Specific Pipeline Research Articles

Comprehensive multiparameter genetic analysis improves circulating tumor DNA detection in head and neck cancer patients.

Tumor-specific genetic aberrations in cell-free DNA (cfDNA) from plasma are promising biomarkers for diagnosis of recurrent head and neck squamous cell carcinoma (HNSCC). However, the sensitivity when using somatic mutations only in cfDNA is suboptimal. Here, we combined detection of copy number aberrations (CNAs), human papillomavirus (HPV) DNA and somatic mutations in a single sequencing workflow. Pretreatment plasmas of 40 patients and 20 non-cancer controls were used for analysis. Plasma DNA underwent low-coverage whole genome sequencing (lcWGS) to detect both CNAs and HPV-DNA, and deep sequencing to detect mutations in 12 frequently altered cancer driver genes in HNSCC using the same sequencing library. A specific analysis pipeline line was developed for data mining. The corresponding tumors were analyzed using slightly adapted protocols. Using the developed method, somatic mutations and CNAs were detected in plasma DNA of HNSCC patients in 67% and 52%, respectively. HPV-DNA in plasma was detected in 100% of patients with HPV-positive tumors, and not in plasma of patients with HPV-negative tumors or non-cancer controls. Combined analysis increased the detection rate of tumor DNA in plasma to 78%. The detection rate was significantly associated with the stage of disease of the tumor. Neither HPV status nor location of the primary tumor influenced detection of CNAs or somatic mutations in plasma. This study demonstrates that the combined analysis of CNAs, HPV and somatic mutations in plasma of HNSCC patients is feasible and contributes to a higher sensitivity of the assay compared to single modality analyses.

High sensitivity optical fiber pressure sensor based on thin-walled oval cylinder

In this study, an optical fiber pressure sensor based on a thin-walled oval cylinder is proposed. To sense the degree of deformation, a pair of fiber Bragg gratings (FBGs) are fixed on the outer wall of the oval cylinder. A finite element analysis is performed to analyze the sensing characteristic of the sensor. The temperature cross-sensitivity is determined using an elimination method. The experiment results show that the pressure sensitivity is 1.198 nm/MPa within a range of 0–1 MPa, with a precision of 0.011 MPa. The proposed sensor combines the advantages of a thin-walled cylinder and a bourdon tube, which realizes pressure measurement with high sensitivity and low crosstalk. The sensor can be applied to specific urban pipeline pressure monitoring.

Viral metagenomics performed in patients with acute febrile syndrome during Toxoplasma gondii outbreak in south Brazil

Toxoplasmosis is a zoonotic infection caused by the protozoan parasite Toxoplasma gondii. The infection is widely disseminated in the human population and is usually benign or asymptomatic. Systemic T. gondii infection presents risks for pregnant women and AIDS patients. Although rare, T. gondii can cause outbreaks in urban centers. The origin of these outbreaks is not completely understood but probably results from introduction of zoonotic T. gondii strains in the population. During such outbreaks other pathogens which mimic T. gondii acute febrile syndrome may also circulate; therefore, detailed investigation of the outbreak is of extreme importance. In this study we performed viral metagenomics next-generation sequencing (mNGS) in patient samples obtained during T. gondii outbreak in Santa Maria city, South Brazil. Specific bioinformatics pipelines specialized in virus discovery were applied in order to identify co-circulating vial agents. Epstein Barr virus and Parvovirus B19 contigs were assembled and these viruses can cause symptoms similar to toxoplasmosis. In conclusion, our findings show the importance of Metagenomics next generation sequencing (mNGS) use to help characterize the outbreak more completely and in the management of the affected patients.

Protein-protein correlations based variable dimension expansion algorithm for high efficient serum biomarker discovery

In this study, we constructed a high specific and efficient serum biomarker discovery pipeline. We utilized dysregulated proteins identified in primary tissue and potentially secreted into the blood as biomarker candidates. The scheduled multiple reaction monitoring method was performed to accurately quantify and verify these candidates directly in serum, thus circumventing the effects of high-abundance proteins. We then generated new variables through assigning values to protein-protein correlations to extend the dimensionality of the dataset (PPC-VDE), and the specificity of disease classification. We successfully applied this pipeline for biomarker discovery of dilated cardiomyopathy and achieved 88.6% accurate classification of dilated cardiomyopathy, ischemic cardiomyopathy and healthy controls with machine learning. This pipeline is straightforward for biomarker discovery in broad clinical field.

Comparison of third-generation sequencing approaches to identify viral pathogens under public health emergency conditions.

The capability of high-throughput sequencing (HTS) for detection of known and unknown viruses timely makes it a powerful tool for public health emergency response. Third-generation sequencing (TGS) offers advantages in speed and length of detection over second-generation sequencing (SGS). Here, we presented the end-to-end workflows for both Oxford Nanopore MinION and Pacbio Sequel on a viral disease emergency event, along with Ion Torrent PGM as a reference. A specific pipeline for comparative analysis on viral genomes recovered by each platform was assembled, given the high errors of base-calling for TGS platforms. All the three platforms successfully identified and recovered at least 85% Norovirus GII genomes. Oxford Nanopore MinION spent the least sample-to-answer turnaround time with relatively low but enough accuracy for taxonomy classification. Pacbio Sequel recovered the most accurate viral genome, while spending the longest time. Overall, Nanopore metagenomics can rapidly characterize viruses, and Pacbio Sequel can accurately recover viruses. This study provides a framework for designing the appropriate experiments that are likely to lead to accurate and rapid virus emergency response.

Quantitative effects of different factors on the thermal characteristics of waxy crude oil pipeline during its shutdown

By means of momentum source term method and additional specific heat capacity method, the thermal characteristics of waxy crude oil pipeline during its shutdown are investigated by the numerical simulation. The quantitative effects of crude oil viscosity, specific heat capacity, pipeline diameter and insulation thickness on the thermal characteristics of waxy crude oil pipeline during shutdown are studied. The results show that pipe diameter has a great influence on the average temperature drop rate, and the average temperature drop rate decreases significantly with the increase of pipe diameter. The thickness of insulation and the viscosity of crude oil have a great influence on the oil temperature variance. As the thickness of insulation layer increases or the viscosity of crude oil increases, the oil temperature variance increases significantly. The viscosity of crude oil has a great influence on the average velocity, and the average velocity decreases significantly with the increase of the viscosity of crude oil.

Pre-Cancerous Stomach Lesion Detections with Multispectral-Augmented Endoscopic Prototype

In this paper, we are interested in the in vivo detection of pre-cancerous stomach lesions. Pre-cancerous lesions are unfortunately rarely explored in research papers as most of them are focused on cancer detection or conducted ex-vivo. For this purpose, a novel prototype is introduced. It consists of a standard endoscope with multispectral cameras, an optical setup, a fiberscope, and an external light source. Reflectance spectra are acquired in vivo on 16 patients with a healthy stomach, chronic gastritis, or intestinal metaplasia. A specific pipeline has been designed for the classification of spectra between healthy mucosa and different pathologies. The pipeline includes a wavelength clustering algorithm, spectral features computation, and the training of a classifier in a “leave one patient out” manner. Good classification results, around 80%, have been obtained, and two attractive wavelength ranges were found in the red and near-infrared ranges: [745, 755 nm] and [780, 840 nm]. The new prototype and the associated results give good arguments in favor of future common use in operating rooms, during upper gastrointestinal exploration of the stomach for the detection of stomach diseases.

The Sensitivity of Estimates of Multiphase Fluid and Solid Properties of Porous Rocks to Image Processing

X-ray microcomputed tomography (X-ray μ-CT) is a rapidly advancing technology that has been successfully employed to study flow phenomena in porous media. It offers an alternative approach to core scale experiments for the estimation of traditional petrophysical properties such as porosity and single-phase flow permeability. It can also be used to investigate properties that control multiphase flow such as rock wettability or mineral topology. In most applications, analyses are performed on segmented images obtained employing a specific processing pipeline on the greyscale images. The workflow leading to a segmented image is not straightforward or unique and, for most of the properties of interest, a ground truth is not available. For this reason, it is crucial to understand how image processing choices control properties estimation. In this work, we assess the sensitivity of porosity, permeability, specific surface area, in situ contact angle measurements, fluid–fluid interfacial curvature measurements and mineral composition to processing choices. We compare the results obtained upon the employment of two processing pipelines: non-local means filtering followed by watershed segmentation; segmentation by a manually trained random forest classifier. Single-phase flow permeability, in situ contact angle measurements and mineral-to-pore total surface area are the most sensitive properties, as a result of the sensitivity to processing of the phase boundary identification task. Porosity, interfacial fluid–fluid curvature and specific mineral descriptors are robust to processing. The sensitivity of the property estimates increases with the complexity of its definition and its relationship to boundary shape.

RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data.

Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers the user an HTML page to scan own data regarding the following aspects: periodicity, ligation and digestion of footprints; reproducibility and batch effects of replicates; drug-related artifacts; unbiased codon enrichment including variability between mRNAs, for A, P and E sites; mining of some causal or confounding factors. We expect our pipeline to allow an optimal use of the wealth of information provided by ribosome profiling experiments.

Detection of Immunoglobulin Heavy Chain Gene Clonality By High-Throughput Sequencing for Minimal Residual Disease Monitoring in Chronic Lymphocytic Leukaemia

Introduction: The negative minimal residual disease (MRD) after treatment has been recently accepted as endpoint for Chronic Lymphocytic Leukaemia (CLL) clinical trials. Conventionally, MRD can be detected by using multi-color Flow Cytometry (FC) with high sensitivity. Determination of the clonal immunoglobulin gene rearrangement can be a useful monitoring marker in a broad range of B-cell lymphoproliferative neoplasms. Moreover, the mutational status of immunoglobulin heavy chain variable (IgHV) rearrangement is considered one of the most important prognostic factors in CLL. Therefore, the identification of the IgHV rearrangement can be a useful marker both at diagnostic and as monitoring marker for MRD. Nowadays, high-throughput sequencing (HTS) technologies has enabled highly sensitive cancer genomic testing in clinical laboratories. There are same initiatives based on HTS to use IgHV rearrangement as marker for MRD monitoring in Acute lymphoblastic leukemia or multiple myeloma, but it remains unharmonized for application on CLL in the clinical laboratory. Objective: We evaluated the performance and clinical applicability of HTS assay for IgHV rearrangement in CLL MRD monitoring in 69 samples from 19 CLL patients treated. Methods: The libraries including IGH locus were performed using the Sequencing Multiplex Kit on IGH consensus primers. To simplify and make automatic the analysis of the data obtained, we developed a specific bioinformatic pipeline that covers from preprocessing to final data summarization and interpretation. The backbone of the analysis includes read preprocessing, mapping against IMGT reference sequences, consensus IgHV reads pairwise alignment to determine mutational status and read classification into rearrangements. Assessment of IgHV mutational status by Sseq, genomic DNA (gDNA; 50-100 ng), were used for IgHV analysis. gDNA was amplified using locus-specific primer sets for IgHV designed to allow for the amplification of all known alleles of the germline IgH sequence, as described previously. Inmunophenotypic studies were performed on erythrocyte-lysed whole PB samples according to Euroflow procedures. PB white blood cells (WBC) was systematically stained with the eight color combination panel recently proposed by the ERIC group for MRD detection (Rawstron AC et al. 2016). Data acquisition was performed on a FACSCanto II flow cytometer Becton-Dickinson Biociences using the FACSDiva software (V8.0; BD). For data analysis, the Infinicyt softwareTM (Cytognos SL, Salamanca, Spain) was used. The MRD levels were reported as fraction of CLL cells of all nucleated cells. MRD negativity was define as a fraction <10 -4 However, for treatments that preferentially clear the blood (for example monoclonal antibodies) the MRD was confirm in the bone marrow as has been recommended. Results: Patient demographics and the results of IGH clonality tests are summarized in Table 1. Interpretable results were obtained with higher sensitivity compared with Sseq at diagnosis stage (19/19 samples), and we are able to determine the same clone at subsequent samples. Among 50 follow-up samples, 44 MRD were positive in both techniques (HTS and FC); 3 follow-up samples, were negative in both determinations (HTS and FC); in contrast, 3 follow-up samples, were negative by FC but positive by HTS (8.3, 17.2, 18.2 samples). This is the case of Patient 8, in which the last follow-up sample, the detection of the primary clone is positive by HTS, while by FC is undetected (Figure 1). In addition, it was possible to detect IgHV clone in all Patient 7 samples. It was under long-term monitoring by HTS and FC, and 17 months after initial diagnosis and first line of treatment (7.5 sample), it was detected a loss of response (Figure 2.). Conclusions: We evaluated an HTS IgHV assay using initial and follow-up samples of 19 CLL patients. Using our pre-designed primer set in library preparation, and developed our specific bioinformatic pipeline that covers from preprocessing to final data summarization and interpretation, we were able to demonstrate that our method was more sensitive than FC in detecting positive follow-up samples and could be able to propose it for MRD monitoring in CLL. However, the prognostic impact of these low-level MRD detected by HTS should be validated with further investigations. Samples were provided by the INCLIVA Biobank. Funded by Gilead Felowship 257/17 Disclosures Ortiz: GILEAD SCIENCES: Research Funding. Terol:Abbvie: Consultancy; Gilead: Research Funding; Janssen: Consultancy, Research Funding; Astra Zeneca: Consultancy; Roche: Consultancy.

Ighv Mutational Status By Deep Next Generation Sequencing Refines Ighv Sanger Sequencing Classification in Patients with Chronic Lymphocytic Leukaemia

Introduction: Determination of the mutational status of rearranged immunoglobulin heavy chain variable (IgHV) genes in patients with Chronic Lymphocytic Leukaemia (CLL), is considered one of the most important prognostic factors: patients with unmutated IgHV (UM; ≥98% of identity to the germline) genes have a more aggressive disease course and develop more frequently unfavourable genetic deletions or mutations than patients with mutated IgHV (M; ≤98%). Mutational status, is currently determined by Sanger sequencing (Sseq) that allows the analysis of the major clone, however, international guidelines recommend caution in assigning mutational status in cases with "Borderline" IgHV identity (97-97.9%), and cases with double rearrangements with discordant mutational status. Objective: Analyze and determine the mutational status of the IgHV locus by High-throughput sequencing (HTS), in a cohort of CLL patients (n=51) with unclassifiable Sseq results: borderline status (n=22); double rearrangements (n=27) with discordant mutational status (n=2). Methods: We included 51 DNA samples extracted from peripheral blood of patients diagnosed of CLL according to the National Cancer Institute Working Group guidelines in our institution between 1986 and 2019 (median absolute lymphocytes 11.4x109/L [2,8-239,5x109/L]). Sseq amplification and analysis of IgHV rearrangements were performed on DNA conforming to the updated ERIC recommendations. In all the cases we were able to determinate the IGVH identity. To switch high-throughput sequencing to the clinical practice, we assessed the reliability of different library preparation methods to sequence IGH locus in patients with CLL. Amplification was performed using the Sequencing Multiplex Kit based on IGH FR (forward primers) and consensus JH (reverse primer) multiplex. PCR products were purified using Magsi-NGS Prep magnetic beads (Magnamedics Diagnostics), normalized and pooled to create a library for sequencing using a MiSeq equipment. To simplify and make automatic the analysis of the same we developed a specific bioinformatic pipeline that covers from preprocessing to final data summarization and interpretation. The backbone of the analysis includes read preprocessing, mapping against IMGT reference sequences, consensus IgHV reads pairwise alignment to determine mutational status and read classification into rearrangements. Results: This approach led to the identification of a dominant clone IgHV in all cases (n=51). Instead, the percentage of identity calculated by HTS analysis varies in: - 15/22 borderline cases whose mutational status could be recalculated into 10 MM and 5 UM. The rest 7 remaining in borderline group. - We could identify both clones in 29 double rearrangements cases, with concordant mutational status except 2/29 undetermined cases, included in UM group regarding HTS results. Our tool led to the identification of a dominant clonotypic IgHV in all cases, and when compared the HTS sequence/mutational status for the most abundant clone with Sseq and for the IgHV status determination, 15 out of 22 (68,18%), could be reclassified. This case showed a major clone with productive rearrangement mutated by Sseq but unmutated by HTS. Conclusions: Analyze and determine the mutational status of the IgHV locus by HTS, would potentially reveal multiple rearrangements and increase the prognostic precision of IgHV mutation analysis. IgHV-HTS classification is able to precisely classify patients with borderline status or/and multiple IgHV rearrangements for which Sseq is inconclusive. In this case, it has been possible to improved prognostication for 17 out of 24 patients. This is helping us to discover the advantages of the data obtained by HTS compared with current Sseq standard technique. Samples were provided by the INCLIVA Biobank. Funded by Gilead Felowship 257/17 Disclosures Terol: Abbvie: Consultancy; Janssen: Consultancy, Research Funding; Gilead: Research Funding; Roche: Consultancy; Astra Zeneca: Consultancy.

Numerical simulation of deformable particles in a Coulter counter.

In Coulter counters, cells counting and volumetry are achieved by monitoring their electrical print when they flow through a sensing zone. However, the volume measurement may be impaired by the cell dynamics, which may be difficult to control. In this paper, numerical simulations of the dynamics and electrical signature of red blood cells in a Coulter counter are presented, accounting for the deformability of the cells. In particular, a specific numerical pipeline is developed to overcome the challenge of the multi-scale nature of the problem. It consists in segmenting the whole computation of the cell dynamics and electrical response in a series of dedicated computations, with a saving of one order of magnitude in computational time. This numerical pipeline is used with rigid spheres and deformable red blood cells in an industrial Coulter counter geometry, and compared with experimental measurements. The simulations not only reproduce electrical signatures typical of those measured experimentally, but also allow an analysis of the electrical signature in terms of the heterogeneity of the electrical field and dynamics of the particles in the measurement zone. This study provides a methodology for computing the sizing of rigid or deformable particles by Coulter counters, opening the way to a better understanding of cells signatures in such devices.

P5398CircRNAs deregulation in heart failure patients

Abstract Background Circular RNAs (circRNAs) are an emerging class of noncoding RNAs stemming from the splicing and circularization of pre-mRNAs exons. CircRNAs can regulate transcription and splicing, sequester microRNAs acting as “sponge” and inducing the respective targets, and bind to RNA binding proteins. Recently, they have been found deregulated in dilated cardiomyopathies (DCM), one of the cardiovascular diseases with the worst rate of morbidity and mortality, and whose molecular mechanisms are only partially known. Purpose Therein, we will evaluate in ischemic DCM patients the modulation of 17 circRNAs, 14 out of them obtained from literature data on DCM ischemic or not, while the other 3 were circRNAs not characterized in the heart previously. The study aims to identify circRNAs candidates for further functional characterization in DCM. In addition, as differential expression (DE) analysis is not easily performed for circRNAs in RNA-seq datasets, the validated circRNAs will be used to set up the most specific and sensitive bioinformatics pipeline for circRNA-DE analysis. Methods We designed divergent and convergent specific primers for 17 circRNAs and their host gene, respectively, and their amplification efficiency was measured by RT-qPCR. Transcripts expression was measured in left ventricle biopsies of 12 patients affected by non end-stage ischemic HF and of 12 matched controls. Results We identified cPVT1, cANKRD17, cBPTF as DE, and validated the modulation of 5 out of the 14 DCM-related circRNAs (cHIPK3, cALPK2, cPCMTD1, cNEBL, cSLC8A1), while cPDRM5, cTTN1 showed opposite modulation, which may be due to the specific disease condition. All of them were modulated differently from the respective host gene. CircRNA/miRNA interactions were predicted using Starbase 3.0. Next, mRNAs-targets of the identified miRNAs were predicted by mirDIP 4.1 and intersected with gene expression datasets of the same patients, previously obtained by microarray analysis. We found that cBPTF and cANKRD17 might sponge 12 and 2 miRNAs, respectively. Enrichment analysis of the relevant targets identified several important pathways implicated in DCM, such as MAPK, FoxO, EGFR, VEGF and Insulin/IGF pathways. In addition, deep RNA-Seq analysis that is currently ongoing and the validated circRNAs will be used to optimize the bioinformatics pipeline for circRNA DE analysis. Conclusions We identified a subset of circRNAs deregulated in ischemic HF potentially implicated in HF pathogenesis.

Assessing the Epigenetic Status of Human Telomeres.

The epigenetic modifications of human telomeres play a relevant role in telomere functions and cell proliferation. Therefore, their study is becoming an issue of major interest. These epigenetic modifications are usually analyzed by microscopy or by chromatin immunoprecipitation (ChIP). However, these analyses could be challenged by subtelomeres and/or interstitial telomeric sequences (ITSs). Whereas telomeres and subtelomeres cannot be differentiated by microscopy techniques, telomeres and ITSs might not be differentiated in ChIP analyses. In addition, ChIP analyses of telomeres should be properly controlled. Hence, studies focusing on the epigenetic features of human telomeres have to be carefully designed and interpreted. Here, we present a comprehensive discussion on how subtelomeres and ITSs might influence studies of human telomere epigenetics. We specially focus on the influence of ITSs and some experimental aspects of the ChIP technique on ChIP analyses. In addition, we propose a specific pipeline to accurately perform these studies. This pipeline is very simple and can be applied to a wide variety of cells, including cancer cells. Since the epigenetic status of telomeres could influence cancer cells proliferation, this pipeline might help design precise epigenetic treatments for specific cancer types.

Pixel Level Instance Segmentation using Single Shot Detectors and Semantic Segmentation Networks

Object detection algorithms are vital in computer vision applications especially the one regarding segmentation of objects in a scene. Instance segmentation using mask RCNN is the state of the art computer vision application using deep neural networks. However it has a complex pipeline for training and real-time testing. Single shot detectors based on CNN such as YOLO are robust in real time object detection compared to Faster RCNN. Combining convolutional networks for semantic segmentation along with single shot object detectors can give superior instance segmentation in real time at less computational complexity. Independent training of instance detection and segmentation networks makes it possible to create application specific pipelines based on context. Lighter architecture using single shot detectors and segmentation networks reduces latency on common processors thereby achieving higher frame rate. Class specific training of detectors improves the average precision of detection. The entire architecture is developed in python over Keras deeplearning framework.OpenCV library is used to render and process the input and output images.

Automated water Distribution System in Metro’s using IOT

In urban regions, the water supply to home and business foundations are given at a settled stream rate. There are occurrences of overabundance water drawn by specific clients/clients for example water will be discharged informally, which is considered as water burglary. In this undertaking, it is proposed to build up an inserted based remote water observing and robbery counteractive action framework by taking the information of water supply at the purchaser/client end. The general goal of a conveyance framework is to convey healthy water to the buyer at specific territory and the inadequate amount and accomplish progression and most extreme inclusion at moderate expense. To accomplish the target the association needs to advance working strategies to guarantee that the framework can be worked palatably, work proficiently and ceaselessly beyond what many would consider possible at most reduced expense. Here we are utilizing PIC16F877A as our controller and furthermore, a couple of sensors are masterminded to distinguish the nearness of water in that specific pipeline. IR sensors are utilized to distinguish the water stream. Water ought to be discharged according to the directions by authority's for example for instance exchange long stretches of supply are given and just amid explicit timeframe however not day by day.

Pipeline Balance and Monitoring for the Integrated Flare System in Map Ta Phut Industrial Estate

This study aims to design flare pipeline network in Map Ta Phut Industrial Estate (MTP IE). This network is designed to transport waste gas from 6 companies in MTP IE to PTT LNG terminal for treatment. At typical operation case, there will be 12.46 tons/hr. of waste gas flow accumulated into the system. In an emergency case, this pipeline network is needed to handle the maximum load at 79.84 tons/hr. of waste gas, through the entire system. The difference of the mass flow rate needs the specific pipeline network design to minimize the back pressure to the system. The route of the network is selected by Google Earth to overview and to find the possible shortest way of waste gas transportation. The sizing of the pipeline system is then proposed. The flare pipeline network is designed using Aspen Flare System Analyzer program. The simulation result shows that the proposed flare pipeline network can handle all waste gas both in regular operation and in emergency cases. All plant back pressures are under the maximum allowable back pressure (MABP) limit, which means that the plant can be operated without any upset from other companies

Abstract B185: Epithelial cancer cell-expressed genes contribute to clinically relevant immune-based classifications of breast cancer

Abstract Introduction: With the development of immunotherapies for breast cancer therapy, reliable methods to evaluate the extent and type of immune involvement present in tumors and investigation of its effect on patient prognosis and treatment are needed. Identifying tumor-specific features that affect immune involvement will be a key to understand tumor-immune involvement. Therefore, we evaluated expression of immune-related mRNA signatures in TCGA breast cancer data to identify distinct immune-related tumor subsets and asociated prognostic values. We also evaluated immune cell features, including B cell and T-cell receptor richness and diversity, as well as epithelial tumor cell-specific features, including somatic mutations, copy number alterations and differential RNA expression between identified groups. Methods: More than 130 published immune related gene signatures were evaluated in 1095 breast tumors and 97 normal mammary samples. Groups were identified by consensus based hierarchical clustering of the immune signatures, using the proportion of ambiguous clustering to select the optimal number of groups. An ElasticNet model trained on TCGA data was applied to two other breast tumor datasets to predict immune group classification. RNA-sequencing (RNAseq) data from 70 breast cancer cell lines and from human tumor xenografts passaged in immune-compromised mice and processed through a human specific sequencing pipeline provided in vitro and in vivo sources of epithelial cancer cell expression with limited stromal content that was used to filter TCGA bulk RNAseq data for epithelial expressed genes. Results: We identified three distinct immune groups present in breast cancer: immune-low, immune-normal, and immune-high. The immune-high group is characterized by high T-cell scores, including both cytotoxic and regulatory T-cell signatures, and increased B cell and macrophage signatures. The immune-normal set shows signs of normal epithelia and low proliferation. The immune-low group has very low immune cell signatures. Intrinsic breast cancer subtypes (Basal, luminal A, Luminal B, Her2 and Normal-like) are present in each of the immune groups; however, enrichment of basal tumors in immune-high, luminal tumors in the immune-low, and normal mammary, normal-like tumors and luminal A tumors in the immune-normal group demonstrate an interaction between intrinsic tumor type and immune involvement. Immune groups are prognostic in TCGA, with the immune-high group having improved recurrence-free survival. Two more breast tumor datasets confirmed improved survival for basal tumors in the immune-high group relative to the immune-low tumors. Total mutation burden, unique somatic mutations, and copy number alterations did not show significant changes between immune-low and –high groups, whereas RNA expression differs between groups. Selecting for genes with evidence of expression by epithelial breast cancer cells identified over 8,000 genes differentially expressed between the immune-low and –high groups, with CCL5, ACAP1, PVRIG, SLA2, LCK and CD8A being among the most significant. Conclusion: Breast cancer can be divided into three clinically relevant immune-related groups. Immune-high has high immune involvement, showing of markers for cytotoxicity and immune suppression and exhaustion. These patients have improved survival, but may still benefit from immune checkpoint inhibition. Immune-normal is reflective of a normal mammary immune state, suggesting a microenvironment that has not been strongly altered by the tumor. Immune-low appears to demonstrate exclusion of immune cells from the tumor, even though tumors contain predicted neoantigens. These patients have poor survival and novel therapeutic strategies to activate immune involvement need to be developed. Epithelial cancer cell expressed many immune-related genes, including CCL5, LCK and CD8A, which may be critical determinants of immune cell attraction. Citation Format: Jonathan Shepherd, Charles Perou. Epithelial cancer cell-expressed genes contribute to clinically relevant immune-based classifications of breast cancer [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B185.

Investigation of Fire Protection Certification for Aircraft Engine Components

Fire protection performance is one of the most important capabilities for aircraft engine, since the result may be hazardous in the case of a fire condition. According to fire protection regulation CCAR 33.17 of China Civil Aviation Regulations, fire-proof tests of a specific pipeline, a fuel tank and a fuel filter assembly were carried out. Test conditions include inlet fluid temperature, fluid pressure, fluid volume flow, fire temperature and heat flux density. The average flame temperature during the fire tests is 2000 degrees Fahrenheit, the heat flux density is 116kW/m2±10kW/m2 and the distance from burner exhaust to the test area is 100mm in these fire tests. Fire test of pipe passed, but the fire test of oil tank failed because of the failure of the oil circulation system and the melting of plastic pipe material in the ventilation pipe separately. The first fire test of the fuel filter failed because of design defect of one oil drainage path, but after design change of the oil drainage path, the second one succeeded. Based on the fire protection tests and results analysis, three essential factors of fire protection performance and type certification were presented: 1. Volume of medium retained in test parts; 2. Mass flow of medium; 3. Pressure in the test parts cavity.

Proxl (Protein Cross-Linking Database): A Public Server, QC Tools, and Other Major Updates.

Proxl is an open-source web application for sharing, visualizing, and analyzing bottom-up protein cross-linking mass spectrometry data and results. Proxl's core features include comparing data sets, structural analysis, customizable and interactive data visualizations, access to all underlying mass spectrometry data, and quality-control tools. All features of Proxl are designed to be independent of specific cross-linker chemistry or software analysis pipelines. Proxl's sharing tools allow users to share their data with the public or securely restrict access to trusted collaborators. Since being published in 2016, Proxl has continued to be expanded and improved through active development and collaboration with cross-linking researchers. Some of Proxl's new features include a centralized, public site for sharing data, greatly expanded quality-control tools and visualizations, support for stable isotope-labeled peptides, and general improvements that make Proxl easier to use, data easier to share and import, and data visualizations more customizable. Source code and more information are found at http://proxl-ms.org/ .