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Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expression in unmeasured regions and tissues can enhance biologists’ histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE, and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region difficult to identify using raw spatial transcriptome data alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

In a substantial number of patients, ductal carcinoma in situ (DCIS) of the breast will never progress to invasive ductal carcinoma, and these patients are often overtreated under the current clinical criteria. Although various candidate markers are available, relevant markers for delineating risk categories have not yet been established. In this study, we analyzed the clinical characteristics of 431 patients with DCIS and performed whole-exome sequencing analysis in a 21-patient discovery cohort and targeted deep sequencing analysis in a 72-patient validation cohort. We determined that age, Satoi Nagasawa and Yuta Kuze et al. report a multi-omic analysis of ductal carcinoma in situ (DCIS) of the breast, including whole-exome, single-cell, and spatial transcriptome sequencing. They find that for patients under 45 years of age, HER2 amplification and GATA3 mutation are associated with higher risk of relapse, suggesting they could be used as predictive markers when deciding on a treatment course.

The agonistic/antagonistic biocharacter of selective estrogen receptor modulators (SERMs) can have therapeutic advantages, particularly in the case of premenopausal breast cancers. Although the contradictory effects of these modulators have been studied in terms of crosstalk between the estrogen receptor α (ER) and coactivator dynamics and growth factor signaling, the molecular basis of these mechanisms is still obscure. We identify a series of regulatory mechanisms controlling cofactor dynamics on ER and SERM function, whose activities require F-box protein 22 (Fbxo22). Skp1, Cullin1, F-box–containing complex (SCF(Fbxo22)) ubiquitylated lysine demethylase 4B (KDM4B) complexed with tamoxifen-bound (TAM-bound) ER, whose degradation released steroid receptor coactivator (SRC) from ER. Depletion of Fbxo22 resulted in ER-dependent transcriptional activation via transactivation function 1 (AF1) function, even in the presence of SERMs. In living cells, TAM released SRC and KDM4B from ER in a Fbxo22-dependent manner. SRC release by TAM required Fbxo22 on almost all ER-SRC–bound enhancers and promoters. TAM failed to prevent the growth of Fbxo22-depleted, ER-positive breast cancers both in vitro and in vivo. Clinically, a low level of Fbxo22 in tumor tissues predicted a poorer outcome in ER-positive/human epidermal growth factor receptor type 2–negative (HER2-negative) breast cancers with high hazard ratios, independently of other markers such as Ki-67 and node status. We propose that the level of Fbxo22 in tumor tissues defines a new subclass of ER-positive breast cancers for which SCF(Fbxo22)-mediated KDM4B degradation in patients can be a therapeutic target for the next generation of SERMs.

Exon 2 of MED12, a subunit of the transcriptional mediator complex, has been frequently mutated in uterine leiomyomas and breast fibroadenomas; however, it has been rarely mutated in other tumors. Although the mutations were also found in uterine leiomyosarcomas, the frequency was significantly lower than in uterine leiomyomas. Here, we examined the MED12 mutation in phyllodes tumors, another biphasic tumor with epithelial and stromal components related to breast fibroadenomas. Mutations in MED12 exon 2 were analyzed in nine fibroadenomas and eleven phyllodes tumors via Sanger sequencing. A panel of cancer- and sarcoma-related genes was also analyzed using Ion Torrent next-generation sequencing. Six mutations in fibroadenomas, including those previously reported (6/9, 67%), and five mutations in phyllodes tumors (5/11, 45%) were observed. Three mutations in the phyllodes tumors were missense mutations at Gly44, which is common in uterine leiomyomas and breast fibroadenomas. In addition, two deletion mutations (in-frame c.133_144del12 and loss of splice acceptor c.100-68_137del106) were observed in the phyllodes tumors. No other recurrent mutation was observed with next-generation sequencing. Frequent mutations in MED12 exon 2 in the phyllodes tumors suggest that it may share genetic etiology with uterine leiomyoma, a subgroup of uterine leiomyosarcomas and breast fibroadenoma.

LSD1, a lysine-specific histone demethylase, is overexpressed in several types of cancers and linked to poor outcomes. In breast cancer, the significance of LSD1 overexpression is not clear. We have performed an in silico analysis to assess the relationship of LSD1 expression to clinical outcome. We demonstrate that LSD1 overexpression is a poor prognostic factor in breast cancer, especially in basal-like breast cancer, a subtype of breast cancer with aggressive clinical features. This link is also observed in samples of triple negative breast cancer. Interestingly, we note that overexpression of LSD1 correlates with down-regulation of BRCA1 in triple negative breast cancer. This phenomenon is also observed in in vitro models of basal-like breast cancer, and is associated with an increased sensitivity to PARP inhibitors. We propose therefore that high expression levels of the demethylase LSD1 is a potential prognostic factor of poor outcome in basal-like breast cancer, and that PARP inhibition may be a therapeutic strategy of interest in this poor prognostic subtype with overexpression of LSD1. KS received a grant of St. Marianna University and ASS received a grant of St. Marianna University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Sí

// Yuko Nakagawa 1, 2, * , Anna S. Sedukhina 1, * , Naoki Okamoto 2 , Satoi Nagasawa 1, 3 , Nao Suzuki 2 , Tomohiko Ohta 1 , Hiroyoshi Hattori 4 , Marta Roche-Molina 5 , Ana J. Narvaez 6 , Anand D. Jeyasekharan 7 , Juan A. Bernal 5 , Ko Sato 1 1 Department of Translational Oncology, St. Marianna University Graduate School of Medicine, Kawasaki 216–8511, Japan 2 Department of Obstetrics and Gynecology, St. Marianna University Graduate School of Medicine, Kawasaki 216–8511, Japan 3 Division of Breast and Endocrine Surgery, Department of Surgery, St. Marianna University Graduate School of Medicine, Kawasaki 216–8511, Japan 4 Laboratory of Advanced Therapy, Department of Hematology and Oncology Research, Clinical Research Center, National Hospital Organization Nagoya Medical Center, Nagoya 460–0001, Japan 5 Department of Cardiovascular Development and Repair, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid 28029, Spain 6 MRC Cancer Unit at the University of Cambridge, Hutchison Research Centre, CB2 0XZ, UK 7 Cancer Science Institute of Singapore, National University of Singapore, Centre for Translational Medicine, 117599, Singapore * These authors have contributed equally to this work Correspondence to: Ko Sato, e-mail: kosato@marianna-u.ac.jp Received: August 12, 2014 Accepted: December 07, 2014 Published: January 12, 2015 ABSTRACT PARP inhibitors are a class of promising anti-cancer drugs, with proven activity in BRCA mutant cancers. However, as with other targeted agents, treatment with PARP inhibitors generates acquired resistance within these tumors. The mechanism of this acquired resistance is poorly understood. We established cell lines that are resistant to PARP inhibitor by continuous treatment with the drug, and then used RNA sequencing to compare gene expression. Pathway analysis on the RNA sequencing data indicates that NF-κB signaling is preferentially up-regulated in PARP inhibitor-resistant cells, and that knockdown of core components in NF-κB signaling reverses the sensitivity to PARP inhibitor in resistant cells. Of therapeutic relevance, we show that PARP inhibitor-resistant cells are sensitive to an NF-κB inhibitor in comparison to their parental controls. Malignancies with up-regulation of NF-κB are sensitive to bortezomib, a proteasome inhibitor that is currently used in the clinic. We also show that treatment with bortezomib results in cell death in the PARP inhibitor-resistant cells, but not in parental cells. Therefore we propose that up-regulation of NF-κB signaling is a key mechanism underlying acquired resistance to PARP inhibition, and that NF-κB inhibition, or bortezomib are potentially effective anti-cancer agents after the acquisition of resistance to PARP inhibitors.