A multi-analyte serum test for the detection of non-small cell lung cancer

Cytokine and soluble programmed death-ligand 1 levels in serum and plasma of cancer patients treated with immunotherapy: Preanalytical and analytical considerations

AIM

To evaluate cytokine and soluble programmed death ligand-1 (sPD-L1) levels in the serum and plasma of cancer patients treated with immunotherapy, and to test different assays.

METHODS

Three Luminex xMAP assays and two ELLA microfluidic cartridges were used to screen 28 immune-related biomarkers in 38 paired serum and citrate-theophylline-adenosine-dipyridamole (CTAD) plasma samples collected from 10 advanced melanoma or non-small cell lung cancer (NSCLC) patients at different time points during immunotherapy.

RESULTS

Twenty-three of 28 biomarkers were detected both in serum and plasma by at least one of the assays, including IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, GM-CSF, IFN-γ, TNF-α, VEGF, IP-10, MCP-1, eotaxin, fractalkine, G-CSF, IFN-α, IL-1RA, IL-13, IL-17A, MIP-1β and sPD-L1. Conversely, FGF-2 and IL-1α were not detected in both matrices; GRO-α factor and EGF were detected only in serum and MIP-1α only in plasma. sPD-L1, MCP-1, IFN-γ, IL-8, MIP-1β and VEGF were, respectively, 1.15-, 1.44-, 1.83-, 2.43-, 2.82-, 6.72-fold higher in serum, whereas IL-10, IL-4, IL-2 and IL-5 were 1.05-, 1.19-, 1.92- and 2.17-fold higher, respectively, in plasma. IP-10 levels were higher in plasma but, as well as for VEGF, the bias serum versus plasma varied depending on the assay used (IP-10: -5.7% to -145%; VEGF: 115% to 165%). No significant differences were found for the remaining nine analyzed cytokines.

CONCLUSION

The cytokine and sPD-L1 levels may differ between serum and plasma samples collected from cancer patients treated with immunotherapy, and the results obtained can be influenced by the different characteristics of the tested assays. The standardization of pre-analytical and analytical procedures is therefore needed for the future implementation of these circulating biomarkers in clinical practice.

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

Temporal and Spatial Patterns of Inflammation and Tissue Injury in Patients with Postoperative Respiratory Failure after Lung Resection Surgery: A Nested Case-Control Study

Thoracic surgeries involving resection of lung tissue pose a risk of severe postoperative pulmonary complications, including acute respiratory distress syndrome (ARDS) and respiratory failure. Lung resections require one-lung ventilation (OLV) and, thus, are at higher risk of ventilator-induced lung injury (VILI) attributable to barotrauma and volutrauma in the one ventilated lung, as well as hypoxemia and reperfusion injury on the operated lung. Further, we also aimed to assess the differences in localized and systemic markers of tissue injury/inflammation in those who developed respiratory failure after lung surgery versus matched controls who did not develop respiratory failure. We aimed to assess the different inflammatory/injury marker patterns induced in the operated and ventilated lung and how this compared to the systemic circulating inflammatory/injury marker pattern. A case-control study nested within a prospective cohort study was performed. Patients with postoperative respiratory failure after lung surgery (n = 5) were matched with control patients (n = 6) who did not develop postoperative respiratory failure. Biospecimens (arterial plasma, bronchoalveolar lavage separately from ventilated and operated lungs) were obtained from patients undergoing lung surgery at two timepoints: (1) just prior to initiation of OLV and (2) after lung resection was completed and OLV stopped. Multiplex electrochemiluminescent immunoassays were performed for these biospecimen. We quantified 50 protein biomarkers of inflammation and tissue injury and identified significant differences between those who did and did not develop postoperative respiratory failure. The three biospecimen types also display unique biomarker patterns.

EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation

BACKGROUND

EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models.

OBJECTIVES

The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis.

DATA SOURCES

MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021.

REVIEW METHODS

A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed.

RESULTS

A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse.

LIMITATIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses.

CONCLUSIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value.

FUTURE WORK

Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42021242248.

FUNDING

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.

Increased sTREM-1 levels identify cirrhotic patients with bacterial infection and predict their 90-day mortality

BACKGROUND AND AIMS

Patients with cirrhosis are susceptible to bacterial infections (BIs) that are major causes of specific complications and mortality. However, the diagnosis of BIs can often be difficult in advanced disease stage since their symptoms may overlap with the ones of acute decompensation (AD). Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is released from monocytes/macrophages and neutrophils during activation and has been reported to correlate with activity of various inflammatory processes. We investigated its diagnostic and prognostic performance in patients with cirrhosis and BI.

METHODS

Sera of 269 patients were assayed for sTREM-1 by ELISA (172 outpatients and 97 patients with AD of whom 56 had BI). We investigated capacity of sTREM-1 to identify patients with BI and conducted a 90-day follow-up observational study to assess its possible association with short-term mortality.

RESULTS

sTREM-1 levels were significantly higher in patients with more severe liver disease, BI, and acute-on-chronic liver failure than in patients without these conditions. sTREM-1 had similar accuracy to CRP identifying BI [sTREM-1: AUROC (95%CI) 0.804 (0.711-0.897), p < 0.0001; CRP: 0.791 (0.702-0.881), p < 0.0001)] among AD patients. The combination of these two molecules and the presence of ascites into a composite score significantly increased their discriminative power (AUROC: 0.878, 95%CI: 0.812-0.944, p < 0.0001). High sTREM-1 level (>660 pg/mL) was an independent predictor of 90-day mortality in patients with BI [HR: 2.941, (95%CI: 1.009-8.573), p = 0.048] in our multivariate model.

CONCLUSIONS

Use of sTREM-1 could increase the recognition of BIs in cirrhosis and help clinicians in mortality risk assessment of these patients.

Relationship between circulating tumor-associated autoantibodies and clinical outcomes in advanced-stage NSCLC patients receiving PD-1/-L1 directed immune checkpoint inhibition

BACKGROUND

Durable tumor regressions are observed in a subset of advanced-stage non-small cell lung cancer (NSCLC) patients receiving PD-1/-L1 targeted immune checkpoint inhibitors (or 'immunotherapy') alone or in combination with chemotherapy. However, the majority of advanced NSCLC patients receiving these agents do not experience long-term disease control. Existing methods to identify patients most likely to gain clinical benefit from PD-1/-L1 immunotherapy have limitations, creating a need for improved methods to guide treatment selection, particularly for those likely to benefit from single-agent immunotherapy. Here, we describe the development of a series of novel assays for tumor-associated autoantibodies as part of an exploratory study intended to determine if these biomarkers have potential prognostic value in this setting.

METHOD

A selection of recombinant tumor autoantigens previously characterized for their diagnostic utility were developed and preliminarily evaluated by this study. These include: Fumarate Dehydrogenase (FH), Hydroxysteroid 17-Beta Dehydrogenase 10 (HSD17B10), Inosine Monophosphate Dehydrogenase 2 (IMPDH2), New York Esophageal Squamous Cell Carcinoma-1 (NY ESO-1), Phosphoglycerate Mutase 1 (PGAM1), and Vimentin. Custom Luminex immunobead assays were developed for these targets to quantitatively assess autoantibody levels in individual patient sera. Assays were erected as indirect immunoassays on MagPlex® Microspheres using standard carbodiimide/NHS-based chemistries, utilizing a biotin-conjugated secondary (i.e. anti-human IgG) antibody and R-phycoerythrin-conjugated streptavidin reporter system. Standard curves were created for quantitative purposes using commercially-available anti-antigen antibodies and permitted analytical performance characteristics to be calculated. These assays were used to preliminarily evaluate a series of pretreatment serum samples from stage IV NSCLC patients receiving anti PD-1/-L1 therapy after failure of at least one prior line of therapy (n = 40) and their classification efficiency calculated based on 12 months overall survival (OS) threshold.

RESULTS

Six assays were developed that each showed dynamic ranges of four orders of magnitude and provided more than 90% classification accuracy based on the observed clinical outcome data. Inter- and intra-assay precision was assessed within these standards and overall %CVs of ≤7% and ≤ 10%, respectively, were calculated. Generally, the baseline level of autoantibodies were significantly (p < 0.05) lower in the ≥12 months survival group relative to the <12 months survival groups. Serum titers of FH, HSD170B, NY-ESO-1, and vimentin were significantly correlated with ≥12 month survival (p-value 0.0038, 0.0061, 0.0073, and 0.022, respectively). IMPDH2 and PGAM1 were found to have marginal significance (p-value 0.08 and 0.076, respectively).

CONCLUSION

This study demonstrates an efficient and promising means for assessing circulating autoantibody titers that could be useful in selecting advanced NSCLC patients for PD-1/-L1 directed immunotherapy. Further exploration and validation of this paradigm is warranted to further refine current treatment selection methods for this therapeutic strategy.

Elevated serum lipid level can serve as early signal for metastasis for Non-Small Cell Lung Cancer patients: A retrospective nested case-control study

Objective: To investigate the association between serum lipid levels in patients with primary non-small cell lung cancer and the risk of developing metastases, a retrospective cohort-based nested case-control study was conducted. Material and method: Patients with primary non-small cell lung cancer admitted to the First and the Third Hospitals of Jilin University from January 2008 through December 2015 were recruited retrospectively based on their electronic medical records. A total of 524 patients were initially considered, consisting of 138 in the case group and 386 as control. Out of these, 110 were finally included in the case group and 110 as control based on additional selection criteria. The following information is collected from all the patients, total cholesterol (TC), low-density lipoprotein (LDL-C), high density lipoprotein (HDL-C) and triglyceride (TG). Logistic regressions were conducted to estimate the odds ratios (ORs) and 95% confidence intervals (95% CI) for non-small cell lung cancer (NSCLC) patients to have metastasis risk when having elevated serum lipid levels. Restricted cubic spline (RCS) curves were used to demonstrate the association between serum lipid levels and the risk of metastasis. Results: Patients with high TC level (P = 0.025, 0R = 1.35, 95% CI: 1.03-1.74) and patients with high LDL-C level (Q4: > 3.47 vs Q1: ≤2.54, P = 0.002, OR = 3.92, 95% CI: 1.31-11.77) are found to have an increased metastasis risk; and their dose-response relationship was validated by our restricted cubic spline analysis (TC: P overall association=0.02, P non-linear association = 0.73; LDL-C: P overall association=0.02, P non-linear association = 0.10). These associations were statistically significant, particularly in men who smoked, never drank, and were 65 years of age or younger. In addition, patients with simultaneously high levels of TC and LDL-C have a 60% increased risk of metastasis compared with patients with high levels of TC and normal LDL-C. Conclusion: Dyslipidemia may be a risk factor for metastasis among NSCLC patients. Examination of serum lipid level on a regular basis can provide early signal of metastasis for NSCLC patients.

The versatile roles and clinical implications of exosomal mRNAs and microRNAs in cancer

Extracellular vesicles (EVs), which include exosomes, microvesicles, and apoptotic bodies, are nanosized structures that are secreted by various cells and act as important mediators in intercellular communication. Recent studies have shown that exosomes carrying bioactive molecules are generated from multivesicular bodies and are present in various body fluids. mRNAs and microRNAs (miRNAs) are encapsulated in exosomes and have been found to be involved in multiple pathophysiological processes. Here, we provide a review of tumor-associated exosomal mRNAs and miRNAs and their roles in metastasis and drug resistance. In particular, we emphasize their clinical application potential as diagnostic and prognostic biomarkers of cancer and in cancer therapy.

An Expert Diagnostic System to Automatically Identify Asthma and Chronic Obstructive Pulmonary Disease in Clinical Settings

Respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD), are affecting a huge percentage of the world’s population with mortality rates exceeding those of lung cancer and breast cancer combined. The major challenge is the number of patients who are incorrectly diagnosed. To address this, we developed an expert diagnostic system that can differentiate among patients with asthma, COPD or a normal lung function based on measurements of lung function and information about patient’s symptoms. To develop accurate classification algorithms, data from 3657 patients were used and then independently verified using data from 1650 patients collected over a period of two years. Our results demonstrate that the expert diagnostic system can correctly identify patients with asthma and COPD with sensitivity of 96.45% and specificity of 98.71%. Additionally, 98.71% of the patients with a normal lung function were correctly classified, which contributed to a 49.23% decrease in demand for conducting additional tests, therefore decreasing financial cost.

Relevance of matrix metalloproteases in non-small cell lung cancer diagnosis

BACKGROUND

The need for novel biomarkers that could aid in non-small cell lung cancer (NSCLC) detection, together with the relevance of Matrix Metalloproteases (MMPs) -1, -2, -7, -9 and -10 in lung tumorigenesis, prompted us to assess the diagnostic usefulness of these MMPs and the Tissue Inhibitor of Metalloproteinase (TIMP) -1 in NSCLC patients.

METHODS

Markers were evaluated in an initial study cohort (19 NSCLC cases and 19 healthy controls). Those that better performed were analyzed in a larger sample including patients with benign lung diseases. Serum MMPs and TIMP-1 were determined by multiplexed immunoassays. Logistic regression was employed for multivariate analysis of biomarker combinations.

RESULTS

MMPs and TIMP-1 were elevated in the serum of NSCLC patients compared to healthy controls. MMP-1, -7 and -9 performed at best and were further evaluated in the sample including benign pathologies, corroborating the superiority of MMP-9 in NSCLC discrimination, also at early-stage NSCLC. The optimal diagnostic value was obtained with the model including MMP-9, gender, age and smoking history, that demonstrated an AUC of 0.787, 85.54% sensitivity and 64.89% specificity.

CONCLUSION

Our results suggest that MMP-9 is a potential biomarker for NSCLC diagnosis and its combined measurement with other biomarkers could improve NSCLC detection.

Differential diagnosis of lung cancer, its metastasis and chronic obstructive pulmonary disease based on serum Vegf, Il-8 and MMP-9

Chronic obstructive pulmonary disease (COPD) patients are at higher risk of developing lung cancer and its metastasis, but no suitable biomarker has been reported for differential diagnosis of these patients. Levels of serum biomarkers (VEGF, IL-8, MMP-9 and MMP-2) were analyzed in these patients, which were compared with healthy donors (HD). Levels of VEGF (P < 0.005) and MMP-9 (P < 0.05) were significantly higher in COPD patients than HD. Compared to HD, a decrease in IL-8 (~8.1 folds; P < 0.0001) but an increase in MMP-9 (~1.6 folds; P < 0.05) levels were observed in the lung cancer patients. Cancer patients showed significantly (P < 0.005) lower levels of serum VEGF (1.9 folds) and IL-8 (~9 folds) than the COPD patients. VEGF level was significantly higher (2.6 folds; P < 0.0005) in metastatic than non-metastatic cancer patients. However, MMP-2 didn't show significant variation in these patients. The Youden's index (YI) values for lung cancer diagnosis in HD using IL-8 was 0.55 with 83.3% overall accuracy. VEGF was able to diagnose COPD in HD with better YI (0.38) and overall accuracy (70.6%). IL-8 was able to diagnose cancer in COPD patients and HD with YI values of 0.35, 0.55 with 71% and 83.3% overall accuracy, respectively.

Elevated serum apolipoprotein E is associated with metastasis and poor prognosis of non-small cell lung cancer

Apolipoprotein E (ApoE) is a factor involved in Alzheimer's disease, which recently attracted great attention as an important protein related to tumorigenesis and metastasis. However, serum ApoE levels and its diagnosis and prognosis value in non-small cell lung cancer (NSCLC) patients are still unknown. In 196 NSCLC patients and 203 healthy controls, serum ApoE was measured by turbidimetric immunoassay. The associations of serum ApoE levels with the clinicopathological characteristics and clinical outcomes of NSCLC patients were analyzed. Serum ApoE levels were obviously elevated in NSCLC patients compared with healthy controls (41.6 ± 11.63 vs. 33.8 ± 6.24 mg/L) and were associated with TNM stage, lymph node metastasis status, and distant metastasis status (all P < 0.0001). For NSCLC diagnosis, the area under the receiver operating characteristic (ROC) curve was 0.71 at a specificity of 0.90 and sensitivity of 0.47. For lymph node metastasis predicting, the area under the ROC curve was 0.68 at a specificity of 0.56 and sensitivity of 0.73. From ROC/area under curve (AUC) analysis, we used 41.25 mg/L as the serum ApoE cut-off value, to divide NSCLC patients into two groups, the median survival was 11.0 weeks (95 % CI = 8.7 to 13.3) for patients in high serum ApoE group and 20.0 weeks (95 % CI = 15.0 to 25.0) in low serum ApoE group. Serum ApoE levels elevated in NSCLC patients, which also associated with TNM stages, lymph node metastasis, distant metastasis, and poor prognosis, suggest that serum ApoE may act as a useful clinical serological biomarkers for evaluating the progress of NSCLC.

Serum calprotectin, CD26 and EGF to establish a panel for the diagnosis of lung cancer

Lung cancer is the most lethal neoplasia, and an early diagnosis is the best way for improving survival. Symptomatic patients attending Pulmonary Services could be diagnosed with lung cancer earlier if high-risk individuals are promptly separated from healthy individuals and patients with benign respiratory pathologies. We searched for a convenient non-invasive serum test to define which patients should have more immediate clinical tests. Six cancer-associated molecules (HB-EGF, EGF, EGFR, sCD26, VEGF, and Calprotectin) were investigated in this study. Markers were measured in serum by specific ELISAs, in an unselected population that included 72 lung cancer patients of different histological types and 56 control subjects (healthy individuals and patients with benign pulmonary pathologies). Boosted regression and random forests analysis were conducted for the selection of the best candidate biomarkers. A remarkable discriminatory capacity was observed for EGF, sCD26, and especially for Calprotectin, these three molecules constituting a marker panel boasting a sensitivity of 83% and specificity of 87%, resulting in an associated misclassification rate of 15%. Finally, an algorithm derived by logistic regression and a nomogram allowed generating classification scores in terms of the risk of a patient of suffering lung cancer. In conclusion, we propose a non-invasive test to identify patients at high-risk for lung cancer from a non-selected population attending a Pulmonary Service. The efficacy of this three-marker panel must be tested in a larger population for lung cancer.

Urinary protein biomarkers in the early detection of lung cancer

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

"Sentinel" circulating tumor cells allow early diagnosis of lung cancer in patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a risk factor for lung cancer. Migration of circulating tumor cells (CTCs) into the blood stream is an early event that occurs during carcinogenesis. We aimed to examine the presence of CTCs in complement to CT-scan in COPD patients without clinically detectable lung cancer as a first step to identify a new marker for early lung cancer diagnosis. The presence of CTCs was examined by an ISET filtration-enrichment technique, for 245 subjects without cancer, including 168 (68.6%) COPD patients, and 77 subjects without COPD (31.4%), including 42 control smokers and 35 non-smoking healthy individuals. CTCs were identified by cytomorphological analysis and characterized by studying their expression of epithelial and mesenchymal markers. COPD patients were monitored annually by low-dose spiral CT. CTCs were detected in 3% of COPD patients (5 out of 168 patients). The annual surveillance of the CTC-positive COPD patients by CT-scan screening detected lung nodules 1 to 4 years after CTC detection, leading to prompt surgical resection and histopathological diagnosis of early-stage lung cancer. Follow-up of the 5 patients by CT-scan and ISET 12 month after surgery showed no tumor recurrence. CTCs detected in COPD patients had a heterogeneous expression of epithelial and mesenchymal markers, which was similar to the corresponding lung tumor phenotype. No CTCs were detected in control smoking and non-smoking healthy individuals. CTCs can be detected in patients with COPD without clinically detectable lung cancer. Monitoring “sentinel” CTC-positive COPD patients may allow early diagnosis of lung cancer.

Current status of circulating protein biomarkers to aid the early detection of lung cancer

ABSTRACT: 

Considerable efforts have been undertaken to produce an effective screening method to reduce lung cancer mortality. Imaging tools such as low-dose computed tomography has shown an increase in the detection of early disease and a reduction in the rate of death. This screening modality has, however, several limitations, such as overdiagnosis and a high rate of false positives. Therefore, new screening methods, such as the use of circulating protein biomarkers, have emerged as an option that could complement imaging studies. In this review, current imaging techniques applied to lung cancer screening protocols are presented, as well as up-to-date status of circulating protein biomarker panels that may improve lung cancer diagnosis. Additionally, diverse statistical and artificial intelligence tools applied to the design and optimization of these panels are discussed along with the presentation of two commercially available blood tests recently developed to help detect lung cancer early.

Development and validation of a plasma biomarker panel for discerning clinical significance of indeterminate pulmonary nodules

INTRODUCTION

The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography-based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography-based screening and promote its rapid implementation.

METHODS

We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules.

RESULTS

Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2Rα, stromal cell-derived factor-1α+β, tumor necrosis factor α, and macrophage inflammatory protein 1 α. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%.

CONCLUSION

We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.

Serum biomarker profiles as diagnostic tools in lung cancer

BACKGROUND

Computed tomography (CT) scanning has emerged as an effective means of early detection for lung cancer. Despite marked improvement over earlier methodologies, the low level of specificity demonstrated by CT scanning has limited its clinical implementation as a screening tool. A minimally-invasive biomarker-based test that could further characterize CT-positive patients based on risk of malignancy would greatly enhance its clinical efficacy.

METHODS

We performed an analysis of 81 serum proteins in 92 patients diagnosed with lung cancer and 172 CT-screened control individuals. We utilize a series of bioinformatics algorithms including Metropolis-Monte Carlo, artificial neural networks, Naïve Bayes, and additive logistic regression to identify multimarker panels capable of discriminating cases from controls with high levels of sensitivity and specificity in distinct training and independent validation sets.

RESULTS

A three-biomarker panel comprised of MIF, prolactin, and thrombospondin identified using the Metropolis-Monte Carlo algorithm provided the best classification with a %Sensitivity/Specificity/Accuracy of 74/90/86 in the training set and 70/93/82 in the validation set. This panel was effective in the classification of control individuals demonstrating suspicious pulmonary nodules and stage I lung cancer patients.

CONCLUSIONS

The selected serum biomarker panel demonstrated a high diagnostic utility in the current study and performance characteristics which compare favorably with previous reports. Further advancements may lead to the development of a diagnostic tool useful as an adjunct to CT-scanning.

Application of proteomics to cancer early detection

Strategies to achieve personalized medicine and improve public health encompass assessment of an individual's risk for disease, early detection, and molecular classification of disease resulting in an informed choice of the most appropriate treatment instituted at an early stage of disease development. An unmet need in this field for which proteomics is well suited to make a major contribution is the development of blood-based tests for early cancer detection. This is illustrated in proteomic studies of epithelial cancer that encompass analysis of specimens collected both at the time of diagnosis and specimens collected before onset of symptoms that are particularly suited for the identification of early detection markers. This overarching effort benefits from the availability of plasmas from subject cohorts and of engineered mouse models that are sampled at early stages of tumor development. Integration of findings from plasma with tumor tissue and cancer cell proteomic and genomic data allows elucidation of signatures in plasma for altered signaling pathways. The discovery and further development of early detection markers take advantage of the availability of in-depth quantitative proteomics methods and bioinformatics resources for data mining.

The state of molecular biomarkers for the early detection of lung cancer

Using biomarkers to select the most at-risk population, to detect the disease while measurable and yet not clinically apparent has been the goal of many investigations. Recent advances in molecular strategies and analytic platforms, including genomics, epigenomics, proteomics, and metabolomics, have identified increasing numbers of potential biomarkers in the blood, urine, exhaled breath condensate, bronchial specimens, saliva, and sputum, but none have yet moved to the clinical setting. Therefore, there is a recognized gap between the promise and the product delivery in the cancer biomarker field. In this review, we define clinical contexts where risk and diagnostic biomarkers may have use in the management of lung cancer, identify the most relevant candidate biomarkers of early detection, provide their state of development, and finally discuss critical aspects of study design in molecular biomarkers for early detection of lung cancer.