Homologous Recombination Deficiency in Pancreatic Cancer: A Systematic Review and Prevalence Meta-Analysis

Abstract

Purpose: To analyze the prevalence of homologous recombination deficiency (HRD) in patients with pancreatic ductal adenocarcinoma (PDAC).

Materials and methods: We conducted a systematic review and meta-analysis of the prevalence of HRD in PDAC from PubMed, Scopus, and Cochrane Library databases, and online cancer genomic data sets. The main outcome was pooled prevalence of somatic and germline mutations in the better characterized HRD genes (BRCA1, BRCA2, PALB2, ATM, ATR, CHEK2, RAD51, and the FANC genes). The secondary outcomes were prevalence of germline mutations overall, and in sporadic and familial cases; prevalence of germline BRCA1/2 mutations in Ashkenazi Jewish (AJ); and prevalence of HRD based on other definitions (ie, alterations in other genes, genomic scars, and mutational signatures). Random-effects modeling with the Freeman-Tukey transformation was used for the analyses. PROSPERO registration number: (CRD42020190813).

Results: Sixty studies with 21,842 participants were included in the systematic review and 57 in the meta-analysis. Prevalence of germline and somatic mutations was BRCA1: 0.9%, BRCA2: 3.5%, PALB2: 0.2%, ATM: 2.2%, CHEK2: 0.3%, FANC: 0.5%, RAD51: 0.0%, and ATR: 0.1%. Prevalence of germline mutations was BRCA1: 0.9% (2.4% in AJ), BRCA2: 3.8% (8.2% in AJ), PALB2: 0.2%, ATM: 2%, CHEK2: 0.3%, and FANC: 0.4%. No significant differences between sporadic and familial cases were identified. HRD prevalence ranged between 14.5%-16.5% through targeted next-generation sequencing and 24%-44% through whole-genome or whole-exome sequencing allowing complementary genomic analysis, including genomic scars and other signatures (surrogate markers of HRD).

Conclusion: Surrogate readouts of HRD identify a greater proportion of patients with HRD than analyses limited to gene-level approaches. There is a clear need to harmonize HRD definitions and to validate the optimal biomarker for treatment selection. Universal HRD screening including integrated somatic and germline analysis should be offered to all patients with PDAC.

FIG 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart of patient selection for the meta-analysis.

FIG 2.

Overview of HRD identification and clinical implications. Although WGS represents the most comprehensive method for HRD identification as it delivers integrated analyses of all genomic events, many barriers limit its utilization in the clinic, feasibility of accessing fresh biopsy material of sufficient size, cost, and analytic complexity. WES is a more accessible strategy and is often proposed as the second choice. However, it seems not to be the optimal method for cancer profiling as many driver events occur outside the coding exome may be missed, on one hand, and the majority of included genes are not cancer genes, on the other. Despite some technical limitations, targeted-capture sequencing delivering comprehensive genomic information, including individual gene mutations, signatures, and structural variation patterns, may represent a reasonable option for real-world applicability (practical and financial advantages compared with WES and WGS). Rating level of sequencing technologies: ++, optimal; +, good; ±, low; –, poor. ^aFunctional assays for real-time HRD status require in vivo or in vitro experiments. CNA, copy-number alterations; HRD, homologous recombination deficiency; LOH, loss of heterozygosity; LST, large-scale transitions; NGS, next-generation sequencing; PDCL, patient-derived cell lines; PDO, patient-derived organoids; PDX, patient-derived xenograft; TAI, telomeric allelic imbalance; WES, whole-exome sequencing; WGS, whole-genome sequencing.