Expression of the RPSA-Containing and 67EBP Laminin Receptors in Relation to the Debatable Nature of the 67 kDa Laminin Receptor 67LR in Colorectal Cancer
Bibliographic record
Abstract
The role of laminin receptors in colorectal cancer (CRC) is the subject of ongoing research. Histopathological studies have suggested that the 67 kDa laminin receptor (67LR) is involved in the carcinogenesis of various malignancies, including CRC. However, the exact composition and nature of 67LR have been a source of confusion for many years. A recent study from our group reported that the 37 kDa form of RPSA participates as a laminin receptor renamed the RPSA-containing laminin receptor (RCLR) but is not the precursor form of the 67LR since the 67 kDa protein associated with 67LR corresponds to the 67 kDa elastin-binding protein (67EBP), which also acts as a laminin receptor. The present study aims to analyze the distinct expression patterns of these two laminin receptor components in CRC. Expressions of RCLR and 67EBP were analyzed in CRC tissues using Western blot and quantitative RT-PCR analyses. The primary colorectal adenocarcinoma tissues and corresponding resection margins showed an overexpression of both RPSA and 67EBP at the protein level in the CRC tissues. An analysis of the publicly available CRC datasets confirmed the overexpression of RPSA and 67EBP in CRC tissues. In conclusion, the elevated expression of these two non-integrin laminin receptors in CRC lesions suggests their critical roles in colorectal carcinogenesis and emphasizes their potential usefulness as tissue biomarkers.
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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 | 0.001 |
| 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".