to be a balanced carrier and the couple had a previous miscarriage. We demonstrate that the breakpoint for the triplicated region from chromosome 11 is adjacent to two IgLON genes, namely Neurotrimin (NTM) and Opioid Binding Protein/Cell Adhesion Molecule-like (OPCML). These genes are highly similar neural cell adhesion molecules that have been implicated in synaptogenesis and oncogenesis, respectively. The children also have a 10q deletion and are compared to other children with the 10q deletion syndrome which generally does not involve autism spectrum disorders (ASDs) or cancer. Together these data support a role for NTM and OPCML in developmental delay and potentially in cancer susceptibility.

The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.

Purpose: High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR causes uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers. Experimental Design: We examined LOH and copy number changes using single nucleotide polymorphism array data from three HGSC cohorts and compared results to a cohort of high-grade breast cancers. The LOH profiles in HGSC were matched to chemotherapy resistance and progression-free survival (PFS). Results: LOH-based clustering divided HGSC into two clusters. The major group displayed extensive LOH and was further divided into two subgroups. The second group contained remarkably less LOH. BRCA1 promoter methylation was associated with the major group. LOH clusters were reproducible when validated in two independent HGSC datasets. LOH burden in the major cluster of HGSC was similar to triple-negative, and distinct from other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS. Conclusions: Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors. Clin Cancer Res; 18(20); 5806–15. ©2012 AACR.

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.

The classification of lymphoma and leukemia is successfully done by using normal cell types as a reference point which is one of the many reasons that better therapies are available for their treatment. In case of breast cancer, clinically it is classified as Estrogen Receptor positive, Human Epidermal Growth Factor Receptor 2 (Her2) positive and triple negative breast cancer while in the research settings, it has been classified by mRNA expression profiling but these classification systems are still evolving. Our laboratory attempted to classify breast cancer by examining the expression of different keratin isoforms and Hormone Receptors (HR) studied through immunostaining in 36 normal breast samples and later in 1731 breast tumors from the Nurses' Health Study (NHS) cohort with a patient follow up extending beyond 25 years. Among the various receptors tested, three of these receptors: Androgen Receptor, Estrogen Receptor and Vitamin D Receptor were capable of identifying four major subgroups being designated as HR0-3, depending on the number of hormone receptors present. More importantly, radically different survival outcomes were observed between these HR sub-groups through Kaplan Meier curve analysis; which highlights their usefulness as vital biological markers as wells as targets for breast cancer treatment. Furthermore, the characterization of these HR was carried out in 20 different breast cancer cell lines and the combination of different receptor modulators alone or in combination was attempted with better anti-proliferative effects being observed in the combinatorial group than either treatment alone. Thus, our new classification not only re-classifies breast cancer but also gives insight on how patients could be treated through targeting hormone receptors. Citation Format: Ankita Thakkar, Sandro Santagata, Ayse Ergonul, Bin Wang, Terri Woo, Rong Hu, J. Chuck Harrell, George McNamara, Matthew Schwede, Aedin C. Culhane, David Kindelberger, Scott Rodig, Andrea Richardson, Stuart J. Schnitt, Rulla M. Tamimi, Tan A. Ince. Taxonomy of breast cancer based on normal cell phenotype and ontology. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr B067.