Human Pluripotent Stem Cell–Derived <i>TSC2</i> -Haploinsufficient Smooth Muscle Cells Recapitulate Features of Lymphangioleiomyomatosis
Bibliographic record
Abstract
Abstract Lymphangioleiomyomatosis (LAM) is a progressive destructive neoplasm of the lung associated with inactivating mutations in the TSC1 or TSC2 tumor suppressor genes. Cell or animal models that accurately reflect the pathology of LAM have been challenging to develop. Here, we generated a robust human cell model of LAM by reprogramming TSC2 mutation–bearing fibroblasts from a patient with both tuberous sclerosis complex (TSC) and LAM (TSC-LAM) into induced pluripotent stem cells (iPSC), followed by selection of cells that resemble those found in LAM tumors by unbiased in vivo differentiation. We established expandable cell lines under smooth muscle cell (SMC) growth conditions that retained a patient-specific genomic TSC2+/− mutation and recapitulated the molecular and functional characteristics of pulmonary LAM cells. These include multiple indicators of hyperactive mTORC1 signaling, presence of specific neural crest and SMC markers, expression of VEGF-D and female sex hormone receptors, reduced autophagy, and metabolic reprogramming. Intriguingly, the LAM-like features of these cells suggest that haploinsufficiency at the TSC2 locus contributes to LAM pathology, and demonstrated that iPSC reprogramming and SMC lineage differentiation of somatic patient cells with germline mutations was a viable approach to generate LAM-like cells. The patient-derived SMC lines we have developed thus represent a novel cellular model of LAM that can advance our understanding of disease pathogenesis and develop therapeutic strategies against LAM. Cancer Res; 77(20); 5491–502. ©2017 AACR.
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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 | 0.001 |
| 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".