Assessment of Integrated Classifier's Ability to Distinguish Benign From Malignant Lung Nodules: Extended Analyses and 2-Year Follow-Up Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) Trial

Protein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment

Lung cancer remains the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and the presence of metastases. Several countries around the world have adopted nation-wide LDCT-based lung cancer screening that will benefit patients, shifting the stage at diagnosis to earlier stages with more therapeutic options. Biomarkers can help to optimize the screening process, as well as refine the TNM stratification of lung cancer patients, providing information regarding prognostics and recommending management strategies. Moreover, novel adjuvant strategies will clearly benefit from previous knowledge of the potential aggressiveness and biological traits of a given early-stage surgically resected tumor. This review focuses on proteins as promising biomarkers in the context of lung cancer screening. Despite great efforts, there are still no successful examples of biomarkers in lung cancer that have reached the clinics to be used in early detection and early management. Thus, the field of biomarkers in early lung cancer remains an evident unmet need. A more specific objective of this review is to present an up-to-date technical assessment of the potential use of protein biomarkers in early lung cancer detection and management. We provide an overview regarding the benefits, challenges, pitfalls and constraints in the development process of protein-based biomarkers. Additionally, we examine how a number of emerging protein analytical technologies may contribute to the optimization of novel robust biomarkers for screening and effective management of lung cancer.

Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules

Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.

Assessing a biomarker's ability to reduce invasive procedures in patients with benign lung nodules: Results from the ORACLE study

A blood-based integrated classifier (IC) has been clinically validated to improve accuracy in assessing probability of cancer risk (pCA) for pulmonary nodules (PN). This study evaluated the clinical utility of this biomarker for its ability to reduce invasive procedures in patients with pre-test pCA ≤ 50%. This was a propensity score matching (PSM) cohort study comparing patients in the ORACLE prospective, multicenter, observational registry to control patients treated with usual care. This study enrolled patients meeting the intended use criteria for IC testing: pCA ≤ 50%, age ≥40 years, nodule diameter 8-30 mm, and no history of lung cancer and/or active cancer (except for non-melanomatous skin cancer) within 5 years. The primary aim of this study was to evaluate invasive procedure use on benign PNs of registry patients as compared to control patients. A total of 280 IC tested, and 278 control patients met eligibility and analysis criteria and 197 were in each group after PSM (IC and control groups). Patients in the IC group were 74% less likely to undergo an invasive procedure as compared to the control group (absolute difference 14%, p <0.001) indicating that for every 7 patients tested, one unnecessary invasive procedure was avoided. Invasive procedure reduction corresponded to a reduction in risk classification, with 71 patients (36%) in the IC group classified as low risk (pCA < 5%). The proportion of IC group patients with malignant PNs sent to surveillance were not statistically different than the control group, 7.5% vs 3.5% for the IC vs. control groups, respectively (absolute difference 3.91%, p 0.075). The IC for patients with a newly discovered PN has demonstrated valuable clinical utility in a real-world setting. Use of this biomarker can change physicians' practice and reduce invasive procedures in patients with benign pulmonary nodules. Trial registration: Clinical trial registration: ClinicalTrials.gov NCT03766958.

Simultaneous Detection of Tumor Derived Exosomal Protein-MicroRNA Pairs with an Exo-PROS Biosensor for Cancer Diagnosis

Tumor derived exosomes (TEXs) have emerged as promising biomarkers for cancer liquid biopsy. Conventional methods (such as ELISA and qRT-PCR) and emerging biosensing technologies mainly detect a single type of exosomal biomarker due to the distinct properties of different biomolecules. Sensitive detection of two different types of TEX biomarkers, i.e., protein and microRNA combined biomarkers, may greatly improve cancer diagnostic accuracy. We developed an exosome protein microRNA one-stop (Exo-PROS) biosensor that not only selectively captured TEXs but also enabled in situ, simultaneous detection of TEX protein-microRNA pairs via a surface plasmon resonance mechanism. Exo-PROS assay is a fast, reliable, low sample consumption, and user-friendly test. With a total of 175 cancer patients and normal controls, we demonstrated that TEX protein-microRNA pairs measured by Exo-PROS assay detected lung cancer and breast cancer with 99% and 96% accuracy, respectively. Exo-PROS assay also showed superior diagnostic performance to conventional ELISA and qRT-PCR methods. Our results demonstrated that Exo-PROS assay is a potent liquid biopsy assay for cancer diagnosis.

Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning

BACKGROUND

Low-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases.

METHODS

Single cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer.

RESULTS

Automated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83-0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were < 20 mm (AUC of 0.94; 95% CI 0.89-0.99). Testing of the model on an independent second set of samples showed an AUC of 0.85 (95% CI 0.71-0.98) with an 83% sensitivity, 77% specificity, 95% negative predictive value and 45% positive predictive value. The model is robust to differences in sample processing and disease state.

CONCLUSION

CyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules < 20 mm in diameter. This test is intended for use after lung cancer screening to improve early-stage lung cancer diagnosis. Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018.

Role of biomarkers in lung nodule evaluation

PURPOSE OF REVIEW

Worldwide, lung cancer is the leading cause of cancer mortality. Much of this mortality is thought to be secondary to detection in later stages, where treatment options and survivability are limited. The goals of lung nodule evaluation are to expedite the diagnosis and treatment of patients with malignant nodules and to minimize unnecessary diagnostic procedures in those with benign nodules. However, the differentiation between benign and malignant has been challenging and is further complicated by the benefits of early diagnosis competing with potential morbidity of invasive diagnostic procedures.

RECENT FINDINGS

Biomarkers have the potential to improve estimates of pretest probability of malignancy in pulmonary nodules, especially in the intermediate-risk subgroup. Four biomarkers have undergone extensive validation and are available for clinical use, and we will discuss each in this review.

SUMMARY

The application of biomarkers to lung cancer risk assessment has the potential to improve cancer probability assessments, which in turn can reduce unnecessary invasive testing and/or reduce delays in diagnosis and treatment.

ATS Core Curriculum 2021. Adult Pulmonary Medicine: Thoracic Oncology

The American Thoracic Society Core Curriculum updates clinicians annually in adult and pediatric pulmonary disease, medical critical care, and sleep medicine at the annual international conference. The 2021 Pulmonary Core Curriculum focuses on lung cancer and include risks and prevention, screening, nodules, therapeutics and associated pulmonary toxicities, and malignant pleural effusions. Although tobacco smoking remains the primary risk factor for developing lung cancer, exposure to other environmental and occupational substances, including asbestos, radon, and burned biomass, contribute to the global burden of disease. Randomized studies have demonstrated that routine screening of high-risk smokers with low-dose chest computed tomography results in detection at an earlier stage and reduction in lung cancer mortality. On the basis of these trials and other lung cancer risk tools, screening recommendations have been developed. When evaluating lung nodules, clinical and radiographic features are used to estimate the probability of cancer. Management guidelines take into account the nodule size and cancer risk estimates to provide recommendations at evaluation. Newer lung cancer therapies, including immune checkpoint inhibitors and molecular therapies, cause pulmonary toxicity more frequently than conventional chemotherapy. Treatment-related toxicity should be suspected in patients receiving these medications who present with respiratory symptoms. Evaluation is aimed at excluding other etiologies, and treatment is based on the severity of symptoms. Malignant pleural effusions can be debilitating. The diagnosis is made by using simple pleural drainage and/or pleural biopsies. Management depends on the clinical scenario and the patient's preferences and includes the use of serial thoracentesis, a tunneled pleural catheter, or pleurodesis.