Genomic Insights into Idiopathic Granulomatous Mastitis through Whole-Exome Sequencing: A Case Report of Eight Patients

Abstract

Idiopathic granulomatous mastitis (IGM) is a rare condition characterised by chronic inflammation and granuloma formation in the breast. The aetiology of IGM is unclear. By focusing on the protein-coding regions of the genome, where most disease-related mutations often occur, whole-exome sequencing (WES) is a powerful approach for investigating rare and complex conditions, like IGM. We report WES results on paired blood and tissue samples from eight IGM patients. Samples were processed using standard genomic protocols. Somatic variants were called with two analytical pipelines: nf-core/sarek with Strelka2 and GATK4 with Mutect2. Our WES study of eight patients did not find evidence supporting a clear genetic component. The discrepancies between variant calling algorithms, along with the considerable genetic heterogeneity observed amongst the eight IGM cases, indicate that common genetic drivers are not readily identifiable. With only three genes, CHIT1, CEP170, and CTR9, recurrently altering in multiple cases, the genetic basis of IGM remains uncertain. The absence of validation for somatic variants by Sanger sequencing raises further questions about the role of genetic mutations in the disease. Other potential contributors to the disease should be explored.

Keywords: breast abscess; breast cancer; breast pathology; idiopathic granulomatous mastitis; mastitis; pathogenic mutations; somatic mutations; suppurative breast lesion; tuberculous mastitis; whole-exome sequencing.

Figure 1

Single-nucleotide variants (SNVs) and insertion and deletion variants (indels) called by Strelka2 and Mutect2, from (a) matched blood/tissue samples and (b) blood samples.

Figure 2

Mutations annotated by Funcotator from variants called with Strelka2 and Mutect2 matched blood/tissue samples. (a) All non-synonymous mutations annotated from Strelka2 and Mutect2 variant calls. Red-dotted line represents median of 11.5 and 49 variants per sample annotated, respectively. (b) Protein-truncating variants (nonsense mutations and frameshift insertions and deletions) annotated from Strelka2 and Mutect 2 variant calls.

Figure 3

Altered genes in PTVs from Strelka2 and Mutect2 matched blood/tissue variant calling.

Figure 4

Patient recruitment, inclusion, and exclusion flowchart.