In order to facilitate implementation of precision medicine in clinical management of cancer, there is a need to harmonise and standardise the reporting and interpretation of clinically relevant genomics data. The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group (TR and PM WG) launched a collaborative project to propose a classification system for molecular aberrations based on the evidence available supporting their value as clinical targets. A group of experts from several institutions was assembled to review available evidence, reach a consensus on grading criteria and present a classification system. This was then reviewed, amended and finally approved by the ESMO TR and PM WG and the ESMO leadership. This first version of the ESMO Scale of Clinical Actionability for molecular Targets (ESCAT) defines six levels of clinical evidence for molecular targets according to the implications for patient management: tier I, targets ready for implementation in routine clinical decisions; tier II, investigational targets that likely define a patient population that benefits from a targeted drug but additional data are needed; tier III, clinical benefit previously demonstrated in other tumour types or for similar molecular targets; tier IV, preclinical evidence of actionability; tier V, evidence supporting co-targeting approaches; and tier X, lack of evidence for actionability. The ESCAT defines clinical evidence-based criteria to prioritise genomic alterations as markers to select patients for targeted therapies. This classification system aims to offer a common language for all the relevant stakeholders in cancer medicine and drug development.

Purpose: We undertook this study to determine the prevalence of estrogen receptor (ER) α (ESR1) mutations throughout the natural history of hormone-dependent breast cancer and to delineate the functional roles of the most commonly detected alterations. Experimental Design: We studied a total of 249 tumor specimens from 208 patients. The specimens include 134 ER-positive (ER⁺/HER2⁻) and, as controls, 115 ER-negative (ER⁻) tumors. The ER⁺ samples consist of 58 primary breast cancers and 76 metastatic samples. All tumors were sequenced to high unique coverage using next-generation sequencing targeting the coding sequence of the estrogen receptor and an additional 182 cancer-related genes. Results: Recurring somatic mutations in codons 537 and 538 within the ligand-binding domain of ER were detected in ER⁺ metastatic disease. Overall, the frequency of these mutations was 12% [9/76; 95% confidence interval (CI), 6%–21%] in metastatic tumors and in a subgroup of patients who received an average of 7 lines of treatment the frequency was 20% (5/25; 95% CI, 7%–41%). These mutations were not detected in primary or treatment-naïve ER⁺ cancer or in any stage of ER⁻ disease. Functional studies in cell line models demonstrate that these mutations render estrogen receptor constitutive activity and confer partial resistance to currently available endocrine treatments. Conclusions: In this study, we show evidence for the temporal selection of functional ESR1 mutations as potential drivers of endocrine resistance during the progression of ER⁺ breast cancer. Clin Cancer Res; 20(7); 1757–67. ©2014 AACR.

PURPOSE: To update recommendations on appropriate use of breast cancer biomarker assay results to guide adjuvant endocrine and chemotherapy decisions in early-stage breast cancer. METHODS: An updated literature search identified randomized clinical trials and prospective-retrospective studies published from January 2016 to October 2021. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert Panel members used informal consensus to develop evidence-based recommendations. RESULTS: The search identified 24 studies informing the evidence base. RECOMMENDATIONS: Clinicians may use Onco type DX, MammaPrint, Breast Cancer Index (BCI), and EndoPredict to guide adjuvant endocrine and chemotherapy in patients who are postmenopausal or age > 50 years with early-stage estrogen receptor (ER)–positive, human epidermal growth factor receptor 2 (HER2)–negative (ER+ and HER2–) breast cancer that is node-negative or with 1-3 positive nodes. Prosigna and BCI may be used in postmenopausal patients with node-negative ER+ and HER2– breast cancer. In premenopausal patients, clinicians may use Onco type in patients with node-negative ER+ and HER2– breast cancer. Current data suggest that premenopausal patients with 1-3 positive nodes benefit from chemotherapy regardless of genomic assay result. There are no data on use of genomic tests to guide adjuvant chemotherapy in patients with ≥ 4 positive nodes. Ki67 combined with other parameters or immunohistochemistry 4 score may be used in postmenopausal patients without access to genomic tests to guide adjuvant therapy decisions. BCI may be offered to patients with 0-3 positive nodes who received 5 years of endocrine therapy without evidence of recurrence to guide decisions about extended endocrine therapy. None of the assays are recommended for treatment guidance in individuals with HER2-positive or triple-negative breast cancer. Treatment decisions should also consider disease stage, comorbidities, and patient preferences. Additional information is available at www.asco.org/breast-cancer-guidelines .

Little is known about how the immune microenvironment of breast cancer evolves during disease progression. We compared tumor infiltrating lymphocyte (TIL) count, PD-L1 protein expression by immunohistochemistry and mRNA levels of 730 immune-related genes using Nanostring technology in primary and metastatic cancer samples. TIL counts and PD-L1 positivity were significantly lower in metastases. Immune cell metagenes corresponding to CD8, T-helper, T-reg, Cytotoxic T, Dendritic and Mastoid cells, and expression of 13 of 29 immuno-oncology therapeutic targets in clinical development including PD1, PD-L1, and CTLA4 were significantly lower in metastases. There was also coordinated down regulation of chemoattractant ligand/receptor pairs (CCL19/CCR7, CXCL9/CXCR3, IL15/IL15R), interferon regulated genes (STAT1, IRF-1,-4,-7, IFI-27,-35), granzyme/granulysin, MHC class I and immune proteasome (PSMB-8,-9,-10) expression in metastases. Immunotherapy response predictive signatures were also lower. The expression of macrophage markers (CD163, CCL2/CCR2, CSF1/CSFR1, CXCR4/CXCL12), pro-tumorigenic toll like receptor pathway genes (CD14/TLR-1,-2,-4,-5,-6/MyD88), HLA-E, ecto-nuclease CD73/NT5E and inhibitory complement receptors (CD-59,-55,-46) remained high in metastases and represent potential therapeutic targets. Metastatic breast cancers are immunologically more inert than the corresponding primary tumors but some immune-oncology targets and macrophage and angiogenesis signatures show preserved expression and suggest therapeutic combinations for clinical testing.

There is growing consensus that multigene prognostic tests provide useful complementary information to tumor size and grade in estrogen receptor (ER)-positive breast cancers. The tests primarily rely on quantification of ER and proliferation-related genes and combine these into multivariate prediction models. Since ER-negative cancers tend to have higher proliferation rates, the prognostic value of current multigene tests in these cancers is limited. First-generation prognostic signatures (Oncotype DX, MammaPrint, Genomic Grade Index) are substantially more accurate to predict recurrence within the first 5 years than in later years. This has become a limitation with the availability of effective extended adjuvant endocrine therapies. Newer tests (Prosigna, EndoPredict, Breast Cancer Index) appear to possess better prognostic value for late recurrences while also remaining predictive of early relapse. Some clinical prediction problems are more difficult to solve than others: there are no clinically useful prognostic signatures for ER-negative cancers, and drug-specific treatment response predictors also remain elusive. Emerging areas of research involve the development of immune gene signatures that carry modest but significant prognostic value independent of proliferation and ER status and represent candidate predictive markers for immune-targeted therapies. Overall metrics of tumor heterogeneity and genome integrity (for example, homologue recombination deficiency score) are emerging as potential new predictive markers for platinum agents. The recent expansion of high-throughput technology platforms including low-cost sequencing of circulating and tumor-derived DNA and RNA and rapid reliable quantification of microRNA offers new opportunities to build extended prediction models across multiplatform data.