Enhancement of a multianalyte serum biomarker panel to identify lymph node metastases in non‐small cell lung cancer with circulating autoantibody biomarkers

Abstract

We recently reported the development of a multianalyte serum algorithm to identify nodal status in non-small cell lung cancer (NSCLC) patients facing an anatomic resection with curative intent. This study aims to enhance the overall performance characteristics of this test by adding autoantibody biomarkers identified through immunoproteomic discovery. More specifically, we used sera from 20 NSCLC patients to probe 2-D immunoblots of HCC827 lysates for tumor-associated autoantigens. Relevant differences in immunoreactivity associated with pathological nodal status were then identified via tandem mass spectrometry. Identified autoantigens were then developed into Luminex immunobead assays alongside a series of autoantigen targets relevant to early-disease detection. These assays were then used to measure circulating autoantibody levels in the identical cohort of NSCLC patients used in our original study. This strategy identified 11 autoantigens found primarily in patients with disease progression to the locoregional lymph nodes. Custom Luminex-based ''direct-capture'' assays (25 total; including autoantibody targets relevant to early-disease detection) were assembled to measure autoantibody levels in sera from 107 NSCLC patients. Multivariate classification algorithms were then used to identify the optimal combination of biomarkers when considered collectively with our original 6-analyte serum panel. The new algorithm resulting from this analysis consists of TNF-a, TNF-RI, MIP-1a and autoantibodies against Ubiquilin-1, hydroxysteroid-(17-b)-dehydrogenase, and triosephosphate isomerase. The inclusion of autoantibody biomarkers provided a dramatic improvement in the overall test performance characteristics, relative to the original test panel, including an 11% improvement in the classification efficiency.Lung cancer is by far the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for roughly 85% of the cases reported annually. 1,2 Approximately 25-30% of NSCLC patients present with localized disease and are eligible for a complete anatomic resection as a potential means for a cure. 3-5 However, as many as 40% of patients with no apparent metastatic progression (i.e., N 0 disease) will die from recurrent disease within 5 years of tumor resection; 6 suggesting that systemic tumor cell dissemination (locoregional or distant) had already occurred at the time of surgery, but went undetected by current clinical and pathological staging methods.In this direction, we recently reported the establishment of a 6-analyte serum algorithm to identify a patient's true (pathologic) nodal status using a cohort of preoperative NSCLC patients (n ¼ 107) and Luminex-based immunobead assays for 47 distinct biomarkers implicated in disease status and/or progression. 7 Using the ''Random Forest'' multivariate classification algorithm developed by Breiman and Cutler, we identified the most efficacious combination of the individually statistically-relevant biomarkers for classifying patien...

Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer

“…2,19 Autoantibody signatures might be useful in cancers in which there are high-risk populations and where existing detection methods lack sensitivity and specificity, particularly in LC. 2 To identify specific LC biomarker, an immunoproteomic approach combined with MS was used to identify interesting proteins and found that three Table 5.…”

Finding biomarkers for non-small cell lung cancer diagnosis and prognosis

“…In NSCLC, the presence of locoregional lymph node metastases remains the most important prognostic factor and significantly guides treatment regimens. Borgia et al established a multi-analyte serum biomarker panel and identified 15 candidate biomarkers in discerning a patient's preoperative nodal status (Borgia et al, 2009;Patel et al, 2011). Some oncogene and tumor suppressor gene products in serum, such as p53, anti-p53 antibodies, sEGFR or Ras have also been utilized as NSCLC biomarkers (Brandt-Rauf et al, 1992;Angelopoulou et al, 1994;Luo et al, 1994;Baron et al, 2009).…”

Utility of Autoantibodies as Biomarkers for Diagnosis and Staging of Neurodegenerative Diseases

“…However, with recent advances in autoantibody identification, Chapman et al were able to test autoantibodies directed against various markers to develop a biomarker panel yielding up to 76% sensitivity and 92% specificity (Chapman et al, 2008). Patel et al went even further to develop an autoantibody "direct-capture" immunobead assay using selected antigens for successful detection of nonsmall-cell lung carcinoma with a sensitivity and specificity of 94% and 97%, respectively (Patel et al, 2011). Similar advances using panels of autoantibodies have been made for the diagnosis of colon cancer (Belousov et al, 2008;Chen et al, 2007;Cioffi et al, 2004;Yoshizawa et al, 2007), stomach cancer (di Mario & Cavallaro, 2008), and hepatocellular carcinoma (Li, Chen, Yu, Li, & Wang, 2008;Marrero et al, 2003).…”