Germline mutations in the new E1’ cryptic exon of the <i>VHL</i> gene in patients with tumours of von Hippel-Lindau disease spectrum or with paraganglioma
Bibliographic record
Abstract
BACKGROUNDS: gene in patients with von Hippel-Lindau (VHL) disease and in patients with paraganglioma or pheochromocytoma (PPGL) is not currently known. METHODS: We studied a large international multicentre cohort of 1167 patients with a previous negative genetic testing. Germline DNA from 75 patients with a single tumour of the VHL spectrum ('Single VHL tumour' cohort), 70 patients with multiple tumours of the VHL spectrum ('Multiple VHL tumours' cohort), 76 patients with a VHL disease as described in the literature ('VHL-like' cohort) and 946 patients with a PPGL were screened for E1' genetic variants. RESULTS: Six different genetic variants in E1' were detected in 12 patients. Two were classified as pathogenic, 3 as variants of unknown significance and 1 as benign. The rs139622356 was found in seven unrelated patients but described in only 16 patients out of the 31 390 of the Genome Aggregation Database (p<0.0001) suggesting that this variant might be either a recurrent mutation or a modifier mutation conferring a risk for the development of tumours and cancers of the VHL spectrum. CONCLUSIONS: E1' cryptic exon mutations contribute to 1.32% (1/76) of 'VHL-like' cohort and to 0.11% (1/946) of PPGL cohort and should be screened in patients with clinical suspicion of VHL, and added to panels for Next Generation Sequencing (NGS) diagnostic testing of hereditary PPGL. Our data highlight the importance of studying variants identified in deep intronic sequences, which would have been missed by examining only coding sequences of genes/exomes. These variants will likely be more frequently detected and studied with the upcoming implementation of whole-genome sequencing into clinical practice.
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 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) | 0.000 | 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) | 0.000 | 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".