Aggrecanases are involved in aggrecanolysis at both the early and advanced stages of disc degeneration. The aggrecan fragmentation profile analysis demonstrates the involvement of aggrecanases, as well as that of matrix metalloproteinases and/or cathepsins, during disc degeneration.

Purpose: Non-small cell lung cancer (NSCLC) has an overall 5-year survival of <15%; however, the 5-year survival for stage I disease is over 50%. Unfortunately, 75% of NSCLC is diagnosed at an advanced stage not amenable to surgery. A convenient serum assay capable of unambiguously identifying patients with NSCLC may provide an ideal diagnostic measure to complement computed tomography-based screening protocols.Experimental Design: Standard immunoproteomic method was used to assess differences in circulating autoantibodies among lung adenocarcinoma patients relative to cancer-free controls. Candidate autoantibodies identified by these discovery phase studies were translated into Luminex-based "direct-capture" immunobead assays along with 10 autoantigens with previously reported diagnostic value. These assays were then used to evaluate a second patient cohort composed of four discrete populations, including: 117 NSCLC (81 T 1-2 N 0 M 0 and 36 T 1-2 N 1-2 M 0 ), 30 chronic obstructive pulmonary disorder (COPD)/ asthma, 13 nonmalignant lung nodule, and 31 "normal" controls. Multivariate statistical methods were then used to identify the optimal combination of biomarkers for classifying patient disease status and develop a convenient algorithm for this purpose.Results: Our immunoproteomic-based biomarker discovery efforts yielded 16 autoantibodies differentially expressed in NSCLC versus control serum. Thirteen of the 25 analytes tested showed statistical significance (Mann-Whitney P < 0.05 and a receiver operator characteristic "area under the curve" over 0.65) when evaluated against a second patient cohort. Multivariate statistical analyses identified a six-biomarker panel with only a 7% misclassification rate.Conclusions: We developed a six-autoantibody algorithm for detecting cases of NSCLC among several high-risk populations. Population-based validation studies are now required to assign the true value of this tool for identifying early-stage NSCLC. Clin Cancer Res; 16(13); 3452-62. ©2010 AACR.Lung cancer remains the leading cause of cancer death nationwide, with ∼160,000 deaths predicted in the United States in 2009 (1). Non-small cell lung cancer (NSCLC) accounts for 80% of all lung cancers and has a poor overall 5-year survival rate of ∼15% (2-4). This low survival rate is largely attributed to the fact that >75% of patients present with local or distant metastasis at diagnosis, which are associated with a 21% and 3% 5-year survival, respectively (2,3,5). In contrast to these dismal figures, stage I disease is associated with a 50% to 67% 5-year survival but accounts for only 15% of patients (2). This suggests that if patients could be diagnosed at an earlier stage, when a complete surgical resection offers the greatest potential for a cure, the mortality associated with this disease could be reduced.To that end, considerable efforts have been undertaken to produce an effective screening method for early NSCLC. In the 1950s, trials of chest X-rays alone or in combination with sputum analysis were com...

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...

Although the biologic role of NG2 remains to be elucidated, the colocalization of NG2 with type VI collagen in the pericellular area suggests that NG2 may play an important role in cell-matrix interactions. The high level of NG2 expression in advanced degeneration also suggests an important role of NG2 in the loss of disc integrity.