Serological screening approaches have allowed for the identification of a large number of potentially relevant tumor antigens in cancer patients. Within this group, cancer testis antigens represent promising targets for cancer immunotherapy, since they are widely expressed in a variety of human cancer entities. In pancreatic cancer, however, there are only few data available about the expression pattern and serological response to cancer testis antigens and other serological-defined tumor antigens. Therefore, we investigated the IgG antibody response against 11 cancer testis antigens (SCP-1, GAGE, LAGE-1a,-1b, CT-7, NY-ESO-1, SSX-1-5) recombinantly expressed on yeast surface (RAYS) in patients with pancreatic cancer (n = 96), chronic pancreatitis (n = 18) and healthy donors (n = 48). We found in 14% of all patients antibody responses to SCP-1, but not to other cancer testis antigens (GAGE, LAGE-1a,-1b, CT-7, NY-ESO-1, SSX-1-5). Antibody response correlated with the expression of SCP-1 in the primary tumor of the respective patient as shown by RT-PCR, immunohistochemistry and Western blot. In contrast, no serological response to cancer testis antigens was observed in healthy donors. The humoral immune response against SCP-1 was associated with the size of tumor, but not with other clinico-pathological parameters such as histology, stage, presence of lymph node metastases, grading, age, gender or gemcitabine treatment. In conclusion, antibody response to cancer testis antigen SCP-1 is found in a proportion of pancreatic carcinoma patients. These results indicate that identification of additional tumor antigens by serological screening of tumor cDNA expression libraries by RAYS is a promising goal in pancreatic cancer.
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http://dx.doi.org/10.1002/ijc.21744 | DOI Listing |
Aging (Albany NY)
January 2025
Department of Public Health Sciences, University of Chicago, Chicago, IL 60615, USA.
Background: DNA methylation (DNAm) data from human samples has been leveraged to develop "epigenetic clock" algorithms that predict age and other aging-related phenotypes. Some DNAm clocks were trained using DNAm obtained from blood cells, while other clocks were trained using data from diverse tissue/cell types. To assess how DNAm clocks perform across non-blood tissue types, we applied DNAm algorithms to DNAm data generated from 9 different human tissue types.
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Sci Rep
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Department of Pathology and Biological Responses, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan.
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View Article and Find Full Text PDFMol Biol Cell
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Department of Biology, University of North Carolina at Chapel Hill, CB#3280, Chapel Hill, NC 27599-3280, USA.
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View Article and Find Full Text PDFMol Biol Res Commun
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Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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