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Cas9 is a prokaryotic RNA-guided DNA endonuclease that binds substrates tightly in vitro but turns over rapidly when used to manipulate genomes in eukaryotic cells. Little is known about the factors responsible for dislodging Cas9 or how they influence genome engineering. Unbiased detection through proximity labeling of transient protein interactions in cell-free Xenopus laevis egg extract identified the dimeric histone chaperone facilitates chromatin transcription (FACT) as an interactor of substrate-bound Cas9. FACT is both necessary and sufficient to displace dCas9, and FACT immunodepletion converts Cas9's activity from multi-turnover to single turnover. In human cells, FACT depletion extends dCas9 residence times, delays genome editing, and alters the balance between indel formation and homology-directed repair. FACT knockdown also increases epigenetic marking by dCas9-based transcriptional effectors with a concomitant enhancement of transcriptional modulation. FACT thus shapes the intrinsic cellular response to Cas9-based genome manipulation most likely by determining Cas9 residence times.
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Proteína 9 Asociada a CRISPR/metabolismo , Proteínas de Unión al ADN/metabolismo , Genoma Humano , Proteínas del Grupo de Alta Movilidad/metabolismo , Factores de Elongación Transcripcional/metabolismo , Animales , Proteínas Asociadas a CRISPR/metabolismo , Línea Celular , ADN/metabolismo , Roturas del ADN de Doble Cadena , Reparación del ADN , Epigénesis Genética , Edición Génica , Técnicas de Silenciamiento del Gen , Humanos , Nucleosomas/metabolismo , Xenopus laevisRESUMEN
The vitamin A metabolite all-trans retinoic acid (ATRA) induces a gut-homing phenotype in activated CD4(+) conventional T cells (Tconv) by upregulating the integrin α4ß7 and the chemokine receptor CCR9. We report that, in contrast to mouse Tconv, only â¼50% of regulatory T cells (Treg) upregulate CCR9 when stimulated by physiological levels of ATRA, even though Tconv and Treg express similar levels of the retinoic acid receptor (RAR). The resulting bimodal CCR9 expression is not associated with differences in the extent of their proliferation, level of Foxp3 expression, or affiliation with naturally occurring Treg or induced Treg in the circulating Treg pool. Furthermore, we find that exposure of Treg to the mechanistic target of rapamycin (mTOR) inhibitor rapamycin suppresses upregulation of both CCR9 and α4ß7, an effect that is not evident with Tconv. This suggests that in Treg, ATRA-induced upregulation of CCR9 and α4ß7 is dependent on activation of a mTOR signaling pathway. The involvement of mTOR is independent of Akt activity, because specific inhibition of Akt, pyruvate dehydrogenase kinase-1, or its downstream target glycogen synthase kinase-3 did not prevent CCR9 expression. Additionally, Rictor (mTOR complex [mTORC]2)-deficient Treg showed unaltered ability to express CCR9, whereas Raptor (mTORC1)-deficient Treg were unable to upregulate CCR9, suggesting the selective participation of mTORC1. These findings reveal a novel difference between ATRA signaling and chemokine receptor induction in Treg versus Tconv and provide a framework via which the migratory behavior of Treg versus Tconv might be regulated differentially for therapeutic purposes.
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Linfocitos T CD4-Positivos/inmunología , Quimiotaxis de Leucocito/inmunología , Complejos Multiproteicos/metabolismo , Linfocitos T Reguladores/inmunología , Serina-Treonina Quinasas TOR/metabolismo , Animales , Linfocitos T CD4-Positivos/efectos de los fármacos , Linfocitos T CD4-Positivos/metabolismo , Separación Celular , Quimiotaxis de Leucocito/efectos de los fármacos , Citometría de Flujo , Diana Mecanicista del Complejo 1 de la Rapamicina , Ratones , Ratones Endogámicos C57BL , Ratones Transgénicos , Proteínas Proto-Oncogénicas c-akt/metabolismo , Receptores CCR/biosíntesis , Transducción de Señal/fisiología , Linfocitos T Reguladores/efectos de los fármacos , Linfocitos T Reguladores/metabolismo , Tretinoina/farmacologíaRESUMEN
Cancer survivors often relapse due to evolving drug-resistant clones and repopulating tumor stem cells. Our preclinical study demonstrated that terminal cancer patient's lymphocytes can be converted from tolerant bystanders in vivo into effective cytotoxic T-lymphocytes in vitro killing patient's own tumor cells containing drug-resistant clones and tumor stem cells. We designed a clinical trial combining peginterferon α-2b with imatinib for treatment of stage III/IV gastrointestinal stromal tumor (GIST) with the rational that peginterferon α-2b serves as danger signals to promote antitumor immunity while imatinib's effective tumor killing undermines tumor-induced tolerance and supply tumor-specific antigens in vivo without leukopenia, thus allowing for proper dendritic cell and cytotoxic T-lymphocyte differentiation toward Th1 response. Interim analysis of eight patients demonstrated significant induction of IFN-γ-producing-CD8(+), -CD4(+), -NK cell, and IFN-γ-producing-tumor-infiltrating-lymphocytes, signifying significant Th1 response and NK cell activation. After a median follow-up of 3.6 years, complete response (CR) + partial response (PR) = 100%, overall survival = 100%, one patient died of unrelated illness while in remission, six of seven evaluable patients are either in continuing PR/CR (5 patients) or have progression-free survival (PFS, 1 patient) exceeding the upper limit of the 95% confidence level of the genotype-specific-PFS of the phase III imatinib-monotherapy (CALGB150105/SWOGS0033), demonstrating highly promising clinical outcomes. The current trial is closed in preparation for a larger future trial. We conclude that combination of targeted therapy and immunotherapy is safe and induced significant Th1 response and NK cell activation and demonstrated highly promising clinical efficacy in GIST, thus warranting development in other tumor types.
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Neoplasias Gastrointestinales/terapia , Tumores del Estroma Gastrointestinal/terapia , Interferón-alfa/administración & dosificación , Piperazinas/administración & dosificación , Polietilenglicoles/administración & dosificación , Pirimidinas/administración & dosificación , Anciano , Anciano de 80 o más Años , Benzamidas , Supervivencia sin Enfermedad , Neoplasias Gastrointestinales/inmunología , Tumores del Estroma Gastrointestinal/inmunología , Humanos , Mesilato de Imatinib , Inmunoterapia/métodos , Interferón alfa-2 , Interferón-alfa/inmunología , Interferón gamma/biosíntesis , Interferón gamma/inmunología , Linfocitos/inmunología , Persona de Mediana Edad , Proteínas Recombinantes/administración & dosificación , Recurrencia , Linfocitos T Citotóxicos/inmunologíaRESUMEN
Automated methods for detecting prostate cancer and distinguishing indolent from aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis and treatment planning. Existing automated methods of prostate cancer detection mostly rely on ground truth labels with limited accuracy, ignore disease pathology characteristics observed on resected tissue, and cannot selectively identify aggressive (Gleason Pattern≥4) and indolent (Gleason Pattern=3) cancers when they co-exist in mixed lesions. In this paper, we present a radiology-pathology fusion approach, CorrSigNIA, for the selective identification and localization of indolent and aggressive prostate cancer on MRI. CorrSigNIA uses registered MRI and whole-mount histopathology images from radical prostatectomy patients to derive accurate ground truth labels and learn correlated features between radiology and pathology images. These correlated features are then used in a convolutional neural network architecture to detect and localize normal tissue, indolent cancer, and aggressive cancer on prostate MRI. CorrSigNIA was trained and validated on a dataset of 98 men, including 74 men that underwent radical prostatectomy and 24 men with normal prostate MRI. CorrSigNIA was tested on three independent test sets including 55 men that underwent radical prostatectomy, 275 men that underwent targeted biopsies, and 15 men with normal prostate MRI. CorrSigNIA achieved an accuracy of 80% in distinguishing between men with and without cancer, a lesion-level ROC-AUC of 0.81±0.31 in detecting cancers in both radical prostatectomy and biopsy cohort patients, and lesion-levels ROC-AUCs of 0.82±0.31 and 0.86±0.26 in detecting clinically significant cancers in radical prostatectomy and biopsy cohort patients respectively. CorrSigNIA consistently outperformed other methods across different evaluation metrics and cohorts. In clinical settings, CorrSigNIA may be used in prostate cancer detection as well as in selective identification of indolent and aggressive components of prostate cancer, thereby improving prostate cancer care by helping guide targeted biopsies, reducing unnecessary biopsies, and selecting and planning treatment.
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Aprendizaje Profundo , Neoplasias de la Próstata , Humanos , Imagen por Resonancia Magnética , Masculino , Próstata/diagnóstico por imagen , Prostatectomía , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/cirugíaRESUMEN
Covalent inhibitors are viable therapeutics. However, off-target reactivity challenges the field. Chemists have attempted to solve this issue by varying the reactivity attributes of electrophilic warheads. Here, we report the development of an approach to increase the selectivity of covalent molecules that is independent of warhead reactivity features and can be used in concert with existing methods. Using the scaffold of the Bruton's tyrosine kinase (BTK) inhibitor Ibrutinib for our proof-of-concept, we reasoned that increasing the steric bulk of fumarate-based electrophiles on Ibrutinib should improve selectivity via the steric exclusion of off-targets but retain rates of cysteine reactivity comparable to that of an acrylamide. Using chemical proteomic techniques, we demonstrate that elaboration of the electrophile to a tert-butyl (t-Bu) fumarate ester decreases time-dependent off-target reactivity and abolishes time-independent off-target reactivity. While an alkyne-bearing probe analogue of Ibrutinib has 247 protein targets, our t-Bu fumarate probe analogue has only 7. Of these 7 targets, BTK is the only time-independent target. The t-Bu inhibitor itself is also more selective for BTK, reducing off-targets by 70%. We investigated the consequences of treatment with Ibrutinib and our t-Bu analogue and discovered that only 8 proteins are downregulated in response to treatment with the t-Bu analogue compared to 107 with Ibrutinib. Of these 8 proteins, 7 are also downregulated by Ibrutinib and a majority of these targets are associated with BTK biology. Taken together, these findings reveal an opportunity to increase cysteine-reactive covalent inhibitor selectivity through electrophilic structure optimization.
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Inhibidores de Proteínas Quinasas , Proteómica , Agammaglobulinemia Tirosina Quinasa/metabolismo , Cisteína , Fumaratos , Inhibidores de Proteínas Quinasas/química , Inhibidores de Proteínas Quinasas/farmacologíaRESUMEN
Compelling evidence from animal studies has demonstrated that allospecific FoxP3(+)CD4(+) regulatory T (Treg) cells expanded ex vivo can be used as effective therapeutic tools in the treatment of allograft rejection and graft-vs-host disease. Despite the promising results from animal studies, there remain major barriers to developing Treg cell-based immunotherapy in humans. Currently, no effective approach has been established for selective expansion of human allospecific Treg cells ex vivo. Additionally, the very low frequency of Treg cells present in human peripheral blood could pose a formidable challenge to obtaining a sufficient number of Treg cells from a single donor for ex vivo expansion for therapeutic utilization. Extending our recent finding that mouse B cells preferentially induce expansion of alloreactive Treg cells, we report herein that human Treg cells can be expanded ex vivo with allogeneic B cells. The expanded Treg cells express very high levels of FoxP3, maintain anergic phenotype, and are potent suppressors capable of inhibiting the alloproliferation of third-party responder T cells at very low Treg-to-T effector cell ratio in an alloantigen-specific manner. The alloantigen specificity demonstrated by B cell-expanded Treg cells is not determined by the HLA haplotypes of the Treg cells, but it is induced and determined by the haplotype of the B cells used to expand them. Our findings represent a significant advance in the development of Treg cell-based immunotherapy in humans and raise the possibility of using third-party Treg cells for therapeutic applications.
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Proliferación Celular , Inmunoterapia/métodos , Isoantígenos/inmunología , Linfocitos T Reguladores/citología , Linfocitos B , Comunicación Celular , Técnicas de Cultivo de Célula/métodos , Técnicas de Cocultivo , Factores de Transcripción Forkhead , Humanos , Linfocitos T Reguladores/inmunologíaRESUMEN
PURPOSE: While multi-parametric magnetic resonance imaging (MRI) shows great promise in assisting with prostate cancer diagnosis and localization, subtle differences in appearance between cancer and normal tissue lead to many false positive and false negative interpretations by radiologists. We sought to automatically detect aggressive cancer (Gleason pattern ≥ 4) and indolent cancer (Gleason pattern 3) on a per-pixel basis on MRI to facilitate the targeting of aggressive cancer during biopsy. METHODS: We created the Stanford Prostate Cancer Network (SPCNet), a convolutional neural network model, trained to distinguish between aggressive cancer, indolent cancer, and normal tissue on MRI. Ground truth cancer labels were obtained by registering MRI with whole-mount digital histopathology images from patients who underwent radical prostatectomy. Before registration, these histopathology images were automatically annotated to show Gleason patterns on a per-pixel basis. The model was trained on data from 78 patients who underwent radical prostatectomy and 24 patients without prostate cancer. The model was evaluated on a pixel and lesion level in 322 patients, including six patients with normal MRI and no cancer, 23 patients who underwent radical prostatectomy, and 293 patients who underwent biopsy. Moreover, we assessed the ability of our model to detect clinically significant cancer (lesions with an aggressive component) and compared it to the performance of radiologists. RESULTS: Our model detected clinically significant lesions with an area under the receiver operator characteristics curve of 0.75 for radical prostatectomy patients and 0.80 for biopsy patients. Moreover, the model detected up to 18% of lesions missed by radiologists, and overall had a sensitivity and specificity that approached that of radiologists in detecting clinically significant cancer. CONCLUSIONS: Our SPCNet model accurately detected aggressive prostate cancer. Its performance approached that of radiologists, and it helped identify lesions otherwise missed by radiologists. Our model has the potential to assist physicians in specifically targeting the aggressive component of prostate cancers during biopsy or focal treatment.
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Neoplasias de la Próstata , Humanos , Imagen por Resonancia Magnética , Masculino , Clasificación del Tumor , Prostatectomía , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/cirugíaRESUMEN
Cancer genotyping has identified a large number of putative tumor suppressor genes. Carcinogenesis is a multistep process, but the importance and specific roles of many of these genes during tumor initiation, growth, and progression remain unknown. Here we use a multiplexed mouse model of oncogenic KRAS-driven lung cancer to quantify the impact of 48 known and putative tumor suppressor genes on diverse aspects of carcinogenesis at an unprecedented scale and resolution. We uncover many previously understudied functional tumor suppressors that constrain cancer in vivo. Inactivation of some genes substantially increased growth, whereas the inactivation of others increases tumor initiation and/or the emergence of exceptionally large tumors. These functional in vivo analyses revealed an unexpectedly complex landscape of tumor suppression that has implications for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches to limit tumor initiation and progression. SIGNIFICANCE: Our high-throughput and high-resolution analysis of tumor suppression uncovered novel genetic determinants of oncogenic KRAS-driven lung cancer initiation, overall growth, and exceptional growth. This taxonomy is consistent with changing constraints during the life history of cancer and highlights the value of quantitative in vivo genetic analyses in autochthonous cancer models.This article is highlighted in the In This Issue feature, p. 1601.
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Genes Supresores de Tumor , Neoplasias Pulmonares/genética , Proteínas Proto-Oncogénicas p21(ras)/genética , Transformación Celular Neoplásica , Humanos , Neoplasias Pulmonares/patologíaRESUMEN
Introduction: Surgical resection of brain tumors is often limited by adjacent critical structures such as blood vessels. Current intraoperative navigations systems are limited; most are based on two-dimensional (2D) guidance systems that require manual segmentation of any regions of interest (ROI; eloquent structures to avoid or tumor to resect). They additionally require time- and labor-intensive processing for any reconstruction steps. We aimed to develop a deep learning model for real-time fully automated segmentation of the intracranial vessels on preoperative non-angiogram imaging sequences. Methods: We identified 48 pediatric patients (10-months to 22-years old) with high resolution (0.5-1 mm axial thickness) isovolumetric, pre-operative T2 magnetic resonance images (MRIs). Twenty-eight patients had anatomically normal brains, and 20 patients had tumors or other lesions near the skull base. Manually segmented intracranial vessels (internal carotid, middle cerebral, anterior cerebral, posterior cerebral, and basilar arteries) served as ground truth labels. Patients were divided into 80/5/15% training/validation/testing sets. A modified 2-D Unet convolutional neural network (CNN) architecture implemented with 5 layers was trained to maximize the Dice coefficient, a measure of the correct overlap between the predicted vessels and ground truth labels. Results: The model was able to delineate the intracranial vessels in a held-out test set of normal and tumor MRIs with an overall Dice coefficient of 0.75. While manual segmentation took 1-2 h per patient, model prediction took, on average, 8.3 s per patient. Conclusions: We present a deep learning model that can rapidly and automatically identify the intracranial vessels on pre-operative MRIs in patients with normal vascular anatomy and in patients with intracranial lesions. The methodology developed can be translated to other critical brain structures. This study will serve as a foundation for automated high-resolution ROI segmentation for three-dimensional (3D) modeling and integration into an augmented reality navigation platform.
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Cell-cell interactions influence all aspects of development, homeostasis, and disease. In cancer, interactions between cancer cells and stromal cells play a major role in nearly every step of carcinogenesis. Thus, the ability to record cell-cell interactions would facilitate mechanistic delineation of the role of the cancer microenvironment. Here, we describe GFP-based Touching Nexus (G-baToN) which relies upon nanobody-directed fluorescent protein transfer to enable sensitive and specific labeling of cells after cell-cell interactions. G-baToN is a generalizable system that enables physical contact-based labeling between various human and mouse cell types, including endothelial cell-pericyte, neuron-astrocyte, and diverse cancer-stromal cell pairs. A suite of orthogonal baToN tools enables reciprocal cell-cell labeling, interaction-dependent cargo transfer, and the identification of higher order cell-cell interactions across a wide range of cell types. The ability to track physically interacting cells with these simple and sensitive systems will greatly accelerate our understanding of the outputs of cell-cell interactions in cancer as well as across many biological processes.
It takes the coordinated effort of more than 40 trillion cells to build and maintain a human body. This intricate process relies on cells being able to communicate across long distances, but also with their immediate neighbors. Interactions between cells in close contact are key in both health and disease, yet tracing these connections efficiently and accurately remains challenging. The surface of a cell is studded with proteins that interact with the environment, including with the proteins on neighboring cells. Using genetic engineering, it is possible to construct surface proteins that carry a fluorescent tag called green fluorescent protein (or GFP), which could help to track physical interactions between cells. Here, Tang et al. test this idea by developing a new technology named GFP-based Touching Nexus, or G-baToN for short. Sender cells carry a GFP protein tethered to their surface, while receiver cells present a synthetic element that recognizes that GFP. When the cells touch, the sender passes its GFP to the receiver, and these labelled receiver cells become 'green'. Using this system, Tang et al. recorded physical contacts between a variety of human and mouse cells. Interactions involving more than two cells could also be detected by using different colors of fluorescent tags. Furthermore, Tang et al. showed that, alongside GFP, G-baToN could pass molecular cargo such as proteins, DNA, and other chemicals to receiver cells. This new system could help to study interactions among many different cell types. Changes in cell-to-cell contacts are a feature of diverse human diseases, including cancer. Tracking these interactions therefore could unravel new information about how cancer cells interact with their environment.
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Comunicación Celular/fisiología , Proteínas Fluorescentes Verdes/metabolismo , Microscopía/métodos , Animales , Línea Celular , Técnicas de Cocultivo , Proteínas Fluorescentes Verdes/química , Humanos , Lentivirus , Ratones , Transporte de ProteínasRESUMEN
PURPOSE: Magnetic resonance imaging (MRI) has great potential to improve prostate cancer diagnosis; however, subtle differences between cancer and confounding conditions render prostate MRI interpretation challenging. The tissue collected from patients who undergo radical prostatectomy provides a unique opportunity to correlate histopathology images of the prostate with preoperative MRI to accurately map the extent of cancer from histopathology images onto MRI. We seek to develop an open-source, easy-to-use platform to align presurgical MRI and histopathology images of resected prostates in patients who underwent radical prostatectomy to create accurate cancer labels on MRI. METHODS: Here, we introduce RAdiology Pathology Spatial Open-Source multi-Dimensional Integration (RAPSODI), the first open-source framework for the registration of radiology and pathology images. RAPSODI relies on three steps. First, it creates a three-dimensional (3D) reconstruction of the histopathology specimen as a digital representation of the tissue before gross sectioning. Second, RAPSODI registers corresponding histopathology and MRI slices. Third, the optimized transforms are applied to the cancer regions outlined on the histopathology images to project those labels onto the preoperative MRI. RESULTS: We tested RAPSODI in a phantom study where we simulated various conditions, for example, tissue shrinkage during fixation. Our experiments showed that RAPSODI can reliably correct multiple artifacts. We also evaluated RAPSODI in 157 patients from three institutions that underwent radical prostatectomy and have very different pathology processing and scanning. RAPSODI was evaluated in 907 corresponding histpathology-MRI slices and achieved a Dice coefficient of 0.97 ± 0.01 for the prostate, a Hausdorff distance of 1.99 ± 0.70 mm for the prostate boundary, a urethra deviation of 3.09 ± 1.45 mm, and a landmark deviation of 2.80 ± 0.59 mm between registered histopathology images and MRI. CONCLUSION: Our robust framework successfully mapped the extent of cancer from histopathology slices onto MRI providing labels from training machine learning methods to detect cancer on MRI.
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Neoplasias de la Próstata , Radiología , Humanos , Imagen por Resonancia Magnética , Masculino , Próstata/diagnóstico por imagen , Próstata/cirugía , Prostatectomía , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/cirugía , Vesículas SeminalesRESUMEN
OBJECTIVE: Imaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for calculating ventricular volume are not structured for clinical use. The authors aimed to develop a fully automated deep learning (DL) model for pediatric cerebral ventricle segmentation and volume calculation for widespread clinical implementation across multiple hospitals. METHODS: The study cohort consisted of 200 children with obstructive hydrocephalus from four pediatric hospitals, along with 199 controls. Manual ventricle segmentation and volume calculation values served as "ground truth" data. An encoder-decoder convolutional neural network architecture, in which T2-weighted MR images were used as input, automatically delineated the ventricles and output volumetric measurements. On a held-out test set, segmentation accuracy was assessed using the Dice similarity coefficient (0 to 1) and volume calculation was assessed using linear regression. Model generalizability was evaluated on an external MRI data set from a fifth hospital. The DL model performance was compared against FreeSurfer research segmentation software. RESULTS: Model segmentation performed with an overall Dice score of 0.901 (0.946 in hydrocephalus, 0.856 in controls). The model generalized to external MR images from a fifth pediatric hospital with a Dice score of 0.926. The model was more accurate than FreeSurfer, with faster operating times (1.48 seconds per scan). CONCLUSIONS: The authors present a DL model for automatic ventricle segmentation and volume calculation that is more accurate and rapid than currently available methods. With near-immediate volumetric output and reliable performance across institutional scanner types, this model can be adapted to the real-time clinical evaluation of hydrocephalus and improve clinician workflow.
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Inteligencia Artificial , Ventrículos Cerebrales/diagnóstico por imagen , Hidrocefalia/diagnóstico por imagen , Hidrocefalia/diagnóstico , Adolescente , Niño , Preescolar , Estudios de Cohortes , Aprendizaje Profundo , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Lactante , Recién Nacido , Imagen por Resonancia Magnética/métodos , Masculino , Modelos Teóricos , Redes Neurales de la Computación , Programas Informáticos , Adulto JovenRESUMEN
Purpose. To determine whether total psoas area (TPA), a simple estimate of muscle mass, is associated with complications after radical cystectomy. Materials and Methods. Patients who underwent radical cystectomy at our institution from 2011 to 2012 were retrospectively identified. Total psoas area was measured on preoperative CT scans and normalized for patient height. Multivariable logistic regression was used to determine whether TPA was a predictor of 90-day postoperative complications. Overall survival was compared between TPA quartiles. Results. 135 patients were identified for analysis. Median follow-up was 24 months (IQR: 6-37 months). Overall 90-day complication rate was 56% (75/135). TPA was significantly lower for patients who experienced any complication (7.8 cm(2)/m(2) versus 8.8 cm(2)/m(2), P = 0.023) and an infectious complication (7.0 cm(2)/m(2) versus 8.7 cm(2)/m(2), P = 0.032) than those who did not. On multivariable analysis, TPA (adjusted OR 0.70 (95% CI 0.56-0.89), P = 0.003) and Charlson comorbidity index (adjusted OR 1.34 (95% CI 1.01-1.79), P = 0.045) were independently associated with 90-day complications. TPA was not a predictor of overall survival. Conclusions. Low TPA is associated with infectious complications and is an independent predictor of experiencing a postoperative complication following radical cystectomy.
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Tregs play important roles in maintaining immune homeostasis, and thus, therapies based on Treg are promising candidates for the treatment for a variety of immune-mediated disorders. These therapies, however, face the significant challenge of obtaining adequate numbers of Tregs from peripheral blood that maintains suppressive function following extensive expansion. Inducing Tregs from non-Tregs offers a viable alternative. Different methods to induce Tregs have been proposed and involve mainly treating cells with TGF-ß-iTreg. However, use of TGF-ß alone is not sufficient to induce stable Tregs. ATRA or rapa has been shown to synergize with TGF-ß to induce stable Tregs. Whereas TGF-ß plus RA-iTregs have been well-described in the literature, the phenotype, function, and migratory characteristics of TGF-ß plus rapa-iTreg have yet to be elucidated. Herein, we describe the phenotype and function of mouse rapa-iTreg and reveal that these cells differ in their in vivo homing capacity when compared with mouse RA-iTreg and mouse TGF-ß-iTreg. This difference in migratory activity significantly affects the therapeutic capacity of each subset in a mouse model of colitis. We also describe the characteristics of iTreg generated in the presence of TGF-ß, RA, and rapa.