Machine Learning in Diagnosis and Prognosis of Lung Cancer by PET-CT

Lili Yuan,1,* Lin An,1,* Yandong Zhu,1 Chongling Duan,1 Weixiang Kong,1 Pei Jiang,2 Qing-Qing Yu1 1Jining NO.1 People’s Hospital, Shandong First Medical University, Jining, People’s Republic of China; 2Translational Pharmaceutical Laboratory, Jining NO.1 People’s Hospital, Shandong First Medical University, Jining, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qing-Qing Yu, Jining No.1 People’s Hospital, Shandong First Medical University, Jining, 272000, People’s Republic of China, Email [email protected] Pei Jiang, Translational Pharmaceutical Laboratory, Jining NO.1 People’s Hospital, Shandong First Medical University, Jining, 272000, People’s Republic of China, Email [email protected]: As a disease with high morbidity and high mortality, lung cancer has seriously harmed people’s health. Therefore, early diagnosis and treatment are more important. PET/CT is usually used to obtain the early diagnosis, staging, and curative effect evaluation of tumors, especially lung cancer, due to the heterogeneity of tumors and the differences in artificial image interpretation and other reasons, it also fails to entirely reflect the real situation of tumors. Artificial intelligence (AI) has been applied to all aspects of life. Machine learning (ML) is one of the important ways to realize AI. With the help of the ML method used by PET/CT imaging technology, there are many studies in the diagnosis and treatment of lung cancer. This article summarizes the application progress of ML based on PET/CT in lung cancer, in order to better serve the clinical. In this study, we searched PubMed using machine learning, lung cancer, and PET/CT as keywords to find relevant articles in the past 5 years or more. We found that PET/CT-based ML approaches have achieved significant results in the detection, delineation, classification of pathology, molecular subtyping, staging, and response assessment with survival and prognosis of lung cancer, which can provide clinicians a powerful tool to support and assist in critical daily clinical decisions. However, ML has some shortcomings such as slightly poor repeatability and reliability.Keywords: machine learning, computed tomography, lung cancer, artificial intelligence, diagnosi

How DNA Barcodes Complement Taxonomy and Explore Species Diversity: The Case Study of a Poorly Understood Marine Fauna

BACKGROUND: The species boundaries of some venerids are difficult to define based solely on morphological features due to their indistinct intra- and interspecific phenotypic variability. An unprecedented biodiversity crisis caused by human activities has emerged. Thus, to access the biological diversity and further the conservation of this taxonomically muddling bivalve group, a fast and simple approach that can efficiently examine species boundaries and highlight areas of unrecognized diversity is urgently needed. DNA barcoding has proved its effectiveness in high-volume species identification and discovery. In the present study, Chinese fauna was chosen to examine whether this molecular biomarker is sensitive enough for species delimitation, and how it complements taxonomy and explores species diversity. METHODOLOGY/PRINCIPAL FINDINGS: A total of 315 specimens from around 60 venerid species were included, qualifying the present study as the first major analysis of DNA barcoding for marine bivalves. Nearly all individuals identified to species level based on morphological traits possessed distinct barcode clusters, except for the specimens of one species pair. Among the 26 individuals that were not assigned binomial names a priori, twelve respectively nested within a species genealogy. The remaining individuals formed five monophyletic clusters that potentially represent species new to science or at least unreported in China. Five putative hidden species were also uncovered in traditional morphospecies. CONCLUSIONS/SIGNIFICANCE: The present study shows that DNA barcoding is effective in species delimitation and can aid taxonomists by indicating useful diagnostic morphological traits, informing needful revision, and flagging unseen species. Moreover, the BOLD system, which deposits barcodes, morphological, geographical and other data, has the potential as a convenient taxonomic platform

Quercetin and Allopurinol Ameliorate Kidney Injury in STZ-Treated Rats with Regulation of Renal NLRP3 Inflammasome Activation and Lipid Accumulation

Hyperuricemia, hyperlipidemia and inflammation are associated with diabetic nephropathy. The NLRP3 inflammasome-mediated inflammation is recently recognized in the development of kidney injury. Urate and lipid are considered as danger signals in the NLRP3 inflammasome activation. Although dietary flavonoid quercetin and allopurinol alleviate hyperuricemia, dyslipidmia and inflammation, their nephroprotective effects are currently unknown. In this study, we used streptozotocin (STZ)-induced diabetic nephropathy model with hyperuricemia and dyslipidemia in rats, and found over-expression of renal inflammasome components NLRP3, apoptosis-associated speck-like protein and Caspase-1, resulting in elevation of IL-1β and IL-18, with subsequently deteriorated renal injury. These findings demonstrated the possible association between renal NLRP3 inflammasome activation and lipid accumulation to superimpose causes of nephrotoxicity in STZ-treated rats. The treatment of quercetin and allopurinol regulated renal urate transport-related proteins to reduce hyperuricemia, and lipid metabolism-related genes to alleviate kidney lipid accumulation in STZ-treated rats. Furthermore, quercetin and allopurinol were found to suppress renal NLRP3 inflammasome activation, at least partly, via their anti-hyperuricemic and anti-dyslipidemic effects, resulting in the amelioration of STZ-induced the superimposed nephrotoxicity in rats. These results may provide a basis for the prevention of diabetes-associated nephrotoxicity with urate-lowering agents such as quercetin and allopurinol

Breast cancer epithelial-to-mesenchymal transition: examining the functional consequences of plasticity

The epithelial-to-mesenchymal transition (EMT) is a critical developmental process that has recently come to the forefront of cancer biology. In breast carcinomas, acquisition of a mesenchymal-like phenotype that is reminiscent of an EMT, termed oncogenic EMT, is associated with pro-metastatic properties, including increased motility, invasion, anoikis resistance, immunosuppression and cancer stem cell characteristics. This oncogenic EMT is a consequence of cellular plasticity, which allows for interconversion between epithelial and mesenchymal-like states, and is thought to enable tumor cells not only to escape from the primary tumor, but also to colonize a secondary site. Indeed, the plasticity of cancer cells may explain the range of pro-metastatic traits conferred by oncogenic EMT, such as the recently described link between EMT and cancer stem cells and/or therapeutic resistance. Continued research into this relationship will be critical in developing drugs that block mechanisms of breast cancer progression, ultimately improving patient outcomes

FOXP3 and FOXP3-regulated microRNAs suppress SATB1 in breast cancer cells

The transcription factor FOXP3 has been identified as a tumour suppressor in the breast and prostate epithelia, but little is known about its specific mechanism of action. We have identified a feed-forward regulatory loop in which FOXP3 suppresses the expression of the oncogene SATB1. In particular, we demonstrate that SATB1 is not only a direct target of FOXP3 repression, but that FOXP3 also induces two miRs, miR-7 and miR-155, which specifically target the 3′-UTR of SATB1 to further regulate its expression. We conclude that FOXP3-regulated miRs form part of the mechanism by which FOXP3 prevents the transformation of the healthy breast epithelium to a cancerous phenotype. Approaches aimed at restoring FOXP3 function and the miRs it regulates could help provide new approaches to target breast cancer.N McInnes, TJ Sadlon, CY Brown, S Pederson, M Beyer, JL Schultze, S McColl, GJ Goodall and SC Barr

Spontaneous Breathing in Early Acute Respiratory Distress Syndrome: Insights From the Large Observational Study to UNderstand the Global Impact of Severe Acute Respiratory FailurE Study

OBJECTIVES: To describe the characteristics and outcomes of patients with acute respiratory distress syndrome with or without spontaneous breathing and to investigate whether the effects of spontaneous breathing on outcome depend on acute respiratory distress syndrome severity. DESIGN: Planned secondary analysis of a prospective, observational, multicentre cohort study. SETTING: International sample of 459 ICUs from 50 countries. PATIENTS: Patients with acute respiratory distress syndrome and at least 2 days of invasive mechanical ventilation and available data for the mode of mechanical ventilation and respiratory rate for the 2 first days. INTERVENTIONS: Analysis of patients with and without spontaneous breathing, defined by the mode of mechanical ventilation and by actual respiratory rate compared with set respiratory rate during the first 48 hours of mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: Spontaneous breathing was present in 67% of patients with mild acute respiratory distress syndrome, 58% of patients with moderate acute respiratory distress syndrome, and 46% of patients with severe acute respiratory distress syndrome. Patients with spontaneous breathing were older and had lower acute respiratory distress syndrome severity, Sequential Organ Failure Assessment scores, ICU and hospital mortality, and were less likely to be diagnosed with acute respiratory distress syndrome by clinicians. In adjusted analysis, spontaneous breathing during the first 2 days was not associated with an effect on ICU or hospital mortality (33% vs 37%; odds ratio, 1.18 [0.92-1.51]; p = 0.19 and 37% vs 41%; odds ratio, 1.18 [0.93-1.50]; p = 0.196, respectively ). Spontaneous breathing was associated with increased ventilator-free days (13 [0-22] vs 8 [0-20]; p = 0.014) and shorter duration of ICU stay (11 [6-20] vs 12 [7-22]; p = 0.04). CONCLUSIONS: Spontaneous breathing is common in patients with acute respiratory distress syndrome during the first 48 hours of mechanical ventilation. Spontaneous breathing is not associated with worse outcomes and may hasten liberation from the ventilator and from ICU. Although these results support the use of spontaneous breathing in patients with acute respiratory distress syndrome independent of acute respiratory distress syndrome severity, the use of controlled ventilation indicates a bias toward use in patients with higher disease severity. In addition, because the lack of reliable data on inspiratory effort in our study, prospective studies incorporating the magnitude of inspiratory effort and adjusting for all potential severity confounders are required

Epidemiology and patterns of tracheostomy practice in patients with acute respiratory distress syndrome in ICUs across 50 countries

Background: To better understand the epidemiology and patterns of tracheostomy practice for patients with acute respiratory distress syndrome (ARDS), we investigated the current usage of tracheostomy in patients with ARDS recruited into the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG-SAFE) study. Methods: This is a secondary analysis of LUNG-SAFE, an international, multicenter, prospective cohort study of patients receiving invasive or noninvasive ventilation in 50 countries spanning 5 continents. The study was carried out over 4 weeks consecutively in the winter of 2014, and 459 ICUs participated. We evaluated the clinical characteristics, management and outcomes of patients that received tracheostomy, in the cohort of patients that developed ARDS on day 1-2 of acute hypoxemic respiratory failure, and in a subsequent propensity-matched cohort. Results: Of the 2377 patients with ARDS that fulfilled the inclusion criteria, 309 (13.0%) underwent tracheostomy during their ICU stay. Patients from high-income European countries (n = 198/1263) more frequently underwent tracheostomy compared to patients from non-European high-income countries (n = 63/649) or patients from middle-income countries (n = 48/465). Only 86/309 (27.8%) underwent tracheostomy on or before day 7, while the median timing of tracheostomy was 14 (Q1-Q3, 7-21) days after onset of ARDS. In the subsample matched by propensity score, ICU and hospital stay were longer in patients with tracheostomy. While patients with tracheostomy had the highest survival probability, there was no difference in 60-day or 90-day mortality in either the patient subgroup that survived for at least 5 days in ICU, or in the propensity-matched subsample. Conclusions: Most patients that receive tracheostomy do so after the first week of critical illness. Tracheostomy may prolong patient survival but does not reduce 60-day or 90-day mortality. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013

Identifying associations between diabetes and acute respiratory distress syndrome in patients with acute hypoxemic respiratory failure: an analysis of the LUNG SAFE database

Background: Diabetes mellitus is a common co-existing disease in the critically ill. Diabetes mellitus may reduce the risk of acute respiratory distress syndrome (ARDS), but data from previous studies are conflicting. The objective of this study was to evaluate associations between pre-existing diabetes mellitus and ARDS in critically ill patients with acute hypoxemic respiratory failure (AHRF). Methods: An ancillary analysis of a global, multi-centre prospective observational study (LUNG SAFE) was undertaken. LUNG SAFE evaluated all patients admitted to an intensive care unit (ICU) over a 4-week period, that required mechanical ventilation and met AHRF criteria. Patients who had their AHRF fully explained by cardiac failure were excluded. Important clinical characteristics were included in a stepwise selection approach (forward and backward selection combined with a significance level of 0.05) to identify a set of independent variables associated with having ARDS at any time, developing ARDS (defined as ARDS occurring after day 2 from meeting AHRF criteria) and with hospital mortality. Furthermore, propensity score analysis was undertaken to account for the differences in baseline characteristics between patients with and without diabetes mellitus, and the association between diabetes mellitus and outcomes of interest was assessed on matched samples. Results: Of the 4107 patients with AHRF included in this study, 3022 (73.6%) patients fulfilled ARDS criteria at admission or developed ARDS during their ICU stay. Diabetes mellitus was a pre-existing co-morbidity in 913 patients (22.2% of patients with AHRF). In multivariable analysis, there was no association between diabetes mellitus and having ARDS (OR 0.93 (0.78-1.11); p = 0.39), developing ARDS late (OR 0.79 (0.54-1.15); p = 0.22), or hospital mortality in patients with ARDS (1.15 (0.93-1.42); p = 0.19). In a matched sample of patients, there was no association between diabetes mellitus and outcomes of interest. Conclusions: In a large, global observational study of patients with AHRF, no association was found between diabetes mellitus and having ARDS, developing ARDS, or outcomes from ARDS. Trial registration: NCT02010073. Registered on 12 December 2013

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe