Identification of lung cancer with high sensitivity and specificity by blood testing

<p>Abstract</p> <p>Background</p> <p>Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer.</p> <p>Methods</p> <p>We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation.</p> <p>Results</p> <p>The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%.</p> <p>Conclusion</p> <p>We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.</p

Strategies for plasma proteomic profiling of cancers

Despite a voluminous literature on potential protein biomarkers and a compelling need for diagnostic tests based on biomarkers to detect cancers at much earlier, more treatable stages, progress has been limited. New methods and new instruments for analysis of differences in gene expression, gene methylation, and proteomics are being employed to try to accelerate the discovery phase. Given the heterogeneity of tumor mechanisms and the limitations of analytical methods, it is likely that a variety of strategies will be needed and will be complementary. That is the basis of this review of proteomic approaches. This article adopts a systems biology view, starting with mRNA transcripts in tumors and cultured tumor cells to detect mRNA overexpression, some of which will be correlated with protein overexpression. Some of those proteins may be secreted or released into proximal biofluids and plasma. Detection of low-abundance tumor proteins in the complex and dynamic mixture that is plasma requires combinations of increasingly powerful technologies. The biological amplification of protein signals through the immune system offers autoantibodies as potential biomarkers. Higher abundance proteins, including acute-phase reactants, may have practical value, especially if the proteins are modified as part of the cancer processes. Low molecular weight proteins, fragments, and peptides may offer complementary biomarkers. Promising biomarker candidates must be confirmed in independent studies. Then they must be submitted to higher-throughput methods practical for large-scale validation studies and, hopefully, for clinical and epidemiological applications. Standardized operating procedures for specimen handling, design and use of various reference standards, care to avoid bias and confounding, and guidelines for reporting findings and contributing datasets should enhance the prospects for predictive proteomic profiling of people at risk for cancers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55851/1/5662_ftp.pd

Identification of an autoantibody panel to separate lung cancer from smokers and nonsmokers

<p>Abstract</p> <p>Background</p> <p>Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways.</p> <p>Methods</p> <p>We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts.</p> <p>Results</p> <p>Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer.</p> <p>Conclusion</p> <p>A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.</p

Disease proteomics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62680/1/nature01514.pd

Epigenetic control of the ubiquitin carboxyl terminal hydrolase 1 in renal cell carcinoma

<p>Abstract</p> <p>Background</p> <p>The ubiquitin carboxyl-terminal hydrolase 1 (UCHL1) gene involved in the regulation of cellular ubiquitin levels plays an important role in different cellular processes including cell growth and differentiation. Aberrant expression of UCHL1 has been found in a number of human solid tumors including renal cell carcinoma (RCC). In RCC, UCHL1 overexpression is associated with tumor progression and an altered von Hippel Lindau gene expression.</p> <p>Methods</p> <p>To determine the underlying mechanisms for the heterogeneous UCHL1 expression pattern in RCC the UCHL1 promoter DNA methylation status was determined in 17 RCC cell lines as well as in 32 RCC lesions and corresponding tumor adjacent kidney epithelium using combined bisulfite restriction analysis as well as bisulfite DNA sequencing.</p> <p>Results</p> <p>UCHL1 expression was found in all 32 tumor adjacent kidney epithelium samples. However, the lack of or reduced UCHL1 mRNA and/or protein expression was detected in 13/32 RCC biopsies and 7/17 RCC cell lines and due to either a total or partial methylation of the UCHL1 promoter DNA. Upon 2'-deoxy-5-azacytidine treatment an induction of UCHL1 mRNA and protein expression was found in 9/17 RCC cell lines, which was linked to the demethylation degree of the UCHL1 promoter DNA.</p> <p>Conclusion</p> <p>Promoter hypermethylation represents a mechanism for the silencing of the UCHL1 gene expression in RCC and supports the concept of an epigenetic control for the expression of UCHL1 during disease progression.</p

Annexin A2 is a new antigenic target for pancreatic cancer immunotherapy

In our recent publication (Zheng et al., PLoS ONE) we described the identification of annexin A2 as a new pancreatic cancer associated tumor antigen. Its involvement in pancreatic cancer progression and metastases supports its role as an antigenic target for the development of both therapeutic antibody and T cell immunotherapy