CD24+/CD38- as new prognostic marker for non-small cell lung cancer
Bibliographic record
Abstract
BACKGROUND: Lung cancer is the leading cause of death among cancers in the world. The annual death toll due to this disease exceeds the combined deaths caused by colon, breast, prostate, and pancreatic cancers. As a result, there has been a tremendous effort to identify new biomarkers for early detection and diagnosis of lung cancer. METHODS: In this study we report the results of screening a panel of eight non-small cell lung cancer (NSCLC) cell lines originating from different subtypes of lung cancer in an attempt to identify potential biomarkers unique to this disease. We used real-time polymerase chain reaction and flow cytometry techniques to analyze the expression of ALDHA1, EpCAM, CD133, CD24, and CD38 in this panel. RESULTS: We demonstrate for the first time that the majority of NSCLC cells do not express levels of CD38 that would qualify it as a new biomarker for the disease. In contrast, we found that CD24 is over-expressed in 6 out of 8 of the cell lines. The combined CD24+/CD38-/low phenotype was detected in 50% of the cell lines that are also positive for CD133 and EpCAM. CONCLUSIONS: We report that CD24+/CD38-/low signature could potentially be used as a new biomarker for the early detection of NSCLC.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".