Cancer Testis Antigen, NOL4, Is an Immunogenic Antigen Specifically Expressed in Small-Cell Lung Cancer
Bibliographic record
Abstract
To identify cancer/testis (CT) antigens and immunogenic proteins, immunoscreening of testicular and small-cell lung cancer cell line NCI-H889 cDNA libraries was performed using serum obtained from a small-cell lung cancer (SCLC) patient. We obtained 113 positive cDNA clones comprised of 74 different genes, designated KP-SCLC-1 through KP-SCLC-74. Of these genes, 59 genes were found to be related to cancers by EMBASE analysis. Three of these antigens, including KP-SCLC-29 (NOL4), KP-SCLC-59 (CCDC83), and KP-SCLC-69 (KIF20B), were CT antigens. RT-PCR and western blot analysis showed that NOL4 was frequently present in small-cell lung cancer cell lines (8/9, 8/9). In addition, NOL4 mRNA was weakly, or at a low frequency, or not detected in various cancer cell lines. Our results reveal that NOL4 was expressed at protein levels in small-cell lung cancer tissues (10/10) but not detected in lung adenocarcinoma and squamous cell carcinoma by immunohistochemical analysis. Serological response to NOL4 was also evaluated by western blot assay using NOL4 recombinant protein. A humoral response against NOL4 proteins was detected in 75% (33/44) of small-cell lung cancer patients and in 65% (13/20) of healthy donors by a serological western blot assay. These data suggest that NOL4 is a specific target that may be useful for diagnosis and immunotherapy in SCLC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".