Deep learning for cancer type classification and driver gene identification.

BACKGROUND: Genetic information is becoming more readily available and is increasingly being used to predict patient cancer types as well as their subtypes. Most classification methods thus far utilize somatic mutations as independent features for classification and are limited by study power. We aim to develop a novel method to effectively explore the landscape of genetic variants, including germline variants, and small insertions and deletions for cancer type prediction. RESULTS: We proposed DeepCues, a deep learning model that utilizes convolutional neural networks to unbiasedly derive features from raw cancer DNA sequencing data for disease classification and relevant gene discovery. Using raw whole-exome sequencing as features, germline variants and somatic mutations, including insertions and deletions, were interactively amalgamated for feature generation and cancer prediction. We applied DeepCues to a dataset from TCGA to classify seven different types of major cancers and obtained an overall accuracy of 77.6%. We compared DeepCues to conventional methods and demonstrated a significant overall improvement (p < 0.001). Strikingly, using DeepCues, the top 20 breast cancer relevant genes we have identified, had a 40% overlap with the top 20 known breast cancer driver genes. CONCLUSION: Our results support DeepCues as a novel method to improve the representational resolution of DNA sequencings and its power in deriving features from raw sequences for cancer type prediction, as well as discovering new cancer relevant genes.

Progesterone receptor antagonists reverse stem cell expansion and the paracrine effectors of progesterone action in the mouse mammary gland.

BACKGROUND: The ovarian hormones estrogen and progesterone (EP) are implicated in breast cancer causation. A specific consequence of progesterone exposure is the expansion of the mammary stem cell (MSC) and luminal progenitor (LP) compartments. We hypothesized that this effect, and its molecular facilitators, could be abrogated by progesterone receptor (PR) antagonists administered in a mouse model. METHODS: Ovariectomized FVB mice were randomized to 14 days of treatment: sham, EP, EP + telapristone (EP + TPA), EP + mifepristone (EP + MFP). Mice were then sacrificed, mammary glands harvested, and mammary epithelial cell lineages separated by flow cytometry using cell surface markers. RNA from each lineage was sequenced and differential gene expression was analyzed using DESeq. Quantitative PCR was performed to confirm the candidate genes discovered in RNA seq. ANOVA with Tukey post hoc analysis was performed to compare relative expression. Alternative splicing events were examined using the rMATs multivariate analysis tool. RESULTS: Significant increases in the MSC and luminal mature (LM) cell fractions were observed following EP treatment compared to control (p < 0.01 and p < 0.05, respectively), whereas the LP fraction was significantly reduced (p < 0.05). These hormone-induced effects were reversed upon exposure to TPA and MFP (p < 0.01 for both). Gene Ontology analysis of RNA-sequencing data showed EP-induced enrichment of several pathways, with the largest effect on Wnt signaling in MSC, significantly repressed by PR inhibitors. In LP cells, significant induction of Wnt4 and Rankl, and Wnt pathway intermediates Lrp2 and Axin2 (confirmed by qRTPCR) were reversed by TPA and MFP (p < 0.0001). Downstream signaling intermediates of these pathways (Lrp5, Mmp7) showed similar effects. Expression of markers of epithelial-mesenchymal transition (Cdh1, Cdh3) and the induction of EMT regulators (Zeb1, Zeb2, Gli3, Snai1, and Ptch2) were significantly responsive to progesterone. EP treatment was associated with large-scale alternative splicing events, with an enrichment of motifs associated with Srsf, Esrp, and Rbfox families. Exon skipping was observed in Cdh1, Enah, and Brd4. CONCLUSIONS: PR inhibition reverses known tumorigenic pathways in the mammary gland and suppresses a previously unknown effect of progesterone on RNA splicing events. In total, our results strengthen the case for reconsideration of PR inhibitors for breast cancer prevention.

Near-infrared remotely triggered drug-release strategies for cancer treatment.

Remotely controlled, localized drug delivery is highly desirable for potentially minimizing the systemic toxicity induced by the administration of typically hydrophobic chemotherapy drugs by conventional means. Nanoparticle-based drug delivery systems provide a highly promising approach for localized drug delivery, and are an emerging field of interest in cancer treatment. Here, we demonstrate near-IR light-triggered release of two drug molecules from both DNA-based and protein-based hosts that have been conjugated to near-infrared-absorbing Au nanoshells (SiO2 core, Au shell), each forming a light-responsive drug delivery complex. We show that, depending upon the drug molecule, the type of host molecule, and the laser illumination method (continuous wave or pulsed laser), in vitro light-triggered release can be achieved with both types of nanoparticle-based complexes. Two breast cancer drugs, docetaxel and HER2-targeted lapatinib, were delivered to MDA-MB-231 and SKBR3 (overexpressing HER2) breast cancer cells and compared with release in noncancerous RAW 264.7 macrophage cells. Continuous wave laser-induced release of docetaxel from a nanoshell-based DNA host complex showed increased cell death, which also coincided with nonspecific cell death from photothermal heating. Using a femtosecond pulsed laser, lapatinib release from a nanoshell-based human serum albumin protein host complex resulted in increased cancerous cell death while noncancerous control cells were unaffected. Both methods provide spatially and temporally localized drug-release strategies that can facilitate high local concentrations of chemotherapy drugs deliverable at a specific treatment site over a specific time window, with the potential for greatly minimized side effects.

BRCA1 mutation influences progesterone response in human benign mammary organoids.

BACKGROUND: Women, who carry a germline BRCA1 gene mutation, have a markedly increased risk of developing breast cancer during their lifetime. While BRCA1 carriers frequently develop triple-negative, basal-like, aggressive breast tumors, hormone signaling is important in the genesis of BRCA1 mutant breast cancers. We investigated the hormone response in BRCA1-mutated benign breast tissue using an in vitro organoid system. METHODS: Scaffold-free, multicellular human breast organoids generated from benign breast tissues from non-carrier or BRCA1 mutation carriers were treated in vitro with a stepwise menstrual cycle hormone regimen of estradiol (E2) and progesterone (P4) over the course of 28 days. RESULTS: Breast organoids exhibited characteristics of the native breast tissue, including expression of hormone receptors, collagen production, and markers of luminal and basal epithelium, and stromal fibroblasts. RNA sequencing analysis revealed distinct gene expression in response to hormone treatment in the non-carrier and BRCA1-mutated organoids. The selective progesterone receptor modulator, telapristone acetate (TPA), was used to identify specifically PR regulated genes. Specifically, extracellular matrix organization genes were regulated by E2+P4+TPA in the BRCA1-mutated organoids but not in the non-carrier organoids. In contrast, in the non-carrier organoids, known PR target genes such as the cell cycle genes were inhibited by TPA. CONCLUSIONS: These data show that BRCA1 mutation influences hormone response and in particular PR activity which differs from that of non-carrier organoids. Our organoid model system revealed important insights into the role of PR in BRCA1-mutated benign breast cells and the critical paracrine actions that modify hormone receptor (HR)-negative cells. Further analysis of the molecular mechanism of BRCA1 and PR crosstalk is warranted using this model system.

Cancer classification and pathway discovery using non-negative matrix factorization.

OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for understanding disease. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type. DESIGN: We applied non-smooth non-negative matrix factorization (nsNMF) and support vector machine (SVM) to utilize the full range of sequencing data, aiming to better aggregate genetic mutations and improve their power to predict disease type. More specifically, we introduce a novel classifier to distinguish cancer types using somatic mutations obtained from whole-exome sequencing data. Mutations were identified from multiple cancers and scored using SIFT, PP2, and CADD, and collapsed at the individual gene level. nsNMF was then applied to reduce dimensionality and obtain coefficient and basis matrices. A feature matrix was derived from the obtained matrices to train a classifier for cancer type classification with the SVM model. RESULTS: We have demonstrated that the classifier was able to distinguish four cancer types with reasonable accuracy. In five-fold cross-validations using mutation counts as features, the average prediction accuracy was 80% (SEM = 0.1%), significantly outperforming baselines and outperforming models using mutation scores as features. CONCLUSION: Using the factor matrices derived from the nsNMF, we identified multiple genes and pathways that are significantly associated with each cancer type. This study presents a generic and complete pipeline to study the associations between somatic mutations and cancers. The proposed method can be adapted to other studies for disease status classification and pathway discovery.

Using natural language processing and machine learning to identify breast cancer local recurrence.

BACKGROUND: Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local recurrences in breast cancer patients can reduce the time-consuming work of a manual chart review. METHODS: We design a novel concept-based filter and a prediction model to detect local recurrences using EHRs. In the training dataset, we manually review a development corpus of 50 progress notes and extract partial sentences that indicate breast cancer local recurrence. We process these partial sentences to obtain a set of Unified Medical Language System (UMLS) concepts using MetaMap, and we call it positive concept set. We apply MetaMap on patients' progress notes and retain only the concepts that fall within the positive concept set. These features combined with the number of pathology reports recorded for each patient are used to train a support vector machine to identify local recurrences. RESULTS: We compared our model with three baseline classifiers using either full MetaMap concepts, filtered MetaMap concepts, or bag of words. Our model achieved the best AUC (0.93 in cross-validation, 0.87 in held-out testing). CONCLUSIONS: Compared to a labor-intensive chart review, our model provides an automated way to identify breast cancer local recurrences. We expect that by minimally adapting the positive concept set, this study has the potential to be replicated at other institutions with a moderately sized training dataset.

Association between breast cancer genetic susceptibility variants and terminal duct lobular unit involution of the breast.

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.

Motivations for contralateral prophylactic mastectomy as a function of socioeconomic status.

BACKGROUND: Despite no demonstrated survival advantage for women at average risk of breast cancer, rates of contralateral prophylactic mastectomy (CPM) continue to increase. Research reveals women with higher socioeconomic status (SES) are more likely to select CPM. This study examines how indicators of SES, age, and disease severity affect CPM motivations. METHODS: Patients (N = 113) who underwent CPM at four Indiana University affiliated hospitals completed telephone interviews in 2013. Participants answered questions about 11 CPM motivations and provided demographic information. Responses to motivation items were factor analyzed, resulting in 4 motivational factors: reducing long-term risk, symmetry, avoiding future medical visits, and avoiding treatments. RESULTS: Across demographic differences, reducing long-term risk was the strongest CPM motivation. Lower income predicted stronger motivation to reduce long-term risk and avoid treatment. Older participants were more motivated to avoid treatment; younger and more-educated patients were more concerned about symmetry. Greater severity of diagnosis predicted avoiding treatments. CONCLUSIONS: Reducing long-term risk is the primary motivation across groups, but there are also notable differences as a function of age, education, income, and disease severity. To stop the trend of increasing CPM, physicians must tailor patient counseling to address motivations that are consistent across patient populations and those that vary between populations.

Ages at menarche- and menopause-related genetic variants in relation to terminal duct lobular unit involution in normal breast tissue.

Reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have been associated with higher breast cancer risk. Younger age at menarche and older age at menopause have been previously related to lower levels of TDLU involution. To determine a possible genetic link, we examined whether single-nucleotide polymorphisms (SNPs) previously established in genome-wide association studies (GWAS) for ages at menarche and menopause are associated with TDLU involution. We conducted a pooled analysis of 862 women from two studies. H&E tissue sections were assessed for numbers of TDLUs and acini/TDLU. Poisson regression models were used to estimate associations of 36 menarche- and 21 menopause-SNPs with TDLU counts, acini counts/TDLU, and the product of these two measures, adjusting for age and study site. Fourteen percent of evaluated SNPs (eight SNPs) were associated with TDLU counts at p < 0.05, suggesting an enrichment of associations with TDLU counts. However, only menopause-SNPs had >50 % that were either significantly or nonsignificantly associated with TDLU measures in the directions consistent with their relationships shown in GWAS. Among ten SNPs that were statistically significantly associated with at least one TDLU involution measure (p < 0.05), seven SNPs (rs466639: RXRG; rs2243803: SLC14A2; rs2292573: GAB2; rs6438424: 3q13.32; rs7606918: METAP1D; rs11668344: TMEM150B; rs1635501: EXO1) were associated in the consistent directions. Our data suggest that the loci associated with ages at menarche and menopause may influence TDLU involution, suggesting some shared genetic mechanisms. However, larger studies are needed to confirm the results.

Progesterone receptor blockade in human breast cancer cells decreases cell cycle progression through G2/M by repressing G2/M genes.

BACKGROUND: The synthesis of specific, potent progesterone antagonists adds potential agents to the breast cancer prevention and treatment armamentarium. The identification of individuals who will benefit from these agents will be a critical factor for their clinical success. METHODS: We utilized telapristone acetate (TPA; CDB-4124) to understand the effects of progesterone receptor (PR) blockade on proliferation, apoptosis, promoter binding, cell cycle progression, and gene expression. We then identified a set of genes that overlap with human breast luteal-phase expressed genes and signify progesterone activity in both normal breast cells and breast cancer cell lines. RESULTS: TPA administration to T47D cells results in a 30 % decrease in cell number at 24 h, which is maintained over 72 h only in the presence of estradiol. Blockade of progesterone signaling by TPA for 24 h results in fewer cells in G2/M, attributable to decreased expression of genes that facilitate the G2/M transition. Gene expression data suggest that TPA affects several mechanisms that progesterone utilizes to control gene expression, including specific post-translational modifications, and nucleosomal organization and higher order chromatin structure, which regulate access of PR to its DNA binding sites. CONCLUSIONS: By comparing genes induced by the progestin R5020 in T47D cells with those increased in the luteal-phase normal breast, we have identified a set of genes that predict functional progesterone signaling in tissue. These data will facilitate an understanding of the ways in which drugs such as TPA may be utilized for the prevention, and possibly the therapy, of human breast cancer.

Phenotypic plasticity in normal breast derived epithelial cells.

BACKGROUND: Normal, healthy human breast tissue from a variety of volunteer donors has become available for research thanks to the establishment of the Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center (KTB). Multiple epithelial (K-HME) and stromal cells (K-HMS) were established from the donated tissue. Explant culture was utilized to isolate the cells from pieces of breast tissue. Selective media and trypsinization were employed to select either epithelial cells or stromal cells. The primary, non-transformed epithelial cells, the focus of this study, were characterized by immunohistochemistry, flow cytometry, and in vitro cell culture. RESULTS: All of the primary, non-transformed epithelial cells tested have the ability to differentiate in vitro into a variety of cell types when plated in or on biologic matrices. Cells identified include stratified squamous epithelial, osteoclasts, chondrocytes, adipocytes, neural progenitors/neurons, immature muscle and melanocytes. The cells also express markers of embryonic stem cells. CONCLUSIONS: The cell culture conditions employed select an epithelial cell that is pluri/multipotent. The plasticity of the epithelial cells developed mimics that seen in metaplastic carcinoma of the breast (MCB), a subtype of triple negative breast cancer; and may provide clues to the origin of this particularly aggressive type of breast cancer. The KTB is a unique biorepository, and the normal breast epithelial cells isolated from donated tissue have significant potential as new research tools.

Next-generation transcriptome sequencing of the premenopausal breast epithelium using specimens from a normal human breast tissue bank.

INTRODUCTION: Our efforts to prevent and treat breast cancer are significantly impeded by a lack of knowledge of the biology and developmental genetics of the normal mammary gland. In order to provide the specimens that will facilitate such an understanding, The Susan G. Komen for the Cure Tissue Bank at the IU Simon Cancer Center (KTB) was established. The KTB is, to our knowledge, the only biorepository in the world prospectively established to collect normal, healthy breast tissue from volunteer donors. As a first initiative toward a molecular understanding of the biology and developmental genetics of the normal mammary gland, the effect of the menstrual cycle and hormonal contraceptives on DNA expression in the normal breast epithelium was examined. METHODS: Using normal breast tissue from 20 premenopausal donors to KTB, the changes in the mRNA of the normal breast epithelium as a function of phase of the menstrual cycle and hormonal contraception were assayed using next-generation whole transcriptome sequencing (RNA-Seq). RESULTS: In total, 255 genes representing 1.4% of all genes were deemed to have statistically significant differential expression between the two phases of the menstrual cycle. The overwhelming majority (221; 87%) of the genes have higher expression during the luteal phase. These data provide important insights into the processes occurring during each phase of the menstrual cycle. There was only a single gene significantly differentially expressed when comparing the epithelium of women using hormonal contraception to those in the luteal phase. CONCLUSIONS: We have taken advantage of a unique research resource, the KTB, to complete the first-ever next-generation transcriptome sequencing of the epithelial compartment of 20 normal human breast specimens. This work has produced a comprehensive catalog of the differences in the expression of protein-coding genes as a function of the phase of the menstrual cycle. These data constitute the beginning of a reference data set of the normal mammary gland, which can be consulted for comparison with data developed from malignant specimens, or to mine the effects of the hormonal flux that occurs during the menstrual cycle.

Characterizing the heterogeneity of triple-negative breast cancers using microdissected normal ductal epithelium and RNA-sequencing.

Triple-negative breast cancers (TNBCs) are a heterogeneous set of tumors defined by an absence of actionable therapeutic targets (ER, PR, and HER-2). Microdissected normal ductal epithelium from healthy volunteers represents a novel comparator to reveal insights into TNBC heterogeneity and to inform drug development. Using RNA-sequencing data from our institution and The Cancer Genome Atlas (TCGA) we compared the transcriptomes of 94 TNBCs, 20 microdissected normal breast tissues from healthy volunteers from the Susan G. Komen for the Cure Tissue Bank, and 10 histologically normal tissues adjacent to tumor. Pathway analysis comparing TNBCs to optimized normal controls of microdissected normal epithelium versus classic controls composed of adjacent normal tissue revealed distinct molecular signatures. Differential gene expression of TNBC compared with normal comparators demonstrated important findings for TNBC-specific clinical trials testing targeted agents; lack of over-expression for negative studies and over-expression in studies with drug activity. Next, by comparing each individual TNBC to the set of microdissected normals, we demonstrate that TNBC heterogeneity is attributable to transcriptional chaos, is associated with non-silent DNA mutational load, and explains transcriptional heterogeneity in addition to known molecular subtypes. Finally, chaos analysis identified 146 core genes dysregulated in >90 % of TNBCs revealing an over-expressed central network. In conclusion, use of microdissected normal ductal epithelium from healthy volunteers enables an optimized approach for studying TNBC and uncovers biological heterogeneity mediated by transcriptional chaos.

Breast cancer prevention with liquiritigenin from licorice through the inhibition of aromatase and protein biosynthesis in high-risk women's breast tissue.

Breast cancer risk continues to increase post menopause. Anti-estrogen therapies are available to prevent postmenopausal breast cancer in high-risk women. However, their adverse effects have reduced acceptability and overall success in cancer prevention. Natural products such as hops (Humulus lupulus) and three pharmacopeial licorice (Glycyrrhiza) species have demonstrated estrogenic and chemopreventive properties, but little is known regarding their effects on aromatase expression and activity as well as pro-proliferation pathways in human breast tissue. We show that Gycyrrhiza inflata (GI) has the highest aromatase inhibition potency among these plant extracts. Moreover, phytoestrogens such as liquiritigenin which is common in all licorice species have potent aromatase inhibitory activity, which is further supported by computational docking of their structures in the binding pocket of aromatase. In addition, GI extract and liquiritigenin suppress aromatase expression in the breast tissue of high-risk postmenopausal women. Although liquiritigenin has estrogenic effects in vitro, with preferential activity through estrogen receptor (ER)-ß, it reduces estradiol-induced uterine growth in vivo. It downregulates RNA translation, protein biosynthesis, and metabolism in high-risk women's breast tissue. Finally, it reduces the rate of MCF-7 cell proliferation, with repeated dosing. Collectively, these data suggest that liquiritigenin has breast cancer prevention potential for high-risk postmenopausal women.

Lipid exposure activates gene expression changes associated with estrogen receptor negative breast cancer.

Improved understanding of local breast biology that favors the development of estrogen receptor negative (ER-) breast cancer (BC) would foster better prevention strategies. We have previously shown that overexpression of specific lipid metabolism genes is associated with the development of ER- BC. We now report results of exposure of MCF-10A and MCF-12A cells, and mammary organoids to representative medium- and long-chain polyunsaturated fatty acids. This exposure caused a dynamic and profound change in gene expression, accompanied by changes in chromatin packing density, chromatin accessibility, and histone posttranslational modifications (PTMs). We identified 38 metabolic reactions that showed significantly increased activity, including reactions related to one-carbon metabolism. Among these reactions are those that produce S-adenosyl-L-methionine for histone PTMs. Utilizing both an in-vitro model and samples from women at high risk for ER- BC, we show that lipid exposure engenders gene expression, signaling pathway activation, and histone marks associated with the development of ER- BC.

Selective progesterone receptor blockade prevents BRCA1-associated mouse mammary tumors through modulation of epithelial and stromal genes.

Pharmacological approaches to breast cancer risk-reduction for BRCA1 mutation carriers would provide an alternative to mastectomy. BRCA1-deficiency dysregulates progesterone signaling, promoting tumorigenesis. Selective progesterone receptor (PR) modulators (SPRMs) are therefore candidate prevention agents. However, their efficacy varies in different BRCA1-deficient mouse models. We examined chemopreventive efficacy of telapristone acetate (TPA), ulipristal acetate (UPA) and mifepristone (MFP) in mice with a conditional knockout of the Brca1 C-terminal domain. The SPRMs displayed a spectrum of efficacy: UPA was most effective, TPA less, and MFP ineffective. Compared to no-treatment controls, UPA reduced tumorigenesis (p = 0.04), and increased tumor latency (p = 0.03). In benign mammary glands, UPA decreased Ki67 (p < 0.001) and increased PR expression (p < 0.0001). RNA sequencing analysis revealed distinct gene expression in response to UPA and MFP. UPA downregulated glycolysis and extracellular matrix-inflammation genes (Fn1, Ptgs2, Tgfb2, Tgfb3) whereas MFP downregulated claudin genes and upregulated amino acid metabolism and inflammation genes. The anti-glucocorticoid effects of MFP appeared not to be tumor-protective, while altering estrogen receptor signaling and NF-kB activation. Our study points to an important role of epithelial PR and its paracrine action on the microenvironment in BRCA1-deficient mammary tumorigenesis, and prevention.

Somatic genetic aberrations in benign breast disease and the risk of subsequent breast cancer.

It is largely unknown how the development of breast cancer (BC) is transduced by somatic genetic alterations in the benign breast. Since benign breast disease is an established risk factor for BC, we established a case-control study of women with a history of benign breast biopsy (BBB). Cases developed BC at least one year after BBB and controls did not develop BC over an average of 17 years following BBB. 135 cases were matched to 69 controls by age and type of benign change: non-proliferative or proliferation without atypia (PDWA). Whole-exome sequencing (WES) was performed for the BBB. Germline DNA (available from n = 26 participants) was utilized to develop a mutation-calling pipeline, to allow differentiation of somatic from germline variants. Among the 204 subjects, two known mutational signatures were identified, along with a currently uncatalogued signature that was significantly associated with triple negative BC (TNBC) (p = 0.007). The uncatalogued mutational signature was validated in 109 TNBCs from TCGA (p = 0.001). Compared to non-proliferative samples, PDWA harbors more abundant mutations at PIK3CA pH1047R (p < 0.001). Among the 26 BBB whose somatic copy number variation could be assessed, deletion of MLH3 is significantly associated with the mismatch repair mutational signature (p < 0.001). Matched BBB-cancer pairs were available for ten cases; several mutations were shared between BBB and cancers. This initial study of WES of BBB shows its potential for the identification of genetic alterations that portend breast oncogenesis. In future larger studies, robust personalized breast cancer risk indicators leading to novel interception paradigms can be assessed.

Selective Progesterone Receptor Modulators in Early-Stage Breast Cancer: A Randomized, Placebo-Controlled Phase II Window-of-Opportunity Trial Using Telapristone Acetate.

PURPOSE: Selective progesterone receptor modulators (SPRMs) show preclinical activity against hormone-sensitive breast cancer, but have not been tested in patients with early, treatment-naïve tumors. PATIENTS AND METHODS: In a double-blind presurgical window trial of oral telapristone acetate (TPA) 12 mg daily versus placebo, 70 patients with early-stage breast cancer were randomized 1:1 (stratified by menopause) and treated for 2 to 10 weeks. The primary endpoint was change in Ki67 between diagnostic biopsy and surgical specimens. Gene expression pre- and posttherapy was assessed using RNA-sequencing and gene set enrichment analysis was performed to determine pathways enriched in response to TPA and placebo treatments. RESULTS: Among 61 evaluable women (29 placebo and 32 telapristone acetate), 91% of tumors were ER/PR positive. The mean Ki67 declined by 5.5% in all women treated with telapristone acetate (P = 0.003), and by 4.2% in all women treated with placebo (P = 0.04). After menopausal stratification, the Ki67 decline remained significant in 22 telapristone acetate-treated premenopausal women (P = 0.03). Differential gene expression analysis showed no significant modulation overall. However, in a subset of tumors that demonstrated ≥30% relative reduction in Ki67 in the telapristone acetate group, genes related to cell-cycle progression, and those in the HER2 amplicon were significantly downregulated. In contrast, no significantly enriched pathways were identified in the placebo group. CONCLUSIONS: Patients treated with telapristone acetate whose Ki67 decreased by ≥30% demonstrated a selective antiproliferative signal, with a potentially important effect on HER2 amplicon genes. Evaluation of SPRMs in a neoadjuvant trial is merited, with attention to predictors of response to SPRM therapy, and inclusion of pre- and postmenopausal women.

Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast.

Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.

Nanoshell-enabled photothermal cancer therapy: impending clinical impact.

Much of the current excitement surrounding nanoscience is directly connected to the promise of new nanoscale applications in cancer diagnostics and therapy. Because of their strongly resonant light-absorbing and light-scattering properties that depend on shape, noble metal nanoparticles provide a new and powerful tool for innovative light-based approaches. Nanoshellsspherical, dielectric core, gold shell nanoparticleshave been central to the development of photothermal cancer therapy and diagnostics for the past several years. By manipulating nanoparticle shape, researchers can tune the optical resonance of nanoshells to any wavelength of interest. At wavelengths just beyond the visible spectrum in the near-infrared, blood and tissue are maximally transmissive. When nanoshell resonances are tuned to this region of the spectrum, they become useful contrast agents in the diagnostic imaging of tumors. When illuminated, they can serve as nanoscale heat sources, photothermally inducing cell death and tumor remission. As nanoshell-based diagnostics and therapeutics move from laboratory studies to clinical trials, this Account examines the highly promising achievements of this approach in the context of the challenges of this complex disease. More broadly, these materials present a concrete example of a highly promising application of nanochemistry to a biomedical problem. We describe the properties of nanoshells that are relevant to their preparation and use in cancer diagnostics and therapy. Specific surface chemistries are necessary for passive uptake of nanoshells into tumors and for targeting specific cell types by bioconjugate strategies. We also describe the photothermal temperature increases that can be achieved in surrogate structures known as tissue phantoms and the accuracy of models of this effect using heat transport analysis. Nanoshell-based photothermal therapy in several animal models of human tumors have produced highly promising results, and we include nanoparticle dosage information, thermal response, and tumor outcomes for these experiments. Using immunonanoshells, infrared diagnostic imaging contrast enhancement and photothermal therapy have been integrated into a single procedure. Finally, we examine a novel "Trojan horse" strategy for nanoparticle delivery that overcomes the challenge of accessing and treating the hypoxic regions of tumors, where blood flow is minimal or nonexistent. The ability to survive hypoxia selects aggressive cells which are likely to be the source of recurrence and metastasis. Treatment of these regions has been incredibly difficult. Ultimately, we look beyond the current research and assess the next challenges as nanoshell-based photothermal cancer therapy is implemented in clinical practice.