Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations

BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC

Resultados a medio y largo plazo de la utilización de videotorascopia en la cirugía de resección de las metástasis pulmonares

La resección quirúrgica de las metástasis pulmonares es un método de tratamiento aceptado como habitual en la cirugía torácica. Sin embargo, continúa siendo un motivo de controversia si esta resección se debe realizar por toracotomía, o por las modernas técnicas vídeo asistidas. Con la finalidad de buscar una respuesta a dicha controversia en nuestro medio de trabajo, se efectuó una revisión de las intervenciones quirúrgicas realizadas con el objetivo de resecar metástasis pulmonares. Entre enero de 1997 y diciembre de 2001, se encontraron 56 pacientes a quienes se había resecado metástasis pulmonares por videotoracoscopia de entre un total de 252 metastasectomías (22,2%). Se clasificaron los tumores primarios en 4 grupos: sarcoma (n=11); colorrectal (n=25); renales (n=5); y otros (n=15). La videotoracoscopia se realizó en el hemitórax derecho (n=28), hemitórax izquierdo (n=22) o en ambos a la vez (n=6). La mortalidad operatoria fue nula y la única morbilidad atribuible a la técnica fue un defecto de reexpansión tras la retirada del drenaje torácico en un paciente. Utilizando el método de Kaplan-Meier, la probabilidad de supervivencia de esta serie de pacientes fue del 60,4% a los 5 años, con tiempo de supervivencia medio de 48 meses. Todos estos datos apoyan en nuestro medio el empleo de videotoracoscopia en pacientes con metástasis pulmonares. Sin embargo, y a la vista de los resultados, es importante al efectuar esta técnica poner un cuidado especial en conseguir buenos márgenes de resección, debido al riesgo real de recurrencia local sobre dichos márgenes a medio plazo. Palabras clave. Cirugía videoasistida. Videotoracoscopia. Metástasis pulmonar. Carcinoma colorrectal. Sarcoma

Long-Term Outcome of Critically Ill Advanced Cancer Patients Managed in an Intermediate Care Unit

Background: To analyze the long-term outcomes for advanced cancer patients admitted to an intermediate care unit (ImCU), an analysis of a do not resuscitate orders (DNR) subgroup was made. Methods: A retrospective observational study was conducted from 2006 to January 2019 in a single academic medical center of cancer patients with stage IV disease who suffered acute severe complications. The Simplified Acute Physiology Score 3 (SAPS 3) was used as a prognostic and severity score. In-hospital mortality, 30-day mortality and survival after hospital discharge were calculated. Results: Two hundred and forty patients with stage IV cancer who attended at an ImCU were included. In total, 47.5% of the cohort had DNR orders. The two most frequent reasons for admission were sepsis (32.1%) and acute respiratory failure (excluding sepsis) (38.7%). Mortality in the ImCU was 10.8%. The mean predicted in-hospital mortality according to SAPS 3 was 51.9%. The observed in-hospital mortality was 37.5% (standard mortality ratio of 0.72). Patients discharged from hospital had a median survival of 81 (30.75–391.25) days (patients with DNR orders 46 days (19.5–92.25), patients without DNR orders 162 days (39.5–632)). The observed mortality was higher in patients with DNR orders: 52.6% vs. 23.8%, p 0 < 0.001. By multivariate logistic regression, a worse ECOG performance status (3–4 vs. 0–2), a higher SAPS 3 Score and DNR orders were associated with a higher in-hospital mortality. By multivariate analysis, non-invasive mechanical ventilation, higher bilirubin levels and DNR orders were significantly associated with 30-day mortality. Conclusion: For patients with advanced cancer disease, even those with DNR orders, who suffer from acute complications or require continuous monitoring, an ImCU-centered multidisciplinary management shows encouraging results in terms of observed-to-expected mortality ratios

Selection of extreme phenotypes: the role of clinical observation in translational research NIH Public Access Author Manuscript

Abstract Systematic collection of phenotypes and their correlation with molecular data has been proposed as a useful method to advance in the study of disease. Although some databases for animal species are being developed, progress in humans is slow, probably due to the multifactorial origin of many human diseases and to the intricacy of accurately classifying phenotypes, among other factors. An alternative approach has been to identify and to study individuals or families with very characteristic, clinically relevant phenotypes. This strategy has shown increased efficiency to identify the molecular features underlying such phenotypes. While on most occasions the subjects selected for these studies presented harmful phenotypes, a few studies have been performed in individuals with very favourable phenotypes. The consistent results achieved suggest that it seems logical to further develop this strategy as a methodology to study human disease, including cancer. The identification and the study with high-throughput techniques of individuals showing a markedly decreased risk of developing cancer or of cancer patients presenting either an unusually favourable prognosis or striking responses following a specific treatment, might be promising ways to maximize the yield of this approach and to reveal the molecular causes that explain those phenotypes and thus highlight useful therapeutic targets. This manuscript reviews the current Correspondence to: José Luis Pérez-Gracia, [email protected]. Conflict of interest The authors declare that they have no conflict of interest relating to the publication of this manuscript. NIH Public Acces