Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer.

The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL's advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Pyrolysis of Chilean Southern Lignocellulosic Biomasses: Isoconversional Kinetics Analysis and Pyrolytic Products Distribution.

Biomass provides potential benefits for obtaining value-added compounds instead of straight burning; as Chile has forestry potential that supports such benefits, it is crucial to understand the biomasses' properties and their thermochemical behaviour. This research presents a kinetic analysis of thermogravimetry, and pyrolysis of representative species in the biomass of southern Chile, heating biomasses at 5 to 40 °C·min-1 rates before being subjected to thermal volatilisation. The activation energy (Ea) was calculated from conversion using model-free methods (Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Friedman (FR)), as well as the Kissinger method based on the maximum reaction rate. The average Ea varied between KAS 117 and 171 kJ·mol-1, FWO 120-170 kJ·mol-1, and FR 115-194 kJ·mol-1 for the five biomasses used. Pinus radiata (PR) was identified as the most suited wood for producing value-added goods based on the Ea profile for the conversion (α), along with Eucalyptus nitens (EN) for its high value of reaction constant (k). Each biomass demonstrated accelerated decomposition (an increase in k relative to α). The highest concentration of bio-oil containing phenolic, ketonic, and furanic compounds was produced by the forestry exploitation biomasses PR and EN, demonstrating the viability of these materials for thermoconversion processes.

Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICIs) show prominent clinical activity across multiple advanced tumors. However, less than half of patients respond even after molecule-based selection. Thus, improved biomarkers are required. In this study, we use an image analysis to capture morphologic attributes relating to the spatial interaction and architecture of tumor cells and tumor-infiltrating lymphocytes (TILs) from digitized H&E images. We evaluate the association of image features with progression-free (PFS) and overall survival in non-small cell lung cancer (NSCLC) (N = 187) and gynecological cancer (N = 39) patients treated with ICIs. We demonstrated that the classifier trained with NSCLC alone was associated with PFS in independent NSCLC cohorts and also in gynecological cancer. The classifier was also associated with clinical outcome independent of clinical factors. Moreover, the classifier was associated with PFS even with low PD-L1 expression. These findings suggest that image analysis can be used to predict clinical end points in patients receiving ICI.

Role of tumor infiltrating lymphocytes and spatial immune heterogeneity in sensitivity to PD-1 axis blockers in non-small cell lung cancer.

BACKGROUND: Tumor infiltrating lymphocytes (TILs) reflect adaptive antitumor immune responses in cancer and are generally associated with favorable prognosis. However, the relationships between TILs subsets and their spatial arrangement with clinical benefit from immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC) remains less explored. METHODS: We used multiplexed quantitative immunofluorescence panels to determine the association of major TILs subpopulations, CD8+ cytotoxic T cells, CD4+ helper T cells and CD20+ B cells, and T cell exhaustion markers, programmed cell death protein-1 (PD-1),lymphocyte-activation gene 3 (LAG-3) and T cell immunoglobulin mucin-3 (TIM-3) with outcomes in a multi-institutional cohort of baseline tumor samples from 179 patients with NSCLC treated with ICI. The analysis of full-face tumor biopsies including numerous fields of view allowed a detailed spatial analysis and assessment of tumor immune heterogeneity using a multiparametric quadratic entropy metric (Rao's Q Index (RQI)). RESULTS: TILs were preferentially located in the stromal tissue areas surrounding tumor-cell nests and CD8+ T cells were the most abundant subset. Higher density of stromal CD8+ cytotoxic T cells was significantly associated with longer survival, and this effect was more prominent in programmed death ligand-1 (PD-L1) positive cases. The role of baseline T cell infiltration to stratify PD-L1 expressing cases was confirmed measuring the T cell receptor-burden in an independent NSCLC cohort studied with whole-exome DNA sequencing. High levels of LAG-3 on T cells or elevated RQI heterogeneity index were associated with worse survival in the cohort. CONCLUSION: Baseline T cell density and T cell exhaustion marker expression can stratify outcomes in PD-L1 positive patients with NSCLC treated with ICI. Spatial immune heterogeneity can be measured using the RQI and is associated with survival in NSCLC.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome.

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer.

BACKGROUND: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). METHODS: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. FINDINGS: CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08). INTERPRETATION: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients. FUNDING: Data collection, anlaysis, and computation resources of the research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers: 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.

Determinantes del subempleo en Colombia: una aproximación a partir de un modelo PROBIT / Determining factors of underemployment in Colombia: An approach based on a Probit model

Resumen El subempleo es un indicador de la calidad del empleo, así como del nivel de subutilización de la capacidad productiva de la población ocupada. En este artículo se analizan los determinantes de la probabilidad de caer en el subempleo en Colombia. Se utilizaron los datos de la Gran Encuesta Integrada de Hogares del año 2017, para estimar un modelo Probit. Se encontró que mayor educación y experiencia se asocia con una menor probabilidad de caer en el subempleo. Las mujeres, los trabajadores cabeza de hogar, los trabajadores por cuenta propia y los empleados domésticos, tienen una mayor probabilidad de ser subempleados.

Abstract Underemployment is an indicator of the quality of employment, as well as the level of underutilization of the productive capacity of the occupied population. This article discusses the determinants of the likelihood of falling into underemployment in Colombia. Data from the Large Integrated Household Survey was used to estimate a Probit model. It was found that better education and experience are associated with a lower likelihood of falling into underemployment. Women, men or women who are heads of family, self-employed workers, and domestic workers, are more likely to be underemployed.

Differentiating Cancerous and Non-cancerous Prostate Tissue Using Multi-scale Texture Analysis on MRI.

Prostate cancer (PCa) diagnosis is established by pathological examination via biopsies, which are associated with significant complications and false negatives. Using MRIs to identify locations with high probability of containing cancer could instead be used to guide the biopsy procedure. The present investigation aims to identify target regions within different prostatic zones on MRI with high probability of being cancerous for assisting in the decision of where and how to perform biopsy. Our approach involved extracting multi-scale texture features for capturing local patterns to distinguish cancer and healthy tissue in different T2W-MRI prostate zones. Three different classification models were fed by the proposed strategy, namely support vector machine (SVM), Adaboost, and Random Forest. SVM with a linear kernel showed the best classification performance, with AUC scores of 0.91 in the anterior fibromuscular stroma area, 0.85 in the peripheral zone, and 0.87 when classification is performed independently of the prostate zone. The proposed method demonstrated that discriminant multi-scale texture features can accurately identify regions of prostate cancer in a zone-specific fashion, via MRI.

Localization of Small Neoplastic Lesions in Colonoscopy by Estimating Edge, Texture and Motion Saliency.

Early screening in Colorectal Cancer consists in finding and removing small precancerous masses or neoplastic lesions developed from the mucosa, usually lesions smaller than 10 mm. Localization of small neoplastic lesions is a very challenging task since colon exploration is highly dependent on the expert training and colon preparation. Several strategies have attempted to locate neoplasias, but usually they are huge lesions that a trained gastroenterologist could hardly miss. This work presents a saliency-based strategy to localize polypoid and non-polypoid neoplastic lesions smaller than 10 mm in colonoscopy videos by combining spatio-temporal descriptors. For doing so, a per-frame-multi-scale representation is computed and edge, texture and motion features are extracted. Each of these features is used to construct a primary saliency map which are then combined to obtain a coarse saliency map. Finally, the neoplasia is localized as the bounding box of a circular region, approximated by the Hough transform, with the largest salience. The proposed approach was evaluated in 8 short colonoscopy videos obtaining an average of Annotated Area Covered of 0.75 and a precision of 0.82.

Niveles séricos del factor neurotrófico derivado del cerebro durante la gestación normal y la preeclampsia / Serum Levels of Brain Derived Neurotrophic Factor during Normal Pregnancy and Preeclampsia

Introducción. La preeclampsia (PE) es una de las principales causas de mortalidad materna y perinatal en el mundo, aparece en la segunda mitad de la gestación y actualmente no hay marcadores que la detecten en forma temprana. Dadas las propiedades angiogénicas del factor neurotrófico derivado del cerebro (BDNF) y la disfunción endotelial de los vasos sanguíneos presente en la PE, se ha propuesto una posible asociación entre el BDNF y PE. Objetivo. Determinar si existe asociación entre niveles séricos de BDNF durante el embarazo y la preeclampsia. Materiales y métodos. Estudio de cohorte prospectivo longitudinal. Se seleccionaron 13 pacientes quienes desarrollaron PE y 31 gestantes de curso normal. Se midieron variables antropométricas y niveles de BDNF, glicemia, insulina y perfil lipídico en la gestación temprana, media y tardía. Se practicó un modelo de regresión logística para verificar si los niveles de BDNF, en conjunto con otras variables, pueden explicar el desarrollo de PE. Resultados. Los niveles de BDNF no variaron significativamente entre el grupo de gestantes que desarrollaron preeclampsia y las que no: en gestación temprana 25.3 y 23.3ng/ml, en gestación media 28 y 24.7ng/ml y en gestación tardía 25.4 y 27.4ng/ml, respectivamente. Se hallaron diferencias entre los dos grupos en el peso, la insulina y la evaluación del modelo homeostático (HOMA). Se encontró asociación entre niveles de BDNF y peso e IMC y glucemia en las gestantes que no desarrollaron PE. Se practicó un modelo de regresión logística en el que la PE se explicó mejor con variables como IMC, PAS y HOMA, pero no con BDNF. Conclusiones. El BDNF puede participar en la regulación del peso corporal y el metabolismo de la glucosa en mujeres gestantes, pero el nivel de BDNF, solo o en conjunto con otras variables, no puede explicar la preeclampsia.

Introduction. Preeclampsia (PE) is one of the major causes of maternal and perinatal mortality in the world. PE appears during the second half of pregnancy and there are currently no markers for its early detection. Given the angiogenic properties of brain derived neurotrophic factor (BDNF) and the endothelial dysfunction of blood vessels that occurs during PE, an association between BDNF and PE has been proposed. Objective. To determine if there is an association between BDNF serum levels and PE during pregnancy. Materials and Methods. Prospective longitudinal cohort study. 13 patients who developed PE and 31 patients with normally coursing pregnancies were selected. Anthropometric variables, BDNF serum levels, glycemia, insulin and lipid profile in early, mid-term and late pregnancies were measured. Results. No significant differences were observed in BDNF levels between women who developed PE and those who did not; in early pregnancy the levels were 25.3 and 23.3 ng/ml, for mid-term pregnancy 28 and 24.7 ng/ml and for late pregnancy 25.4 and 27.4 ng/ml for PE and normal pregnancy, respectively. An association between BDNF and weight and BMI and serum glucose was found in women who did not develop PE. A logistic regression model was carried out where PE was better explained through variables such as BMI, SBP and homoeostasis model assessment (HOMA), however BDNF was not taken into account here. Conclusions. BDNF might have a role in regulating body weight and glucose metabolism in pregnant women but there is no evidence to suggest that BDNF alone or in combination with other variables can account for PE.

[ANTHROPOMETRIC CHILEAN TABLE TENNIS PLAYERS OF COMPETITIVE FEATURES]. / CARACTERÍSTICAS ANTROPOMÉTRICAS EN JUGADORES CHILENOS DE TENIS DE MESA DE NIVEL COMPETITIVO.

The aim of the study was to characterize the anthropometric profile and somatotype of a sample of 50 players table tennis competitive with an average age 21.6 (± 3.1) years belonging to the Chilean team and institutions of higher education in the region of Valparaiso. The evaluation was conducted under the protocol marking the International Society for the Advancement of Kinanthropometry (ISAK) for the measurement procedure 25 restricted profile variables described by Drinkwater, Norton and Olds. Order to determine the body composition, fat, muscle, bone, skin and tissue residual was considered, using the equations proposed by Kerr. The body shape is characterized through somatotype method proposed by Carter. The sample was divided into 4 groups; Chilean Selection, Traditional Private Universities, State Universities and Private Universities Traditional Nontraditional. Regarding body composition; the Chilean team has the highest values of muscle tissue (45.6 ± 1.7%) and the lowest values of adipose tissue (25.2 ± 1.8%), also presenting lesser value in the Σ 6 skinfolds (mm) . The results showed no significant differences between groups in the aforementioned variables. In general somatotype compared by analyzing SANOVA no significant differences between groups (p = 0.409) was observed. The results show a biotype with such a characterization of endo-mesomorph with average values (4,1-4,9-1,8). This study provides updated data biotypological reference for this sport that can be used for decision-making.

El objetivo del estudio fue caracterizar el perfil antropometrico y el somatotipo de una muestra de 50 jugadores de tenis de mesa de nivel competitivo con un promedio de edad 21,6 (± 3,1) anos pertenecientes a la seleccion chilena e instituciones de educacion superior de la region de Valparaiso. La evaluacion se realizo bajo el protocolo de marcaje de la International Society for the Advancement of Kinanthropometry (ISAK) para el procedimiento de medicion de 25 variables de perfil restringido descrito por Drinkwater1, Norton & Olds2. Con el objetivo de determinar la composicion corporal, se considero el tejido adiposo, muscular, oseo, residual y de piel, utilizando las ecuaciones propuestas por Kerr3. La forma corporal se caracterizo a traves del metodo del somatotipo propuesto por Carter4. La muestra se distribuyo en cuatro grupos: seleccion chilena, universidades privadas tradicionales, universidades estatales tradicionales y universidades privadas no tradicionales. Respecto a la composicion corporal; la seleccion chilena presenta los mayores valores de tejido muscular (45,6 ± 1,7%) y los menores valores de tejido adiposo (25,2 ± 1,8%), presentando tambien menor valor en la Σ seis pliegues (mm). Los resultados no evidenciaron diferencias significativas entre los grupos en las variables antes mencionadas. En la comparacion general del somatotipo a traves del analisis SANOVA no se aprecian diferencias significativas entre los grupos (p = 0,409). Los resultados obtenidos muestran un biotipo con una caracterizacion de tipo endo-mesomorfo con valores promedio de (4,1-4,9-1,8). Este estudio aporta datos biotipologicos actualizados de referencia para este deporte que pueden ser utilizados para la toma de decisiones.