Hippo pathway in cancer cells induces NCAM1+αSMA+ fibroblasts to modulate tumor microenvironment
Bibliographic record
Abstract
Cancer cells adeptly manipulate the tumor microenvironment (TME) to evade host antitumor immunity. However, the role of cancer cell-intrinsic signaling in shaping the immunosuppressive TME remains unclear. Here, we found that the Hippo pathway in cancer cells orchestrates the TME by influencing the composition of cancer-associated fibroblasts (CAFs). In a 4T1 mouse breast cancer model, Hippo pathway kinases, large tumor suppressor 1 and 2 (LATS1/2), promoted the formation of neural cell adhesion molecule 1 (NCAM1)+alpha-smooth muscle actin (αSMA)+ CAFs expressing the transforming growth factor-β, which is associated with T cell inactivation and dysfunction. Depletion of LATS1/2 in cancer cells resulted in a less immunosuppressive TME, indicated by the reduced proportions of NCAM1+αSMA+ CAFs and dysfunctional T cells. Notably, similar Hippo pathway-induced NCAM1+αSMA+ CAFs were observed in human breast cancer, highlighting the potential of TME-manipulating strategies to reduce immunosuppression in cancer immunotherapy. Single-cell RNA sequencing reveals that the Hippo pathway in cancer cells influences the composition of cancer-associated fibroblasts and modulates the tumor microenvironment, thereby promoting cancer growth.
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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".