***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background Gene expression signatures indicative of tumor proliferative capacity and tumor-immune cell interactions have emerged as principal biology-driven predictors of breast cancer outcomes . How these signatures relate to one another in biological and prognostic context s remains to be clarified . Results To investigate the relationship between proliferation and immune gene signatures , we analyzed an integrated data set of 1,954 clinical ly annotated breast tumor expression profiles r and omized into training and test sets to allow two-way discovery and validation of gene-survival associations . Hierarchical clustering revealed a large cluster of distant metastasis-free survival-associated genes with known immunological functions that further partitioned into three distinct immune metagenes likely reflecting B cells and /or plasma cells ; T cells and natural killer cells ; and monocytes and /or dendritic cells . A proliferation metagene allowed stratification of cases into proliferation tertiles . The prognostic strength of these metagenes was largely restricted to tumors within the highest proliferation tertile , though intrinsic subtype-specific differences were observed in the intermediate and low proliferation tertiles . In highly proliferative tumors , high tertile immune metagene expression equated with markedly reduced risk of metastasis whereas tumors with low tertile expression of any one of the three immune metagenes were associated with poor outcome despite higher expression of the other two metagenes . Conclusions These findings suggest that a productive interplay among multiple immune cell types at the tumor site promotes long-term anti-metastatic immunity in a proliferation-dependent manner . The emergence of a subset of effective immune responders among highly proliferative tumors has novel prognostic ramifications CONTEXT Prediction of high probability of survival from st and ard cancer treatments is fundamental for individualized cancer treatment strategies . OBJECTIVE To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer . DESIGN , SETTING , AND PATIENTS Prospect i ve multicenter study conducted from June 2000 to March 2010 at the M. D. And erson Cancer Center to develop and test genomic predictors for neoadjuvant chemotherapy .  Patients were those with newly diagnosed ERBB2 ( HER2 or HER2/neu)-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens  ( then endocrine therapy  if estrogen receptor [ER]-positive ) . Different predictive signatures for resistance and response to preoperative ( neoadjuvant ) chemotherapy ( stratified according to ER status ) were developed from gene expression microarrays of newly diagnosed breast cancer ( 310 patients ) . Breast cancer treatment sensitivity was then predicted using the combination of signatures for ( 1 ) sensitivity to endocrine therapy , ( 2 ) chemoresistance , and ( 3 ) chemosensitivity , with independent validation ( 198 patients ) and comparison with other reported genomic predictors of chemotherapy response . MAIN OUTCOME MEASURES Distant relapse-free survival ( DRFS ) if predicted treatment sensitive and absolute risk reduction ( [ ARR ] , difference in DRFS between 2 predicted groups ) at median follow-up ( 3 years ) . RESULTS Patients in the independent validation cohort ( 99 % clinical stage II-III ) who were predicted to be treatment sensitive ( 28 % ) had 56 % ( 95 % CI , 31%-78 % ) probability of excellent pathologic response and DRFS of 92 % ( 95 % CI , 85%-100 % ) , with an ARR of 18 % ( 95 % CI , 6%-28 % ) . Survival was predicted in ER-positive ( 30 % predicted sensitive ; DRFS , 97 % [ 95 % CI , 91%-100 % ] ; ARR , 11 % [ 95 % CI , 0.1%-21 % ] ) and ER-negative ( 26 % predicted sensitive ; DRFS , 83 % [ 95 % CI , 68%-100 % ] ; ARR , 26 % [ 95 % CI , 4%-48 % ] ) subsets and was significant in multivariate analysis . Other genomic predictors showed paradoxically worse survival for patients predicted to be responsive to chemotherapy . CONCLUSION A genomic predictor combining ER status , predicted chemoresistance , predicted chemosensitivity , and predicted endocrine sensitivity identified patients with high probability of survival following taxane and anthracycline chemotherapy 
    Output:
    
However , high SIX3 mRNA level was a protective factor for OS and RFS of basal-like breast cancer patients .Our study suggested that members of SIX family played distinct roles in breast cancer .