Impact of breast cancer subtypes on 3-year survival among adolescent and young adult women.

IntroductionYoung women have poorer survival after breast cancer than do older women. It is unclear whether this survival difference relates to the unique distribution of hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2)-defined molecular breast cancer subtypes among adolescent and young adult (AYA) women aged 15 to 39 years. The purpose of our study was to examine associations between breast cancer subtypes and short-term survival in AYA women, as well as to determine whether the distinct molecular subtype distribution among AYA women explains the unfavorable overall breast cancer survival statistics reported for AYA women compared with older women.MethodsData for 5,331 AYA breast cancers diagnosed between 2005 and 2009 were obtained from the California Cancer Registry. Survival by subtype (triple-negative; HR+/HER2-; HR+/HER2+; HR-/HER2+) and age-group (AYA versus 40- to 64-year-olds) was analyzed with Cox proportional hazards regression with follow-up through 2010.ResultsWith up to 6 years of follow-up and a mean survival time of 3.1 years (SD = 1.5 years), AYA women diagnosed with HR-/HER + and triple-negative breast cancer experienced a 1.6-fold and 2.7-fold increased risk of death, respectively, from all causes (HR-/HER + hazard ratio: 1.55; 95% confidence interval (CI): 1.10 to 2.18; triple-negative HR: 2.75; 95% CI, 2.06 to 3.66) and breast cancer (HR-/HER + hazard ratio: 1.63; 95% CI, 1.12 to 2.36; triple-negative hazard ratio: 2.71; 95% CI, 1.98 to 3.71) than AYA women with HR+/HER2- breast cancer. AYA women who resided in lower socioeconomic status neighborhoods, had public health insurance, and were of Black, compared with White, race/ethnicity experienced worse survival. This race/ethnicity association was attenuated somewhat after adjusting for breast cancer subtypes (hazard ratio, 1.33; 95% CI, 0.98 to 1.82). AYA women had similar all-cause and breast cancer-specific short-term survival as older women for all breast cancer subtypes and across all stages of disease.ConclusionsAmong AYA women with breast cancer, short-term survival varied by breast cancer subtypes, with the distribution of breast cancer subtypes explaining some of the poorer survival observed among Black, compared with White, AYA women. Future studies should consider whether distribution of breast cancer subtypes and other factors, including differential receipt of treatment regimens, influences long-term survival in young compared with older women

Knowledge regarding and patterns of genetic testing in patients newly diagnosed with breast cancer participating in the iCanDecide trial

BackgroundThe current study reports rates of knowledge regarding the probability of a BRCA1 and/or S pathogenic variant and genetic testing in patients with breast cancer, collected as part of a randomized controlled trial of a tailored, comprehensive, and interactive decision tool (iCanDecide).MethodsA total of 537 patients newly diagnosed with early‐stage breast cancer were enrolled at the time of their first visit in 22 surgical practices, and were surveyed 5 weeks (496 patients; Response Rate [RR], 92%) after enrollment after treatment decision making. Primary outcomes included knowledge regarding the probability of carrying a BRCA1 and/or BRCA2 pathogenic variant and genetic testing after diagnosis.ResultsOverall knowledge regarding the probability of having a BRCA1 and/or BRCA2 pathogenic variant was low (29.8%). Significantly more patients in the intervention group compared with the control group had knowledge regarding the probability of a BRCA1 and/or BRCA2 pathogenic variant (35.8% vs 24.4%; P <.006). In multivariable logistic regression, the intervention arm remained significantly associated with knowledge regarding the probability of having a BRCA1 and/or BRCA2 pathogenic variant (odds ratio, 1.79; 95% confidence interval, 1.18‐2.70).ConclusionsThe results of the current study suggest that although knowledge concerning the probability of having a BRCA1 and/or BRCA2 pathogenic variant remains low in this patient population, the interactive decision tool improved rates compared with a static Web site. As interest in genetic testing continues to rise, so will the need to integrate tools into the treatment decision process to improve informed decision making.As interest in genetic testing increases, so will the need to integrate tools into the treatment decision process. Results from the current study suggest that although knowledge regarding the probability of a BRCA1 and/or BRCA2 pathogenic variant remains low in this patient population, the interactive decision tool improved rates compared with a static Web site.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146553/1/cncr31731.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146553/2/cncr31731_am.pd

Rapid detection of BRCA1/2 recurrent mutations in Chinese breast and ovarian cancer patients with multiplex SNaPshot genotyping panels.

BRCA1/2 mutations are significant risk factors for hereditary breast and ovarian cancer (HBOC), its mutation frequency in HBOC of Chinese ethnicity is around 9%, in which nearly half are recurrent mutations. In Hong Kong and China, genetic testing and counseling are not as common as in the West. To reduce the barrier of testing, a multiplex SNaPshot genotyping panel that targeted 25 Chinese BRCA1/2 mutation hotspots was developed, and its feasibility was evaluated in a local cohort of 441 breast and 155 ovarian cancer patients. For those who tested negative, they were then subjected to full-gene testing with next-generation sequencing (NGS). BRCA mutation prevalence in this cohort was 8.05% and the yield of the recurrent panel was 3.52%, identifying over 40% of the mutation carriers. Moreover, from 79 Chinese breast cancer cases recruited overseas, 2 recurrent mutations and one novel BRCA2 mutation were detected by the panel and NGS respectively. The developed genotyping panel showed to be an easy-to-perform and more affordable testing tool that can provide important contributions to improve the healthcare of Chinese women with cancer as well as family members that harbor high risk mutations for HBOC

Synergistic drug combinations from electronic health records and gene expression.

ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.MethodWe applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.ResultsFrom EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.ConclusionsThis is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing

Primary care provider–reported involvement in breast cancer treatment decisions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149227/1/cncr31998.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149227/2/cncr31998_am.pd

Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer

Purpose: Tumor-infiltrating lymphocytes (TIL) in pretreatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer–specific mortality (BCM) and overall mortality (OM) in TNBC. Experimental Design: Data on treatments and diagnostic tests from electronic medical records of two health care systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM, and OM. For a subgroup with TIL data available, we explored the relationship between TILs and peripheral lymphocyte counts. Results: A total of 1,463 stage I–III TNBC patients were diagnosed from 2000 to 2014; 1,113 (76%) received neoadjuvant/adjuvant chemotherapy within 1 year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC <1.0 K/μL). On multivariable analysis, higher minimum ALC, but not absolute neutrophil count, predicted lower OM [HR = 0.23; 95% confidence interval (CI), 0.16–0.35] and BCM (HR = 0.19; CI, 0.11–0.34). Five-year probability of BCM was 15% for patients who were ever lymphopenic versus 4% for those who were not. An exploratory analysis (n = 70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy. Conclusions: Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment

Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines

BACKGROUND: To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery. METHODOLOGY/PRINCIPAL FINDINGS: We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy. CONCLUSIONS/SIGNIFICANCE: For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of 'liquid biopsies' to better model drug discovery