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Abstract P2-03-01: Mutational landscape of breast cancers from PALB2 germline mutation carriers

2017· article· en· W2503509770 on OpenAlexaff
KA Burke, Samuel Berman, FC Geyer, Salvatore Piscuoglio, CK Ng, YH Wen, Paolo Peterlongo, Carlo Tondini, Markéta Janatová, Tae-Hong Hwang, PS Ng, Lai‐Meng Looi, Georgia Chenevix‐Trench, Melissa C. Southey, Britta Weigelt, William D. Foulkes, Marc Tischkowitz, JS Reis‐Filho

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMcGill University
Fundersnot available
KeywordsPALB2Germline mutationBreast cancerLoss of heterozygosityGeneticsGermlineBiologyCancer researchExomeMutationMissense mutationAlleleExome sequencingCancerGene

Abstract

fetched live from OpenAlex

Abstract Background: The PALB2 gene encodes the partner and localizer of the BRCA2 protein, which participates in homologous recombination during DNA repair via an interaction with BRCA1 and BRCA2. Germline mutations in PALB2 are associated with an increased risk of breast cancer, with a cumulative risk of 35% by age 70 in female PALB2 mutant carriers. The aims of this project were to characterize the genomic landscape of PALB2 breast cancers and define the differences in the repertoire of somatic genetic alterations and mutational signatures between PALB2, BRCA1 and BRCA2 breast cancers. Methods: Representative samples from fourteen breast cancers from patients with known PALB2 germline mutations (seven frame-shift (2 H1170fs, 3 K346fs, 1 T841fs and 1 L531fs), five truncating (3 W1038* and 2 Q775*) and two missense (W1140G and L35P)) were microdissected to ensure a tumor cell content of >70%. DNA samples from microdissected tumors and their matched normal counterparts were subjected to whole exome sequencing on an Illumina HiSeq2000 to a median depth of 118x (range 33-193x). Somatic single nucleotide variations were detected using MuTect, and small insertions and deletions were identified using Strelka and Varscan2. Using ABSOLUTE and FACETS, we investigated the presence of loss of heterozygosity (LOH) of the PALB2 wild-type allele in these tumors. In addition, the mutational signatures and large scale state transitions (LSTs) were defined. The repertoire of somatic mutations identified in PALB2 breast cancers was compared to that of breast cancers from BRCA1 (n=11) and BRCA2 (n=10) germline mutation carriers from The Cancer Genome Atlas study. Results: PALB2 breast cancers were found to harbor a median of 80 somatic mutations (range 22-286) and one somatic mutation (range 0-13) affecting known cancer genes. Somatic loss of the PALB2 wild-type allele was found in five cases, and in three additional cases, a second PALB2 somatic mutation likely constituted the second 'hit' (two with truncating mutations, Q479* and Q61*, and one with a Q921fs frameshift mutation). Six PALB2 breast cancers displayed the BRCA mutations signature; of these, five had PALB2 bi-allelic inactivation (three LOH of the wild-type allele and two a second PALB2 somatic mutation). 71% of the samples were found to have LSTs, including all cases with a BRCA mutational signature. A significant association between PALB2 bi-allelic inactivation and concurrent BRCA signature and high LST was observed (p=0.015). Breast cancers from PALB2 mutation carriers had fewer somatic TP53 mutations than BRCA1 breast cancers (3/14, 21% vs 9/11, 82%, p=0.004), but no difference in the repertoire of somatic mutations compared to that of BRCA2 breast cancers. Conclusions: PALB2 breast cancers were found to harbor pathogenic mutations in driver genes, including TP53, PIK3CA, NF1 and NCOR1, however lacked highly recurrent somatic mutations. Unlike BRCA1/2 breast cancers, the majority of breast cancers from PALB2 germline mutation carriers lacked LOH of the PALB2 wild-type allele. Importantly, however, an association between PALB2 bi-allelic inactivation and the BRCA mutational signature and LSTs was observed, providing additional evidence for a homologous recombination-deficient phenotype at least in a subset of PALB2 cancers. Citation Format: Burke KA, Berman S, Geyer FC, Piscuoglio S, Ng CK, Wen YH, Mannermaa A, Peterlongo P, Tondini C, Janatova M, Soo Hwang T, Ng P-S, Looi LM, Chenevix-Trench G, Southey MC, Weigelt B, Foulkes W, Tischkowitz M, Reis-Filho JS, PALB2 Interest Group. Mutational landscape of breast cancers from PALB2 germline mutation carriers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-03-01.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.044
GPT teacher head0.393
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes1
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