Ovarian cancer mutational processes drive site-specific immune evasion.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1-4 patterned by distinct mutational processes5,6, tumour heterogeneity7-9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11-13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFß signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer.

Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.

Harnessing multimodal data integration to advance precision oncology.

Advances in quantitative biomarker development have accelerated new forms of data-driven insights for patients with cancer. However, most approaches are limited to a single mode of data, leaving integrated approaches across modalities relatively underdeveloped. Multimodal integration of advanced molecular diagnostics, radiological and histological imaging, and codified clinical data presents opportunities to advance precision oncology beyond genomics and standard molecular techniques. However, most medical datasets are still too sparse to be useful for the training of modern machine learning techniques, and significant challenges remain before this is remedied. Combined efforts of data engineering, computational methods for analysis of heterogeneous data and instantiation of synergistic data models in biomedical research are required for success. In this Perspective, we offer our opinions on synthesizing complementary modalities of data with emerging multimodal artificial intelligence methods. Advancing along this direction will result in a reimagined class of multimodal biomarkers to propel the field of precision oncology in the coming decade.

Characterization of Recurrences Following Second Breast-Conserving Surgery with Intraoperative Radiotherapy.

BACKGROUND: Breast-conserving surgery with breast re-irradiation is an emerging technique in the treatment of selected cases of locally recurrent breast cancer. Further information is needed to characterize factors that may select for an appropriate patient population for this treatment approach. METHODS: We report herein a single-institution retrospective analysis of patients with ipsilateral breast cancer recurrence treated with a second breast-conserving therapy with intraoperative radiotherapy. Patient records were reviewed to analyze toxicity, further recurrence, and characteristics of recurrent patients following this treatment approach. RESULTS: We included 57 patients in the analysis. At median follow-up of 24.5 months, ipsilateral breast tumor recurrence occurred in six patients (11%), four of which localized to the quadrant of the initial recurrent disease and two of which recurred elsewhere in the treated breast. Locoregional control was 89%, and disease-free survival was 81%. Only one patient was found to have grade 3 or greater toxicity. CONCLUSION: A second breast-conserving surgery with intraoperative radiotherapy is tolerable with acceptable toxicity for patients with locally recurrent disease refusing mastectomy. Prospective clinical trials are needed to define the subset of patients who may be appropriate for this treatment approach as an alternative to mastectomy.

Systematic Review of the Effects of Phosphodiesterase-5 Inhibitors and Dexamethasone on High Altitude Pulmonary Edema (HAPE).

OBJECTIVE: To review and synthesize the current available evidence of the effects of phosphodiesterase-5 inhibitors and dexamethasone on the outcomes of individuals affected by acute mountain sickness symptoms and High Altitude Pulmonary Edema (HAPE). METHODS: In 2015, two authors independently performed separate searches using three different databases (PubMed, Ovid and Web of Science) later reviewed by the third author. The searches used the following terms "High Altitude Pulmonary Edema" and "Phosphodiesterase-5 Inhibitors" while the second search used "High Altitude Pulmonary Edema" and "Dexamethasone". The following exclusion criteria were utilized: patients < 18 years old, non-human studies, studies at altitudes < 2,000 meters. The search included articles from year 2000 to current. RESULTS: A total of 237 manuscripts were initially reviewed. The search involving phosphodiesterase-5 inhibitors initially yielded 37 manuscripts, four of which met inclusion criteria. A total of 101 patients were included in these articles. For the Dexamethasone search, 200 manuscripts were retrieved. Three of these studies met the inclusion criteria, reporting data on a total of 66 patients. None of the studies reported significant improvements in outcomes of patients from the use of either phosphodiesterase-5 inhibitors or dexamethasone. CONCLUSIONS: According to the current available literature, neither phosphodiesterase -5 inhibitors or dexamethasone significantly alter the outcome of individuals affected by HAPE.

An Atypical Case of Transverse Diverticulitis and the Changing Management of Diverticular Disease.

Diverticulitis is an inflammation of an out pouching of the lower gastrointestinal tract, particularly in the large intestine. Although the condition is taught to medical students as typically occurring in the left lower quadrant of the abdomen, right-sided and transverse forms diverticulitis can occur. Uncomplicated, e.g., non-perforated, diverticulitis is usually treated with antibiotics. Complicated, e.g. perforated, is usually treated with surgery. The purpose of this case report is to present an atypical case of perforated diverticulitis and review current recommendations for this condition. This was a case of transverse diverticulitis in a man in his late 40's who recovered with non-operative treatment. The widespread use of computerized tomography (CT) scans makes diagnosing diverticular disease relatively simple, but treatment is evolving. The case summarized here shows that less invasive measures can be used in treating both complicated and uncomplicated diverticular disease. After an uncomplicated in-patient admission for intravenous antibiotics, the patient was discharged in stable condition with a prescription for oral antibiotics and clinic follow-up. Classic medical school teaching concerning treatments for complicated and uncomplicated forms of diverticulitis have been updated but require further research testing.

Transient Hyperammonemia Seen in Post Seizure Activity: A Series of Six Case Reports.

Elevations in serum ammonia levels (i.e., hyperammonemia) have often been interpreted as signs of liver failure or errors in metabolism. The purpose of this series of case studies is to evaluate a trend in both the markedly elevated levels of ammonia, along with its rapid clearance in patients with seizures. These patient cases each occurred in a community-based, academic emergency department in the metropolitan Detroit area that provided care to approximately 70,000 patients during a four-year period. These six patient cases had each been found with observed seizure activity in which an initial and repeat ammonia in the emergency department was ordered. In all six cases, there was an initial elevation in ammonia with rapid subsequent clearance of ammonia. As demonstrated in this series of case studies, transient hyperammonemia levels may occur within the clinical context of seizure activity. With further research, it may be confirmed to be a differential diagnostic marker to delineate new onset or recurrent seizures in the ED.

First Report of Survival in Refractory Ventricular Fibrillation After Dual-Axis Defibrillation and Esmolol Administration.

There is a subset of patients who suffer a witnessed ventricular fibrillation (VF) arrest and despite receiving reasonable care with medications (epinephrine and amiodarone) and multiple defibrillations (3+ attempts at 200 joules of biphasic current) remain in refractory VF (RVF), also known as electrical storm. The mortality for these patients is as high as 97%. We present the case of a patient who, with a novel approach, survived RVF to outpatient follow up.

Improved Prediction of CYP-Mediated Metabolism with Chemical Fingerprints.

Molecule and atom fingerprints, similar to path-based Daylight fingerprints, can substantially improve the accuracy of P450 site-of-metabolism prediction models. Only two chemical fingerprints have been used in metabolism prediction, so little is known about the importance of fingerprint parameters on site of metabolism predictions. It is possible that different fingerprints might yield more accurate models. Here, we study if tuning fingerprints to specific site of metabolism data sets can lead to improved models. We measure the impact of 484 specific chemical fingerprints on the accuracy of P450 site-of-metabolism prediction models on nine P450 isoform site of metabolism data sets. Using a range of search depths, we study path, circular, and subgraph fingerprints. Two different labelings, also, are considered, both standard SMILES labels and also a labeling that marks ring bonds differently than nonring bonds, enabling ortho, para, and meta positioning of substituents to be more clearly encoded. Optimal fingerprint models chosen by cross-validation performance on the full training data are, on average, 3.8% (Top-2; percent of molecules with a site of metabolism in the top two predictions) and 1.4% (AUC; area under the ROC curve) more accurate than base fingerprint models. These gains represent, respectively, a 25.6% and 16.7% reduction in error. A more rigorous assessment selects fingerprints within each cross-validation fold, sometimes selecting different fingerprints for different folds, but yielding a more reliable estimate of generalization error. In this assessment, averaging the scores from the top few fingerprints yields performances improvements of, on average, 3.0% (Top-2) and 0.7% (AUC). These gains are statistically significant and represent, respectively, a 20.1% and 8.8% reduction in error. Between different isoforms, not many consistencies were observed among the top performing fingerprints, with different fingerprints working best for different isoforms. These results suggest that there are important gains achievable in site of metabolism modeling by including and optimizing atom and molecule fingerprints. The optimal site of metabolism models determined by this approach are available for use at http://swami.wustl.edu/.

Retrievable stent thrombectomy in the treatment of acute ischemic stroke: analysis of a revolutionizing treatment technique.

Acute ischemic stroke resulting from intracranial vessel occlusion is associated with high morbidity and mortality. The mainstays of therapy are fibrinolytics and mechanical thrombectomy in properly selected patients. A new Food and Drug Administration-approved technology to perform thrombectomy, retrievable stenting, may provide superior revascularization rates and improved patient outcomes. We analyzed the cumulative human experience reported for the Trevo Pro Retrieval System (Stryker, Kalamazoo, MI, USA) and the Solitaire FR Revascularization Device (ev3, Irvine, CA, USA) as the definitive treatment for acute ischemic stroke. A literature search was undertaken to identify studies using the retrievable stents published up to September 2012. Nineteen studies identified a total of 576 patients treated with either the Trevo (n=221) or Solitaire (n=355) devices. Pooled data analysis identified median baseline National Institutes of Health Stroke Scale scores of 18.5 ± 0.289 (standard error of the mean) and 17.9 ± 0.610, and time to recanalization of 53.9 ± 23.6 minutes and 59.0 ± 8.0 minutes for the Trevo and Solitaire groups, respectively. Recanalization was variably defined by individual studies, most commonly achieving at least a thrombolysis in cerebral infarction score of 2a-3 or a thrombolysis in myocardial infarction score of 2-3. Revascularization (83%, 82%), mortality (31%, 14%), hemorrhage (8%, 6%), device complications (5%, 6%), and good patient outcomes (51%, 47%) were found with the Trevo and Solitaire devices, respectively. Preliminary analysis reveals excellent clinical outcomes for retrievable stent technology. This may be attributable to both high rates of revascularization with a relatively short time to perfusion restoration.

An Acute Ibuprofen Overdose Masking a Severe Staphylococcus aureus Meningitis: A Case Report.

Acute bacterial meningitis has a low incidence (3/100,000 in the United States) and yet high fatality rate (approximately 14-16%) and classically presents as a triad of fever, neck stiffness, and altered mental status. However, less than half of patients with meningitis present with this classic triad. We present the clinical course of a patient who initially presented to the emergency department after overdosing on ibuprofen for what he described as back pain secondary to mechanical injury. However, the patient's condition quickly deteriorated: he developed tachycardia, mental status changes, was intubated due to respiratory distress, and then suffered an 8-minute PEA arrest before return of spontaneous circulation was achieved. After the patient was stabilized, in addition to the nonsteroidal anti-inflammatory drug (NSAID) overdose Staphylococcus aureus meningitis, bacteremia, and pneumonia were diagnosed. We report this case to illustrate that the initial presentation of meningitis may be extremely unusual especially in the setting of NSAID overdose and the acutely decompensating patient. As the risk of adverse clinical outcomes increases with delays in appropriate antibiotic therapy, it is therefore crucial to recognize the many signs and symptoms of meningitis, typical and atypical, and quickly begin appropriate treatment.

Pacemaker related infective endocarditis from Staphylococcus lugdunensis: a case report.

Staphylococcus lugdunensis is a common skin flora not typically associated with infection. There are, however, several cases reported in the literature of Staphylococcus lugdunensis as a causative bacterium of various infections. This paper reports an additional case of pacemaker associated endocarditis with Staphylococcus lugdunensis as the causative bacterium.

Improved data normalization methods for reverse phase protein microarray analysis of complex biological samples.

Reverse phase protein microarrays (RPMA) are designed for quantitative, multiplexed analysis of proteins, and their posttranslational modified forms, from a limited amount of sample. To correct for sample to sample variability due to the number of cells in each lysate and the presence of extracellular proteins or red blood cells, a normalization method is required that is independent of these potentially confounding parameters. We adopted a gene microarray algorithm for use with RPMA to optimize the proteomic data normalization process and developed a systematic approach to RPMA processing and analysis, tailored to the study set. Our approach capitalizes on the gene microarray algorithms geNorm and NormFinder to identify the normalization parameter with the lowest variability across a proteomic sample set. Seven analytes (ssDNA, glyceraldehyde 3-phosphate dehydrogenase, α/ß-tubulin, mitochondrial ribosomal protein L11, ribosomal protein L13a, ß-actin, and total protein) were compared across sample sets including cell lines, tissues subjected to laser capture microdissection, and blood-contaminated tissues. We examined normalization parameters to correct for red blood cell content. We show that single-stranded DNA (ssDNA) is proportional to total non-red blood cell content and is a suitable RPMA normalization parameter. Simple modifications to RPMA processing allow flexibility in using ssDNA-or protein-based normalization molecules.