Expression of Tetraspanin 4 Relative to Therapy-induced Senescence Markers in Breast Cancer in Response to Neoadjuvant Chemotherapy
Bibliographic record
Abstract
Therapy-induced senescence (TIS) is a component of breast cancer (BC) treatment. Tetraspanins have emerging roles in cancer biology. Tetraspanin 4 (TSPAN4 [ NAG2 ]) has been implicated in tumor progression, however, its association with TIS remains unexplored. We investigated TSPAN4 expression in BC samples from patients who received neoadjuvant chemotherapy (NAC) and its association with TIS markers. Thirty-eight paired pre- and post-NAC BC samples were analyzed using immunohistochemistry (IHC) staining for TSPAN4 and TIS-associated biomarkers (Lamin B1 and Ki67). Pairwise analysis of senescence-related gene expression ( LMNB1, MKI67, CDKN1A, ATM, IGFBP7, MMP2, CXCL14 , and CCL5) was performed in an independent geneset of 68 paired pre- and post-NAC BC patient samples. NAC reduced the expression of senescence-associated proliferation markers Ki67 and Lamin B1 in BC samples, with 84% and 76% of patients showing decreased expression, respectively ( p <0.001). Senescence-associated gene expression analysis revealed consistent upregulation of CDKN1A, ATM, IGFBP7, MMP2, CXCL14 , and CCL5 post-NAC ( p <0.001), while LMNB1 and MKI67 were significantly downregulated ( p<0.0001 and p =0.007, respectively). A subset (15/38; 39%) of samples demonstrated upregulation of the TSPAN4 expression post-NAC ( p <0.01). NAG2 was upregulated in 54/68 patients post-NAC ( p <0.00001) and its expression correlated positively with senescence-associated genes. An association between TSPAN4 and TIS post-NAC was identified.
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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 | 0.000 | 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) | 0.001 | 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".