BRST5:The polygenic component of breast cancer susceptibility: Difference between revisions

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<span style="color:#0070C0">(''General Instructions – The main focus of these pages is the clinically significant genetic alterations in each disease type. Use [https://www.genenames.org/ <u>HUGO-approved gene names and symbols</u>] (italicized when appropriate), [https://varnomen.hgvs.org/ HGVS-based nomenclature for variants], as well as generic names of drugs and testing platforms or assays if applicable. Please complete tables whenever possible and do not delete them (add N/A if not applicable in the table and delete the examples); to add (or move) a row or column to a table, click nearby within the table and select the > symbol that appears to be given options. Please do not delete or alter the section headings. The use of bullet points alongside short blocks of text rather than only large paragraphs is encouraged. Additional instructions below in italicized blue text should not be included in the final page content. Please also see'' </span><u>''[[Author_Instructions]]''</u><span style="color:#0070C0"> ''and [[Frequently Asked Questions (FAQs)|<u>FAQs</u>]] as well as contact your [[Leadership|<u>Associate Editor</u>]] or [mailto:CCGA@cancergenomics.org <u>Technical Support</u>])''</span>
<span style="color:#0070C0">(''General Instructions – The main focus of these pages is the clinically significant genetic alterations in each disease type. Use [https://www.genenames.org/ <u>HUGO-approved gene names and symbols</u>] (italicized when appropriate), [https://varnomen.hgvs.org/ HGVS-based nomenclature for variants], as well as generic names of drugs and testing platforms or assays if applicable. Please complete tables whenever possible and do not delete them (add N/A if not applicable in the table and delete the examples); to add (or move) a row or column to a table, click nearby within the table and select the > symbol that appears to be given options. Please do not delete or alter the section headings. The use of bullet points alongside short blocks of text rather than only large paragraphs is encouraged. Additional instructions below in italicized blue text should not be included in the final page content. Please also see'' </span><u>''[[Author_Instructions]]''</u><span style="color:#0070C0"> ''and [[Frequently Asked Questions (FAQs)|<u>FAQs</u>]] as well as contact your [[Leadership|<u>Associate Editor</u>]] or [mailto:CCGA@cancergenomics.org <u>Technical Support</u>])''</span>
==Primary Author(s)*==
==Primary Author(s)*==
Xiaolin Hu
Xiaolin Hu, GeneDx
==WHO Classification of Disease==
==WHO Classification of Disease==
<span style="color:#0070C0">(Will be autogenerated; Book will include name of specific book and have a link to the online WHO site)</span>
<span style="color:#0070C0">(Will be autogenerated; Book will include name of specific book and have a link to the online WHO site)</span>
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==Definition / Description of Disease==
==Definition / Description of Disease==
The polygenic component of breast cancer refers to the combined effect of many common SNPs, each conferring a small increase in risk, typically under 1.3-fold. Identified mainly through GWAS, these low-penetrance variants collectively explain 18–20% of familial breast cancer risk and are quantified using a polygenic risk score (PRS).
The polygenic component of breast cancer refers to the combined effect of many common SNPs, each conferring a small increase in risk, typically under 1.3-fold. Identified mainly through GWAS, these low-penetrance variants collectively explain 18–20% of familial breast cancer risk and are quantified using a polygenic risk score (PRS) <ref>{{Cite journal|last=Michailidou|first=Kyriaki|last2=Lindström|first2=Sara|last3=Dennis|first3=Joe|last4=Beesley|first4=Jonathan|last5=Hui|first5=Shirley|last6=Kar|first6=Siddhartha|last7=Lemaçon|first7=Audrey|last8=Soucy|first8=Penny|last9=Glubb|first9=Dylan|date=2017-11-02|title=Association analysis identifies 65 new breast cancer risk loci|url=https://pubmed.ncbi.nlm.nih.gov/29059683|journal=Nature|volume=551|issue=7678|pages=92–94|doi=10.1038/nature24284|issn=1476-4687|pmc=5798588|pmid=29059683}}</ref><ref>{{Cite journal|last=Mavaddat|first=Nasim|last2=Pharoah|first2=Paul D. P.|last3=Michailidou|first3=Kyriaki|last4=Tyrer|first4=Jonathan|last5=Brook|first5=Mark N.|last6=Bolla|first6=Manjeet K.|last7=Wang|first7=Qin|last8=Dennis|first8=Joe|last9=Dunning|first9=Alison M.|date=2015-05|title=Prediction of breast cancer risk based on profiling with common genetic variants|url=https://pubmed.ncbi.nlm.nih.gov/25855707|journal=Journal of the National Cancer Institute|volume=107|issue=5|pages=djv036|doi=10.1093/jnci/djv036|issn=1460-2105|pmc=4754625|pmid=25855707}}</ref>.
==Synonyms / Terminology==
==Synonyms / Terminology==
Polygenic breast cancer risk; Common low-penetrance breast cancer alleles
Polygenic breast cancer risk; Common low-penetrance breast cancer alleles
==Epidemiology / Prevalence==
==Epidemiology / Prevalence==
Over 170 low-penetrance alleles have been identified, primarily in populations of European descent, accounting for approximately 18% of familial breast cancer risk. These loci are found in the general population with varying allele frequencies and are being increasingly incorporated into risk prediction models.
Over 170 low-penetrance alleles have been identified, primarily in populations of European descent, accounting for approximately 18% of familial breast cancer risk<ref>{{Cite journal|last=Adam|first=Kevin|last2=Hunter|first2=Tony|date=2018-02|title=Histidine kinases and the missing phosphoproteome from prokaryotes to eukaryotes|url=https://pubmed.ncbi.nlm.nih.gov/29058706|journal=Laboratory Investigation; a Journal of Technical Methods and Pathology|volume=98|issue=2|pages=233–247|doi=10.1038/labinvest.2017.118|issn=1530-0307|pmc=5815933|pmid=29058706}}</ref>. These loci are found in the general population with varying allele frequencies and are being increasingly incorporated into risk prediction models.
==Clinical Features==
==Clinical Features==
<br />
<br />

Revision as of 09:52, 22 June 2025

(General Instructions – The main focus of these pages is the clinically significant genetic alterations in each disease type. Use HUGO-approved gene names and symbols (italicized when appropriate), HGVS-based nomenclature for variants, as well as generic names of drugs and testing platforms or assays if applicable. Please complete tables whenever possible and do not delete them (add N/A if not applicable in the table and delete the examples); to add (or move) a row or column to a table, click nearby within the table and select the > symbol that appears to be given options. Please do not delete or alter the section headings. The use of bullet points alongside short blocks of text rather than only large paragraphs is encouraged. Additional instructions below in italicized blue text should not be included in the final page content. Please also see Author_Instructions and FAQs as well as contact your Associate Editor or Technical Support)

Primary Author(s)*

Xiaolin Hu, GeneDx

WHO Classification of Disease

(Will be autogenerated; Book will include name of specific book and have a link to the online WHO site)

Structure Disease
Book
Category
Family
Type
Subtype(s)

Definition / Description of Disease

The polygenic component of breast cancer refers to the combined effect of many common SNPs, each conferring a small increase in risk, typically under 1.3-fold. Identified mainly through GWAS, these low-penetrance variants collectively explain 18–20% of familial breast cancer risk and are quantified using a polygenic risk score (PRS) [1][2].

Synonyms / Terminology

Polygenic breast cancer risk; Common low-penetrance breast cancer alleles

Epidemiology / Prevalence

Over 170 low-penetrance alleles have been identified, primarily in populations of European descent, accounting for approximately 18% of familial breast cancer risk[3]. These loci are found in the general population with varying allele frequencies and are being increasingly incorporated into risk prediction models.

Clinical Features


Signs and Symptoms EXAMPLE: Asymptomatic (incidental finding on complete blood counts)

EXAMPLE: B-symptoms (weight loss, fever, night sweats)

EXAMPLE: Lymphadenopathy (uncommon)

Laboratory Findings EXAMPLE: Cytopenias

EXAMPLE: Lymphocytosis (low level)

Sites of Involvement

Breast tissue (parenchyma)

Morphologic Features

Put your text here (Instructions: Brief description of typically approximately one paragraph)

Immunophenotype

N/A

Finding Marker
Positive (universal) EXAMPLE: CD1
Positive (subset)
Negative (universal)
Negative (subset)

Chromosomal Rearrangements (Gene Fusions)

N/A

Chromosomal Rearrangement Genes in Fusion (5’ or 3’ Segments) Pathogenic Derivative Prevalence Diagnostic Significance (Yes, No or Unknown) Prognostic Significance (Yes, No or Unknown) Therapeutic Significance (Yes, No or Unknown) Notes
EXAMPLE: t(9;22)(q34;q11.2) EXAMPLE: 3'ABL1 / 5'BCR EXAMPLE: der(22) EXAMPLE: 20% (COSMIC)

EXAMPLE: 30% (add reference)

EXAMPLE: Yes EXAMPLE: No EXAMPLE: Yes EXAMPLE:

The t(9;22) is diagnostic of CML in the appropriate morphology and clinical context (add reference). This fusion is responsive to targeted therapy such as Imatinib (Gleevec) (add reference).

Individual Region Genomic Gain / Loss / LOH

N/A

Chr # Gain / Loss / Amp / LOH Minimal Region Genomic Coordinates [Genome Build] Minimal Region Cytoband Diagnostic Significance (Yes, No or Unknown) Prognostic Significance (Yes, No or Unknown) Therapeutic Significance (Yes, No or Unknown) Notes
EXAMPLE:

7

EXAMPLE: Loss EXAMPLE:

chr7:1-159,335,973 [hg38]

EXAMPLE:

chr7

EXAMPLE: Yes EXAMPLE: Yes EXAMPLE: No EXAMPLE:

Presence of monosomy 7 (or 7q deletion) is sufficient for a diagnosis of AML with MDS-related changes when there is ≥20% blasts and no prior therapy (add reference). Monosomy 7/7q deletion is associated with a poor prognosis in AML (add reference).

EXAMPLE:

8

EXAMPLE: Gain EXAMPLE:

chr8:1-145,138,636 [hg38]

EXAMPLE:

chr8

EXAMPLE: No EXAMPLE: No EXAMPLE: No EXAMPLE:

Common recurrent secondary finding for t(8;21) (add reference).

Characteristic Chromosomal Patterns

N/A

Chromosomal Pattern Diagnostic Significance (Yes, No or Unknown) Prognostic Significance (Yes, No or Unknown) Therapeutic Significance (Yes, No or Unknown) Notes
EXAMPLE:

Co-deletion of 1p and 18q

EXAMPLE: Yes EXAMPLE: No EXAMPLE: No EXAMPLE:

See chromosomal rearrangements table as this pattern is due to an unbalanced derivative translocation associated with oligodendroglioma (add reference).

Gene Mutations (SNV / INDEL)

Put your text here and fill in the table (Instructions: This table is not meant to be an exhaustive list; please include only genes/alterations that are recurrent and common as well either disease defining and/or clinically significant. Can include references in the table. For clinical significance, denote associations with FDA-approved therapy (not an extensive list of applicable drugs) and NCCN or other national guidelines if applicable; Can also refer to CGC workgroup tables as linked on the homepage if applicable as well as any high impact papers or reviews of gene mutations in this entity. Do not delete table.)

Gene; Genetic Alteration Presumed Mechanism (Tumor Suppressor Gene [TSG] / Oncogene / Other) Prevalence (COSMIC / TCGA / Other) Concomitant Mutations Mutually Exclusive Mutations Diagnostic Significance (Yes, No or Unknown) Prognostic Significance (Yes, No or Unknown) Therapeutic Significance (Yes, No or Unknown) Notes
Multiple SNPs (e.g., FGFR2, MAP3K1, TOX3) Regulatory/epigenetic, not traditional oncogenes/TSGs Common, MAF >1% Varies Varies No Limited Yes (PRS applications Target gene expression changes may affect oncogenic pathways

Note: A more extensive list of mutations can be found in cBioportal (https://www.cbioportal.org/), COSMIC (https://cancer.sanger.ac.uk/cosmic), ICGC (https://dcc.icgc.org/) and/or other databases. When applicable, gene-specific pages within the CCGA site directly link to pertinent external content.

Epigenomic Alterations

Common variants are often located in enhancer regions, affecting chromatin accessibility, transcription factor binding, and gene expression regulation (e.g., at ESR1, FGFR2, MAP3K1 loci).

Genes and Main Pathways Involved


Gene; Genetic Alteration Pathway Pathophysiologic Outcome
MAP3K1 ERK1/2 cascade Altered signal transduction
FGFR2 FGF signaling Enhanced cell proliferation
TOX3 Transcriptional regulation Affects chromatin remodeling
ESR1 Estrogen signaling Influences hormone response in breast cancer

Genetic Diagnostic Testing Methods

Polygenic risk is assessed through genotyping panels or whole-genome SNP arrays followed by computational calculation of the PRS.

Familial Forms

These low-penetrance alleles can act additively or multiplicatively with rare high-penetrance pathogenic variants (e.g., BRCA1, BRCA2) and may modify cancer risk within families with hereditary breast and ovarian cancer syndromes.

Additional Information

The utility of PRS in clinical practice is growing, both for general population risk stratification and for risk modification in individuals with known pathogenic variants in high-risk genes.

Links

(use the "Link" icon that looks like two overlapping circles at the top of the page) (Instructions: Highlight text to which you want to add a link in this section or elsewhere, select the "Link" icon at the top of the page, and search the name of the internal page to which you want to link this text, or enter an external internet address by including the "http://www." portion.)

References

(use the "Cite" icon at the top of the page) (Instructions: Add each reference into the text above by clicking on where you want to insert the reference, selecting the “Cite” icon at the top of the page, and using the “Automatic” tab option to search such as by PMID to select the reference to insert. The reference list in this section will be automatically generated and sorted. If a PMID is not available, such as for a book, please use the “Cite” icon, select “Manual” and then “Basic Form”, and include the entire reference.)

Notes

*Primary authors will typically be those that initially create and complete the content of a page. If a subsequent user modifies the content and feels the effort put forth is of high enough significance to warrant listing in the authorship section, please contact the CCGA coordinators (contact information provided on the homepage). Additional global feedback or concerns are also welcome.

  1. Michailidou, Kyriaki; et al. (2017-11-02). "Association analysis identifies 65 new breast cancer risk loci". Nature. 551 (7678): 92–94. doi:10.1038/nature24284. ISSN 1476-4687. PMC 5798588. PMID 29059683.
  2. Mavaddat, Nasim; et al. (2015-05). "Prediction of breast cancer risk based on profiling with common genetic variants". Journal of the National Cancer Institute. 107 (5): djv036. doi:10.1093/jnci/djv036. ISSN 1460-2105. PMC 4754625. PMID 25855707. Check date values in: |date= (help)
  3. Adam, Kevin; et al. (2018-02). "Histidine kinases and the missing phosphoproteome from prokaryotes to eukaryotes". Laboratory Investigation; a Journal of Technical Methods and Pathology. 98 (2): 233–247. doi:10.1038/labinvest.2017.118. ISSN 1530-0307. PMC 5815933. PMID 29058706. Check date values in: |date= (help)