Generative Adversarial Networks Accurately Reconstruct Pan-Cancer Histology from Pathologic, Genomic, and Radiographic Latent Features.

Artificial intelligence models have been increasingly used in the analysis of tumor histology to perform tasks ranging from routine classification to identification of novel molecular features. These approaches distill cancer histologic images into high-level features which are used in predictions, but understanding the biologic meaning of such features remains challenging. We present and validate a custom generative adversarial network - HistoXGAN - capable of reconstructing representative histology using feature vectors produced by common feature extractors. We evaluate HistoXGAN across 29 cancer subtypes and demonstrate that reconstructed images retain information regarding tumor grade, histologic subtype, and gene expression patterns. We leverage HistoXGAN to illustrate the underlying histologic features for deep learning models for actionable mutations, identify model reliance on histologic batch effect in predictions, and demonstrate accurate reconstruction of tumor histology from radiographic imaging for a 'virtual biopsy'.

The VEGF-Hypoxia Signature Is Upregulated in Basal-like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer.

PURPOSE: Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry. EXPERIMENTAL DESIGN: We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets. RESULTS: The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002). CONCLUSIONS: These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment.

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased γ-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment.

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased γ-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

Increased Otoferlin Expression in B Cells Is Associated with Muscle Weakness in Untreated Juvenile Dermatomyositis: A Pilot Study.

Otoferlin mRNA expression is increased in JDM patients' PBMCs and muscle compared to healthy controls. This study aims to evaluate the role of otoferlin in JDM disease pathophysiology and its association with disease activity in untreated children with JDM. A total of 26 untreated JDM (88.5% female, 92.3% white, non-Hispanic) and 15 healthy controls were included in this study. Otoferlin mRNA expression was determined by qRT-PCR before and a few months after therapy. Detailed flow cytometry of various cell surface markers and cytoplasmic otoferlin was performed to identify cells expressing otoferlin. In addition, muscle otoferlin expression was evaluated in situ in six untreated JDM patients and three healthy controls. There was a significant increase in otoferlin expression in JDM children compared to controls (Median 67.5 vs. 2.1; p = 0.001). There was a positive correlation between mRNA otoferlin expression and the following disease activity markers: disease activity scores (DAS)-total (rs = 0.62, p < 0.001); childhood myositis assessment scale (CMAS) (rs = -0.61, p = 0.002); neopterin (rs = 0.57, p = 0.004) and von Willebrand factor antigen (vWF: Ag) (rs = 0.60, p = 0.004). Most of the otoferlin-positive cells were unswitched B cells (63-99.4%), with 65-75% of them expressing plasmablast markers (CD19+, IgM+, CD38hi, CD24-). The findings of this pilot study suggest that otoferlin expression is associated with muscle weakness, making it a possible biomarker of disease activity. Additionally, B cells and plasmablasts were the primary cells expressing otoferlin.

Expression analysis of BACH1 with clinical variables using the US breast cancer patient cohort.

Background: Studies on functional roles of BACH1 reveal that BACH1 promotes cancer metastasis and regulates metabolic networks for metastatic processes. However, little is known about BACH1 protein expression in breast tumors and its relevance to clinical variables as a biomarker for patients with breast tumors. Methods: Using a tissue microarray (TMA) of breast tumor tissues isolated from a patient cohort (N = 130) expression of BACH1 and its target gene MCT1 (encoded by SLC16A1) were monitored by immunohistochemistry (IHC) assays and scored for further analyses. We examined the association between scores of BACH1 (Allredscoretotal) or MCT1 (Hscoretotal3×2×1x) with clinical variables including: breast cancer subtypes, tissue types, tumor size, patient's racial/ethnic background, and age group. Groups were compared using the Mann-Whitney U test (or the non-parametric Kruskal-Wallis test when appropriate) for numerical data. A proportional odds ordinal logistic model was used to examine multiple covariates. Associations between variables were evaluated with the Spearman's correlation coefficient. Results: BACH1 and MCT1 expression were detected in 90.76% (N = 118/130) and 92.30% (N = 120/130) of patients by IHC, respectively, in our study. After dichotomizing tumor size (small: 3-25 in diameter vs. big: 27-85 mm in diameter), BACH1 expression scores were significantly higher (p = 0.015) in the bigger tumor group (mean [SD]; 4.20 [1.796]) compared with the smaller tumor group (3.920 [1.693]). Of interest, we also observed significantly higher BACH1 scores (p = 0.004) in tumors from Black women (3.971 [1.514]; N = 69) compared with those of White women (3.02 [1.942]; N = 49). Consistent with mRNA expression analysis, BACH1 expression is most abundant in the basal-like tumors among all subtypes, specifically in Black women, whereas MCT1 expression scores are considerably higher in the basal-like tumors regardless of race. In addition, there was a positive association between BACH1 and MCT1 IHC scores in tumors from Black women, although a weak association between them in tumors from White women. In general, we did not detect associations between MCT1 IHC scores and race, tumor size, tissue types, or patient's age. Conclusions: We found strong associations of BACH1 expression with tumor size and the basal-like subtype, respectively. Importantly, BACH1 expresses significantly higher in tumors from Black women than White women, as well as in the basal-like subtype of breast tumors from Black women. Our study suggests that BACH1 expression could serve as a potential race-associated biomarker indicating poor prognosis.

Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populations.

BACKGROUND: Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways. METHODS: De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression. RESULTS: After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P < 0.05) and the overall cohort (AA = 28% vs. EA = 37%, P = 2.08e-05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P < 0.05) and HR+/HER2- (24% vs. 15%, P = 3e-03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e-162), HSPA1A (logFC = - 2.73, P = 2.43e-49), ATRX (logFC = - 1.93, P = 5.89e-83), and NUTM2F (logFC = 2.28, P = 3.22e-196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e-06), LTE2_UP.V1_UP (P = 2.90e-05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074). CONCLUSIONS: We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

Deep learning generates synthetic cancer histology for explainability and education.

Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks make their predictions remains a significant challenge, but explainability tools help provide insights into what models have learned when corresponding histologic features are poorly defined. Here, we present a method for improving explainability of DNN models using synthetic histology generated by a conditional generative adversarial network (cGAN). We show that cGANs generate high-quality synthetic histology images that can be leveraged for explaining DNN models trained to classify molecularly-subtyped tumors, exposing histologic features associated with molecular state. Fine-tuning synthetic histology through class and layer blending illustrates nuanced morphologic differences between tumor subtypes. Finally, we demonstrate the use of synthetic histology for augmenting pathologist-in-training education, showing that these intuitive visualizations can reinforce and improve understanding of histologic manifestations of tumor biology.

Integration of clinical features and deep learning on pathology for the prediction of breast cancer recurrence assays and risk of recurrence.

Gene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute to delays in care, and may not be available in low-resource settings. Here, we describe the training and independent validation of a deep learning model that predicts recurrence assay result and risk of recurrence using both digital histology and clinical risk factors. We demonstrate that this approach outperforms an established clinical nomogram (area under the receiver operating characteristic curve of 0.83 versus 0.76 in an external validation cohort, p = 0.0005) and can identify a subset of patients with excellent prognoses who may not need further genomic testing.

An enhancer variant associated with breast cancer susceptibility in Black women regulates TNFSF10 expression and antitumor immunity in triple-negative breast cancer.

Women of African ancestry have the highest mortality from triple-negative breast cancer (TNBC) of all racial groups. To understand the genomic basis of breast cancer in the populations, we previously conducted genome-wide association studies and identified single nucleotide polymorphisms (SNPs) associated with breast cancer in Black women. In this study, we investigated the functional significance of the top associated SNP rs13074711. We found the SNP served as an enhancer variant and regulated TNFSF10 (TRAIL) expression in TNBC cells, with a significant association between the SNP genotype and TNFSF10 expression in breast tumors. Mechanistically, rs13074711 modulated the binding activity of c-MYB at the motif and thereby controlled TNFSF10 expression. Interestingly, TNFSF10 expression in many cancers was consistently lower in African Americans compared with European Americans. Furthermore, TNFSF10 expression in TNBC was significantly correlated with the expression of antiviral immune genes and was regulated by type I interferons (IFNs). Accordingly, loss of TNFSF10 resulted in a profound decrease in apoptosis of TNBC cells in response to type I IFNs and poly(I:C), a synthetic analogue of double stranded virus. Lastly, in a syngeneic mouse model of breast cancer, TNFSF10-deficiency in breast tumors decreased tumor-infiltrated CD4+ and CD8+ T cell quantities. Collectively, our results suggested that TNFSF10 plays an important role in the regulation of antiviral immune responses in TNBC, and the expression is in part regulated by a genetic variant associated with breast cancer in Black women. Our results underscore the important contributions of genetic variants to immune defense mechanisms.

Clinicopathological pattern of oestrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 over-expression of epithelial ovarian carcinomas in Nigeria.

Background: Ovarian cancer is the leading cause of death from all gynaecological malignancies. Only few biomarkers of epithelial ovarian cancer (EOC) prognosis have been studied so far among Nigerian patients. Objective: To determine the pattern of oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2) expression in patients with EOC seen in Nigeria. Materials and Methods: This was a retrospective multicentre study of 102 cases of epithelial ovarian cancers. Relevant clinical information was obtained from hospital-based records in the 3 participating centres. Tissue microarrays were constructed using representative tumour tissue and the ER, PR and HER2 immunohistochemical staining was carried out at the University of Chicago, United States of America. Results: Serous carcinomas predominated (71% of cases). ER positivity was observed in 31.4%, PR positivity in 21.5% and HER2/neu in 16.7% of tumours. Fifty-two percent of tumours were triple negative. Serous tumours were significantly associated with ER positivity (p=0.001). Mean patient age for EOC was 52.6 ± 13.1 years. There were no statistically significant associations between hormone receptor status and histological grade, FIGO staging or survival. Conclusion: Serous tumours were significantly associated with ER expression while non-serous tumours tended to be triple negative.

Racial disparities in survival outcomes among breast cancer patients by molecular subtypes.

PURPOSE: Differences in tumor biology, genomic architecture, and health care delivery patterns contribute to the breast cancer mortality gap between White and Black patients in the US. Although this gap has been well documented in previous literature, it remains uncertain how large the actual effect size of race is for different survival outcomes and the four breast cancer subtypes. METHODS: We established a breast cancer patient cohort at the University of Chicago Comprehensive Cancer Center. We chose five major survival outcomes to study: overall survival, recurrence-free survival, breast-cancer-specific survival, time-to-recurrence and post-recurrence survival. Cox proportional hazards models were used to estimate the hazard ratios between Black and White patients, adjusting for selected patient, tumor, and treatment characteristics, and also stratified by the four breast cancer subtypes. RESULTS: The study included 2795 stage I-III breast cancer patients (54% White and 38% Black). After adjusting for selected patient, tumor and treatment characteristics, Black patients still did worse than White patients in all five survival outcomes. The racial difference was highest within the HR-/HER2+ subgroup, in both overall survival (hazard ratio = 4.00, 95% CI 1.47-10.86) and recurrence-free survival (hazard ratio = 3.00, 95% CI 1.36-6.60), adjusting for age at diagnosis, cancer stage, and comorbidities. There was also a significant racial disparity within the HR+/HER2- group in both overall survival and recurrence-free survival. CONCLUSIONS: Our study confirmed that racial disparity existed between White and Black breast cancer patients in terms of both survival and recurrence, and found that this disparity was largest among HR-/HER2+ and HR+/HER2- patients.

p50 mono-ubiquitination and interaction with BARD1 regulates cell cycle progression and maintains genome stability.

p50, the mature product of NFKB1, is constitutively produced from its precursor, p105. Here, we identify BARD1 as a p50-interacting factor. p50 directly associates with the BARD1 BRCT domains via a C-terminal phospho-serine motif. This interaction is induced by ATR and results in mono-ubiquitination of p50 by the BARD1/BRCA1 complex. During the cell cycle, p50 is mono-ubiquitinated in S phase and loss of this post-translational modification increases S phase progression and chromosomal breakage. Genome-wide studies reveal a substantial decrease in p50 chromatin enrichment in S phase and Cycln E is identified as a factor regulated by p50 during the G1 to S transition. Functionally, interaction with BARD1 promotes p50 protein stability and consistent with this, in human cancer specimens, low nuclear BARD1 protein strongly correlates with low nuclear p50. These data indicate that p50 mono-ubiquitination by BARD1/BRCA1 during the cell cycle regulates S phase progression to maintain genome integrity.

Gain-of-Function Mutant p53 R273H Interacts with Replicating DNA and PARP1 in Breast Cancer.

Over 80% of triple-negative breast cancers (TNBC) express mutant p53 (mtp53) and some contain oncogenic gain-of-function (GOF) p53. We previously reported that GOF mtp53 R273H upregulates the chromatin association of mini chromosome maintenance (MCM) proteins MCM2-7 and PARP and named this the mtp53-PARP-MCM axis. In this study, we dissected the function and association between mtp53 and PARP using a number of different cell lines, patient-derived xenografts (PDX), tissue microarrays (TMA), and The Cancer Genome Atlas (TCGA) database. Endogenous mtp53 R273H and exogenously expressed R273H and R248W bound to nascent 5-ethynyl-2´-deoxyuridine-labeled replicating DNA. Increased mtp53 R273H enhanced the association of mtp53 and PARP on replicating DNA. Blocking poly-ADP-ribose gylcohydrolase also enhanced this association. Moreover, mtp53 R273H expression enhanced overall MCM2 levels, promoted cell proliferation, and improved the synergistic cytotoxicity of treatment with the alkylating agent temozolomide in combination with the PARP inhibitor (PARPi) talazoparib. Staining of p53 and PARP1 in breast cancer TMAs and comparison with the TCGA database indicated a higher double-positive signal in basal-like breast cancer than in luminal A or luminal B subtypes. Higher PARP1 protein levels and PAR proteins were detected in mtp53 R273H than in wild-type p53-expressing PDX samples. These results indicate that mtp53 R273H and PARP1 interact with replicating DNA and should be considered as dual biomarkers for identifying breast cancers that may respond to combination PARPi treatments. SIGNIFICANCE: p53 gain-of-function mutant 273H and PARP1 interact with replication forks and could serve as potential biomarkers for breast cancer sensitivity to PARP inhibitors. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/3/394/F1.large.jpg.

Radiogenomics of breast cancer using dynamic contrast enhanced MRI and gene expression profiling.

BACKGROUND: Imaging techniques can provide information about the tumor non-invasively and have been shown to provide information about the underlying genetic makeup. Correlating image-based phenotypes (radiomics) with genomic analyses is an emerging area of research commonly referred to as "radiogenomics" or "imaging-genomics". The purpose of this study was to assess the potential for using an automated, quantitative radiomics platform on magnetic resonance (MR) breast imaging for inferring underlying activity of clinically relevant gene pathways derived from RNA sequencing of invasive breast cancers prior to therapy. METHODS: We performed quantitative radiomic analysis on 47 invasive breast cancers based on dynamic contrast enhanced 3 Tesla MR images acquired before surgery and obtained gene expression data by performing total RNA sequencing on corresponding fresh frozen tissue samples. We used gene set enrichment analysis to identify significant associations between the 186 gene pathways and the 38 image-based features that have previously been validated. RESULTS: All radiomic size features were positively associated with multiple replication and proliferation pathways and were negatively associated with the apoptosis pathway. Gene pathways related to immune system regulation and extracellular signaling had the highest number of significant radiomic feature associations, with an average of 18.9 and 16 features per pathway, respectively. Tumors with upregulation of immune signaling pathways such as T-cell receptor signaling and chemokine signaling as well as extracellular signaling pathways such as cell adhesion molecule and cytokine-cytokine interactions were smaller, more spherical, and had a more heterogeneous texture upon contrast enhancement. Tumors with higher expression levels of JAK/STAT and VEGF pathways had more intratumor heterogeneity in image enhancement texture. Other pathways with robust associations to image-based features include metabolic and catabolic pathways. CONCLUSIONS: We provide further evidence that MR imaging of breast tumors can infer underlying gene expression by using RNA sequencing. Size and shape features were appropriately correlated with proliferative and apoptotic pathways. Given the high number of radiomic feature associations with immune pathways, our results raise the possibility of using MR imaging to distinguish tumors that are more immunologically active, although further studies are necessary to confirm this observation.

Germline variants and somatic mutation signatures of breast cancer across populations of African and European ancestry in the US and Nigeria.

Somatic mutation signatures may represent footprints of genetic and environmental exposures that cause different cancer. Few studies have comprehensively examined their association with germline variants, and none in an indigenous African population. SomaticSignatures was employed to extract mutation signatures based on whole-genome or whole-exome sequencing data from female patients with breast cancer (TCGA, training set, n = 1,011; Nigerian samples, validation set, n = 170), and to estimate contributions of signatures in each sample. Association between somatic signatures and common single nucleotide polymorphisms (SNPs) or rare deleterious variants were examined using linear regression. Nine stable signatures were inferred, and four signatures (APOBEC C>T, APOBEC C>G, aging and homologous recombination deficiency) were highly similar to known COSMIC signatures and explained the majority (60-85%) of signature contributions. There were significant heritable components associated with APOBEC C>T signature (h2 = 0.575, p = 0.010) and the combined APOBEC signatures (h2 = 0.432, p = 0.042). In TCGA dataset, seven common SNPs within or near GNB5 were significantly associated with an increased proportion (beta = 0.33, 95% CI = 0.21-0.45) of APOBEC signature contribution at genome-wide significance, while rare germline mutations in MTCL1 was also significantly associated with a higher contribution of this signature (p = 6.1 × 10-6 ). This is the first study to identify associations between germline variants and mutational patterns in breast cancer across diverse populations and geography. The findings provide evidence to substantiate causal links between germline genetic risk variants and carcinogenesis.

Metabolically activated adipose tissue macrophages link obesity to triple-negative breast cancer.

Obesity is associated with increased incidence and severity of triple-negative breast cancer (TNBC); however, mechanisms underlying this relationship are incompletely understood. Here, we show that obesity reprograms mammary adipose tissue macrophages to a pro-inflammatory metabolically activated phenotype (MMe) that alters the niche to support tumor formation. Unlike pro-inflammatory M1 macrophages that antagonize tumorigenesis, MMe macrophages are pro-tumorigenic and represent the dominant macrophage phenotype in mammary adipose tissue of obese humans and mice. MMe macrophages release IL-6 in an NADPH oxidase 2 (NOX2)-dependent manner, which signals through glycoprotein 130 (GP130) on TNBC cells to promote stem-like properties including tumor formation. Deleting Nox2 in myeloid cells or depleting GP130 in TNBC cells attenuates obesity-augmented TNBC stemness. Moreover, weight loss reverses the effects of obesity on MMe macrophage inflammation and TNBC tumor formation. Our studies implicate MMe macrophage accumulation in mammary adipose tissue as a mechanism for promoting TNBC stemness and tumorigenesis during obesity.

Author Correction: Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features.

The original version of this Article contained an error in the author affiliations. The affiliation of Kevin P. White with Tempus Labs, Inc. Chicago, IL, USA was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article.

Intensive Surveillance with Biannual Dynamic Contrast-Enhanced Magnetic Resonance Imaging Downstages Breast Cancer in BRCA1 Mutation Carriers.

PURPOSE: To establish a cohort of high-risk women undergoing intensive surveillance for breast cancer.Experimental Design: We performed dynamic contrast-enhanced MRI every 6 months in conjunction with annual mammography (MG). Eligible participants had a cumulative lifetime breast cancer risk ≥20% and/or tested positive for a pathogenic mutation in a known breast cancer susceptibility gene. RESULTS: Between 2004 and 2016, we prospectively enrolled 295 women, including 157 mutation carriers (75 BRCA1, 61 BRCA2); participants' mean age at entry was 43.3 years. Seventeen cancers were later diagnosed: 4 ductal carcinoma in situ (DCIS) and 13 early-stage invasive breast cancers. Fifteen cancers occurred in mutation carriers (11 BRCA1, 3 BRCA2, 1 CDH1). Median size of the invasive cancers was 0.61 cm. No patients had lymph node metastasis at time of diagnosis, and no interval invasive cancers occurred. The sensitivity of biannual MRI alone was 88.2% and annual MG plus biannual MRI was 94.1%. The cancer detection rate of biannual MRI alone was 0.7% per 100 screening episodes, which is similar to the cancer detection rate of 0.7% per 100 screening episodes for annual MG plus biannual MRI. The number of recalls and biopsies needed to detect one cancer by biannual MRI were 2.8 and 1.7 in BRCA1 carriers, 12.0 and 8.0 in BRCA2 carriers, and 11.7 and 5.0 in non-BRCA1/2 carriers, respectively. CONCLUSIONS: Biannual MRI performed well for early detection of invasive breast cancer in genomically stratified high-risk women. No benefit was associated with annual MG screening plus biannual MRI screening.See related commentary by Kuhl and Schrading, p. 1693.

Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features.

Racial/ethnic disparities in breast cancer mortality continue to widen but genomic studies rarely interrogate breast cancer in diverse populations. Through genome, exome, and RNA sequencing, we examined the molecular features of breast cancers using 194 patients from Nigeria and 1037 patients from The Cancer Genome Atlas (TCGA). Relative to Black and White cohorts in TCGA, Nigerian HR + /HER2 - tumors are characterized by increased homologous recombination deficiency signature, pervasive TP53 mutations, and greater structural variation-indicating aggressive biology. GATA3 mutations are also more frequent in Nigerians regardless of subtype. Higher proportions of APOBEC-mediated substitutions strongly associate with PIK3CA and CDH1 mutations, which are underrepresented in Nigerians and Blacks. PLK2, KDM6A, and B2M are also identified as previously unreported significantly mutated genes in breast cancer. This dataset provides novel insights into potential molecular mechanisms underlying outcome disparities and lay a foundation for deployment of precision therapeutics in underserved populations.