Department of Medical Oncology and Therapeutics, City of Hope Comprehensive Cancer Center, Monrovia, CA, USA.
Neuro Oncology Program, Inova Schar Cancer Institute, Fairfax, VA, USA.
Mol Syst Biol. 2022 Jun;18(6):e10558. doi: 10.15252/msb.202110558.
Advanced and metastatic estrogen receptor-positive (ER ) breast cancers are often endocrine resistant. However, endocrine therapy remains the primary treatment for all advanced ER breast cancers. Treatment options that may benefit resistant cancers, such as add-on drugs that target resistance pathways or switching to chemotherapy, are only available after progression on endocrine therapy. Here we developed an endocrine therapy prognostic model for early and advanced ER breast cancers. The endocrine resistance (ENDORSE) model is composed of two components, each based on the empirical cumulative distribution function of ranked expression of gene signatures. These signatures include a feature set associated with long-term survival outcomes on endocrine therapy selected using lasso-regularized Cox regression and a pathway-based curated set of genes expressed in response to estrogen. We extensively validated ENDORSE in multiple ER clinical trial datasets and demonstrated superior and consistent performance of the model over clinical covariates, proliferation markers, and multiple published signatures. Finally, genomic and pathway analyses in patient data revealed possible mechanisms that may help develop rational stratification strategies for endocrine-resistant ER breast cancer patients.
晚期和转移性雌激素受体阳性(ER)乳腺癌通常对内分泌治疗有抗性。然而,内分泌治疗仍然是所有晚期 ER 乳腺癌的主要治疗方法。对于耐药性癌症可能有益的治疗选择,例如针对耐药途径的附加药物或改用化疗,仅在内分泌治疗进展后才可用。在这里,我们为早期和晚期 ER 乳腺癌开发了一种内分泌治疗预后模型。该模型由两个部分组成,每个部分都基于基因表达谱排名的经验累积分布函数。这些特征集包括使用套索正则化 Cox 回归选择的与内分泌治疗长期生存结果相关的特征集,以及基于通路的一组对雌激素有反应的基因。我们在多个 ER 临床试验数据集中广泛验证了 ENDORSE,并证明该模型在临床协变量、增殖标志物和多个已发表的特征集上具有优越且一致的性能。最后,对患者数据的基因组和通路分析揭示了可能有助于为内分泌抵抗性 ER 乳腺癌患者制定合理分层策略的潜在机制。