Genomic Signatures in Luminal Breast Cancer

Puppe, Julian; Seifert, Tabea; Eichler, Christian; Pilch, Henryk; Mallmann, Peter; Malter, Wolfram

doi:10.1159/000509846

Cited by 26 publications

(31 citation statements)

References 98 publications

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“…Several molecular assays are now available for hormone receptor-positive/HER2-negative breast cancer 25 , and, recently, some molecular assays have been also developed for HER2-positive disease 26 .…”

Section: Discussionmentioning

confidence: 99%

PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer

et al. 2022

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The prognostic performance of PREDICT in patients with HER2-positive early breast cancer (EBC) treated in the modern era with effective chemotherapy and anti-HER2 targeted therapies is unclear. Therefore, we investigated its prognostic performance using data extracted from ALTTO, a phase III trial evaluating adjuvant lapatinib ± trastuzumab vs. trastuzumab alone in patients with HER2-positive EBC. Our analysis included 2794 patients. After a median follow-up of 6.0 years (IQR, 5.8–6.7), 182 deaths were observed. Overall, PREDICT underestimated 5-year OS by 6.7% (95% CI, 5.8–7.6): observed 5-year OS was 94.7% vs. predicted 88.0%. The underestimation was consistent across all subgroups, including those according to the type of anti HER2-therapy. The highest absolute differences were observed for patients with hormone receptor negative-disease, nodal involvement, and large tumor size (13.0%, 15.8%, and 15.3%, respectively). AUC under the ROC curve was 73.7% (95% CI 69.7–77.8) in the overall population, ranging between 61.7% and 77.7% across the analyzed subgroups. In conclusion, our analysis showed that PREDICT highly underestimated OS in HER2-positive EBC. Hence, it should be used with caution to give prognostic estimation to HER2-positive EBC patients treated in the modern era with effective chemotherapy and anti-HER2 targeted therapies.

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Section: Discussionmentioning

confidence: 99%

PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer

et al. 2022

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“… 7 , 8 Thus, while adjuvant endocrine therapy is recommended for nearly all patients with operable HR-positive breast cancer, only a subset of patients with a higher risk for recurrence benefit from adjuvant chemotherapy. 9 Traditionally, the decision to pursue aggressive treatment in HR-positive HER2-negative breast cancer has relied on a combination of clinical features such as age and menopausal status, as well as clinicopathologic factors such as tumor size, grade, lymph node involvement and intrinsic subtyping, which depends on the quantitative measurement of estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 by immunohistochemistry. 10 , 11 While intrinsic subtyping and histopathological evaluation can help determine prognosis, the reliance on these features as a risk stratification tool is limited by their lack of standardization across laboratories.…”

Section: Development and Uptake Of Oncotype DX Rsmentioning

confidence: 99%

Oncotype DX Recurrence Score in premenopausal women

2022

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In the past 20 years, clinicians have shifted away from relying solely on clinicopathologic indicators toward increasing use of multigene expression assays in guiding treatment decisions regarding adjuvant chemotherapy for early-stage hormone receptor (HR)-positive, HER2-negative breast cancer. Oncotype DX Recurrence Score (RS) is one of the most widely used multigene assays when considering indications for adjuvant chemotherapy, and guidelines have recently incorporated its use in women with early HR-positive HER2-negative breast cancer and up to three positive lymph nodes. While multiple retrospective and prospective clinical studies have demonstrated that most women with a low- to mid-range RS (0–25) can safely forgo chemotherapy, premenopausal women remain an important subgroup for which recommendations based on RS are ill-defined. The majority of patients included in clinical trials and retrospective analyses validating the use of RS have been postmenopausal women. In the subgroup of premenopausal women with HR-positive HER2-negative breast cancer, studies indicate that traditional clinicopathologic methods for assessing risk continue to be powerful tools when combined with RS to predict benefit from chemotherapy. This suggests that there is an element of uncaptured risk inherent to the premenopausal state that evades characterization by RS alone. This review describes the evidence that has supported the recommendation of RS in clinical guidelines, specifically focusing on data for its current use in premenopausal women. We review available data regarding the impact of the menstrual cycle on hormonally regulated gene expression, which may drive variations in the RS. Further research on the reliability and interpretation of the RS in the premenopausal subgroup is necessary and represents a gap in knowledge of how the RS should be applied in premenopausal women.

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“…Compared with a single biomarker, multigene signatures have been proven to produce a higher accuracy prognosis [ 14 ]. Previous studies have primarily focused on the prognostic value of the ferroptosis-related signature [ 15 ] and immune-related signature [ 16 ] in breast cancer.…”

Section: Introductionmentioning

confidence: 99%

An iron metabolism and immune related gene signature for the prediction of clinical outcome and molecular characteristics of triple-negative breast cancer

Zhang

et al. 2022

BMC Cancer

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Background An imbalance of intracellular iron metabolism can lead to the occurrence of ferroptosis. Ferroptosis can be a factor in the remodeling of the immune microenvironment and can affect the efficacy of cancer immunotherapy. How to combine ferroptosis-promoting modalities with immunotherapy to suppress triple-negative breast cancer (TNBC) has become an issue of great interest in cancer therapy. However, potential biomarkers related to iron metabolism and immune regulation in TNBC remain poorly understand. Methods We constructed an optimal prognostic TNBC-IMRGs (iron metabolism and immune-related genes) signature using least absolute shrinkage and selection operator (LASSO) cox regression. Survival analysis and ROC curves were analyzed to identify the predictive value in a training cohort and external validation cohorts. The correlations of gene signature with ferroptosis regulators and immune infiltration are also discussed. Finally, we combined the gene signature with the clinical model to construct a combined model, which was further evaluated using a calibration curve and decision curve analysis (DCA). Results Compared with the high-risk group, TNBC patients with low-risk scores had a remarkably better prognosis in both the training set and external validation sets. Both the IMRGs signature and combined model had a high predictive capacity, 1/3/5- year AUC: 0.866, 0.869, 0.754, and 1/3/5-yaer AUC: 0.942, 0.934, 0.846, respectively. The calibration curve and DCA also indicate a good predictive performance of the combined model. Gene set enrichment analysis (GSEA) suggests that the high-risk group is mainly enriched in metabolic processes, while the low-risk group is mostly clustered in immune related pathways. Multiple algorithms and single sample GSEA further show that the low-risk score is associated with a high tumor immune infiltration level. Differences in expression of ferroptosis regulators are also observed among different risk groups. Conclusions The IMRGs signature based on a combination of iron metabolism and immune factors may contribute to evaluating prognosis, understanding molecular characteristics and selecting treatment options in TNBC.

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Genomic Signatures in Luminal Breast Cancer

Cited by 26 publications

References 98 publications

PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer

PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer

Oncotype DX Recurrence Score in premenopausal women

An iron metabolism and immune related gene signature for the prediction of clinical outcome and molecular characteristics of triple-negative breast cancer

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