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Sphingosine 1-phosphate type 1 (S1P 1 ) receptors are expressed on lymphocytes and regulate immune cells trafficking. Sphingosine 1-phosphate and its analogues cause internalization and degradation of S1P 1 receptors, preventing the auto reactivity of immune cells in the target tissues. It has been shown that S1P 1 receptor agonists such as fingolimod can be suitable candidates for treatment of autoimmune diseases. The current study aimed to generate GRIND-based 3D-QSAR predictive models for agonistic activities of 2-imino-thiazolidin-4-one derivatives on S1P 1 to be used in virtual screening of chemical libraries. The developed model for the S1P 1 receptor agonists showed appropriate power of predictivity in internal (r 2 acc 0.93 and SDEC 0.18) and external (r 2 0.75 and MAE (95% data), 0.28) validations. The generated model revealed the importance of variables DRY-N1 and DRY-O in the potency and selectivity of these compounds towards S1P 1 receptor. To propose potential chemical entities with S1P 1 agonistic activity, PubChem chemicals database was searched and the selected compounds were virtually tested for S1P 1 receptor agonistic activity using the generated models, which resulted in four potential compounds with high potency and selectivity towards S1P 1 receptor. Moreover, the affinities of the identified compounds towards S1P 1 receptor were evaluated using molecular dynamics simulations. The results indicated that the binding energies of the compounds were in the range of -39.31 to -46.18 and -3.20 to -9.75 kcal mol -1 , calculated by MM-GBSA and MM-PBSA algorithms, respectively. The findings in the current work may be useful for the identification of potent and selective S1P 1 receptor agonists with potential use in diseases such as multiple sclerosis., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The functional role of U2AF1 mutations in lung adenocarcinomas (LUADs) remains incompletely understood. Here, we report a significant co-occurrence of U2AF1 S34F mutations with ROS1 translocations in LUADs. To characterize this interaction, we profiled effects of S34F on the transcriptome-wide distribution of RNA binding and alternative splicing in cells harboring the ROS1 translocation. Compared to its wild-type counterpart, U2AF1 S34F preferentially binds and modulates splicing of introns containing CAG trinucleotides at their 3' splice junctions. The presence of S34F caused a shift in cross-linking at 3' splice sites, which was significantly associated with alternative splicing of skipped exons. U2AF1 S34F induced expression of genes involved in the epithelial-mesenchymal transition (EMT) and increased tumor cell invasion. Finally, S34F increased splicing of the long over the short SLC34A2-ROS1 isoform, which was also associated with enhanced invasiveness. Taken together, our results suggest a mechanistic interaction between mutant U2AF1 and ROS1 in LUAD.

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules would be valuable for vaccine development and cancer immunotherapies. Current computational methods trained on in vitro binding data are limited by insufficient training data and algorithmic constraints. Here we describe MARIA (major histocompatibility complex analysis with recurrent integrated architecture; https://maria.stanford.edu/ ), a multimodal recurrent neural network for predicting the likelihood of antigen presentation from a gene of interest in the context of specific HLA class II alleles. In addition to in vitro binding measurements, MARIA is trained on peptide HLA ligand sequences identified by mass spectrometry, expression levels of antigen genes and protease cleavage signatures. Because it leverages these diverse training data and our improved machine learning framework, MARIA (area under the curve = 0.89-0.92) outperformed existing methods in validation datasets. Across independent cancer neoantigen studies, peptides with high MARIA scores are more likely to elicit strong CD4 + T cell responses. MARIA allows identification of immunogenic epitopes in diverse cancers and autoimmune disease.

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms., (Copyright © 2019. Published by Elsevier Inc.)

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

The activated B cell (ABC-like) subtype of diffuse large B cell lymphoma (DLBCL) is characterized by chronic activation of signaling initiated by immunoglobulin μ (IgM). By analyzing the DNA copy number profiles of 1000 DLBCL tumors, we identified gains of 18q21.2 as the most frequent genetic alteration in ABC-like DLBCL. Using integrative analysis of matched gene expression profiling data, we found that the TCF4 ( E2-2 ) transcription factor gene was the target of these alterations. Overexpression of TCF4 in ABC-like DLBCL cell lines led to its occupancy on immunoglobulin ( IGHM ) and MYC gene enhancers and increased expression of these genes at the transcript and protein levels. Inhibition of TCF4 activity with dominant-negative constructs was synthetically lethal to ABC-like DLBCL cell lines harboring TCF4 DNA copy gains, highlighting these gains as an attractive potential therapeutic target. Furthermore, the TCF4 gene was one of the top BRD4-regulated genes in DLBCL cell lines. BET proteolysis-targeting chimera (PROTAC) ARV771 extinguished TCF4, MYC, and IgM expression and killed ABC-like DLBCL cells in vitro. In DLBCL xenograft models, ARV771 treatment reduced tumor growth and prolonged survival. This work highlights a genetic mechanism for promoting immunoglobulin signaling in ABC-like DLBCL and provides a functional rationale for the use of BET inhibitors in this disease., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Aim: Hepatocellular carcinoma (HCC) is the most common liver malignancy and the second leading cause of cancer-related deaths in the world. Sorafenib is the first-line treatment of HCC. Although sorafenib has positive effects on the survival of patients, novel therapeutic strategies are needed to extend survival and improve the efficacy of sorafenib. This study combines sorafenib with mesenchymal stem cells (MSCs) as a new approach to enhance the efficacy of sorafenib., Material and Methods: A subcutaneous xenograft model of HCC, established by human HepG2 cell lines, was implanted into the flank of nude mice and was used to evaluate tumor growth after treatment with sorafenib alone or in combination with MSCs. The aspartate aminotransferase, alanine aminotransferase, blood urea nitrogen, and creatinine levels were measured for safety assessment. Histopathological studies were performed using hematoxylin and eosin staining, and immunohistochemistry tests were performed to evaluate proliferation (Ki67) and angiogenesis (CD34). The TUNEL assay was used to detect apoptosis and measure the expression of major inflammatory cytokines (IL-1a, IL-10, and TNF-α) with real-time polymerase chain reaction., Result: Sorafenib, in combination with MSCs, strongly inhibited tumor growth in the xenograft model. Furthermore, the combination therapy significantly inhibited HCC cell proliferation, decreased tumor angiogenesis, and induced apoptosis and maintained antitumor-associated anti-inflammatory effects of MSCs., Conclusion: This combination therapy strategy could be used as a new therapeutic approach to the treatment of HCC that significantly improves upon the results achieved using sorafenib as monotherapy., (© 2018 Wiley Periodicals, Inc.)

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, P = 0.02) and cytology and cystoscopy combined ( P ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. SIGNIFICANCE: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring. This article is highlighted in the In This Issue feature, p. 453 ., (©2018 American Association for Cancer Research.)

Background: An essential requirement for performing robotic-assisted surgery on a freely beating heart is a prediction algorithm that can estimate the future heart trajectory., Method: Heart motion, respiratory volume (RV) and electrocardiogram (ECG) signal were measured from two dogs during thoracotomy surgery. A comprehensive multimodality prediction algorithm was developed based on the multivariate autoregressive model to incorporate the heart trajectory and cardiorespiratory data with multiple inherent measurement rates explicitly., Results: Experimental results indicated strong relationships between the dominant frequencies of heart motion with RV and ECG. The prediction algorithm revealed a high steady state accuracy, with the root mean square (RMS) errors in the range of 82 to 162 μm for a 300-second interval, less than half of that of the best competitor., Conclusion: The proposed multimodality prediction algorithm is promising for practical use in robotic assisted beating heart surgery, considering its capability of providing highly accurate predictions in long horizons., (© 2018 John Wiley & Sons, Ltd.)

Single-chain fragment variable (scFv) antibodies are antibody fragments consist of variable domains of full antibodies known to retain antigen binding properties while having much lower molecular weights granting some beneficial properties to them. In our previous study, three phage particles each displaying an individual scFv antibody (i.e. J43, J44, and J48) were identified as tumor necrosis factor alpha (TNF-α) binders. The current study aimed to produce previously identified anti-TNF-α scFv antibodies and to investigate their abilities to bind and inhibit TNF-α biological effect. The estimated free energy of folding determined using spectrofluorimetry method for the prepared scFv proteins was in the range of 6.35-12.45 kJ mol -1 indicating their proper folding in the solution. In ELISA experiment, the produced scFvs showed an appropriate affinity towards TNF-α with K d values in the range of 0.5-2.18 µM. They also inhibited the TNF-α-induced cytotoxicity on L929 cells with sub-micromolar IC 50 values (0.12 and 0.73 μM for J44 and J48, respectively). Molecular docking studies showed that J44 could mimic adalimumab interactions with TNF-α, confirming its relatively high TNF-α inhibitory effect compared to J43 and J48. It seems that the findings in the current study can be useful for designing more potent anti-TNF-α antibodies.

In recent years, for neurodegenerative diseases therapy, research has focused on the stem cells therapy. Due to promising findings in stem cell therapy, there are various sources of stem cells for transplantation in human. The aim of this study was to evaluate sciatic nerve regeneration in the rat after nerve transaction followed by human endometrial stem cells (hEnSCs) treatment into poly (e-caprolactone)/collagen/nanobioglass (PCL/collagen/NBG) nanofibrous conduits. After treatment of animals, the performance in motor and sensory tests, showed significant improvement in rats treated with hEnSCs as an autograft. H&E images provided from cross-sectional and, longitudinal-sections of the harvested regenerative nerve as well as immunohistochemistry results indicated that regenerative nerve fibres had been formed and accompanied with new blood vessels in the conduit cell group. Due to the advantage of high surface area for cell attachment, it is reported that this electrospun nerve conduit could find more application in cell therapy for nerve regeneration in future, to further improve the functional regeneration outcome, especially for longer nerve defect restoration. In conclusion, our results suggest that the PCL/collagen/NBG nanofibrous conduit filled with hEnSCs is a suitable strategy to improve nerve regeneration after a nerve transaction in rat.

Iron overload is a serious clinical condition for humans and is a key target in drug development. The aim of this study was to investigate the coordination of iron(III) ions with curcumin ligand that may be used in the treatment of iron overload. Iron(III) complex of curcumin was synthesized and structurally characterized in its solid and solution state by FT-IR, UV-Vis, elemental analysis, and magnetic susceptibility. Electrochemical behaviour of the ligand and the complexes were examined using cyclic voltammetry. The cytotoxic activities of the ligand and the iron(III) complex were evaluated by the MTT assay. Curcumin reacted with iron in high concentrations at physiological pH at room temperature. Subsequently, a brown-red complex was formed. Data regarding magnetic susceptibility showed that the complexes with a 1:2 (metal/ligand) mole ratio had octahedral geometry. The complex showed higher anti-oxidant effect towards the cell line ECV304 at IC 50 values of 4.83 compared to curcumin. The complex exhibited very high cytotoxic activity and showed a cytotoxic effect that was much better than that of the ligand. The potentials for redox were calculated as 0.180 V and 0.350 V, respectively. The electrochemistry studies showed that Fe 3+ /Fe 2+ couple redox process occurred at low potentials. This value was within the range of compounds that are expected to show superoxide dismutase activity. This finding indicates that the iron complex is capable of removing free radicals. The observed cytotoxicity could be pursued to obtain a potential drug. Further studies investigating the use of curcumin for this purpose are needed., (© 2018 John Wiley & Sons Australia, Ltd.)

Purpose: Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes., Patients and Methods: We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans., Results: Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival., Conclusion: Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.

Neuroendocrine tumors (NETs) arising from tailgut cysts are a rare but increasingly reported entity with gene expression profiles that may be indicative of the gastrointestinal cell of origin. We present a case report describing the unique pathological and genomic characteristics of a tailgut cyst NET that metastasized to liver. The histologic and immunohistochemical findings were consistent with a well-differentiated NET. Genomic testing indicates a germline frameshift in BRCA1 and a few somatic mutations of unknown significance. Transcriptomic analysis suggests an enteroendocrine L cell in the tailgut as a putative cell of origin. Genomic profiling of a rare NET and metastasis provides insight into its origin, development, and potential therapeutic options., (© 2018 Erdrich et al.; Published by Cold Spring Harbor Laboratory Press.)

An essential requirement for performing robotic assisted surgery on a freely beating heart is a prediction algorithm which can estimate the future trajectory of the heart in the varying heart rate (HR) conditions of real surgery with a high accuracy. In this study, a hybrid amplitude modulation- (AM) and autoregressive- (AR) based algorithm was developed to enable estimating the global and local oscillations of the beating heart, raised from its major and minor physiological activities. The AM model was equipped with an estimator of the heartbeat frequency to compensate for the HR variations. The RMS of the prediction errors of the hybrid algorithm was in the range of 165-361 μm for the varying HR motion, 21% less than that of the single AM model. With the capability of providing highly accurate predictions in a wide range of HR variation, the hybrid model is promising for practical use in robotic assisted beating heart surgery.

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA. Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma. Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles. Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688-99. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Exposure to cigarette smoke (CS) causes vessel damage and mechanism of this damage has not yet been clearly identified. Therefore, in this study we aimed to investigate whether vessel damage due to the CS exposure will be prevented by the alpha-linolenic acid (ALA) or not which has anti-inflammatory effect in mice. For this reason, mice were grouped as controls (with and without CS) and ALA (with and without CS). The CS application continued 5 days a week for two months. At the end of two months, the mice were killed by cervical dislocation and their blood and thoracic aortas were isolated. ALA Treatment increased acetylcholine relaxations. CS decreased acetylcholine relaxation. CS with ALA treatment increased acetylcholine relaxations versus just CS treatment. CS caused rising in cyclooxigenase-2 and phospholipase A2 levels. This rise is inhibited with ALA treatment. CS decreased eNOS levels. But this result was not statistically significant. Furthermore, according to electron microscopic study CS damaged both smooth muscle and endothelium. While ALA treatment prevented smooth muscle damage it didn't prevent endothelial damage. Using cigarette and CS exposure is a risk factor for cardiovascular disease. Our study showed that this disease., (Copyright © 2018 Elsevier Masson SAS. All rights reserved.)

Background: Accurate tracking of the heart surface motion is a major requirement for robot assisted beating heart surgery., Method: The feasibility of a stereo infrared tracking system for measuring the free beating heart motion was investigated by experiments on a heart motion simulator, as well as model surgery on a dog., Results: Simulator experiments revealed a high tracking accuracy (81 μm root mean square error) when the capturing times were synchronized and the tracker pointed at the target from a 100 cm distance. The animal experiment revealed the applicability of the infrared tracker with passive markers in practical heart surgery conditions., Conclusion: With the current technology, infrared tracking with passive markers might be the optimal solution for accurate, fast, and reliable tracking of heart motion during robot assisted beating heart surgery., (Copyright © 2017 John Wiley & Sons, Ltd.)

Chromium(III) chloride mediates DNA-DNA cross-linking. Some chromium complexes promote programmed cell death in specific ligand environment through binding to DNA. One strategy that can be supposed for reduction of Cr 3+ binding affinity to DNA is using curcumin as a chelator. In the current study, the [Cr(Curcumin)(EtOH) 2 ](NO 3 ) 2 (CCC) was synthesized and characterized by UV/Vis, FT-IR, CHN and spectrophotometric titration techniques. The mole ratio plot revealed a 1:1 complex between Cr 3+ and curcumin in solution. Binding interaction of this complex with calf thymus-DNA (CT-DNA) was investigated using UV/Vis, circular dichroism (CD), FT-IR and cyclic voltammetry. The intrinsic binding constants of CCC with DNA, measured by UV/Vis and cyclic voltammetry, were 1.60 × 10 5 and 1.13 × 10 5 , respectively. The thermodynamic studies showed that the reaction is enthalpy and entropy favoured. CD analysis revealed that only Λ-CCC interacts with DNA and Δ-CCC form has no tendency towards DNA. Based on FT-IR studies, it was understood that CCC interacts with DNA via minor groove binding. The docking simulation was carried out for finding the binding mode of CCC to DNA, too. All of data demonstrated that the curcumin significantly reduced the affinity of Cr 3+ to the DNA and the form of Δ-CCC has no interaction with DNA.

Tumor infiltrating leukocytes (TILs) are an integral component of the tumor microenvironment and have been found to correlate with prognosis and response to therapy. Methods to enumerate immune subsets such as immunohistochemistry or flow cytometry suffer from limitations in phenotypic markers and can be challenging to practically implement and standardize. An alternative approach is to acquire aggregative high dimensional data from cellular mixtures and to subsequently infer the cellular components computationally. We recently described CIBERSORT, a versatile computational method for quantifying cell fractions from bulk tissue gene expression profiles (GEPs). Combining support vector regression with prior knowledge of expression profiles from purified leukocyte subsets, CIBERSORT can accurately estimate the immune composition of a tumor biopsy. In this chapter, we provide a primer on the CIBERSORT method and illustrate its use for characterizing TILs in tumor samples profiled by microarray or RNA-Seq.

We introduce a novel data reduction technique whereby we select a subset of tiles to "cover" maximally events of interest in large-scale biological datasets (e.g., genetic mutations), while minimizing the number of tiles. A tile is a genomic unit capturing one or more biological events, such as a sequence of base pairs that can be sequenced and observed simultaneously. The goal is to reduce significantly the number of tiles considered to those with areas of dense events in a cohort, thus saving on cost and enhancing interpretability. However, the reduction should not come at the cost of too much information, allowing for sensible statistical analysis after its application. We envisage application of our methods to a variety of high throughput data types, particularly those produced by next generation sequencing (NGS) experiments. The procedure is cast as a convex optimization problem, which is presented, along with methods of its solution. The method is demonstrated on a large dataset of somatic mutations spanning 5000+ patients, each having one of 29 cancer types. Applied to these data, our method dramatically reduces the number of gene locations required for broad coverage of patients and their mutations, giving subject specialists a more easily interpretable snapshot of recurrent mutational profiles in these cancers. The locations identified coincide with previously identified cancer genes. Finally, despite considerable data reduction, we show that our covering designs preserve the cancer discrimination ability of multinomial logistic regression models trained on all of the locations (> 1 M ).

Identifying molecular residual disease (MRD) after treatment of localized lung cancer could facilitate early intervention and personalization of adjuvant therapies. Here, we apply cancer personalized profiling by deep sequencing (CAPP-seq) circulating tumor DNA (ctDNA) analysis to 255 samples from 40 patients treated with curative intent for stage I-III lung cancer and 54 healthy adults. In 94% of evaluable patients experiencing recurrence, ctDNA was detectable in the first posttreatment blood sample, indicating reliable identification of MRD. Posttreatment ctDNA detection preceded radiographic progression in 72% of patients by a median of 5.2 months, and 53% of patients harbored ctDNA mutation profiles associated with favorable responses to tyrosine kinase inhibitors or immune checkpoint blockade. Collectively, these results indicate that ctDNA MRD in patients with lung cancer can be accurately detected using CAPP-seq and may allow personalized adjuvant treatment while disease burden is lowest. Significance: This study shows that ctDNA analysis can robustly identify posttreatment MRD in patients with localized lung cancer, identifying residual/recurrent disease earlier than standard-of-care radiologic imaging, and thus could facilitate personalized adjuvant treatment at early time points when disease burden is lowest. Cancer Discov; 7(12); 1394-403. ©2017 AACR. See related commentary by Comino-Mendez and Turner, p. 1368 This article is highlighted in the In This Issue feature, p. 1355 ., (©2017 American Association for Cancer Research.)

Objectives: KLHL6 is a recently described BTB-Kelch protein with selective expression in lymphoid tissues and is most strongly expressed in germinal center B cells., Methods: Using gene expression profiling as well as immunohistochemistry with an anti-KLHL6 monoclonal antibody, we have characterized the expression of this molecule in normal and neoplastic tissues. Protein expression was evaluated in 1,058 hematopoietic neoplasms., Results: Consistent with its discovery as a germinal center marker, KLHL6 was positive mainly in B-cell neoplasms of germinal center derivation, including 95% of follicular lymphomas (106/112). B-cell lymphomas of non-germinal center derivation were generally negative (0/33 chronic lymphocytic leukemias/small lymphocytic lymphomas, 3/49 marginal zone lymphomas, and 2/66 mantle cell lymphomas)., Conclusions: In addition to other germinal center markers, including BCL6, CD10, HGAL, and LMO2, KLHL6 immunohistochemistry may prove a useful adjunct in the diagnosis and future classification of B-cell lymphomas., (© American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com)

Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different types of cancer makes them promising target in cancer therapy and hence, the identification of novel FGFR inhibitors is of great interest. In the current study we aimed to develop an alignment independent three dimensional quantitative structure-activity relationship (3D-QSAR) model for a set of 26 FGFR2 kinase inhibitors allowing the prediction of activity and identification of important structural features for these inhibitors. Methods: Pentacle software was used to calculate grid independent descriptors (GRIND) for the active conformers generated by docking followed by the selection of significant variables using fractional factorial design (FFD). The partial least squares (PLS) model generated based on the remaining descriptors was assessed by internal and external validation methods. Results: Six variables were identified as the most important probes-interacting descriptors with high impact on the biological activity of the compounds. Internal and external validations were lead to good statistical parameters (r 2 values of 0.93 and 0.665, respectively). Conclusion: The results showed that the model has good predictive power and may be used for designing novel FGFR2 inhibitors.

Noninvasive monitoring of minimal residual disease (MRD) has led to significant advances in personalized management of patients with hematologic malignancies. Improved therapeutic options and prolonged survival have further increased the need for sensitive tumor assessment that can inform treatment decisions and patient outcomes. At diagnosis or relapse of most hematologic neoplasms, malignant cells are often easily accessible in the blood as circulating tumor cells (CTCs), making them ideal targets to noninvasively profile the molecular features of each patient. In other cancer types, CTCs are generally rare and noninvasive molecular detection relies on circulating tumor DNA (ctDNA) shed from tumor deposits into circulation. The ability to precisely detect and quantify CTCs and ctDNA could minimize invasive procedures and improve prediction of clinical outcomes. Technical advances in MRD detection methods in recent years have led to reduced costs and increased sensitivity, specificity, and applicability. Among currently available tests, high-throughput sequencing (HTS)-based approaches are increasingly attractive for noninvasive molecular testing. HTS-based methods can simultaneously identify multiple genetic markers with high sensitivity and specificity without individual optimization. In this review, we present an overview of techniques used for noninvasive molecular disease detection in selected myeloid and lymphoid neoplasms, with a focus on the current and future role of HTS-based assays., (© 2017 by The American Society of Hematology.)

In a recently published article in Genome Biology, Li and colleagues introduced TIMER, a gene expression deconvolution approach for studying tumor-infiltrating leukocytes (TILs) in 23 cancer types profiled by The Cancer Genome Atlas. Methods to characterize TIL biology are increasingly important, and the authors offer several arguments in favor of their strategy. Several of these claims warrant further discussion and highlight the critical importance of data normalization in gene expression deconvolution applications.Please see related Li et al correspondence: www.dx.doi.org/10.1186/s13059-017-1256-5 and Zheng correspondence: www.dx.doi.org/10.1186/s13059-017-1258-3.

Background: Anomalous origin of left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital malformation. We sought to evaluate in-hospital and mid-term outcomes of patients with a diagnosis of ALCAPA who underwent surgical repair., Objectives: The objective of this study is to evaluate the mid-term outcomes of surgical repair of ALCAPA at our center and to analyze the surgical techniques used., Materials and Methods: In a retrospective study, we analyzed early and mid-term clinical and echocardiographic data to determine the outcomes of patients who underwent surgical repair of ALCAPA in our institution between 2005 and 2015., Results: Twenty-one patients underwent surgical repair for ALCAPA using aortic reimplantation ( n = 10, 47.6%), ostial closure ( n = 8, 38.1%), or ligation ( n = 3, 14.3%). The median age of patients was 24 months (range 22 days to 51 years). There were 2 (9.5%) in-hospital mortalities in infants undergoing the reimplantation technique. All patients were followed up for a median of 21 months (range 1-60 months). No patients required reoperation, and there was no mortality from discharge to mid-term follow-up. Severe early postoperative mitral regurgitation (MR) was associated with composite end-point, defined as a combination of mortality after surgery, moderate to severe MR, and moderate to severe left ventricular dysfunction at late follow-up ( P = 0.019) while mitral valve repair was not ( P = 0.469)., Conclusion: The surgical management of ALCAPA can be associated with good in-hospital and mid-term outcomes regardless of the age, at which the patient has been operated., Competing Interests: There are no conflicts of interest.

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

Kinases downstream of B-cell antigen receptor (BCR) represent attractive targets for therapy in non-Hodgkin lymphoma (NHL). As clinical responses vary, improved knowledge regarding activation and regulation of BCR signaling in individual patients is needed. Here, using phosphospecific flow cytometry to obtain malignant B-cell signaling profiles from 95 patients representing 4 types of NHL revealed a striking contrast between chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) tumors. Lymphoma cells from diffuse large B-cell lymphoma patients had high basal phosphorylation levels of most measured signaling nodes, whereas follicular lymphoma cells represented the opposite pattern with no or very low basal levels. MCL showed large interpatient variability in basal levels, and elevated levels for the phosphorylated forms of AKT, extracellular signal-regulated kinase, p38, STAT1, and STAT5 were associated with poor outcome. CLL tumors had elevated basal levels for the phosphorylated forms of BCR-signaling nodes (Src family tyrosine kinase, spleen tyrosine kinase [SYK], phospholipase Cγ), but had low α-BCR-induced signaling. This contrasted MCL tumors, where α-BCR-induced signaling was variable, but significantly potentiated as compared with the other types. Overexpression of CD79B, combined with a gating strategy whereby signaling output was directly quantified per cell as a function of CD79B levels, confirmed a direct relationship between surface CD79B, immunoglobulin M (IgM), and IgM-induced signaling levels. Furthermore, α-BCR-induced signaling strength was variable across patient samples and correlated with BCR subunit CD79B expression, but was inversely correlated with susceptibility to Bruton tyrosine kinase (BTK) and SYK inhibitors in MCL. These individual differences in BCR levels and signaling might relate to differences in therapy responses to BCR-pathway inhibitors., (© 2017 by The American Society of Hematology.)

The aim of this study was to identify novel TNF-α blocking peptide(s) using phage display technology. Two novel 7-mer TNF-α binding peptides P51 and P52 with K d values of 1.47 and 0.51nM were identified. Phage particles displaying P51 and P52 peptides at 0.318nM concentration prevent cytotoxic effect of TNF-α on L929 cells by 8.2% and 16.15%, respectively. Synthesized P51 and P52 peptides also inhibited TNF-α induced cytotoxicity with IC 50 values of 25.15±2.18 and 7.08±2.24μM, respectively. The result of RT-PCR also supports the inhibitory activity of the identified peptides, where P51 and P52 significantly inhibit the inductive effect of TNF-α on IκB-α mRNA levels. The inhibitory effects of the peptides were attributed to their abilities of binding at the inter-subunit interfaces leading to TNF-α dissociation. The results of molecular docking studies revealed that the peptides-TNF-α complexes are mostly stabilized by hydrophobic contacts., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Lung squamous cell carcinoma (LSCC) pathogenesis remains incompletely understood, and biomarkers predicting treatment response remain lacking. Here, we describe novel murine LSCC models driven by loss of Trp53 and Keap1, both of which are frequently mutated in human LSCCs. Homozygous inactivation of Keap1 or Trp53 promoted airway basal stem cell (ABSC) self-renewal, suggesting that mutations in these genes lead to expansion of mutant stem cell clones. Deletion of Trp53 and Keap1 in ABSCs, but not more differentiated tracheal cells, produced tumors recapitulating histologic and molecular features of human LSCCs, indicating that they represent the likely cell of origin in this model. Deletion of Keap1 promoted tumor aggressiveness, metastasis, and resistance to oxidative stress and radiotherapy (RT). KEAP1/NRF2 mutation status predicted risk of local recurrence after RT in patients with non-small lung cancer (NSCLC) and could be noninvasively identified in circulating tumor DNA. Thus, KEAP1/NRF2 mutations could serve as predictive biomarkers for personalization of therapeutic strategies for NSCLCs., Significance: We developed an LSCC mouse model involving Trp53 and Keap1, which are frequently mutated in human LSCCs. In this model, ABSCs are the cell of origin of these tumors. KEAP1/NRF2 mutations increase radioresistance and predict local tumor recurrence in radiotherapy patients. Our findings are of potential clinical relevance and could lead to personalized treatment strategies for tumors with KEAP1/NRF2 mutations. Cancer Discov; 7(1); 86-101. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1., Competing Interests: of potential conflicts of interest – A.M.N., A.A.A., and M.D. are co-inventors on patent applications related to CAPP-Seq. A.L. is currently an employee of Roche. A.M.N., A.A.A., and M.D. are consultants for Roche. Other authors disclose no conflicts of interest., (©2016 American Association for Cancer Research.)

Patients with diffuse large B cell lymphoma (DLBCL) exhibit marked diversity in tumor behavior and outcomes, yet the identification of poor-risk groups remains challenging. In addition, the biology underlying these differences is incompletely understood. We hypothesized that characterization of mutational heterogeneity and genomic evolution using circulating tumor DNA (ctDNA) profiling could reveal molecular determinants of adverse outcomes. To address this hypothesis, we applied cancer personalized profiling by deep sequencing (CAPP-Seq) analysis to tumor biopsies and cell-free DNA samples from 92 lymphoma patients and 24 healthy subjects. At diagnosis, the amount of ctDNA was found to strongly correlate with clinical indices and was independently predictive of patient outcomes. We demonstrate that ctDNA genotyping can classify transcriptionally defined tumor subtypes, including DLBCL cell of origin, directly from plasma. By simultaneously tracking multiple somatic mutations in ctDNA, our approach outperformed immunoglobulin sequencing and radiographic imaging for the detection of minimal residual disease and facilitated noninvasive identification of emergent resistance mutations to targeted therapies. In addition, we identified distinct patterns of clonal evolution distinguishing indolent follicular lymphomas from those that transformed into DLBCL, allowing for potential noninvasive prediction of histological transformation. Collectively, our results demonstrate that ctDNA analysis reveals biological factors that underlie lymphoma clinical outcomes and could facilitate individualized therapy., (Copyright © 2016, American Association for the Advancement of Science.)

Tumors are complex ecosystems comprised of diverse cell types including malignant cells, mesenchymal cells, and tumor-infiltrating leukocytes (TILs). While TILs are well known to play important roles in many aspects of cancer biology, recent developments in immuno-oncology have spurred considerable interest in TILs, particularly in relation to their optimal engagement by emerging immunotherapies. Traditionally, the enumeration of TIL phenotypic diversity and composition in solid tumors has relied on resolving single cells by flow cytometry and immunohistochemical methods. However, advances in genome-wide technologies and computational methods are now allowing TILs to be profiled with increasingly high resolution and accuracy directly from RNA mixtures of bulk tumor samples. In this review, we highlight recent progress in the development of in silico tumor dissection methods, and illustrate examples of how these strategies can be applied to characterize TILs in human tumors to facilitate personalized cancer therapy., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment.

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by about threefold, and synergize when combined to yield ∼15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to non-small cell lung cancer (NSCLC) patients, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and >99.99% specificity at the variant level, and with 90% sensitivity and 96% specificity at the patient level. In addition, our approach allowed monitoring of NSCLC ctDNA down to 4 in 10(5) cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.

Purpose: TNF-α is an inflammatory cytokine with a key role in initiation of inflammatory responses. Anti-TNF-α antibodies are being used in clinic for the purpose of diagnosis and treatment due to their high specificity. The objective of the current study was to express and purify an anti-TNF-α scFv antibody identified by phage display technology., Methods: The DNA coding sequence of the identified scFv was cloned into pET28a vector and the corresponding protein was expressed as 6×His tagged using E.coli BL21 (DE3) pLysS expression system followed by affinity purification on Ni-Sepharose affinity column., Results: The J44 scFv antibody was cloned into the expression vector and successfully expressed and purified. The purity of the scFv fraction was confirmed using SDS-PAGE analysis. Western blotting technique was used to detect expression of 6×His tagged protein., Conclusion: In the current study an anti-TNF-α scFv antibody was successfully expressed in bacterial expression system and purified on affinity column. The purified protein can be used in different in vitro and in vivo experiments in order to elucidate its functionality.

Interference with microtubule polymerization results in cell cycle arrest leading to cell death. Colchicine is a well-known microtubule polymerization inhibitor which does so by binding to a specific site on tubulin. A set of 3', 4'-bis (substituted phenyl)-4'H-spiro [indene-2, 5'-isoxazol]-1(3H)-one derivatives with known antiproliferative activities were evaluated for their tubulin binding modes. 3D structures of the derivatives were docked into the colchicine binding site of tubulin using GOLD 5.0 program under flexible ligand and semi-flexible receptor condition. The spiroisoxazoline derivatives bind tubulin in a similar manner to colchicine by establishing at least a hydrogen bonding to Cys(241) as well as hydrophobic interactions with Leu(255), Ile(378) and Lys(254) and few other residues at the binding pocket. It can be concluded that the spiroisoxazoline core structure common to the studied derivatives is a suitable scaffold for placing the antitubulin pharmacophoric groups in appropriate spatial positions required for tubulin binding activity.

Purpose: Tumor necrosis factor alpha (TNF-α) is an inflammatory cytokine, involved in both physiological and pathological pathways. Because of central role of TNF-α in pathogenesis of inflammatory diseases, in the current study, we aimed to identify novel scFv antibodies against TNF-α using phage display technology., Methods: Using libraries composed of phagemid displaying scFv antibodies, four rounds of biopanning against TNF-α were carried out, which led to identification of scFvs capable of binding to TNF-α. The scFv antibody with appropriate binding affinity towards TNF-α, was amplified and used in ELISA experiment., Results: Titration of phage achieved from different rounds of biopanning showed an enrichment of specific anti-TNF-α phages during biopanning process. Using ELISA experiment, a binding constant (Kd) of 1.11 ± 0.32 nM was determined for the phage displaying J48 scFv antibody., Conclusion: The findings in the current work revealed that the identified novel scFv antibody displayed at the N-terminal of minor coat proteins of phagemid binds TNF-α with suitable affinity. However, the soluble form of the antibody is needed to be produced and evaluated in more details regarding its binding properties to TNF-α.

Tumors continually shed DNA into the blood where it can be detected as circulating tumor DNA (ctDNA). Although this phenomenon has been recognized for decades, techniques that are sensitive and specific enough to robustly detect ctDNA have only become available recently. Quantification of ctDNA represents a new approach for cancer detection and disease burden quantification that has the potential to revolutionize response assessment and personalized treatment in radiation oncology. Analysis of ctDNA has many potential applications, including detection of minimal residual disease following radiotherapy, noninvasive tumor genotyping, and early detection of tumor recurrence. Ultimately, ctDNA-based assays could lead to personalization of therapy based on identification of somatic alterations present in tumors and changes in ctDNA concentrations before and after treatment. In this review, we discuss methods of ctDNA detection and clinical applications of ctDNA-based biomarkers in radiation oncology, with a focus on recently developed techniques that use next-generation sequencing for ctDNA quantification., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Formaldehyde is universally used to fix tissue specimens, where it forms hemiaminal and aminal adducts with biomolecules, hindering the ability to retrieve molecular information. Common methods for removing these adducts involve extended heating, which can cause extensive degradation of nucleic acids, particularly RNA. Here, we show that water-soluble bifunctional catalysts (anthranilates and phosphanilates) speed the reversal of formaldehyde adducts of mononucleotides over standard buffers. Studies with formaldehyde-treated RNA oligonucleotides show that the catalysts enhance adduct removal, restoring unmodified RNA at 37 °C even when extensively modified, while avoiding the high temperatures that promote RNA degradation. Experiments with formalin-fixed, paraffin-embedded cell samples show that the catalysis is compatible with common RNA extraction protocols, with detectable RNA yields increased by 1.5-2.4-fold using a catalyst under optimized conditions and by 7-25-fold compared with a commercial kit. Such catalytic strategies show promise for general use in reversing formaldehyde adducts in clinical specimens.

Background: Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables., Methods: Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided., Results: The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK., Conclusion: The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.

Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.

Background: A tissue valve is the prosthesis of choice in the majority of children and adults requiring pulmonary valve replacement (PVR). Mechanical valves, on the other hand, are more durable but require anticoagulation therapy and carry the elevated risk of thrombosis. The aim of this study was to investigate the long-term outcomes of mechanical prosthetic valves in a single referral tertiary center. Patients and, Methods: Recorded data of 121 patients who underwent mechanical PVR between April 2003 and April 2013 at our center were reviewed, retrospectively. Eighty-four patients (69.4%) were male and their mean age was 23.12 ± 7.86 years. Tetralogy of Fallot was the most common diagnosis (n = 109). Complete follow-up was performed for all patients (mean 7.02 ± 1.90 years)., Results: Nobody died and no significant bleeding event was detected during follow-up. Mechanical valve malfunction happened in 10 patients (8.3%) while in 1 of them malfunction happened because of pannus formation and in the remaining 9 because of thrombosis. Just one of the thrombotic events could not be treated with streptokinase and required reoperation. Freedom from reoperation rates were 100, 99, and 98% at 1, 5, and 10 years, respectively; freedom from valve thrombosis event rates were 100, 93, and 91% at 1, 5, and 10 years, respectively; and freedom from bleeding event rates was 98% at 1, 5, and 10 years., Conclusion: Mechanical prosthetic valves demonstrated excellent durability and a low risk of valve thrombosis at the pulmonary position when patients are adequately anticoagulated., (Georg Thieme Verlag KG Stuttgart · New York.)

While many age-associated immune changes have been reported, a comprehensive set of metrics of immune aging is lacking. Here we report data from 243 healthy adults aged 40-97, for whom we measured clinical and functional parameters, serum cytokines, cytokines and gene expression in stimulated and unstimulated PBMC, PBMC phenotypes, and cytokine-stimulated pSTAT signaling in whole blood. Although highly heterogeneous across individuals, many of these assays revealed trends by age, sex, and CMV status, to greater or lesser degrees. Age, then sex and CMV status, showed the greatest impact on the immune system, as measured by the percentage of assay readouts with significant differences. An elastic net regression model could optimally predict age with 14 analytes from different assays. This reinforces the importance of multivariate analysis for defining a healthy immune system. These data provide a reference for others measuring immune parameters in older people.