Isolation and characterization of human lung cancer antigens by serological screening with autologous antibodies

Serological analysis of a recombinant cDNA expression library (SEREX) derived from two lung adenocarcinoma cancer cell lines using autologous sera led to the isolation of 41 positive cDNA clones comprising 28 different antigens. They coded for a variety of nuclear and cytoplasmic proteins. Among the antigens, nucleoporin 107 (NUP107) was isolated most frequently (5 of 41 clones). The second most frequently isolated antigen was coded for by C21orf58 (4 of 41 clones). During serological analysis of selected antigens based on their reactivity to sera from normal individuals and lung cancer patients, none of the antigens showed a cancer-restricted recognition pattern. However, five genes including NUP107 showed higher expression when we examined the changes in gene expression in five different adenocarcinoma cell lines, including those used in SEREX, compared with their levels in normal lung tissues by cDNA microarray analysis. On the other hand, the expression levels of five genes including C21orf58 were down regulated in all adenocarcinoma cell lines. This SEREX study combining comprehensive gene expression assays has added to the growing list of lung cancer antigens, which may aid the development of diagnostic and immunotherapeutic reagents for patients with lung cancer

Isolation and characterization of human lung cancer antigens by serological screening with autologous antibodies

Serological analysis of a recombinant cDNA expression library (SEREX) derived from two lung adenocarcinoma cancer cell lines using autologous sera led to the isolation of 41 positive cDNA clones comprising 28 different antigens. They coded for a variety of nuclear and cytoplasmic proteins. Among the antigens, nucleoporin 107 (NUP107) was isolated most frequently (5 of 41 clones). The second most frequently isolated antigen was coded for by C21orf58 (4 of 41 clones). During serological analysis of selected antigens based on their reactivity to sera from normal individuals and lung cancer patients, none of the antigens showed a cancer-restricted recognition pattern. However, five genes including NUP107 showed higher expression when we examined the changes in gene expression in five different adenocarcinoma cell lines, including those used in SEREX, compared with their levels in normal lung tissues by cDNA microarray analysis. On the other hand, the expression levels of five genes including C21orf58 were down regulated in all adenocarcinoma cell lines. This SEREX study combining comprehensive gene expression assays has added to the growing list of lung cancer antigens, which may aid the development of diagnostic and immunotherapeutic reagents for patients with lung cancer

Evaluating real-life performance of the state-of-the-art in facial expression recognition using a novel YouTube-based datasets

Facial expression recognition (FER) is one of the most active areas of research in computer science, due to its importance in a large number of application domains. Over the years, a great number of FER systems have been implemented, each surpassing the other in terms of classification accuracy. However, one major weakness found in the previous studies is that they have all used standard datasets for their evaluations and comparisons. Though this serves well given the needs of a fair comparison with existing systems, it is argued that this does not go in hand with the fact that these systems are built with a hope of eventually being used in the real-world. It is because these datasets assume a predefined camera setup, consist of mostly posed expressions collected in a controlled setting, using fixed background and static ambient settings, and having low variations in the face size and camera angles, which is not the case in a dynamic real-world. The contributions of this work are two-fold: firstly, using numerous online resources and also our own setup, we have collected a rich FER dataset keeping in mind the above mentioned problems. Secondly, we have chosen eleven state-of-the-art FER systems, implemented them and performed a rigorous evaluation of these systems using our dataset. The results confirm our hypothesis that even the most accurate existing FER systems are not ready to face the challenges of a dynamic real-world. We hope that our dataset would become a benchmark to assess the real-life performance of future FER systems

Serological identification of Tektin5 as a cancer/testis antigen and its immunogenicity

<p><b>A</b>bstract</p> <p>Background</p> <p>Identification of new cancer antigens is necessary for the efficient diagnosis and immunotherapy. A variety of tumor antigens have been identified by several methodologies. Among those antigens, cancer/testis (CT) antigens have became promising targets.</p> <p>Methods</p> <p>The serological identification of antigens by the recombinant expression cloning (SEREX) methodology has been successfully used for the identification of cancer/testis (CT) antigens. We performed the SEREX analysis of colon cancer.</p> <p>Results</p> <p>We isolated a total of 60 positive cDNA clones comprising 38 different genes. They included 2 genes with testis-specific expression profiles in the UniGene database, such as <it>TEKT5</it> and a CT-like gene, <it>A kinase anchoring protein 3</it> (<it>AKAP3</it>). Quantitative real-time RT-PCR analysis showed that the expression of <it>TEKT5</it> was restricted to the testis in normal adult tissues. In malignant tissues, <it>TEKT5</it> was aberrantly expressed in a variety of cancers, including colon cancer. A serological survey of 101 cancer patients with different cancers by ELISA revealed antibodies to TEKT5 in 13 patients, including colon cancer. None of the 16 healthy donor serum samples were reactive in the same test.</p> <p>Conclusion</p> <p>We identified candidate new CT antigen of colon cancer, TEKT5. The findings indicate that TEKT5 is immunogenic in humans, and suggest its potential use as diagnostic as well as an immunotherapeutic reagent for cancer patients.</p