The many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDA's draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach.
Alterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial signatures, using a pan-pathogen microarray strategy. The signature (includes viruses, bacteria, fungi, and parasites) of each tumor subtype was correlated with clinical data to identify microbes with prognostic potential. The subtypes of BC had specific viromes and microbiomes, with ER+ and TN tumors showing the most and least diverse microbiome, respectively. The specific microbial signatures allowed discrimination between different BC subtypes. Furthermore, we demonstrated correlations between the presence and absence of specific microbes in BC subtypes with the clinical outcomes. This study provides a comprehensive map of the oncobiome of BC subtypes, with insights into disease prognosis that can be critical for precision therapeutic intervention strategies.
Interval cancers (ICs), defined as cancers detected between regular screening mammograms, have been shown to be of higher grade, larger size, and associated with lower survival, compared with screen-detected cancers (SDCs) and comprise 17% of cancers from population-based screening programs. We sought to determine the frequency of ICs in a study of locally advanced breast cancers, the I-SPY 1 TRIAL. Screening was defined as having a mammogram with 2 years, and the proportion of ICs at 1 and 2 years was calculated for screened patients. Differences in clinical characteristics for ICs versus SDCs and screened versus non-screened cancers were assessed. For the 219 evaluable women, mean tumor size was 6.8 cm. Overall, 80% of women were over 40 and eligible for screening; however, only 31% were getting screened. Among women screened, 85% were ICs, with 68% diagnosed within 1 year of a previously normal mammogram. ICs were of higher grade (49% vs. 10%) than SDCs. Among non-screened women, 28% (43/152) were younger than the recommended screening age of 40. Of the entire cohort, 12% of cancers were mammographically occult (MO); the frequency of MO cancers did not differ between screened (11%) and non-screened (15%). ICs were common in the I-SPY 1 TRIAL suggesting the potential need for new approaches beyond traditional screening to reduce mortality in women who present with larger palpable cancers.
Second malignancies are a significant concern for survivors of childhood acute lymphoblastic leukemia (ALL), in particular patients who have been treated with cranial irradiation. Brain tumors, most commonly meningiomas, are among the most common second neoplasms discovered in these patients. Breast cancer can occur in association with meningioma, but is not thought to be a consequence of treatment for childhood ALL. We describe the molecular genetics and therapy of childhood ALL, the molecular genetics of meningioma, as well as the possible association between meningioma and breast cancer.
BACKGROUND: Further stratification of the 70-gene MammaPrint(TM) prognostic signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), using a threshold predefined by the median cut-point of I-SPY 1 participants who fit the eligibility criteria for I-SPY 2. MP1/2 classification was added to HR and HER2 to define the subtypes used in the I-SPY 2 adaptive randomization engine. The first two experimental agents/combinations to graduate from I-SPY 2 were veliparib/carboplatin (V/C) in the TN subset, and neratinib (N) in the HR-HER2+ subset. MP2 was found to be a sensitivity marker for V/C but not N, whereas MP1 class appears associated with resistance to N within the HER2- subset. Despite these associations with response, it remains unclear whether MP1/MP2 classification represents differences in tumor biology. Here, we present exploratory analysis to elucidate the pathway differences between the MP classes. METHODS: 263 patients (V/C: 71, N: 115, and controls: 77) with pre-treatment Agilent 44K microarrays and MP1/2 class assessments were considered in this analysis. To identify signature genes associated with MP1 vs. MP2 class, we (1) apply a Wilcoxon rank sum test and (2) fit a logistic model. P-values are corrected for multiple comparisons using the Benjamini-Hochberg (BH) method, with a significance threshold of BH p<0.05 from both tests. We then perform pathway enrichment analysis using DAVID. In addition, we perform multivariate analysis adjusting for receptor subtype. Our study is exploratory and does not adjust for multiplicities of other biomarkers in the trial but outside this study. RESULTS: 63% (165/263) of patients are MP1 class and 37% (98/263) MP2. MP1/2 class is associated with receptor subtype (Fisher's exact test: p<2E-16), where 71% of TN patients are MP2 and 96% of HR+HER2+ patients are MP1. Of the 70 signature genes, 86% (60/70) differ in expression between MP1 and MP2, with 70% (42/60) expressed at a higher level in MP2, including CDCA7, MELK and CENPA. In a whole transcriptome analysis, 10,500 genes (of ∼30,000) appear differentially expressed. Following adjustment for HR and HER2 status, 4368 genes are significantly differentially expressed between MP1 and MP2. By DAVID enrichment analysis, the biggest pathway-level differences are found in cell cycle, proliferation, and DNA repair, with the MP2 set showing higher expression. CONCLUSION: MP2 class appears associated with higher expression of cell cycle & DNA repair genes. Association between MP2 class and response to V/C suggests that higher cell cycle activity may contribute to V/C sensitivity. Citation Format: Denise M. Wolf, Christina Yau, Lamorna Brown-Swigart, Gillian Hirst, Meredith Buxton, Melissa Paoloni, I-SPY 2 TRIAL Investigators, Olufunmilayo Olopade, Angela De Michele, Fraser Symmans, Hope Rugo, Don Berry, Laura Esserman, Laura van ‘t Veer. Gene and pathway differences between MammaPrint High1/High2 risk classes: results from the I-SPY 2 TRIAL in breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 859.
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