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Record W2885570830 · doi:10.1158/1538-7445.am2018-3007

Abstract 3007: Monogenic and polygenic associations with subsequent breast cancer risk in survivors of childhood cancer: The St. Jude Lifetime Cohort Study (SJLIFE)

2018· article· en· W2885570830 on OpenAlexaff
Zhaoming Wang, Carmen L. Wilson, Qi Liu, John Easton, Heather L. Mulder, Michael Rusch, Michael N. Edmonson, Shawn Levy, Aman Patel, Ying Shao, Ti‐Cheng Chang, Stephen V. Rice, Yadav Sapkota, Russell J. Brooke, Wonjong Moon, Evadnie Rampersaud, Xiaotu Ma, Cynthia Pepper, Xin Zhou, Xiang Chen, Wenan Chen, Angela Jones, Braden Boone, Matthew J. Ehrhardt, Rebecca M. Howell, Nicholas S. Phillips, Courtney Lewis, Chimene Kesserwan, Gang Wu, Kim E. Nichols, James R. Downing, Melissa M. Hudson, Jinghui Zhang, Yutaka Yasui, Leslie L. Robison

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCHEK2Odds ratioBreast cancerCancerMedicinePenetranceAllelePALB2PopulationGeneticsCohortOncologyIncidence (geometry)Internal medicineDemographyBiologyGermline mutationMutationGene

Abstract

fetched live from OpenAlex

Abstract The allelic spectrum of the genetic architecture of breast cancer (BC) susceptibility includes at least 172 common variants with small effect sizes (per-allele odds ratio range: 1.03-1.31), plus rare variants with high (BRCA1, BRCA2, CHD1, PTEN, STK11, TP53) or moderate penetrance (ATM, CHEK2, NBN, NF1, PALB2). While these common variants confer modest risk individually, their combined effect in the form of a polygenic risk score (PRS) may be substantial. The SJLIFE whole-genome sequencing (WGS) data provide a unique opportunity to evaluate common and rare sets of genetic variants jointly, along with treatment exposures, for their contributions to subsequent BC risk in adult survivors of childhood cancer. This analysis utilized WGS data from 1131 females of European ancestry [median age at last follow-up: 34.9 years (range: 6.2-68.6)] of whom 47 were diagnosed with a subsequent BC (median age at BC 40.3 years, range: 25.5-53.0). The PRS (mean, 10.1; range, 8.3-12.2) was calculated using a weighted sum of the number of risk alleles and their log per-allele odds ratio from Michailidou et al. (Nature, Nov. 2017). A total of 34 (3.0%) survivors were carriers of pathogenic or likely pathogenic (P/LP) variants in the 11 BC predisposition genes (listed above). The standardized incidence ratio (SIR) for BC was 6.7 (95% CI, 5.0-8.9) for survivors relative to the SEER population. The SIR varied from 3.7 (95% CI, 1.4-8.1) for survivors with PRS in the 1st quintile to 3.6 (95% CI, 1.2-8.3), 7.3 (95% CI, 3.8-12.7), 7.6 (95% CI, 3.6-14.0), and 11.4 (95% CI, 6.8-18.1) in the 2nd, 3rd, 4th, and 5th quintiles, respectively. In the multivariable model adjusting for age at diagnosis, chest irradiation, alkylating agents, anthracyclines, attained age, and significant genotype eigenvectors, the relative rates (RR) of BC were 16.5 (95% CI, 6.4 - 42.6), 11.5 (95% CI, 4.4-29.9), and 47.8 (95% CI, 8.2-278.3) for carriers vs. non-carriers of the P/LP variants among all survivors, and survivors with and without chest irradiation, respectively. The RR per one standard deviation of PRS were 1.5 (95% CI, 1.1-1.9), 1.6 (95% CI, 1.2-2.0) and 1.3 (95% CI, 0.7-2.2), respectively, for the same three groups. Importantly, PRS was significantly associated with the rate of subsequent BC under the age of 45 (RR, 1.7; 95% CI, 1.3-2.2) but not over 45 (RR, 0.9; 95% CI, 0.6-1.5). To our knowledge, this is the first assessment of the joint effects of rare and common genetic variations implicated in the etiology of BC in the general population, among long-term survivors of childhood cancer. Clinically, we anticipate that an individual genetic profile utilizing common susceptibility loci in combination with rare P/LP variants will inform an improved strategy for personalized BC risk stratification and management for childhood cancer survivors. Further replication studies are warranted to confirm and refine our findings. Citation Format: Zhaoming Wang, Carmen L. Wilson, Qi Liu, John Easton, Heather L. Mulder, Michael Rusch, Michael Edmonson, Shawn Levy, Aman Patel, Ying Shao, Ti-Cheng Chang, Stephen V. Rice, Yadav Sapkota, Russell J. Brooke, Wonjong Moon, Evadnie Rampersaud, Xiaotu Ma, Cynthia Pepper, Xin Zhou, Xiang Chen, Wenan Chen, Angela Jones, Braden Boone, Matthew J. Ehrhardt, Rebecca M. Howell, Nicholas Phillips, Courtney Lewis, Chimene A. Kesserwan, Gang Wu, Kim E. Nichols, James R. Downing, Melissa M. Hudson, Jinghui Zhang, Yutaka Yasui, Leslie L. Robison. Monogenic and polygenic associations with subsequent breast cancer risk in survivors of childhood cancer: The St. Jude Lifetime Cohort Study (SJLIFE) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3007.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.347
Teacher spread0.328 · 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
Published2018
Admission routes1
Has abstractyes

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