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We have implemented a strategy to identify tumor antigens that induce a humoral immune response in lung cancer based on the analysis of tumor cell proteins. Chromatographically fractionated protein extracts from three lung cancer cell lines were subjected to Western blotting and hybridization with individual sera to determine serum antibody binding. Two sets of sera were initially investigated. One set consisted of sera from 19 newly diagnosed subjects with lung adenocarcinoma and 19 matched controls. A second independent set consisted of sera from 26 newly diagnosed subjects with lung adenocarcinoma and 24 controls matched for age, gender, and smoking history. One protein that exhibited significant reactivity with both sets of cancer sera (P = 0.0008) was confidently identified by mass spectrometry as 14-3-3𝛉. Remarkably, significant autoantibody reactivity against 14-3-3𝛉 was also observed in an analysis of a third set consisting of 18 prediagnostic lung cancer sera collected as part of the Beta-Carotene and Retinol Efficacy Trial cohort study, relative to 19 matched controls (P = 0.0042). A receiver operating characteristic curve constructed with a panel of three proteins consisting of 14-3-3𝛉 identified in this study, plus annexin 1 and protein gene product 9.5 proteins previously identified as associated with autoantibodies in lung cancer, gave a sensitivity of 55% at 95% specificity (area under the curve, 0.838) in discriminating lung cancer at the preclinical stage from matched controls. [Cancer Res 2007;67(24):12000–6]

The identification of circulating tumor antigens or their related autoantibodies provides a means for early cancer diagnosis as well as leads for therapy. We have used a proteomic approach to identify proteins that commonly induce a humoral response in pancreatic cancer. Aliquots of solubilized proteins from a pancreatic cancer cell line (Panc-1) were subjected to two-dimensional PAGE, followed by Western blot analysis in which sera of individual patients were tested for primary antibodies. Sera from 36 newly diagnosed patients with pancreatic cancer, 18 patients with chronic pancreatitis, 33 patients with other cancers, and 15 healthy subjects were analyzed. Autoantibodies were detected against either one or two calreticulin isoforms identified by mass spectrometry in sera from 21 of 36 patients with pancreatic cancer. One of 18 chronic pancreatitis patients and 1 of 15 healthy controls demonstrated autoantibodies to calreticulin isoform 1; none demonstrated autoantibodies to isoform 2. None of the sera from patients with colon cancer exhibited reactivity against either of these two proteins. One of 14 sera from lung adenocarcinoma patients demonstrated autoantibodies to calreticulin isoform 1; 2 of 14 demonstrated autoantibodies to isoform 2. Immunohistochemical analysis of calreticulin in pancreatic/ampullary tumor tissue arrays using an isoform nonspecific antibody revealed diffuse and consistent cytoplasmic staining in the neoplastic epithelial cells of the pancreatic and ampullary adenocarcinomas. The detection of autoantibodies to calreticulin isoforms may have utility for the early diagnosis of pancreatic cancer.

The dawn of the post-genome era is leading to extraordinary opportunities in biomedicine. Our group has embarked on a major effort to integrate genomics, transcriptomics and proteomics for the profiling of tumor tissues, an approach we refer to as operomics. Our major goals are the molecular classification of tumors and the identification of markers for the early detection of cancer. Molecular analyses of tumors rely on microdissected tissues, which are simultaneously investigated for genomic, transcriptomic and proteomic changes. Genomic alterations in tumor cells being investigated include deletions, amplifications and methylation changes across the entire genome as well as point mutations in specific genes. Expression analysis at the RNA level is being undertaken using oligonucleotide and cDNA based microarrays. An important aspect of our approach is the large-scale identification and quantitative analysis of tumor proteins in whole cell lysates as well as in protein compartments. Protein separation strategies include two-dimensional polyacrylamide gel electrophoresis and liquid chromatography. Specific protein subsets, of interest include membrane proteins, secreted proteins and antigenic proteins as sources of biomarkers for early detection of cancer. Our current approach is illustrated with findings stemming from our studies of human gliomas.

We have developed a comprehensive approach to identifying molecular changes in lung cancer that includes both genomic and proteomic analyses. The related effort has produced a large amount of data pertaining to gene expression at the RNA and protein levels. As a result, we have constructed a database that contains protein expression data on lung cancer as well as other relevant data including DNA microarray derived data. A large number of proteins that are expressed in different types of lung cancer have been identified and have been correlated with the expression measures for their corresponding genes at the RNA level. The database is intended to facilitate our effort at developing novel classification schemes for lung cancer and the identification of novel markers for early diagnosis.

A common therapy for nonorgan-confined prostate cancer involves androgen deprivation. To develop a better understanding of the effect of androgen on prostatic cells, we have analyzed gene expression changes induced by dihydrotestosterone (DHT) in the androgen responsive prostate cancer line LNCaP, at both RNA and protein levels. Changes at the RNA level induced by DHT were determined by means of serial analysis of gene expression (SAGE), and protein profiling was done by means of quantitative two-dimensional polyacrylamide gel electrophoresis. Among 123,371 transcripts analyzed, a total of 28,844 distinct SAGE tags were identified representing 16,570 genes. Some 351 genes were significantly affected by DHT treatment at the RNA level (p < 0.05), of which 147 were induced and 204 repressed by androgen. In two independent experiments, the integrated intensity of 32 protein spots increased and 12 decreased at least two-fold in response to androgen, out of a total of 1031 protein spots analyzed. The change in intensity for most of the affected proteins identified could not be predicted based on the level of their corresponding RNA. Our study provides a global assessment of genes regulated by DHT and suggests a need for profiling at both RNA and protein levels for a comprehensive evaluation of patterns of gene expression.

There is currently limited data available pertaining to the global characterization of the cell surface proteome. We have implemented a strategy for the comprehensive profiling and identification of surface membrane proteins. This strategy has been applied to cancer cells, including the SH-SY5Y neuroblastoma, the A549 lung adenocarcinoma, the LoVo colon adenocarcinoma, and the Sup-B15 acute lymphoblastic leukemia (B cell) cell lines and ovarian tumor cells. Surface membrane proteins of viable, intact cells were subjected to biotinylation then affinity-captured and purified on monomeric avidin columns. The biotinylated proteins were eluted from the monomeric avidin columns as intact proteins and were subsequently separated by two-dimensional PAGE, transferred to polyvinylidene difluoride membranes, and visualized by hybridization with streptavidin-horseradish peroxidase. Highly reproducible, but distinct, two-dimensional patterns consisting of several hundred biotinylated proteins were obtained for the different cell populations analyzed. Identification of a subset of biotinylated proteins among the different cell populations analyzed using matrix-assisted laser desorption ionization and tandem mass spectrometry uncovered proteins with a restricted expression pattern in some cell line(s), such as CD87 and the activin receptor type IIB. We also identified more widely expressed proteins, such as CD98, and a sushi repeat-containing protein, a member of the selectin family. Remarkably, a set of proteins identified as chaperone proteins were found to be highly abundant on the cell surface, including GRP78, GRP75, HSP70, HSP60, HSP54, HSP27, and protein disulfide isomerase. Comprehensive profiling of the cell surface proteome provides an effective approach for the identification of commonly occurring proteins as well as proteins with restricted expression patterns in this compartment.

Rapamycin has been shown to affect translation. We have utilized two complementary approaches to identify genes that are predominantly affected by rapamycin in Jurkat T cells. One was to compare levels of polysome-bound and total RNA using oligonucleotide microarrays complementary to 6,300 human genes. Another was to determine protein synthesis levels using two-dimensional PAGE. Analysis of expression changes at the polysome-bound RNA levels showed that translation of most of the expressed genes was partially reduced following rapamycin treatment. However, translation of 136 genes (6% of the expressed genes) was totally inhibited. This group included genes encoding RNA-binding proteins and several proteasome subunit members. Translation of a set of 159 genes (7%) was largely unaffected by rapamycin treatment. These genes included transcription factors, kinases, phosphatases, and members of the RAS superfamily. Analysis of [(35)S]methionine-labeled proteins from the same cell populations using two-dimensional PAGE showed that the integrated intensity of 111 of 830 protein spots changed in rapamycin-treated cells by at least 3-fold (70 increased, 41 decreased). We identified 22 affected protein spots representing protein products of 16 genes. The combined microarray and proteomic approach has uncovered novel genes affected by rapamycin that may be involved in its immunosuppressive effect and other genes that are not affected at the level of translation in a context of general inhibition of cap-dependent translation.

The dawn of the post-genome era is leading to extraordinary opportunities in biomedicine. Our group has embarked on a major effort to integrate genomics, transcriptomics and proteomics for the profiling of tumor tissues, an approach we refer to as operomics. Our major goals are the molecular classification of tumors and the identification of markers for the early detection of cancer. Molecular analyses of tumors rely on microdissected tissues, which are simultaneously investigated for genomic, transcriptomic and proteomic changes. Genomic alterations in tumor cells being investigated include deletions, amplifications and methylation changes across the entire genome as well as point mutations in specific genes. Expression analysis at the RNA level is being undertaken using oligonucleotide and cDNA based microarrays. An important aspect of our approach is the large-scale identification and quantitative analysis of tumor proteins in whole cell lysates as well as in protein compartments. Protein separation strategies include two-dimensional polyacrylamide gel electrophoresis and liquid chromatography. Specific protein subsets, of interest include membrane proteins, secreted proteins and antigenic proteins as sources of biomarkers for early detection of cancer. Our current approach is illustrated with findings stemming from our studies of human gliomas.