Publications by Year: 2016

Oh H, Eliassen HA, Wang M, Smith-Warner SA, Beck AH, Schnitt SJ, Collins LC, Connolly JL, Montaser-Kouhsari L, Polyak K, Tamimi RM. Expression of estrogen receptor, progesterone receptor, and Ki67 in normal breast tissue in relation to subsequent risk of breast cancer. NPJ Breast Cancer 2016;2Abstract
Although expression of estrogen receptor (ER), progesterone receptor (PR), and cell proliferation marker Ki67 serve as predictive and prognostic factors in breast cancers, little is known about their roles in normal breast tissue. Here in a nested case-control study within the Nurses' Health Studies (90 cases, 297 controls), we evaluated their expression levels in normal breast epithelium in relation to subsequent breast cancer risk among women with benign breast disease. Tissue microarrays were constructed using cores obtained from benign biopsies containing normal terminal duct lobular units and immunohistochemical stained for these markers. We found PR and Ki67 expression was non-significantly but positively associated with subsequent breast cancer risk, whereas ER expression was non-significantly inversely associated. After stratifying by lesion subtype, Ki67 was significantly associated with higher risk among women with proliferative lesions with atypical hyperplasia. However, given the small sample size, further studies are required to confirm these results.
Beca F, Beck AH. Precision Cancer Diagnostics: Tracking Genomic Evolution in Clinical Trials. PLoS Med 2016;13(12):e1002177.Abstract
In a Perspective, Francisco Beca and Andrew Beck discuss Charles Swanton and colleagues' accompanying Research Article on somatic mutations in patients with inflammatory breast cancer treated in a Phase II clinical trial.
Safikhani Z, El-Hachem N, Smirnov P, Freeman M, Goldenberg A, Birkbak NJ, Beck AH, Aerts HJWL, Quackenbush J, Haibe-Kains B. Safikhani et al. reply. Nature 2016;540(7631):E6-E8.
Safikhani Z, El-Hachem N, Smirnov P, Freeman M, Goldenberg A, Birkbak NJ, Beck AH, Aerts HJWL, Quackenbush J, Haibe-Kains B. Safikhani et al. reply. Nature 2016;540(7631):E11-E12.
Safikhani Z, El-Hachem N, Smirnov P, Freeman M, Goldenberg A, Birkbak NJ, Beck AH, Aerts HJWL, Quackenbush J, Haibe-Kains B. Safikhani et al. reply. Nature 2016;540(7631):E2-E4.
Henry WS, Laszewski T, Tsang T, Beca F, Beck AH, McAllister SS, Toker A. Aspirin suppresses growth in PI3K-mutant breast cancer by activating AMPK and inhibiting mTORC1 signaling [Internet]. Cancer Research 2016;:2400. Publisher's Version
Ahern TP, Beck AH, Rosner BA, Glass B, Frieling G, Collins LC, Tamimi RM. Continuous measurement of breast tumour hormone receptor expression: a comparison of two computational pathology platforms. J Clin Pathol 2016;Abstract
AIMS: Computational pathology platforms incorporate digital microscopy with sophisticated image analysis to permit rapid, continuous measurement of protein expression. We compared two computational pathology platforms on their measurement of breast tumour oestrogen receptor (ER) and progesterone receptor (PR) expression. METHODS: Breast tumour microarrays from the Nurses' Health Study were stained for ER (n=592) and PR (n=187). One expert pathologist scored cases as positive if ≥1% of tumour nuclei exhibited stain. ER and PR were then measured with the Definiens Tissue Studio (automated) and Aperio Digital Pathology (user-supervised) platforms. Platform-specific measurements were compared using boxplots, scatter plots and correlation statistics. Classification of ER and PR positivity by platform-specific measurements was evaluated with areas under receiver operating characteristic curves (AUC) from univariable logistic regression models, using expert pathologist classification as the standard. RESULTS: Both platforms showed considerable overlap in continuous measurements of ER and PR between positive and negative groups classified by expert pathologist. Platform-specific measurements were strongly and positively correlated with one another (r≥0.77). The user-supervised Aperio workflow performed slightly better than the automated Definiens workflow at classifying ER positivity (AUCAperio=0.97; AUCDefiniens=0.90; difference=0.07, 95% CI 0.05 to 0.09) and PR positivity (AUCAperio=0.94; AUCDefiniens=0.87; difference=0.07, 95% CI 0.03 to 0.12). CONCLUSIONS: Paired hormone receptor expression measurements from two different computational pathology platforms agreed well with one another. The user-supervised workflow yielded better classification accuracy than the automated workflow. Appropriately validated computational pathology algorithms enrich molecular epidemiology studies with continuous protein expression data and may accelerate tumour biomarker discovery.
German NJ, Yoon H, Yusuf RZ, Murphy PJ, Finley LWS, Laurent G, Haas W, Satterstrom KF, Guarnerio J, Zaganjor E, Santos D, Pandolfi PP, Beck AH, Gygi SP, Scadden DT, Kaelin WG, Haigis MC. PHD3 Loss in Cancer Enables Metabolic Reliance on Fatty Acid Oxidation via Deactivation of ACC2. Mol Cell 2016;63(6):1006-20.Abstract
While much research has examined the use of glucose and glutamine by tumor cells, many cancers instead prefer to metabolize fats. Despite the pervasiveness of this phenotype, knowledge of pathways that drive fatty acid oxidation (FAO) in cancer is limited. Prolyl hydroxylase domain proteins hydroxylate substrate proline residues and have been linked to fuel switching. Here, we reveal that PHD3 rapidly triggers repression of FAO in response to nutrient abundance via hydroxylation of acetyl-coA carboxylase 2 (ACC2). We find that PHD3 expression is strongly decreased in subsets of cancer including acute myeloid leukemia (AML) and is linked to a reliance on fat catabolism regardless of external nutrient cues. Overexpressing PHD3 limits FAO via regulation of ACC2 and consequently impedes leukemia cell proliferation. Thus, loss of PHD3 enables greater utilization of fatty acids but may also serve as a metabolic and therapeutic liability by indicating cancer cell susceptibility to FAO inhibition.
Henry WS, Hendrickson DG, Beca F, Glass B, Lindahl-Allen M, He L, Ji Z, Struhl K, Beck AH, Rinn JL, Toker A. LINC00520 is induced by Src, STAT3, and PI3K and plays a functional role in breast cancer. Oncotarget 2016;7(50):81981-81994.Abstract
Long non-coding RNAs (lncRNAs) have been implicated in normal cellular homeostasis as well as pathophysiological conditions, including cancer. Here we performed global gene expression profiling of mammary epithelial cells transformed by oncogenic v-Src, and identified a large subset of uncharacterized lncRNAs potentially involved in breast cancer development. Specifically, our analysis revealed a novel lncRNA, LINC00520 that is upregulated upon ectopic expression of oncogenic v-Src, in a manner that is dependent on the transcription factor STAT3. Similarly, LINC00520 is also increased in mammary epithelial cells transformed by oncogenic PI3K and its expression is decreased upon knockdown of mutant PIK3CA. Additional expression profiling highlight that LINC00520 is elevated in a subset of human breast carcinomas, with preferential enrichment in the basal-like molecular subtype. ShRNA-mediated depletion of LINC00520 results in decreased cell migration and loss of invasive structures in 3D. RNA sequencing analysis uncovers several genes that are differentially expressed upon ectopic expression of LINC00520, a significant subset of which are also induced in v-Src-transformed MCF10A cells. Together, these findings characterize LINC00520 as a lncRNA that is regulated by oncogenic Src, PIK3CA and STAT3, and which may contribute to the molecular etiology of breast cancer.
Warner ET, Hu R, Collins LC, Beck AH, Schnitt S, Rosner B, Eliassen HA, Michels KB, Willett WC, Tamimi RM. Height and Body Size in Childhood, Adolescence, and Young Adulthood and Breast Cancer Risk According to Molecular Subtype in the Nurses' Health Studies. Cancer Prev Res (Phila) 2016;9(9):732-8.Abstract
Height and body size in childhood and young adulthood have been consistently associated with breast cancer risk; whether associations differ across molecular subtypes is unclear. In a pooled analysis of the Nurses' Health Studies, we prospectively examined the association of four exposures: height, body mass index (BMI) at the age of 18 years, childhood and adolescent somatotypes, with breast cancer risk according to molecular subtypes defined by immunohistochemical markers. We used multivariable-adjusted Cox proportional hazards regression to estimate HRs and 95% confidence intervals (CI). We identified 2,983 luminal A, 1,281 luminal B, 318 HER2-enriched, 408 basal-like, and 128 unclassified tumors. Height was positively associated with all subtypes (Pheterogeneity = 0.78). BMI at the age of 18 (Pheterogeneity = 0.001), childhood (Pheterogeneity = 0.51), and adolescent somatotype (Pheterogeneity = 0.046) were inversely associated, but with differences in magnitude of association. BMI at the age of 18 of ≥25 kg/m(2) (compared with 20-21.9 kg/m(2)) was associated with a 52% decreased risk of HER2-enriched (HR, 0.48; 95% CI, 0.26-0.91; Ptrend < 0.0001) and 39% reduced risk of basal-like tumors (HR, 0.61; 95% CI, 0.36-1.02; Ptrend = 0.008). Compared with the lowest category, women in the highest adolescent body size category were 71% less likely to develop HER2-enriched (HR, 0.29; 95% CI, 0.10-0.85; Ptrend = 0.0005) and 60% less likely to develop basal-like (HR, 0.40; 95% CI, 0.17-0.95; Ptrend = 0.0008). Height was positively associated with risk of all breast cancer molecular subtypes. BMI at 18 years and childhood and adolescent were inversely associated with risk of most breast cancer molecular subtypes with somewhat stronger associations with HER2-enriched and basal-like subtypes. Cancer Prev Res; 9(9); 732-8. ©2016 AACR.
Guarnerio J, Bezzi M, Jeong JC, Paffenholz SV, Berry K, Naldini MM, Lo-Coco F, Tay Y, Beck AH, Pandolfi PP. Oncogenic Role of Fusion-circRNAs Derived from Cancer-Associated Chromosomal Translocations. Cell 2016;166(4):1055-1056.
Eliassen HA, Warner ET, Rosner B, Collins LC, Beck AH, Quintana LM, Tamimi RM, Hankinson SE. Plasma 25-Hydroxyvitamin D and Risk of Breast Cancer in Women Followed over 20 Years. Cancer Res 2016;76(18):5423-30.Abstract
Experimental evidence supports a protective role of 25-hydroxyvitamin D [25(OH)D] in breast carcinogenesis, but epidemiologic evidence is inconsistent. Whether plasma 25(OH)D interacts with breast tumor expression of vitamin D receptor (VDR) and retinoid X receptor-α (RXR) has not been investigated. We conducted a nested case-control study in the Nurses' Health Study, with 1,506 invasive breast cancer cases diagnosed after blood donation in 1989-1990, 417 of whom donated a second sample in 2000-2002. VDR and RXR expression were assessed by immunohistochemical staining of tumor microarrays (n = 669 cases). Multivariate relative risks (RR) and 95% confidence intervals (CI) were calculated using conditional logistic regression. Plasma 25(OH)D levels were not associated with breast cancer risk overall [top (≥32.7 ng/mL) vs. bottom (<17.2 ng/mL) quintile RR = 0.87; 95% CI, 0.67-1.13; P trend = 0.21]. 25(OH)D measured in summer (May-October) was significantly inversely associated with risk (top vs. bottom quintile RR = 0.66; 95% CI, 0.46-0.94; P trend = 0.01); winter levels (November-April) were not (RR = 1.10; 95% CI, 0.75-1.60; P trend = 0.64; P interaction = 0.03). 25(OH)D levels were inversely associated with risk of tumors with high expression of stromal nuclear VDR [≥30 ng/mL vs. <30 ng/mL RR (95% CI): VDR ≥ median = 0.67 (0.48-0.93); VDR < median = 0.98 (0.72-1.35), P heterogeneity = 0.12] and significantly stronger for summer measures (P heterogeneity = 0.01). Associations were not significantly different by RXR expression. No overall association was observed between plasma 25(OH)D and breast cancer risk. However, our results suggest women with high, compared with low, plasma 25(OH)D levels in the summer have a reduced breast cancer risk, and plasma 25(OH)D may be inversely associated with risk of tumors expressing high levels of VDR. Cancer Res; 76(18); 5423-30. ©2016 AACR.
Dong F, Davineni PK, Howitt BE, Beck AH. A BRCA1/2 Mutational Signature and Survival in Ovarian High-Grade Serous Carcinoma. Cancer Epidemiol Biomarkers Prev 2016;25(11):1511-1516.Abstract
BACKGROUND: Mutational signatures have been identified by the broad sequencing of cancer genomes and reflect underlying processes of mutagenesis. The clinical application of mutational signatures is not well defined. Here we aim to assess the prognostic utility of mutational signatures in ovarian high-grade serous carcinoma. METHODS: Open access data of 15,439 somatic mutations of 310 ovarian high-grade serous carcinomas from The Cancer Genome Atlas (TCGA) are used to construct a Bayesian model to classify each cancer as either having or lacking a BRCA1/2 mutational signature. We evaluate the association of the BRCA1/2 signature with overall survival on the TCGA dataset and on an independent cohort of 92 ovarian high-grade serous carcinomas from the Australian Ovarian Cancer Study (AOCS). RESULTS: Patients from TCGA with tumors harboring the BRCA1/2 mutational signature have improved survival (55.2 months vs. 38.0 months), which is independent of BRCA1/2 gene mutation status, age, stage, and grade (HR = 0.64; P = 0.02). In the AOCS dataset, the BRCA1/2 mutational signature is also associated with improved overall survival (46.3 months vs. 23.6 months) independent of age and stage (HR = 0.52; P = 0.007). CONCLUSIONS: A BRCA1/2 mutational signature is a prognostic marker in ovarian high-grade serous carcinoma. Mutational signature analysis of ovarian cancer genomes may be useful in addition to testing for BRCA1/2 mutations. IMPACT: This study identifies the use of mutational signatures as a biomarker for survival outcome in ovarian high-grade serous carcinoma. Cancer Epidemiol Biomarkers Prev; 25(11); 1511-6. ©2016 AACR.
Ngo M, Han A, Lakatos A, Sahoo D, Hachey SJ, Weiskopf K, Beck AH, Weissman IL, Boiko AD. Antibody Therapy Targeting CD47 and CD271 Effectively Suppresses Melanoma Metastasis in Patient-Derived Xenografts. Cell Rep 2016;16(6):1701-16.Abstract
The high rate of metastasis and recurrence among melanoma patients indicates the existence of cells within melanoma that have the ability to both initiate metastatic programs and bypass immune recognition. Here, we identify CD47 as a regulator of melanoma tumor metastasis and immune evasion. Protein and gene expression analysis of clinical melanoma samples reveals that CD47, an anti-phagocytic signal, correlates with melanoma metastasis. Antibody-mediated blockade of CD47 coupled with targeting of CD271(+) melanoma cells strongly inhibits tumor metastasis in patient-derived xenografts. This therapeutic effect is mediated by drastic changes in the tumor and metastatic site immune microenvironments, both of whichwhich exhibit greatly increased density of differentiated macrophages and significantly fewer inflammatory monocytes, pro-metastatic macrophages (CCR2(+)/VEGFR1(+)), and neutrophils, all of which are associated with disease progression. Thus, antibody therapy that activates the innate immune response in combination with selective targeting of CD271(+) melanoma cells represents a powerful therapeutic approach against metastatic melanoma.
Irshad H, Oh E-Y, Schmolze D, Quintana LM, Collins L, Tamimi RM, Beck AH. Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method [Internet]. arXiv 2016; Publisher's VersionAbstract

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image labeling and nuclei labeling, and compare their performance with automated methods. Crowdsourcing-derived scores obtained greater concordance with the pathologist interpretations for both image labeling and nuclei labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,483 TMA images from 1,909 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

Wang D, Khosla A, Gargeya R, Irshad H, Beck AH. Deep Learning for Identifying Metastatic Breast Cancer [Internet]. arXiv 2016; Publisher's VersionAbstract

The International Symposium on Biomedical Imaging
(ISBI) held a grand challenge to evaluate computational
systems for the automated detection of metastatic breast
cancer in whole slide images of sentinel lymph node biopsies.
Our team won both competitions in the grand challenge,
obtaining an area under the receiver operating curve
(AUC) of 0.925 for the task of whole slide image classification
and a score of 0.7051 for the tumor localization task.
A pathologist independently reviewed the same images, obtaining
a whole slide image classification AUC of 0.966 and
a tumor localization score of 0.733. Combining our deep
learning system’s predictions with the human pathologist’s
diagnoses increased the pathologist’s AUC to 0.995, representing
an approximately 85 percent reduction in human
error rate. These results demonstrate the power of using
deep learning to produce significant improvements in the
accuracy of pathological diagnoses.

Nagarkar DB, Mercan E, Weaver DL, Brunyé TT, Carney PA, Rendi MH, Beck AH, Frederick PD, Shapiro LG, Elmore JG. Region of interest identification and diagnostic agreement in breast pathology. Mod Pathol 2016;29(9):1004-11.Abstract
A pathologist's accurate interpretation relies on identifying relevant histopathological features. Little is known about the precise relationship between feature identification and diagnostic decision making. We hypothesized that greater overlap between a pathologist's selected diagnostic region of interest (ROI) and a consensus derived ROI is associated with higher diagnostic accuracy. We developed breast biopsy test cases that included atypical ductal hyperplasia (n=80); ductal carcinoma in situ (n=78); and invasive breast cancer (n=22). Benign cases were excluded due to the absence of specific abnormalities. Three experienced breast pathologists conducted an independent review of the 180 digital whole slide images, established a reference consensus diagnosis and marked one or more diagnostic ROIs for each case. Forty-four participating pathologists independently diagnosed and marked ROIs on the images. Participant diagnoses and ROI were compared with consensus reference diagnoses and ROI. Regression models tested whether percent overlap between participant ROI and consensus reference ROI predicted diagnostic accuracy. Each of the 44 participants interpreted 39-50 cases for a total of 1972 individual diagnoses. Percent ROI overlap with the expert reference ROI was higher in pathologists who self-reported academic affiliation (69 vs 65%, P=0.002). Percent overlap between participants' ROI and consensus reference ROI was then classified into ordinal categories: 0, 1-33, 34-65, 66-99 and 100% overlap. For each incremental change in the ordinal percent ROI overlap, diagnostic agreement increased by 60% (OR 1.6, 95% CI (1.5-1.7), P<0.001) and the association remained significant even after adjustment for other covariates. The magnitude of the association between ROI overlap and diagnostic agreement increased with increasing diagnostic severity. The findings indicate that pathologists are more likely to converge with an expert reference diagnosis when they identify an overlapping diagnostic image region, suggesting that future computer-aided detection systems that highlight potential diagnostic regions could be a helpful tool to improve accuracy and education.
Gupta M, Babic A, Beck AH, Terry K. TNF-α expression, risk factors, and inflammatory exposures in ovarian cancer: evidence for an inflammatory pathway of ovarian carcinogenesis?. Hum Pathol 2016;54:82-91.Abstract
Inflammatory cytokines, like tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), are elevated in ovarian cancer. Differences in cytokine expression by histologic subytpe or ovarian cancer risk factors can provide useful insight into ovarian cancer risk and etiology. We used ribonucleic acid in situ hybridization to assess TNF-α and IL-6 expression on tissue microarray slides from 78 epithelial ovarian carcinomas (51 serous, 12 endometrioid, 7 clear cell, 2 mucinous, 6 other) from a population-based case-control study. Cytokine expression was scored semiquantitatively, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using polytomous logistic regression. TNF-α was expressed in 46% of the tumors, whereas sparse IL-6 expression was seen in only 18% of the tumors. For both markers, expression was most common in high-grade serous carcinomas followed by endometrioid carcinomas. Parity was associated with a reduced risk of TNF-α-positive (OR, 0.3; 95% CI, 0.1-0.7 for 3 or more children versus none) but not TNF-α-negative tumors (P heterogeneity=.02). In contrast, current smoking was associated with a nearly 3-fold increase in risk of TNF-α-negative (OR, 2.8; 95% CI, 1.2-6.6) but not TNF-α-positive tumors (P heterogeneity = .06). Our data suggest that TNF-α expression in ovarian carcinoma varies by histologic subtype and provides some support for the role of inflammation in ovarian carcinogenesis. The novel associations detected in our study need to be validated in a larger cohort of patients in future studies.
Guarnerio J, Bezzi M, Jeong JC, Paffenholz SV, Berry K, Naldini MM, Lo-Coco F, Tay Y, Beck AH, Pandolfi PP. Oncogenic Role of Fusion-circRNAs Derived from Cancer-Associated Chromosomal Translocations. Cell 2016;165(2):289-302.Abstract
Chromosomal translocations encode oncogenic fusion proteins that have been proven to be causally involved in tumorigenesis. Our understanding of whether such genomic alterations also affect non-coding RNAs is limited, and their impact on circular RNAs (circRNAs) has not been explored. Here, we show that well-established cancer-associated chromosomal translocations give rise to fusion circRNAs (f-circRNA) that are produced from transcribed exons of distinct genes affected by the translocations. F-circRNAs contribute to cellular transformation, promote cell viability and resistance upon therapy, and have tumor-promoting properties in in vivo models. Our work expands the current knowledge regarding molecular mechanisms involved in cancer onset and progression, with potential diagnostic and therapeutic implications.
Hirko KA, Willett WC, Hankinson SE, Rosner BA, Beck AH, Tamimi RM, Eliassen HA. Healthy dietary patterns and risk of breast cancer by molecular subtype. Breast Cancer Res Treat 2016;155(3):579-88.Abstract
We examined associations between dietary quality indices and breast cancer risk by molecular subtype among 100,643 women in the prospective Nurses' Health Study (NHS) cohort, followed from 1984 to 2006. Dietary quality scores for the Alternative Healthy Eating Index (AHEI), alternate Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) dietary patterns were calculated from semi-quantitative food frequency questionnaires collected every 2-4 years. Breast cancer molecular subtypes were defined according to estrogen receptor (ER), progesterone receptor, human epidermal growth factor 2 (HER2), cytokeratin 5/6 (CK5/6), and epidermal growth factor receptor status from immunostained tumor microarrays in combination with histologic grade. Cox proportional hazards models, adjusted for age and breast cancer risk factors, were used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Competing risk analyses were used to assess heterogeneity by subtype. We did not observe any significant associations between the AHEI or aMED dietary patterns and risk of breast cancer by molecular subtype. However, a significantly reduced risk of HER2-type breast cancer was observed among women in 5th versus 1st quintile of the DASH dietary pattern [n = 134 cases, Q5 vs. Q1 HR (95 % CI) = 0.44 (0.25-0.77)], and the inverse trend across quintiles was significant (p trend = 0.02). We did not observe any heterogeneity in associations between AHEI (p het = 0.25), aMED (p het = 0.71), and DASH (p het = 0.12) dietary patterns and breast cancer by subtype. Adherence to the AHEI, aMED, and DASH dietary patterns was not strongly associated with breast cancer molecular subtypes.