Genome profiles of lymphovascular breast cancer cells reveal multiple clonally differentiated outcomes with multi-regional LCM and G&T-seq
Bibliographic record
Abstract
Lymphovascular invasion (LVI) is a critical step in the metastatic process but has received relatively little attention due to the technical challenges associated with their isolation. In this study, we used laser capture microdissection (LCM) to isolate 97 cancer cell clusters from pathological frozen sections within lymphatic vessels, primary tumor tissue, and axillary lymph nodes of a triple negative breast cancer (TNBC) patient. Simultaneous genome and transcriptome amplification and sequencing (G&T-seq) performed on these clusters permitted a comprehensive depiction of the genomic and transcriptional profiles of cancer cells associated with LVI. Combination phylogeny analysis pointed to three evolutionarily distinct pathways of tumor clone development and metastasis in this patient, each of which was associated with a unique mRNA signature, and correlated to disparate overall survival outcomes. Moreover, hub gene evaluation found extensive down regulation of ribosomal protein mRNA to be a potential marker of poor prognosis in breast cancer patients.
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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".