Elevated expression of complement factor I in lung cancer cells associates with shorter survival-Potentially via non-canonical mechanism.

While numerous membrane-bound complement inhibitors protect the body's cells from innate immunity's autoaggression, soluble inhibitors like complement factor I (FI) are rarely produced outside the liver. Previously, we reported the expression of FI in non-small cell lung cancer (NSCLC) cell lines. Now, we assessed the content of FI in cancer biopsies from lung cancer patients and associated the results with clinicopathological characteristics and clinical outcomes. Immunohistochemical staining intensity did not correlate with age, smoking status, tumor size, stage, differentiation grade, and T cell infiltrates, but was associated with progression-free survival (PFS), overall survival (OS) and disease-specific survival (DSS). Multivariate Cox analysis of low vs. high FI content revealed HR 0.55, 95 % CI 0.32-0.95, p=0.031 for PFS, HR 0.51, 95 % CI 0.25-1.02, p=0.055 for OS, and HR 0.32, 95 % CI 0.12-0.84, p=0.021 for DSS. Unfavorable prognosis might stem from the non-canonical role of FI, as the staining pattern did not correlate with C4d - the product of FI-supported degradation of active complement component C4b. To elucidate that, we engineered three human NSCLC cell lines naturally expressing FI with CRISPR/Cas9 technology, and compared the transcriptome of FI-deficient and FI-sufficient clones in each cell line. RNA sequencing revealed differentially expressed genes engaged in intracellular signaling pathways controlling proliferation, apoptosis, and responsiveness to growth factors. Moreover, in vitro colony-formation assays showed that FI-deficient cells formed smaller foci than FI-sufficient NSCLC cells, but their size increased when purified FI protein was added to the medium. We postulate that a non-canonical activity of FI influences cellular physiology and contributes to the poor prognosis of lung cancer patients.

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.

Molecular biomarkers in early stage lung cancer.

Low dose computed tomography (LDCT) screening, together with the recent advances in targeted and immunotherapies, have shown to improve non-small cell lung cancer (NSCLC) survival. Furthermore, screening has increased the number of early stage-detected tumors, allowing for surgical resection and multimodality treatments when needed. The need for improved sensitivity and specificity of NSCLC screening has led to increased interest in combining clinical and radiological data with molecular data. The development of biomarkers is poised to refine inclusion criteria for LDCT screening programs. Biomarkers may also be useful to better characterize the risk of indeterminate nodules found in the course of screening or to refine prognosis and help in the management of screening detected tumors. The clinical implications of these biomarkers are still being investigated and whether or not biomarkers will be included in further decision-making algorithms in the context of screening and early lung cancer management still needs to be determined. However, it seems clear that there is much room for improvement even in early stage lung cancer disease-free survival (DFS) rates; thus, biomarkers may be the key to refine risk-stratification and treatment of these patients. Clinicians' capacity to register, integrate, and analyze all the available data in both high risk individuals and early stage NSCLC patients will lead to a better understanding of the disease's mechanisms, and will have a direct impact in diagnosis, treatment, and follow up of these patients. In this review, we aim to summarize all the available data regarding the role of biomarkers in LDCT screening and early stage NSCLC from a multidisciplinary perspective. We have highlighted clinical implications, the need to combine risk stratification, clinical data, radiomics, molecular information and artificial intelligence in order to improve clinical decision-making, especially regarding early diagnostics and adjuvant therapy. We also discuss current and future perspectives for biomarker implementation in routine clinical practice.

A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer.

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20-2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

Multiplex RNA-based detection of clinically relevant MET alterations in advanced non-small cell lung cancer.

MET inhibitors have shown activity in non-small-cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping (METΔex14). However, patient stratification is imperfect, and thus, response rates have varied widely. Here, we studied MET alterations in 474 advanced NSCLC patients by nCounter, an RNA-based technique, together with next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and reverse transcriptase polymerase chain reaction (RT-PCR), exploring correlation with clinical benefit. Of the 474 samples analyzed, 422 (89%) yielded valid results by nCounter, which identified 13 patients (3%) with METΔex14 and 15 patients (3.5%) with very-high MET mRNA expression. These two subgroups were mutually exclusive, displayed distinct phenotypes and did not generally coexist with other drivers. For METΔex14, 3/8 (37.5%) samples positive by nCounter tested negative by NGS. Regarding patients with very-high MET mRNA, 92% had MET amplification by FISH and/or NGS. However, FISH failed to identify three patients (30%) with very-high MET RNA expression, among which one received MET tyrosine kinase inhibitor treatment deriving clinical benefit. Our results indicate that quantitative mRNA-based techniques can improve the selection of patients for MET-targeted therapies.

A novel protein-based prognostic signature improves risk stratification to guide clinical management in early-stage lung adenocarcinoma patients.

Each of the pathological stages (I-IIIa) of surgically resected non-small-cell lung cancer has hidden biological heterogeneity, manifested as heterogeneous outcomes within each stage. Thus, the finding of robust and precise molecular classifiers with which to assess individual patient risk is an unmet medical need. Here, we identified and validated the clinical utility of a new prognostic signature based on three proteins (BRCA1, QKI, and SLC2A1) to stratify early-stage lung adenocarcinoma patients according to their risk of recurrence or death. Patients were staged according to the new International Association for the Study of Lung Cancer (IASLC) staging criteria (8th edition, 2018). A test cohort (n = 239) was used to assess the value of this new prognostic index (PI) based on the three proteins. The prognostic signature was developed by Cox regression with the use of stringent statistical criteria (TRIPOD: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The model resulted in a highly significant predictor of 5-year outcome for disease-free survival (p < 0.001) and overall survival (p < 0.001). The prognostic ability of the model was externally validated in an independent multi-institutional cohort of patients (n = 114, p = 0.021). We also demonstrated that this molecular classifier adds relevant information to the gold standard TNM-based pathological staging, with a highly significant improvement of the likelihood ratio. We subsequently developed a combined PI including both the molecular and the pathological data that improved the risk stratification in both cohorts (p ≤ 0.001). Moreover, the signature may help to select stage I-IIA patients who might benefit from adjuvant chemotherapy. In summary, this protein-based signature accurately identifies those patients with a high risk of recurrence and death, and adds further prognostic information to the TNM-based clinical staging, even when the new IASLC 8th edition staging criteria are applied. More importantly, it may be a valuable tool for selecting patients for adjuvant therapy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Determining optimal fluid and air leak cut off values for chest drain management in general thoracic surgery.

BACKGROUND: Chest drain duration is one of the most important influencing aspects of hospital stay but the management is perhaps one of the most variable aspects of thoracic surgical care. The aim of our study is to report outcomes associated with increasing fluid and air leak criteria of protocol based management. METHODS: A 6-year retrospective analysis of protocolised chest drain management starting in 2007 with a fluid criteria of 3 mL/kg increasing to 7 mL/kg in 2011 to no fluid criteria in 2012, and an air leak criteria of 24 hours without leak till 2012 when digital air leak monitoring was introduced with a criteria of <20 mL/min of air leak for more than 6 hours. Patient data were obtained from electronic hospital records and digital chest films were reviewed to determine the duration of chest tube drainage and post-drain removal complications. RESULTS: From 2009 to 2012, 626 consecutive patients underwent thoracic surgery procedures under a single consultant. A total of 160 did not require a chest drain and data was missing in 22, leaving 444 for analysis. The mean age [standard deviation (SD)] was 57±19 years and 272 (61%) were men. There were no differences in the incidence of pneumothoraces (P=0.191), effusion (P=0.344) or re-interventions (P=0.431) for drain re-insertions as progressively permissive criteria were applied. The median drain duration dropped from 1-3 days (P<0.001) and accordingly hospital stay reduced from 4-6 days (P<0.001). CONCLUSIONS: Our results show that chest drains can be safely removed without fluid criteria and air leak of less than 20 mL/min with median drain duration of 1 day, associated with a reduced length of hospital stay.