Distinct pancreatic and neuronal Lung Carcinoid molecular subtypes revealed by integrative omic analysis
Bibliographic record
Abstract
Summary Lung Carcinoids (L-CDs) are uncommon low-grade neuroendocrine tumours that are only recently becoming characterised at the molecular level. Notably data on the molecular events that precipitate altered gene expression programmes are very limited. Here we have identified two discrete L-CD subtypes from transcriptomic and whole-genome DNA methylation data, and comprehensively defined their molecular profiles using Whole-Exome Sequencing (WES) and Single Nucleotide Polymorphism (SNP) genotyping. Subtype (Group) 1 features upregulation of neuronal markers (L-CD-NeU) and is characterised by focal spindle cell morphology, peripheral location (71%), high mutational load ( P =3.4×10 −4 ), recurrent copy number alterations and is enriched for Atypical Lung Carcinoids. Group 2 (L-CD-PanC) are centrally located and feature upregulation of pancreatic and metabolic pathway genes concordant with promoter hypomethylation of beta cell and genes related to insulin secretion ( P <1×10 −6 ). L-CD-NeU tumours harbour mutations in chromatin remodelling and in SWI/SNF complex members, while L-CD-PanC tumours show aflatoxin mutational signatures and significant DNA methylation loss genome-wide, particularly enriched in repetitive elements ( P <2.2 × 10 −16 ). Our findings provide novel insights into the distinct mechanisms of epigenetic dysregulation in these lung malignancies, potentially opening new avenues for biomarker selection and treatment in L-CD patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".