BackgroundThe objective of this study was to identify serum biomarkers capable of predicting clinical outcomes in previously-treated NSCLC patients with wild-type for EGFR activating mutations or insufficient tissue for mutation status determination.MethodsSixty-six Luminex immunoassays representative of biological themes that emerged from a re-analysis of transcriptome data from the Cancer Genome Atlas (TCGA) were evaluate against pretreatment serum specimens from previously-treated advanced NSCLC patients received either cytotoxic chemotherapy (n=32) or erlotinib (n=79). Known EGFR mutation positive cases were excluded from analysis. Associations of biomarkers with outcome parameters and their differential interaction with treatment for survival outcomes were assessed using multivariate Cox PH analyses.ResultsOur EMT-based transcriptomic analysis revealed a range of biological processes associated with angiogenesis, apoptosis, cachexia, inflammation, and metabolism emerging as those most highly associated with patient outcome. These processes were evaluated via surrogate serum biomarkers. A treatment-biomarker interaction analysis revealed that higher pretreatment levels of c-Met signaling biomarkers (i.e. HGF levels), pro-inflammatory/ pro-cachexia (e.g. IL-8, sIL-2Rα, FGF-2) processes and a pro-angiogenic (e.g. TGF-α, IL-8, VEGF) milieu were associated with inferior survival (HR=0.35, 0.29, 0.58, 0.50, 0.61, 0.45, respectively; all p<0.05) for patients receiving chemotherapy, relative to erlotinib. In contrast, high levels of decoy receptor for IL-1, sIL-1RII, and a high tissue vimentin/E-cadherin ratio were associated with a poor OS (HR=3.78; p=0.00055) in the erlotinib cohort.ConclusionsContemporary precision medicine initiatives that pair patient tumor characteristics with the optimal therapy type may maximize the use of agents targeting EGFR in the treatment of NSCLC.
Background: Detection rates of early-stage lung cancer are traditionally low, which contributes to inconsistent treatment responses and high rates of annual cancer deaths. Currently, low-dose computed tomography (LDCT) screening produces a high false discovery rate. This limitation has prompted research to identify biomarkers to more clearly define eligible patients for LDCT screening, differentiate indeterminate pulmonary nodules, and select individualized cancer therapy. Biomarkers within the Insulin-like Growth Factor (IGF) family have come to the forefront of this research. Main Body: Multiple biomarkers within the IGF family have been investigated, most notably IGF-I and IGF binding protein 3. However, newer studies seek to expand this search to other molecules within the IGF axis. Certain studies have demonstrated these biomarkers are useful when used in combination with lung cancer screening, but other findings were not as conclusive, possibly owing to measurement bias and non-standardized assay techniques. Research also has suggested IGF biomarkers may be beneficial in the prognostication and subsequent treatment via systemic therapy. Despite these advances, additional knowledge of complex regulatory mechanisms inherent to this system are necessary to more fully harness the potential clinical utility for diagnostic and therapeutic purposes. Conclusions: The IGF system likely plays a role in multiple phases of lung cancer; however, there is a surplus of conflicting data, especially prior to development of the disease and during early stages of detection. IGF biomarkers may be valuable in the screening, prognosis, and treatment of lung cancer, though their exact application requires further study.
Soluble HLA molecules may have diagnostic value for early-stage NSCLC. Validation studies are currently underway using sera from a lung cancer screening cohort.
3054 Background: We previously reported associations of pretreatment serum biomarkers with clinical outcomes in a cohort of advanced NSCLC patients that progressed on front-line therapy. This study aims to elucidate mechanisms underlying cancer cachexia/ pre-cachexia by evaluating relationships between baseline serum biomarker values and sequential changes in body weight, body mass index (BMI), and neutrophil/lymphocyte ratio (NLR) in NSCLC patients. Methods: We used Luminex immunobead assays to survey 101 protein biomarkers in sera from advanced NSCLC (n = 138) collected prior to their salvage regimen. Serial parameters associated with cancer cachexia included body weight, BMI, and NLR. Outcome variables (progression-free survival (PFS) and overall survival (OS)) were extracted with full IRB-approval. Biomarkers were evaluated as continuous variables with the cachexia surrogates using Pearson correlations, whereas associations of PFS and OS were accomplished with the Cox PH test. Results: High baseline values of BMI and low baseline NLR were associated with both OS and PFS (each p < 0.05), though weight failed to reach significance. PFS and OS were similarly associated with percent changes (relative to baseline) in weight (p < 0.01), BMI (p < 0.01), and NLR (p < 0.001). Thirteen biomarkers were found to be associated (p < 0.05) with baseline BMI values, including positive correlations with leptin, sol.VEGFR2, and c-peptide and inverse correlations with adiponectin, ferritin, ghrelin, IGFBP-1 and IL-8; fifteen biomarkers were associated with baseline NLR (all p < 0.05), including positive correlations with visfatin, insulin, and serum amyloid A and inverse correlations with IGF-II. Fifteen biomarkers were found to be associated (p < 0.05) in common with percent weight and BMI changes, including positive correlations with IGFBP-3 and inverse correlations with insulin, FGF-2, TNF-alpha, and resistin. Only prolactin and placental growth factor were found to be associated (p < 0.05) with percent change in NLR. Conclusions: A series of circulating protein biomarkers primarily connected with metabolic regulation and systemic inflammation/ acute phase response were found to be associated with cachexia/ pre-cachexia in NSCLC patients. Additional cohorts are currently being tested to verify these findings.
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