Implementation of a Pilot Study to Analyze Circulating Tumor DNA in Early-Stage Lung Cancer.

INTRODUCTION: Liquid biopsies based on plasma circulating tumour deoxyribonucleic acid (ctDNA) have shown promise in monitoring lung cancer evolution. The expression of ctDNA across time, its relationship with clinicopathological parameters and its association with lung cancer progression through imaging allow us to weigh how useful ctDNA could be in monitoring surgically resectable lung cancer. The aim of this study was to assess the impact of ctDNA analysis implementation in early-stage lung cancer. METHODS: A cohort of 47 patients was sequentially recruited. Only 34 patients with early-stage lung cancer were included. All patients had a tissue specimen and five blood samples drawn: at the preoperative stage, from the pulmonary vein, at surgical discharge, at the first follow-up and at the last follow-up. All blood samples were evaluated for ctDNA expression. RESULTS: On average, the maximum yield of ctDNA was obtained in liquid biopsies at the surgical discharge of patients when compared with PO, PV, and F1 (p < 0.0001, p < 0.0001, p < 0.0001 respectively). No statistically significant differences were found when comparing the last follow-up to surgical discharge ctDNA expression (p = 0.851). The correlation between ctDNA concentration according to five-time points and the four clinicopathological characteristics showed that patients younger than 70 years had a statistically significant reduction of the concentration of ctDNA at the preoperative and surgical discharge time point [ß = -16 734 (-27 707; - 5760); p = 0.003; ß = -21 785 (-38 447; -5123); p = 0.010], as opposed to an increase of the concentration of ctDNA at the pulmonary vein and last follow-up time points [ß = 8369 (0.359; 16 378); p = 0.041; ß = 34 402 (12 549; 56 254); p = 0.002] all with a confidence level of 95%. In the cases where actionable mutations were identified in tissue biopsies, the expected mutation was found in five out of six patients plasma samples at the pre-operatory time point and in two out of six patients plasma samples at the pulmonary vein time point. Two out of six patients with actionable mutations had disease progression. CONCLUSION: The results of this pilot study suggest that the maximum yield of ctDNA is obtained at the surgical discharge of the patients and that the pre-operatory timepoint is the one offering the highest sensitivity for the detection of actionable mutations in ctDNA in early-stage lung cancer.

Multiple instance learning for lung pathophysiological findings detection using CT scans.

Lung diseases affect the lives of billions of people worldwide, and 4 million people, each year, die prematurely due to this condition. These pathologies are characterized by specific imagiological findings in CT scans. The traditional Computer-Aided Diagnosis (CAD) approaches have been showing promising results to help clinicians; however, CADs normally consider a small part of the medical image for analysis, excluding possible relevant information for clinical evaluation. Multiple Instance Learning (MIL) approach takes into consideration different small pieces that are relevant for the final classification and creates a comprehensive analysis of pathophysiological changes. This study uses MIL-based approaches to identify the presence of lung pathophysiological findings in CT scans for the characterization of lung disease development. This work was focus on the detection of the following: Fibrosis, Emphysema, Satellite Nodules in Primary Lesion Lobe, Nodules in Contralateral Lung and Ground Glass, being Fibrosis and Emphysema the ones with more outstanding results, reaching an Area Under the Curve (AUC) of 0.89 and 0.72, respectively. Additionally, the MIL-based approach was used for EGFR mutation status prediction - the most relevant oncogene on lung cancer, with an AUC of 0.69. The results showed that this comprehensive approach can be a useful tool for lung pathophysiological characterization.

Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges.

Advancements in the development of computer-aided decision (CAD) systems for clinical routines provide unquestionable benefits in connecting human medical expertise with machine intelligence, to achieve better quality healthcare. Considering the large number of incidences and mortality numbers associated with lung cancer, there is a need for the most accurate clinical procedures; thus, the possibility of using artificial intelligence (AI) tools for decision support is becoming a closer reality. At any stage of the lung cancer clinical pathway, specific obstacles are identified and "motivate" the application of innovative AI solutions. This work provides a comprehensive review of the most recent research dedicated toward the development of CAD tools using computed tomography images for lung cancer-related tasks. We discuss the major challenges and provide critical perspectives on future directions. Although we focus on lung cancer in this review, we also provide a more clear definition of the path used to integrate AI in healthcare, emphasizing fundamental research points that are crucial for overcoming current barriers.

Liquid biopsy: the value of different bodily fluids.

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

COPD: How can evidence from randomised controlled trials apply to patients treated in everyday clinical practice?

OBJECTIVES: To evaluate the degree to which evidence from large clinical trials can be applied to patients treated in a local hospital cohort of COPD outpatients. METHODS: The authors selected seventeen RCTs identified in a systematic way from GOLD 2019 consensus document, and applied their inclusion and exclusion criteria to a real-world cohort of a previous cross-sectional study of 303 COPD outpatients included consecutively. RESULTS: When the inclusion criteria of the 17 RCTs were applied to a real-world cohort of COPD outpatients, only a small portion of them were eligible to participate in the referred trials, from 4.29% to 60.07%. However, when both the inclusion and the exclusion criteria were applied, only as little as 3.63% to as much as 40.59% of patients were eligible to participate. Hence, only a small fraction of patients from this cohort could benefit from the findings of these RCTs. CONCLUSIONS: There is a need to complement the efficacy evidence provided by large RCTs according to the extent to which their results, designed to target significant patient populations, can be applied to typical patients treated in routine clinical practice.

The value of cell-free circulating tumour DNA profiling in advanced non-small cell lung cancer (NSCLC) management.

Liquid biopsy (LB) has boosted a remarkable change in the management of cancer patients by contributing to tumour genomic profiling. Plasma circulating cell-free tumour DNA (ctDNA) is the most widely searched tumour-related element for clinical application. Specifically, for patients with lung cancer, LB has revealed valuable to detect the diversity of targetable genomic alterations and to detect and monitor the emergence of resistance mechanisms. Furthermore, its non-invasive nature helps to overcome the difficulty in obtaining tissue samples, offering a comprehensive view about tumour diversity. However, the use of the LB to support diagnostic and therapeutic decisions still needs further clarification. In this sense, this review aims to provide a critical view of the clinical importance of plasma ctDNA analysis, the most widely applied LB, and its limitations while anticipating concepts that will intersect the present and future of LB in non-small cell lung cancer patients.

Management of Coronavirus Disease 2019 Patients With Lung Cancer: Experience From a Thoracic Oncology Center.

BACKGROUND: Cancer patients appear to be at a higher risk of complications from coronavirus disease 2019 (COVID-19). Specific data related to lung cancer (LC) patient management, active treatment, and/or recent diagnosis are still very limited. Here, we aimed to investigate the clinical presentation, baseline features, and clinical outcomes of LC patients with COVID-19. METHODS: A retrospective case study was performed at Centro Hospitalar Universitário de São Joao, a tertiary hospital in the North of Portugal. Data from LC patients diagnosed with COVID-19 were collected during the first 10 months of the COVID-19 pandemic (March 2020-January 2021). RESULTS: Twenty-eight patients with active LC were diagnosed with COVID-19, being adenocarcinoma the most common histological type present (n = 13, 46.4%). Sixteen patients had metastatic stage IV LC (61.5%). Twenty-five patients (89.3%) had relevant comorbidities including hypertension (39.3%) and chronic obstructive pulmonary disease (32.1%). For patients undergoing antineoplastic treatment, the median time from the last chemotherapy administration to COVID-19 diagnosis was of 16 days (interquartile range = 13-41 days). Half of patients were previously on corticosteroid therapy. Twenty patients (71.4%) needed hospitalization, 18 received oxygen therapy (64.3%), 3 (10.7%) of them received high-flow nasal cannula with good tolerability, and 1 (3.6%) needed non-invasive ventilation. Hydroxychloroquine and antibiotics were given to 4 (14.3%) and 12 (42.9%) patients, respectively. Seven patients (25%) died at a median time of 5 days following COVID-19 diagnosis. CONCLUSION: This is one of the first studies reporting the adverse outcomes associated with COVID-19 in LC patients at same time that adds evidence regarding the need to create protocols and guidelines to reduce the infection risk in such patients.

Liquid Biopsy for Disease Monitoring in Non-Small Cell Lung Cancer: The Link between Biology and the Clinic.

INTRODUCTION: Cell-free DNA (cfDNA) analysis offers a non-invasive method to identify sensitising and resistance mutations in advanced Non-Small Cell Lung Cancer (NSCLC) patients. Next-generation sequencing (NGS) of circulating free DNA (cfDNA) is a valuable tool for mutations detection and disease's clonal monitoring. MATERIAL AND METHODS: An amplicon-based targeted gene NGS panel was used to analyse 101 plasma samples of advanced non-small cell lung cancer (NSCLC) patients with known oncogenic mutations, mostly EGFR mutations, serially collected at different clinically relevant time points of the disease. RESULTS: The variant allelic frequency (VAF) monitoring in consecutive plasma samples demonstrated different molecular response and progression patterns. The decrease in or the clearance of the mutant alleles was associated with response and the increase in or the emergence of novel alterations with progression. At the best response, the median VAF was 0% (0.0% to 3.62%), lower than that at baseline, with a median of 0.53% (0.0% to 9.9%) (p = 0.004). At progression, the VAF was significantly higher (median 4.67; range: 0.0-36.9%) than that observed at the best response (p = 0.001) and baseline (p = 0.006). These variations anticipated radiographic changes in most cases, with a median time of 0.86 months. Overall, the VAF evolution of different oncogenic mutations predicts clinical outcomes. CONCLUSION: The targeted NGS of circulating tumour DNA (ctDNA) has clinical utility to monitor treatment response in patients with advanced lung adenocarcinoma.

Sharing Biomedical Data: Strengthening AI Development in Healthcare.

Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive datasets and computational resources to create automatic tools for complex tasks that, until now, have been performed by humans. Massive data is a fundamental aspect of the most powerful AI-based algorithms. However, for AI-based healthcare solutions, there are several socioeconomic, technical/infrastructural, and most importantly, legal restrictions, which limit the large collection and access of biomedical data, especially medical imaging. To overcome this important limitation, several alternative solutions have been suggested, including transfer learning approaches, generation of artificial data, adoption of blockchain technology, and creation of an infrastructure composed of anonymous and abstract data. However, none of these strategies is currently able to completely solve this challenge. The need to build large datasets that can be used to develop healthcare solutions deserves special attention from the scientific community, clinicians, all the healthcare players, engineers, ethicists, legislators, and society in general. This paper offers an overview of the data limitation in medical predictive models; its impact on the development of healthcare solutions; benefits and barriers of sharing data; and finally, suggests future directions to overcome data limitations in the medical field and enable AI to enhance healthcare. This perspective is dedicated to the technical requirements of the learning models, and it explains the limitation that comes from poor and small datasets in the medical domain and the technical options that try or can solve the problem related to the lack of massive healthcare data.

Clinical Application of Next-Generation Sequencing of Plasma Cell-Free DNA for Genotyping Untreated Advanced Non-Small Cell Lung Cancer.

BACKGROUND: Analysis of circulating tumor DNA (ctDNA) has remarkable potential as a non-invasive lung cancer molecular diagnostic method. This prospective study addressed the clinical value of a targeted-gene amplicon-based plasma next-generation sequencing (NGS) assay to detect actionable mutations in ctDNA in patients with newly diagnosed advanced lung adenocarcinoma. METHODS: ctDNA test performance and concordance with tissue NGS were determined, and the correlation between ctDNA findings, clinical features, and clinical outcomes was evaluated in 115 patients with paired plasma and tissue samples. RESULTS: Targeted-gene NGS-based ctDNA and NGS-based tissue analysis detected 54 and 63 genomic alterations, respectively; 11 patients presented co-mutations, totalizing 66 hotspot mutations detected, 51 on both tissue and plasma, 12 exclusively on tissue, and 3 exclusively on plasma. NGS-based ctDNA revealed a diagnostic performance with 81.0% sensitivity, 95.3% specificity, 94.4% PPV, 83.6% NPV, test accuracy of 88.2%, and Cohen's Kappa 0.764. PFS and OS assessed by both assays did not significantly differ. Detection of ctDNA alterations was statistically associated with metastatic disease (p = 0.013), extra-thoracic metastasis (p = 0.004) and the number of organs involved (p = 0.010). CONCLUSIONS: This study highlights the potential use of ctDNA for mutation detection in newly diagnosed NSCLC patients due to its high accuracy and correlation with clinical outcomes.

Monitoring and Managing Lorlatinib Adverse Events in the Portuguese Clinical Setting: A Position Paper.

Rearrangements in the anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) genes characterise two distinct molecular subsets of non-small cell lung cancer (NSCLC) tumours. Lorlatinib is a third-generation ALK/ROS1 tyrosine kinase inhibitor (TKI) shown to have systemic and intracranial activity in treatment-naive patients and in those who progressed on first- and second-generation TKIs. Despite being generally well tolerated, lorlatinib has a unique and challenging safety profile that includes hyperlipidaemia and central and peripheral nervous system adverse events (AEs). This article summarises a set of strategies designed to monitor and manage lorlatinib-related AEs that were agreed upon by a multidisciplinary panel of specialists in a meeting held in July 2020. Among the recommendations hereby described, special emphasis was placed on communication: prescribing physicians should inform patients and their families/caregivers about the likelihood and nature of lorlatinib AEs, encouraging them to report any symptoms, while at the same time reassuring them that most events are manageable and resolve spontaneously and have little to no interference with cancer treatment. Importantly, all patients should undergo a set of baseline assessments, including biochemical analysis, evaluation of cardiovascular risk, electrocardiogram (ECG), neurological evaluation and contrast-enhanced magnetic resonance imaging of the brain, which should be repeated regularly during lorlatinib treatment. Supportive medications to treat or relieve lorlatinib AEs were also discussed, as were the conditions requiring specialist consultations and/or adjustments in lorlatinib therapy. The overall goal of this article is to serve as a practical guide for oncologists to systematically and effectively approach lorlatinib AEs.

Resistance Profile of Osimertinib in Pre-treated Patients With EGFR T790M-Mutated Non-small Cell Lung Cancer.

Background: Osimertinib efficacy in pre-treated patients with epidermal growth factor receptor (EGFR) T790M-mutated non-small cell lung cancer (NSCLC) has been demonstrated in clinical trials, but real-world data, particularly regarding resistance profile, remains limited. This study aims to analyze the resistance mechanisms acquired after treatment with Osimertinib. Methods: Clinical outcomes and molecular results from re-biopsies at the time of osimertinib progression of EGFR T790M-mutated NSCLC patient were analyzed. Results: Twenty-one patients with stage IV adenocarcinoma were included [median 69 years; 57.1% female; 85.7% never-smokers; 23.8% ECOG performance status (PS) ≥2]. Median PFS and OS were 13.4 (95% CI: 8.0-18.9) and 26.4 (95% IC: 8.9-43.8) months, respectively. At the time of analysis, 10 patients had tumor progression (47.6%). T790M loss occurred in 50%, being associated with earlier progression (median PFS 8.1 vs. 21.4 months, p = 0.011). Diverse molecular alterations were identified, including C797S mutation (n = 1), PIK3CA mutation (n = 2), MET amplification (n = 1), CTNNB1 mutation (n = 1), and DCTN1-ALK fusion (n = 1). Histological transformation into small cell carcinoma occurred in one patient. Conclusions: This real-world life study highlights the relevance of re-biopsy at the time of disease progression, contributing to understand resistance mechanisms and to guide treatment strategies.

The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer.

Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.

Impact of montelukast as add on treatment to the novel coronavirus pneumonia (COVID-19): protocol for an investigator-initiated open labeled randomized controlled pragmatic trial.

BACKGROUND: Montelukast, a safe drug widely use in asthmatic patients, may be an adjuvant in the treatment of Covid-19, either by improving lung injury and inflammation, or by acting as an anti-viral drug. We aim to assess the efficacy and safety of montelukast as add-on treatment in patients with Covid-19. METHODS: We propose a randomized, controlled, parallel, open-label trial involving 160 hospitalized adult patients with confirmed Covid-19. Patients will be randomly assigned in a 1:1 ratio to receive either montelukast 10 mg, once a day for 14 days, in addition to standard of care (SoC), or SoC alone. SoC will follow the best practice for treating these patients, according to updated recommendations. The primary outcome is time to recovery. Participants will be assessed using diary cards to capture data on treatment-related improvements in an 8-point ordinal scale. Secondary endpoints will include changes in respiratory and inflammatory parameters, and adverse events. This phase IV clinical trial will take place at the University Hospital of São João, Porto. EudraCT number: 2020-001747-21. RESULTS: This study intends to generate scientific evidence on efficacy and safety of montelukast as add-on treatment in Covid-19. The results will be essential to improve clinical outcomes which remains to be determined. CONCLUSION: Montelukast has been suggested as a potential drug with 2 main actions on Covid-19. The validation of montelukast as an adjuvant treatment may improve lung injury, inflammation, and symptoms leading to a better prognosis. The use of this drug may fulfil the existing gap on therapeutic options.

Modified Glasgow Prognostic Score predicts survival among advanced non-small cell lung carcinoma patients treated with anti-PD1 agents.

Immune checkpoint inhibitors were approved for advanced nonsmall cell lung cancer (NSCLC) treatment. Despite improved survival, not all patients benefit from these agents. Here, the prognostic impact of pretreatment modified Glasgow Prognostic Score (mGPS) and neutrophil-to-lymphocyte ratio (NLR) was assessed. From 77 patients included, 83.2% received at least one prior systemic therapy. Immune-related adverse events (irAE) occurred in 20 patients. A lower mGPS was associated with higher median overall survival (OS), and a lower Eastern Cooperative Oncology Group (ECOG), irAE and fewer metastatic sites with better survival. A trend towards greater OS and progression-free survival (PFS) was stated among patients with NLR <5. mGPS 0 was associated with better survival; ≥3 metastatic sites with worse PFS and OS; ECOG >2 with worse OS and irAE with better survival. Pretreatment mGPS seems to be useful for predicting survival among advanced NSCLC patients treated with anti-programmed cell death 1 drugs, with ECOG performance status, irAE occurrence, and number of metastatic sites acting as survival predictors.

Is an Early Diagnosis of COPD Clinically Useful? / ¿Es clínicamente útil un diagnóstico temprano de EPOC?

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Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS.

EGFR and KRAS are the most frequently mutated genes in lung cancer, being active research topics in targeted therapy. The biopsy is the traditional method to genetically characterise a tumour. However, it is a risky procedure, painful for the patient, and, occasionally, the tumour might be inaccessible. This work aims to study and debate the nature of the relationships between imaging phenotypes and lung cancer-related mutation status. Until now, the literature has failed to point to new research directions, mainly consisting of results-oriented works in a field where there is still not enough available data to train clinically viable models. We intend to open a discussion about critical points and to present new possibilities for future radiogenomics studies. We conducted high-dimensional data visualisation and developed classifiers, which allowed us to analyse the results for EGFR and KRAS biological markers according to different combinations of input features. We show that EGFR mutation status might be correlated to CT scans imaging phenotypes; however, the same does not seem to hold for KRAS mutation status. Also, the experiments suggest that the best way to approach this problem is by combining nodule-related features with features from other lung structures.