Several new systemic therapy options have become available for patients with metastatic breast cancer, which have led to improvements in survival. In addition to patient and clinical factors, the treatment selection primarily depends on the tumor biology (hormone-receptor status and HER2-status). The NCCN Guidelines specific to the workup and treatment of patients with recurrent/stage IV breast cancer are discussed in this article.

The therapeutic options for patients with noninvasive or invasive breast cancer are complex and varied. These NCCN Clinical Practice Guidelines for Breast Cancer include recommendations for clinical management of patients with carcinoma in situ, invasive breast cancer, Paget disease, phyllodes tumor, inflammatory breast cancer, and management of breast cancer during pregnancy. The content featured in this issue focuses on the recommendations for overall management of ductal carcinoma in situ and the workup and locoregional management of early stage invasive breast cancer. For the full version of the NCCN Guidelines for Breast Cancer, visit NCCN.org.

The NCCN Guidelines for Breast Cancer include up-to-date guidelines for clinical management of patients with carcinoma in situ, invasive breast cancer, Paget disease, phyllodes tumor, inflammatory breast cancer, male breast cancer, and breast cancer during pregnancy. These guidelines are developed by a multidisciplinary panel of representatives from NCCN Member Institutions with breast cancer–focused expertise in the fields of medical oncology, surgical oncology, radiation oncology, pathology, reconstructive surgery, and patient advocacy. These NCCN Guidelines Insights focus on the most recent updates to recommendations for adjuvant systemic therapy in patients with nonmetastatic, early-stage, hormone receptor–positive, HER2-negative breast cancer.

Multiparameter analysis of core regulatory proteins involved in G1 -S and G2 -M cell-cycle transitions provides a powerful biomarker readout for assessment of the cell-cycle state. We have applied this algorithm to breast cancer to investigate how the cell cycle impacts on disease progression. Protein expression profiles of key constituents of the DNA replication licensing pathway (Mcm2, geminin) and mitotic machinery (Plk1, Aurora A and the Aurora substrate histone H3S10ph) were generated for a cohort of 182 patients and linked to clinicopathological parameters. Arrested differentiation and genomic instability were associated with an increased engagement of cells into the cell division cycle (Po0.0001). Three unique cell-cycle phenotypes were identified: (1) welldifferentiated tumours composed predominantly of Mcm2-negative cells, indicative of an out-of-cycle state (18% of cases); (2) high Mcm2-expressing tumours but with low geminin, Aurora A, Plk1 and H3S10ph levels (S -G2 -M progression markers), indicative of a G1-delayed/arrested state (24% cases); and (3) high Mcm2-expressing tumours and also expressing high levels of the S -G2 -M progression markers, indicative of accelerated cell-cycle progression (58% of cases). The active cell-cycle progression phenotype had a higher risk of relapse when compared with out-of-cycle and G1-delayed/arrested phenotypes (HR ¼ 3.90 (1.81 -8.40, Po0.001)), and was associated with Her-2 and triple negative subtypes (Po0.001). It is of note that high-grade tumours with the G1-delayed/ arrested phenotype showed an identical low risk of relapse compared with well-differentiated out-of-cycle tumours (HR ¼ 1.00 (0.22 -4.46), P ¼ 0.99). Our biomarker algorithm provides novel insights into the cell-cycle state of dynamic tumour cell populations in vivo. This information is of major prognostic significance and may impact on individualised therapeutic decisions. Patients with an accelerated phenotype are more likely to derive benefit from S-and M-phase-directed chemotherapeutic agents.

Background-Intra-tumor heterogeneity implies that sub-populations of cancer cells that differ in genetic, phenotypic, or behavioral characteristics coexist in a single tumor 1,2. Tumor heterogeneity drives progression, metastasis and treatment resistance, but its relationship with tumor infiltrating immune cells is a matter of debate where some argue that tumors with high heterogeneity may generate neo-antigens that attract immune cells, and the others claim that immune cells provide selection pressure that shapes tumor heterogeneity 3,4. Here we sought to study the association between tumor heterogeneity and immune cells in a real-world cohort utilizing The Cancer Genome Atlas (TCGA). Methods-Mutant Allele Tumor Heterogeneity (MATH) was calculated to estimate intra-tumoral heterogeneity, and immune cell compositions were estimated by CIBERSORT. Survival analyses were demonstrated by Kaplan Meir curves. Results-Tumors with high heterogeneity (High MATH) associated with worse overall survival (p=0.049) as well as ER+ (p=0.011) and non-triple negative tumors (p=0.01). High MATH tumors associated with less infiltration of anti-tumor CD8 (p<0.013) and CD4 T cells (p<0.00024), more tumor promoting regulatory T cells (p<4e-04), lower expression of T cell exhaustion markers; PDL-1 (p=0.0031), IDO2 (p=0.34), ADORA2A (p=0.018), VISTA (p=0.00013), and CCR4 (p<0.00001), lower expression of cytolytic enzymes granzyme-A (p=0.0056) and perforin 1 (p=0.053) as well as low cytolytic activity score (p=0.0028). Conclusions-High heterogeneity tumors are associated with less immune cell infiltration, less activation of the immune response, and worse survival in breast cancer. Our results support the notion that tumor heterogeneity is shaped by selection pressure of tumor infiltrating immune cells.

MRI is an effective tool for predicting response to NAC. The accuracy of MRI in estimating postchemotherapy tumor size varies with tumor subtype. It is highest in ER-/HER2+ and TN and lowest in luminal tumors. Knowledge of how tumor subtype affects MRI accuracy can guide recommendations for surgery following NAC.

Some microRNAs (miRNAs) are known to suppress breast cancer. However, whether the expressions of these tumor suppressive miRNAs translate to patient survival were not investigated in large cohort. Nine miRNAs (miR-30a, miR-30c, miR-31, miR-126, miR-140, miR-146b, miR-200c, miR-206, and miR-335) known to be tumor suppressive miRNAs in breast cancer were investigated in Genomic Data Common data portal miRNA-Seq dataset and The Cancer Genome Atlas (TCGA) (n = 1052). Of the 9 miRNAs, miR-30a, miR-30c, miR-126, miR-140, miR-206, and miR-335 were found to have significantly lower expression in breast cancer tissues compared to paired normal breast tissue. High expression of miR-30a or miR-200c was associated with significantly better overall survival (OS). Gene Set Enrichment Analysis (GSEA) demonstrated that low expression levels of miR-30a had the tendency to associate with gene enrichment of EMT, while miR-200c did not, in TCGA cohort, and our findings support the need of validation using large cohort to use miRNA as prognostic biomarker for patients with breast cancer.

Patients > or = 55 had a greater mortality for all forms of treatment of their blunt splenic injury and failed NOM more frequently than patients < 55. Women > or = 55 had significantly greater mortality and failure of NOM than women < 55.