BMC cancer · 2026
Clinical prognostic value of homologous recombination repair axis markers and PARP1 expression in breast cancer: a systematic review, meta-analysis, and independent cohort validation.
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Shen Kezhen, Cai Lei, Wu Wei
Аннотация
BACKGROUND: Resistance to poly ADP-ribose polymerase (PARP) inhibitors limits durable clinical benefit in breast cancer. The translational relevance of resistance-associated genes to patient prognosis remains poorly characterized. This systematic review and meta-analysis evaluated the clinical prognostic value of homologous recombination repair axis markers and PARP1 expression in breast cancer.
METHODS: PubMed, Embase, and Web of Science were searched from January 2015 to April 2026 for studies reporting survival outcomes associated with PARP inhibitor resistance-associated or homologous recombination repair-related markers. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model, with subgroup, sensitivity, and independent TCGA validation analyses.
RESULTS: Eighteen studies (13,641 patients) met inclusion criteria. Primary meta-analysis (five studies, n = 909) showed that HR repair axis positivity was associated with reduced mortality risk (HR = 0.508, 95% CI: 0.411-0.627, p < 0.0001; I2 = 0%), with consistent effects in PARPi-treated (HR = 0.458) and untreated cohorts (HR = 0.557; p for interaction = 0.363). Vote-counting of PARP1 expression (four studies) found three studies reporting high expression as a risk factor, one study protective. TCGA validation suggested an association with worse survival (HR = 1.437, p = 0.013), but this was threshold-dependent and non-significant with an upper-quartile cut-off (p = 0.504). Of note, TCGA assessed mRNA expression, which does not directly measure functional HR deficiency. Evidence for PARP1 as an adverse prognostic marker remains inconclusive. A clinical prioritization framework was developed for HR repair axis markers.
CONCLUSIONS: HR repair axis positivity is associated with reduced mortality risk in breast cancer, independent of PARPi exposure. High PARP1 expression shows an inconclusive prognostic role. These findings support a conceptual distinction between functional HR deficiency and transcriptional biomarker overexpression. However, primary findings are based on limited studies (k = 5) and require prospective validation.
METHODS: PubMed, Embase, and Web of Science were searched from January 2015 to April 2026 for studies reporting survival outcomes associated with PARP inhibitor resistance-associated or homologous recombination repair-related markers. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model, with subgroup, sensitivity, and independent TCGA validation analyses.
RESULTS: Eighteen studies (13,641 patients) met inclusion criteria. Primary meta-analysis (five studies, n = 909) showed that HR repair axis positivity was associated with reduced mortality risk (HR = 0.508, 95% CI: 0.411-0.627, p < 0.0001; I2 = 0%), with consistent effects in PARPi-treated (HR = 0.458) and untreated cohorts (HR = 0.557; p for interaction = 0.363). Vote-counting of PARP1 expression (four studies) found three studies reporting high expression as a risk factor, one study protective. TCGA validation suggested an association with worse survival (HR = 1.437, p = 0.013), but this was threshold-dependent and non-significant with an upper-quartile cut-off (p = 0.504). Of note, TCGA assessed mRNA expression, which does not directly measure functional HR deficiency. Evidence for PARP1 as an adverse prognostic marker remains inconclusive. A clinical prioritization framework was developed for HR repair axis markers.
CONCLUSIONS: HR repair axis positivity is associated with reduced mortality risk in breast cancer, independent of PARPi exposure. High PARP1 expression shows an inconclusive prognostic role. These findings support a conceptual distinction between functional HR deficiency and transcriptional biomarker overexpression. However, primary findings are based on limited studies (k = 5) and require prospective validation.