The serum-based VeriStrat® test is associated with proinflammatory reactants and clinical outcome in non-small cell lung cancer patients.

BACKGROUND: The VeriStrat test is a serum proteomic signature originally discovered in non-responders to second line gefitinib treatment and subsequently used to predict differential benefit from erlotinib versus chemotherapy in previously treated advanced non-small cell lung cancer (NSCLC). Multiple studies highlight the clinical utility of the VeriStrat test, however, the mechanistic connection between VeriStrat-poor classification and poor prognosis in untreated and previously treated patients is still an active area of research. The aim of this study was to correlate VeriStrat status with other circulating biomarkers in advanced NSCLC patients - each with respect to clinical outcomes. METHODS: Serum samples were prospectively collected from 57 patients receiving salvage chemotherapy and 70 non-EGFR mutated patients receiving erlotinib. Patients were classified as either VeriStrat good or poor based on the VeriStrat test. Luminex immunoassays were used to measure circulating levels of 102 distinct biomarkers implicated in tumor aggressiveness and treatment resistance. A Cox PH model was used to evaluate associations between biomarker levels and clinical outcome, whereas the association of VeriStrat classifications with biomarker levels was assessed via the Mann-Whitney Rank Sum test. RESULTS: VeriStrat was prognostic for outcome within the erlotinib treated patients (HR = 0.29, p < 0.0001) and predictive of differential treatment benefit between erlotinib and chemotherapy ((interaction HR = 0.25; interaction p = 0.0035). A total of 27 biomarkers out of 102 unique analytes were found to be significantly associated with OS (Cox PH p ≤ 0.05), whereas 16 biomarkers were found to be associated with PFS. Thrombospondin-2, C-reactive protein, TNF-receptor I, and placental growth factor were the analytes most highly associated with OS, all with Cox PH p-values ≤0.0001. VeriStrat status was found to be significantly associated with 23 circulating biomarkers (Mann-Whitney Rank Sum p ≤ 0.05), 6 of which had p < 0.001, including C-reactive protein, IL-6, serum amyloid A, CYFRA 21.1, IGF-II, osteopontin, and ferritin. CONCLUSIONS: Strong associations were observed between survival and VeriStrat classifications as well as select circulating biomarkers associated with fibrosis, inflammation, and acute phase reactants as part of this study. The associations between these biomarkers and VeriStrat classification might have therapeutic implications for poor prognosis NSCLC patients, particularly with new immunotherapeutic treatment options.

Serum Biomarkers May Prognosticate Recurrence in Node-Negative, Non-Small Cell Lung Cancers Less Than 4 Centimeters.

BACKGROUND: A significant proportion of patients who undergo lung resection for less than 4 cm non-small cell lung cancer (NSCLC) will die of disease recurrence within 5 years. The ability to identify patients at greatest risk for recurrence may help individualize treatment and surveillance regimens and improve outcomes. We hypothesized that a serum-based biomarker panel could help risk stratify patients with node-negative NSCLC less than 4 cm for recurrence after lung resection. METHODS: An institutional biorepository of more than 1,800 cases was used to identify patients with resected, node-negative NSCLC less than 4 cm in size. Clinical and radiographic data were collected. Preoperative serum specimens were evaluated in a blinded manner for 47 biomarkers that sampled biological processes associated with metastatic progression, including angiogenesis, energy metabolism, apoptosis, and inflammation. Receiver-operating characteristics curves and log rank tests were used to evaluate individual biomarkers with respect to recurrence, followed by random forest analysis to generate and cross validate a multiple-analyte panel to risk stratify patients for recurrence. RESULTS: The cohort included 123 patients with a median follow-up of 58.2 months; 23 patients had recurrences. A seven-analyte panel consisting of human epididymis protein 4, insulinlike growth factor-binding protein 1, beta-human chorionic gonadotropin, follistatin, prolactin, angiopoietin-2, and hepatocyte growth factor optimally identified patients with disease recurrence with a cross-validated specificity of 91%, sensitivity of 22%, negative predictive value of 83%, positive predictive value of 36%, and accuracy of 78%, providing an area under the receiver-operating characteristics curve of 0.70. CONCLUSIONS: Serum-based biomarkers may be useful for risk stratifying patients with node-negative NSCLC less than 4 cm for recurrence after lung resection.

Differential expression of circulating biomarkers of tumor phenotype and outcomes in previously treated non-small cell lung cancer patients receiving erlotinib vs. cytotoxic chemotherapy.

BACKGROUND: The 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. METHODS: Sixty-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. RESULTS: Our 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. CONCLUSIONS: Contemporary 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.