Heterozygous mutations in the <i>PALB2</i> hereditary breast cancer predisposition gene impact on the three‐dimensional nuclear organization of patient‐derived cell lines
Bibliographic record
Abstract
PALB2/FANCN is a BRCA1- and BRCA2-interacting Fanconi Anemia (FA) protein crucial for key BRCA2 genome caretaker functions. Heterozygous germline mutations in PALB2 predispose to breast cancer and biallelic mutations cause FA. FA proteins play a critical role in the telomere maintenance pathway, with telomeric shortening observed in FA cells. Less is known about telomere maintenance in the heterozygous state. Here, we investigate the roles of PALB2 heterozygous mutations in genomic instability, an important carcinogenesis precursor. Patient-derived lymphoblastoid (LCL) and fibroblast (FCL) cell lines with monoallelic truncating PALB2 mutations were investigated using a combination of molecular imaging techniques including centromeric FISH, telomeric Q-FISH and spectral karyotyping (SKY). Mitomycin C and Cisplatin sensitivity was assayed via cellular metabolism of WST-1. The PALB2 c.229delT FCL showed increases in telomere counts associated with increased mean intensity compared with two wild-type FCLs generated from first-degree relatives (P =1.04E-10 and P =9.68E-15) and it showed evidence of chromosomal rearrangements. Significant differences in centromere distribution were observed in one of three PALB2 heterozygous FCLs analyzed when compared with PALB2 wild-type, BRCA1 and BRCA2 heterozygous FCLs. No significant consistently increased sensitivity to Mitomycin C or Cisplatin was observed in LCLs. Our results are suggestive of an altered centromere distribution profile and a telomere instability phenotype. Together, these may indicate critical nuclear organization defects associated with the predisposition to transformation and early stage development of PALB2-related cancers.
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".