Characterization of Distinct Populations of Carcinoma-Associated Fibroblasts from Non–Small Cell Lung Carcinoma Reveals a Role for ST8SIA2 in Cancer Cell Invasion
Bibliographic record
Abstract
Carcinoma-associated fibroblasts (CAFs) are abundant stromal cells in tumor microenvironment that are critically involved in cancer progression. Contrasting reports have shown that CAFs can have either pro- or antitumorigenic roles, indicating that CAFs are functionally heterogeneous. Therefore, to precisely target the cancer-promoting CAF subsets, it is necessary to identify specific markers to define these subpopulations and understand their functions. We characterized two CAFs subsets from 28 non-small cell lung cancer (NSCLC) patient tumors that were scored and classified based on desmoplasia [mainly characterized by proliferating CAFs; high desmoplastic CAFs (HD-CAF; n = 15) and low desmoplastic CAFs (LD-CAF; n = 13)], which is an independent prognostic factor. Here, for the first time, we demonstrate that HD-CAFs and LD-CAFs show different tumor-promoting abilities. HD-CAFs showed higher rate of collagen matrix remodeling, invasion, and tumor growth compared to LD-CAFs. Transcriptomic analysis identified 13 genes that were differentially significant (fold ≥1.5; adjusted P value < .1) between HD-CAFs and LD-CAFs. The top upregulated differentially expressed gene, ST8SIA2 (11.3 fold; adjusted P value = .02), enhanced NSCLC tumor cell invasion in 3D culture compared to control when it was overexpressed in CAFs, suggesting an important role of ST8SIA2 in cancer cell invasion. We confirmed the protumorigenic role of ST8SIA2, showing that ST8SIA2 was significantly associated with the risk of relapse in three independent NSCLC clinical datasets. In summary, our studies show that functional heterogeneity in CAF plays key role in promoting cancer cell invasion in NSCLC.
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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 | 0.000 |
| 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) | 0.000 | 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".