Small proline-rich protein 1A promotes lung adenocarcinoma progression and indicates unfavorable clinical outcomes
Bibliographic record
Abstract
Small proline-rich protein 1A (SPRR1A) plays a critical role in regulating squamous cell differentiation. SPRR1A overexpression was reported to be closely related to the progression of some tumors, such as gastric cancer and colon cancer. However, the function of SPRR1A in lung adenocarcinoma (LUAD) has not been elucidated. Here, we first examined the expression pattern of SPRR1A in LUAD tissues, which indicated that the SPRR1A expression level was significantly elevated in LUAD tissues compared with normal lung tissues. High expression of SPRR1A was closely related to larger tumor size. LUAD patients with higher SPRR1A expression had poorer overall survival and SPRR1A was identified as an independent unfavorable prognosis factor. In addition, the effects of SPRR1A on lung cancer cells were tested through cellular experiments and the result demonstrated that knockdown of SPRR1A can suppress the proliferation and invasion capacities of tumor cells, while overexpressing SPRR1A exerted opposite effects. Finally, our findings were substantiated by the data obtained from in vivo xenografts using a mice model. In conclusion, LUAD patients with higher SPRR1A expression were more predisposed to poorer clinical outcomes and unfavorable prognoses, indicating the potential role of SPRR1A as a novel clinical biomarker and therapeutic target.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 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".