Co-expression of cancer stem cell markers, SALL4/ALDH1A1, is associated with tumor aggressiveness and poor survival in patients with serous ovarian carcinoma
Bibliographic record
Abstract
BACKGROUND: Spalt-like transcription factor 4 (SALL4) and aldehyde dehydrogenase1 family member A1 (ALDH1A1) expressing cells have been characterized as possessing stem cell-like properties known as cancer stem cell marker in serous ovarian carcinoma (SOC). METHODS: The association between SALL4 and ALDH1A1 was observed based on literature review and bioinformatics tools. Therefore, this study aimed to investigate the association between the co-expression of SALL4/ALDH1A1 proteins and clinicopathological parameters and their prognostic value in SOC patients using immunohistochemical staining on tissue microarrays (TMAs). Furthermore, benign tumors and normal tissue samples were compared with the expression of the tumor tissue samples. RESULTS: Increased co-expression of SALL4/ALDH1A1 was found to be significantly associated with the advanced FIGO stage (P = 0.047), and distant metastasis (P = 0.028). The results of Kaplan-Meier survival analysis indicated significant differences between disease- specific survival (DSS; P = 0.034) or progression-free survival (PFS; P = 0.018) and the patients with high and low co-expression of SALL4/ALDH1A1, respectively. Furthermore, high level co-expression of SALL4/ALDH1A1 was a significant predictor of worse DSS and PFS in the univariate analysis. The data also indicated that the co-expression of SALL4/ALDH1A1 was an independent prognostic factor affecting PFS. Moreover, the co-expression of SALL4/ALDH1A1 added prognostic values of DSS in patients with SOC who had grade III versus grade I in multivariate analysis. CONCLUSIONS: Our data demonstrated that high co-expression of SALL4/ALDH1A1 was found to be significantly associated with tumor aggressiveness and worse DSS or PFS in SOC patients. Therefore, co-expression of SALL4/ALDH1A1 may serve as a potential prognostic biomarker of cancer progression in these cases.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".