Peter MacCallum cancer Centre, Melbourne, VIC, Australia
Andrea Knox , Heidi Fettke , Christine Hauser , Patricia Bukczynska , Nicole Ng , Siavash Foroughi , Lisa-Jane K. Graham , Kate Lynette Mahon , Winston Tan , Tiantian Zheng , Chao Dai , Pan Du , Shidong Jia , Lisa Horvath , Manish Kohli , Arun Azad , Edmond Michael Kwan , Amy Wang
Background: With the evolving use of targeted therapies exploiting genomic vulnerabilities in mCRPC, screening patients for sensitizing alterations is of increasing relevance. However, the influence of age on the detection of relevant genomic alterations is incompletely understood. In this study, we compared the cell-free DNA (cfDNA) profiles of younger (age <70) versus older (age ≥70) men with mCRPC and assessed the relative prognostic impact of common genomic alterations. Methods: A next-generation sequencing-based Predicine cfDNA assay was used to profile 276 mCRPC patients from two independent international cohorts. The frequency of genomic alterations across age categories was compared using the chi-squared test, while circulating tumour DNA fraction (ctDNA%) was compared using the Mann–Whitney U test. Cox proportional hazards analysis with interaction testing was used to assess the association between age, genomic alteration and overall survival. Results: The median age of the combined cohort was 72 years (IQR 66-78), with 170 (62%) patients ≥70 years old. Despite differences in baseline characteristics (poorer performance status in older patients, higher Gleason score and denovo metastatic disease in younger patients), there was no significant difference in ctDNA% (median 22% vs 30%, p=0.6). We observed similar frequencies of genomic alterations across the 10 most commonly aberrant genes, including AR (<70 vs ≥70: 46% vs 49%, p=0.6), TP53 (40% vs 36%, p=0.6), BRCA2 (29% vs 21%, p=0.13) and PTEN (39% vs 35%, p=0.5). This similarity persisted when analysing mutations and copy number alterations in isolation. While driver alterations in both age categories were strongly associated with unfavourable outcomes (Table), an exploratory analysis revealed that copy number gain in PIK3CA may have a worse prognostic impact in younger men (p for interaction = 0.03), with a lesser effect observed in AR gain (p = 0.1) and MYC gain (p = 0.1). Conclusions: The genomic profiles of pertinent alterations between younger and older men are comparable. Certain genomic alterations may carry a worse prognosis in younger men. Patients should be considered for precision medicine assessment and directed therapies, regardless of age.
<70 yo HR (95% CI) | ≥70 yo HR (95% CI) | Interaction p value | |
---|---|---|---|
AR gain | 4.3 (2.6-7.1) | 2.7 (1.9-3.9) | 0.10 |
AR mutation | 1.0 (0.56-1.8) | 1.8 (1.2-2.7) | 0.16 |
TP53 loss | 3.0 (1.7-5.2) | 2.9 (1.7-4.7) | 0.74 |
TP53 mutation | 2.2 (1.3-3.5) | 1.4 (0.94-2.0) | 0.14 |
PTEN loss | 3.4 (2.1-5.5) | 2.7 (1.8-3.9) | 0.27 |
PIK3CA gain | 4.2 (2.4-7.5) | 1.9 (1.2-3.0) | 0.03 |
BRCA2 loss | 2.5 (1.5-4.1) | 2.3 (1.5-3.6) | 0.59 |
MYC gain | 3.6 (2.1-6.2) | 2.1 (1.3-3.3) | 0.10 |
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