Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.

BACKGROUND: Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen. METHODS: Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set. RESULTS: The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95). CONCLUSIONS: We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.

Timely targeted testing for hereditary cancer syndromes - Importance of clinician-facilitated cascade testing in the first year post-diagnosis.

OBJECTIVE: Cascade testing for hereditary cancer syndromes allows relatives to estimate cancer risk and pursue prevention and early detection strategies. The current paradigm relies on patient coordinated care, resulting in only one-third of relatives successfully completing testing. Studies suggest that team-based approaches, where clinicians facilitate testing, can increase uptake. As institutions consider implementing such programs, understanding patient characteristics associated with interest is crucial for resource allocation. We aim to assess interest in clinician-facilitated testing and evaluate barriers. METHODS: Patients with cancer-associated pathogenic variants seen at a gynecologic oncology clinic were offered clinician-facilitated cascade testing. Patient interest and demographic variables were recorded and patients that declined were interviewed regarding the decision. RESULTS: From 11/2023-4/2024, 139 patients were offered clinician-facilitated cascade testing. Median patient age was 43 years (IQR 17), 97 (69.8 %) self-identified as White and 101 (72.7 %) as non-Hispanic. Fifty-six (40.3 %) patients harbored a BRCA1 pathogenic variant, 37 (26.6 %) BRCA2, and 46 (33.1 %) other cancer-associated genes. Fifty-seven (41.0 %) patients expressed interest in the intervention. Interested patients were more likely to have been diagnosed in the prior year vs. patients who were not interested on univariate (OR 4.6, 95 % CI 2.0-10.2, P = 0.0002) and multivariable analyses (adjusted OR 3.8, 95 % CI 1.622-9.009, P = 0.0022). CONCLUSIONS: Our study demonstrates that patients are almost five time more likely to be interested in cascade genetic testing within the first year of diagnosis of a pathogenic variant. Given the utility of such programs and their resource requirements, targeting this population could maximize effectiveness and uptake of cascade services.

Uptake of Cascade Genetic Testing for Hereditary Breast and Ovarian Cancer: A Systematic Review and Meta-Analysis.

This is a systematic review and meta-analysis evaluating the uptake of cascade genetic testing for hereditary breast and ovarian cancer syndrome. Among 30 studies included for meta-analysis, the uptake of cascade genetic testing was 33% (95% CI 25%-42%), with higher uptake rates among females compared with male relatives, and among first-degree compared with second-degree relatives. These findings indicate suboptimal uptake of cascade genetic testing among people at risk for hereditary breast and ovarian cancer syndrome, representing a missed opportunity for cancer prevention and early detection. There is a need for interventions to improve uptake rates.

Rapid Antigen and Antibody Microfluidic Immunofluorescence Assays Compared to Culture, PCR, and Laboratory Reference Tests: Performance in a Longitudinal Cohort.

We evaluated the performance of rapid antigen (RAg) and antibody (RAb) microfluidic diagnostics with serial sampling of 71 participants at 6 visits over 2 months following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Rapid tests showed strong agreement with laboratory references (κAg = 81.0%; κAb = 87.8%). RAg showed substantial concordance to both virus growth in culture and PCR positivity 0-5 days since symptom onset (κAg-culture = 60.1% and κAg-PCR = 87.1%). PCR concordance to virus growth in culture was similar (κPCR-culture = 70.0%), although agreement between RAg and culture was better overall (κAg-culture = 45.5% vs κPCR-culture = 10.0%). Rapid antigen and antibody testing by microfluidic immunofluorescence platform are highly accurate for characterization of acute infection.

Automated liquid handling robot for rapid lateral flow assay development.

The lateral flow assay (LFA) is one of the most popular technologies on the point-of-care diagnostics market due to its low cost and ease of use, with applications ranging from pregnancy to environmental toxins to infectious disease. While the use of these tests is relatively straightforward, significant development time and effort are required to create tests that are both sensitive and specific. Workflows to guide the LFA development process exist but moving from target selection to an LFA that is ready for field testing can be labor intensive, resource heavy, and time consuming. To reduce the cost and the duration of the LFA development process, we introduce a novel development platform centered on the flexibility, speed, and throughput of an automated robotic liquid handling system. The system comprises LFA-specific hardware and software that enable large optimization experiments with discrete and continuous variables such as antibody pair selection or reagent concentration. Initial validation of the platform was demonstrated during development of a malaria LFA but was readily expanded to encompass development of SARS-CoV-2 and Mycobacterium tuberculosis LFAs. The validity of the platform, where optimization experiments are run directly on LFAs rather than in solution, was based on a direct comparison between the robotic system and a more traditional ELISA-like method. By minimizing hands-on time, maximizing experiment size, and enabling improved reproducibility, the robotic system improved the quality and quantity of LFA assay development efforts.

Machine learning classification of disrotatory IRC and conrotatory non-IRC trajectory motion for cyclopropyl radical ring opening.

Quasiclassical trajectory analysis is now a standard tool to analyze non-minimum energy pathway motion of organic reactions. However, due to the large amount of information associated with trajectories, quantitative analysis of the dynamic origin of reaction selectivity is complex. For the electrocyclic ring opening of cyclopropyl radical, more than 4000 trajectories were run showing that allyl radicals are formed through a mixture of disrotatory intrinsic reaction coordinate (IRC) motion as well as conrotatory non-IRC motion. Geometric, vibrational mode, and atomic velocity transition-state features from these trajectories were used for supervised machine learning analysis with classification algorithms. Accuracy >80% with a random forest model enabled quantitative and qualitative assessment of transition-state trajectory features controlling disrotatory IRC versus conrotatory non-IRC motion. This analysis revealed that there are two key vibrational modes where their directional combination provides prediction of IRC versus non-IRC motion.

SARS-CoV-2 Coronavirus Nucleocapsid Antigen-Detecting Half-Strip Lateral Flow Assay Toward the Development of Point of Care Tests Using Commercially Available Reagents.

The SARS-CoV-2 pandemic has created an unprecedented need for rapid diagnostic testing to enable the efficient treatment and mitigation of COVID-19. The primary diagnostic tool currently employed is reverse transcription polymerase chain reaction (RT-PCR), which can have good sensitivity and excellent specificity. Unfortunately, implementation costs and logistical problems with reagents during the global SARS-CoV-2 pandemic have hindered its universal on demand adoption. Lateral flow assays (LFAs) represent a class of diagnostic that, if sufficiently clinically sensitive, may fill many of the gaps in the current RT-PCR testing regime, especially in low- and middle-income countries (LMICs). To date, many serology LFAs have been developed, though none meet the performance requirements necessary for diagnostic use cases, primarily due to the relatively long delay between infection and seroconversion. However, on the basis of previously reported results from SARS-CoV-1, antigen-based SARS-CoV-2 assays may have significantly better clinical sensitivity than serology assays. To date, only a very small number of antigen-detecting LFAs have been developed. Development of a half-strip LFA is a useful first step in the development of any LFA format. In this work, we present a half-strip LFA using commercially available antibodies for the detection of SARS-CoV-2. We have tested this LFA in buffer and measured an LOD of 0.65 ng/mL (95% CI of 0.53 to 0.77 ng/mL) ng/mL with recombinant antigen using an optical reader with sensitivity equivalent to a visual read. Further development, including evaluating the appropriate sample matrix, will be required for this assay approach to be made useful in a point of care setting, though this half-strip LFA may serve as a useful starting point for others developing similar tests.

Machine Learning Analysis of Direct Dynamics Trajectory Outcomes for Thermal Deazetization of 2,3-Diazabicyclo[2.2.1]hept-2-ene.

Experimentally, the thermal gas-phase deazetization of 2,3-diazabicyclo[2.2.1]hept-2-ene (1) results in the loss of N2 and the formation of bicyclo products 3 (exo) and 4 (endo) in a nonstatistical ratio, with preference for the exo product. Here, we report unrestricted M06-2X quasiclassical trajectories initialized from the concerted N2 ejection transition state that were able to replicate the experimental preference to form 3. We found that the 3:4 ratio results from the relative amounts of very fast (ballistic) exotype trajectories versus trajectories that lead to the 1,3-diradical intermediate 2. These quasiclassical trajectories provided a set of transition-state vibrational, velocity, momenta, and geometric features for the machine learning analysis. A selection of popular supervised classification algorithms (e.g., random forest) provided poor prediction of trajectory outcomes based on only transition-state vibrational quanta and energy features. However, these machine learning models provided more accurate predictions using atomic velocities and atomic positions, attaining ∼70% accuracy using initial conditions and between 85 and 95% accuracy at later reaction time steps. This increased accuracy allowed the feature importance analysis to reveal that, at the later-time analysis, the methylene bridge out-of-plane bending is correlated with trajectory outcomes for the formation of either the exo product or toward the diradical intermediate. Possible reasons for the struggle of machine learning algorithms to classify trajectories based on transition-state features is the heavily overlapping feature values, the finite but very large possible vibrational mode combinations, and the possibility of chaos as trajectories propagate. We examined this chaos by comparing a set of nearly identical trajectories that differed by only a very small scaling of the kinetic energies resulting from the transition-state reaction coordinate.

A Non-Canonical Calmodulin Target Motif Comprising a Polybasic Region and Lipidated Terminal Residue Regulates Localization.

Calmodulin (CaM) is a Ca2+-sensor that regulates a wide variety of target proteins, many of which interact through short basic helical motifs bearing two hydrophobic 'anchor' residues. CaM comprises two globular lobes, each containing a pair of EF-hand Ca2+-binding motifs that form a Ca2+-induced hydrophobic pocket that binds an anchor residue. A central flexible linker allows CaM to accommodate diverse targets. Several reported CaM interactors lack these anchors but contain Lys/Arg-rich polybasic sequences adjacent to a lipidated N- or C-terminus. Ca2+-CaM binds the myristoylated N-terminus of CAP23/NAP22 with intimate interactions between the lipid and a surface comprised of the hydrophobic pockets of both lobes, while the basic residues make electrostatic interactions with the negatively charged surface of CaM. Ca2+-CaM binds farnesylcysteine, derived from the farnesylated polybasic C-terminus of KRAS4b, with the lipid inserted into the C-terminal lobe hydrophobic pocket. CaM sequestration of the KRAS4b farnesyl moiety disrupts KRAS4b membrane association and downstream signaling. Phosphorylation of basic regions of N-/C-terminal lipidated CaM targets can reduce affinity for both CaM and the membrane. Since both N-terminal myristoylated and C-terminal prenylated proteins use a Singly Lipidated Polybasic Terminus (SLIPT) for CaM binding, we propose these polybasic lipopeptide elements comprise a non-canonical CaM-binding motif.

High-throughput screen, using time-resolved FRET, yields actin-binding compounds that modulate actin-myosin structure and function.

We have used a novel time-resolved FRET (TR-FRET) assay to detect small-molecule modulators of actin-myosin structure and function. Actin-myosin interactions play crucial roles in the generation of cellular force and movement. Numerous mutations and post-translational modifications of actin or myosin disrupt muscle function and cause life-threatening syndromes. Here, we used a FRET biosensor to identify modulators that bind to the actin-myosin interface and alter the structural dynamics of this complex. We attached a fluorescent donor to actin at Cys-374 and a nonfluorescent acceptor to a peptide containing the 12 N-terminal amino acids of the long isoform of skeletal muscle myosin's essential light chain. The binding site on actin of this acceptor-labeled peptide (ANT) overlaps with that of myosin, as indicated by (a) a similar distance observed in the actin-ANT complex as in the actin-myosin complex and (b) a significant decrease in actin-ANT FRET upon binding myosin. A high-throughput FRET screen of a small-molecule library (NCC, 727 compounds), using a unique fluorescence lifetime readout with unprecedented speed and precision, showed that FRET is significantly affected by 10 compounds in the micromolar range. Most of these "hits" alter actin-activated myosin ATPase and affect the microsecond dynamics of actin detected by transient phosphorescence anisotropy. We conclude that the actin-ANT TR-FRET assay enables detection of pharmacologically active compounds that affect actin structural dynamics and actomyosin function. This assay establishes feasibility for the discovery of allosteric modulators of the actin-myosin interaction, with the ultimate goal of developing therapies for muscle disorders.

Implementation research on community health workers' provision of maternal and child health services in rural Liberia.

OBJECTIVE: To assess changes in the use of essential maternal and child health services in Konobo, Liberia, after implementation of an enhanced community health worker (CHW) programme. METHODS: The Liberian Ministry of Health partnered with Last Mile Health, a nongovernmental organization, to implement a pilot CHW programme with enhanced recruitment, training, supervision and compensation. To assess changes in maternal and child health-care use, we conducted repeated cross-sectional cluster surveys before (2012) and after (2015) programme implementation. FINDINGS: Between 2012 and 2015, 54 CHWs, seven peer supervisors and three clinical supervisors were trained to serve a population of 12 127 people in 44 communities. The regression-adjusted percentage of children receiving care from formal care providers increased by 60.1 (95% confidence interval, CI: 51.6 to 68.7) percentage points for diarrhoea, by 30.6 (95% CI: 20.5 to 40.7) for fever and by 51.2 (95% CI: 37.9 to 64.5) for acute respiratory infection. Facility-based delivery increased by 28.2 points (95% CI: 20.3 to 36.1). Facility-based delivery and formal sector care for acute respiratory infection and diarrhoea increased more in agricultural than gold-mining communities. Receipt of one-or-more antenatal care sessions at a health facility and postnatal care within 24 hours of delivery did not change significantly. CONCLUSION: We identified significant increases in uptake of child and maternal health-care services from formal providers during the pilot CHW programme in remote rural Liberia. Clinic-based services, such as postnatal care, and services in specific settings, such as mining areas, require additional interventions to achieve optimal outcomes.

Highly Sensitive Two-Dimensional Paper Network Incorporating Biotin-Streptavidin for the Detection of Malaria.

Recently, two-dimensional paper networks have been developed to enable multistep assays to be performed in a lateral flow format. These devices have been used to perform simple enzyme linked immunoassays on paper. However, these devices have yet to incorporate more complex immunoassays, including the use of streptavidin-biotin detection strategies. Here we present a modified two-dimensional paper network capable of consecutively delivering six reagents. The device requires only a single user step and delivers (i) the sample, (ii) the biotinylated detection antibody, (iii) streptavidin horseradish peroxidase, (iv) a wash buffer, (v) a colorimetric substrate, and (vi) a final wash buffer. To demonstrate the utility of this approach we designed an assay to detect the malaria protein Pf HRP2. Using this platform, we were able to achieve a limit-of-detection equivalent to that of a traditional 96-well plate sandwich ELISA. In addition to improvements in the limit-of-detection, the inclusion of streptavidin-biotin simplifies the development of similar tests for other targets.

Protocol for Health Risk Information Technology-Assisted Genetic Evaluation (HeRITAGE): a randomised controlled trial of digital genetic cancer risk assessment in a diverse underserved gynaecology clinic.

INTRODUCTION: In the USA, up to 95% of individuals harbouring cancer-predisposing germline pathogenic variants have not been identified despite recommendations for screening at the primary care level. METHODS AND ANALYSIS: Our primary objective is to use a two-arm, single-institution randomised controlled trial to compare the proportion of eligible patients that are recommended genetic testing for hereditary cancer syndromes using a digital tool versus clinician interview for genetic cancer risk assessment in an urban academic gynaecology clinic. New gynaecology patients will be consented and randomised 1:1 to either the intervention arm, in which a digital tool is used for genetic cancer risk assessment, or usual care, in which the clinician performs genetic cancer risk assessment. Individuals will be considered eligible for hereditary cancer syndrome genetic testing if criteria set forth by the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology are met. Eligible patients are 18 years or older, speak and read English, have not yet undergone hereditary cancer genetic testing and have access to a smartphone. The study aims to enrol 50 patients in each arm to allow for 80% power with two-tailed alpha of 5% to detect a 20% difference in proportion of eligible patients recommended for genetic testing. The primary outcome is the proportion of eligible individuals recommended genetic testing in the digital tool arm versus usual care arm, analysed using the χ2 or Fisher's exact test as appropriate for sample size. The secondary outcome is completion of genetic testing, as well as exploration of patient factors, particularly social determinants of health, which may affect the receipt, utilisation and experience with genetic services. ETHICS AND DISSEMINATION: This study has been approved by the Weill Cornell Institutional Review Board (Protocol No. 21-11024123). Participants will be informed of the benefits and risks of participation prior to consent. Dissemination of data will be deidentified and conducted through academic conferences and journals. Patients identified to be eligible for genetic testing who did not receive counselling from their providers will be contacted; participants will not receive direct notification of trial results. REGISTRATION DETAILS: This trial is registered at clinicaltrials.gov (NCT05562778) in September 2022. PROTOCOL VERSION: This is protocol version 1, as of 22 May 2024. COUNTRIES OF RECRUITMENT AND RECRUITMENT STATUS: USA, currently recruiting. HEALTH CONDITIONS/PROBLEMS STUDIED: Genetic predisposition to cancers such as breast, ovarian, uterine and pancreatic. DEIDENTIFIED INDIVIDUAL CLINICAL TRIAL PARTICIPANT-LEVEL DATA IDP SHARING STATEMENT: IDP will not be shared. TRIAL REGISTRATION NUMBER: NCT05562778.

Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality Improvement.

PURPOSE: Lung cancer screening programs generate a high volume of low-dose computed tomography (LDCT) reports that contain valuable information, typically in a free-text format. High-performance named-entity recognition (NER) models can extract relevant information from these reports automatically for inter-radiologist quality control. METHODS: Using LDCT report data from a longitudinal lung cancer screening program (8,305 reports; 3,124 participants; 2006-2019), we trained a rule-based model and two bidirectional long short-term memory (Bi-LSTM) NER neural network models to detect clinically relevant information from LDCT reports. Model performance was tested using F1 scores and compared with a published open-source radiology NER model (Stanza) in an independent evaluation set of 150 reports. The top performing model was applied to a data set of 6,948 reports for an inter-radiologist quality control assessment. RESULTS: The best performing model, a Bi-LSTM NER recurrent neural network model, had an overall F1 score of 0.950, which outperformed Stanza (F1 score = 0.872) and a rule-based NER model (F1 score = 0.809). Recall (sensitivity) for the best Bi-LSTM model ranged from 0.916 to 0.991 for different entity types; precision (positive predictive value) ranged from 0.892 to 0.997. Test performance remained stable across time periods. There was an average of a 2.86-fold difference in the number of identified entities between the most and the least detailed radiologists. CONCLUSION: We built an open-source Bi-LSTM NER model that outperformed other open-source or rule-based radiology NER models. This model can efficiently extract clinically relevant information from lung cancer screening computerized tomography reports with high accuracy, enabling efficient audit and feedback to improve quality of patient care.

Real-World Treatment Sequencing, Toxicities, Health Utilities, and Survival Outcomes in Patients with Advanced ALK-Rearranged Non-Small-Cell Lung Cancer.

OBJECTIVES: This real-world analysis describes treatment patterns, sequencing and clinical effectiveness, toxicities, and health utility outcomes in advanced-stage, incurable ALK-positive NSCLC patients across five different ALK-TKIs. MATERIALS AND METHODS: Clinicodemographic, treatment, and toxicity data were collected retrospectively in patients with advanced-stage ALK-positive NSCLC at Princess Margaret Cancer Centre. Patient-reported symptoms, toxicities, and health utilities were collected prospectively. RESULTS: Of 148 ALK-positive NSCLC patients seen July 2009-May 2021, median age was 58.9 years; 84 (57%) were female; 112 (76%) never-smokers; 54 (47%) Asian and 40 (35%) white; 139 (94%) received at least one ALK-TKI: crizotinib (n = 74; 54%) and alectinib (n = 61; 44%) were administered mainly as first-line ALK-TKI, ceritinib, brigatinib and lorlatinib were administered primarily after previous ALK-TKI failure. Median overall survival (OS) was 54.0 months; 31 (21%) patients died within two years of advanced-stage diagnosis. Treatment modifications were observed in 35 (47%) patients with crizotinib, 19 (61%) with ceritinib, 41 (39%) with alectinib, 9 (41%) with brigatinib and 8 (30%) with lorlatinib. Prevalence of dose modifications and self-reported toxicities were higher with early versus later generation ALK-TKIs (P<.05). The presence of early treatment modification was not negatively associated with progression-free survival (PFS) and OS analyses. CONCLUSION: Serial ALK-TKI sequencing approaches are viable therapeutic options that can extend quality of life and quantity-of-life, though a fifth of patients died within two years. No best single sequencing approach could be determined. Clinically relevant toxicities occurred across all ALK-TKIs. Treatment modifications due to toxicity may not necessarily compromise outcomes, allowing multiple approaches to deal with ALK-TKI toxicities.

Duration of viral infectiousness and correlation with symptoms and diagnostic testing in non-hospitalized adults during acute SARS-CoV-2 infection: A longitudinal cohort study.

BACKGROUND: Guidelines for SARS-CoV-2 have relied on limited data on duration of viral infectiousness and correlation with COVID-19 symptoms and diagnostic testing. METHODS: We enrolled ambulatory adults with acute SARS-CoV-2 infection and performed serial measurements of COVID-19 symptoms, nasal swab viral RNA, nucleocapsid (N) and spike (S) antigens, and replication-competent SARS-CoV-2 by viral growth in culture. We determined average time from symptom onset to a first negative test result and estimated risk of infectiousness, as defined by positive viral growth in culture. RESULTS: Among 95 adults, median [interquartile range] time from symptom onset to first negative test result was 9 [5] days, 13 [6] days, 11 [4] days, and >19 days for S antigen, N antigen, culture growth, and viral RNA by RT-PCR, respectively. Beyond two weeks, virus growth and N antigen titers were rarely positive, while viral RNA remained detectable among half (26/51) of participants tested 21-30 days after symptom onset. Between 6-10 days from symptom onset, N antigen was strongly associated with culture positivity (relative risk=7.61, 95% CI: 3.01-19.22), whereas neither viral RNA nor symptoms were associated with culture positivity. During the 14 days following symptom onset, the presence of N antigen remained strongly associated (adjusted relative risk=7.66, 95% CI: 3.96-14.82) with culture positivity, regardless of COVID-19 symptoms. CONCLUSIONS: Most adults have replication-competent SARS-CoV-2 for 10-14 after symptom onset. N antigen testing is a strong predictor of viral infectiousness and may be a more suitable biomarker, rather than absence of symptoms or viral RNA, to discontinue isolation within two weeks from symptom onset.

Circulating proteome for pulmonary nodule malignancy.

BACKGROUND: Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules. METHODS: Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated. RESULTS: We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001). CONCLUSIONS: Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Synthesis, electropolymerization and functionalization via click chemistry of N-alkynylated dithieno[3,2-b:2',3'-d]pyrrole.

A new N-alkynylated dithieno[3,2-b:2',3'-d]pyrrole (DTP) monomer was synthesized using a Buchwald-Hartwig amination of 3,3'-dibromo-2,2'-bithiophene with pent-4-yn-1-amine. The obtained monomer was investigated for the possibility of a pre-polymerization modification via Huisgen 1,3-dipolar cycloaddition ("click") reaction with azide-containing organic compounds. The synthesized N-alkynylated DTP monomer is soluble in a number of organic solvents and reacts with organic azides via "click" reactions in mild conditions, achieving high yields. The N-alkynylated DTP monomer and its "click"-modified derivative can be electropolymerized to form polymeric films. Herein, the synthesis and characterization of a "click" modified DTP monomer, its pre-modified derivative, and their corresponding polymers are described. The developed method is a facile route to synthesize a new generation of various N-functionalized DTP homopolymers.

EGFR mutation prevalence, real-world treatment patterns, and outcomes among patients with resected, early-stage, non-small cell lung cancer in Canada.

OBJECTIVES: The ADAURA trial demonstrated the benefit of adjuvant osimertinib among patients with resected, early-stage, epidermal growth factor receptor-mutated (EGFRm) non-small cell lung cancer (NSCLC). To understand the potential population impact, it is critical to deduce the prevalence, management, and outcomes of this patient population in the real-world setting before use of adjuvant osimertinib. MATERIALS AND METHODS: Using PALEOS (Pan-cAnadian Lung cancEr Observational Study) data (2012-2019), a retrospective, multi-center, observational cohort study was conducted among patients with early-stage (IB-IIIA) resected NSCLC who had not received neoadjuvant therapy. Study outcomes included EGFRm prevalence, treatment patterns, recurrence outcomes, and overall and disease-free survival (OS/DFS). RESULTS: Among patients undergoing reflexive EGFRm testing by a pathologist at time of diagnosis irrespective of disease stage (N = 535), 23 % were EGFRm-positive; 15.9 % had common mutations and 5.6 % had uncommon mutations. Within the EGFRm-positive cohort (N = 156), mean age at diagnosis was 68 years, 65 % of patients were female, and 35 % were of Asian descent. At diagnosis, 48 %, 31 %, and 21 % had stage IB, II, or IIIA disease, respectively; 46 % received adjuvant therapy after resection. Half of patients experienced disease recurrence, typically involving distant sites; central nervous system metastasis varied from 12 % to 15.0 % across disease stages. EGFR tyrosine kinase inhibitors were the most commonly received therapy after first metastatic recurrence. Median OS (DFS) was not reached, 71.2 (22.8) months, and 50.1 (18.0) months among stage IB, II, and IIIA patients. Patients with uncommon EGFRm had a lower probability of survival than those with common EGFRm (2 years: 87 % vs 91 %-94 %; 4 years: 56 % vs 73 %-82 %). CONCLUSION: Approximately-one-quarter of patients with resected, early-stage NSCLC were EGFRm-positive in this study. These patients had high recurrence rates and suboptimal long-term survival after treatment with current therapies. New adjuvant treatments are warranted.