During the past decade there has been a substantial advance in our understanding of estrogen signaling both from a clinical as well as a preclinical perspective. Estrogen signaling is a balance between two opposing forces in the form of two distinct receptors (ERα and ERβ) and their splice variants. The prospect that these two pathways can be selectively stimulated or inhibited with subtype-selective drugs constitutes new and promising therapeutic opportunities in clinical areas as diverse as hormone replacement, autoimmune diseases, prostate and breast cancer, and depression. Molecular biological, biochemical, and structural studies have generated information which is invaluable for the development of more selective and effective ER ligands. We have also become aware that ERs do not function by themselves but require a number of coregulatory proteins whose cell-specific expression explains some of the distinct cellular actions of estrogen. Estrogen is an important morphogen, and many of its proliferative effects on the epithelial compartment of glands are mediated by growth factors secreted from the stromal compartment. Thus understanding the cross-talk between growth factor and estrogen signaling is essential for understanding both normal and malignant growth. In this review we focus on several of the interesting recent discoveries concerning estrogen receptors, on estrogen as a morphogen, and on the molecular mechanisms of anti-estrogen signaling.

Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.

Estrogen receptor (ER) β counteracts the activity of ERα in many systems. In agreement with this, we show in this study that induced expression of ERβ in the breast cancer cell line T47D reduces 17β-estradiol-stimulated proliferation when expression of ERβ mRNA equals that of ERα. Induction of ERβ reduces growth of exponentially proliferating cells with a concomitant decrease in components of the cell cycle associated with proliferation, namely cyclin E, Cdc25A (a key regulator of Cdk2), p45 Skp2 (a key regulator of p27 Kip1 proteolysis), and an increase in the Cdk inhibitor p27 Kip1 . We also observed a reduced Cdk2 activity. These findings suggest a possible role for ERβ in breast cancer and imply that ERβ-specific ligands may reduce proliferation of ER-positive breast cancer cells through actions on the G 1 phase cell-cycle machinery.

PURPOSE To investigate whether hormonal receptors and human epidermal growth factor receptor 2 (HER2) change throughout tumor progression, because this may alter patient management. PATIENTS AND METHODS The study cohort included female patients with breast cancer in the Stockholm health care region who relapsed from January 1, 1997, to December 31, 2007. Either biochemical or immunohistochemical (IHC)/immunocytochemical (ICC) methods were used to determine estrogen receptor (ER), progesterone receptor (PR), and HER2 status, which was then confirmed by fluorescent in situ hybridization for IHC/ICC 2+ and 3+ status. Results ER (459 patients), PR (430 patients), and HER2 (104 patients) from both primary tumor and relapse were assessed, revealing a change in 32.4% (McNemar's test P < .001), 40.7% (P < .001), and 14.5% (P = .44) of patients, respectively. Assessment of ER (119 patients), PR (116 patients), and HER2 (32 patients) with multiple (from two to six) consecutive relapses showed an alteration in 33.6%, 32.0%, and 15.7% of patients, respectively. A statistically significant differential overall survival related to intraindividual ER and PR status in primary tumor and relapse (log-rank P < .001) was noted. In addition, women with ER-positive primary tumors that changed to ER-negative tumors had a significant 48% increased risk of death (hazard ratio, 1.48; 95% CI, 1.08 to 2.05) compared with women with stable ER-positive tumors. CONCLUSION Patients with breast cancer experience altered hormone receptor and HER2 status throughout tumor progression, possibly influenced by adjuvant therapies, which significantly influences survival. Hence, marker investigations at relapse may potentially improve patient management and survival.

Vascular pericytes, an important cellular component in the tumor microenvironment, are often associated with tumor vasculatures, and their functions in cancer invasion and metastasis are poorly understood. Here we show that PDGF-BB induces pericyte-fibroblast transition (PFT), which significantly contributes to tumor invasion and metastasis. Gain-and loss-of-function experiments demonstrate that PDGF-BB-PDGFRβ signaling promotes PFT both in vitro and in in vivo tumors. Genome-wide expression analysis indicates that PDGF-BB-activated pericytes acquire mesenchymal progenitor features. Pharmacological inhibition and genetic deletion of PDGFRβ ablate the PDGF-BB-induced PFT. Genetic tracing of pericytes with two independent mouse strains, TN-AP-CreERT2:R26R-tdTomato and NG2-CreERT2:R26R-tdTomato, shows that PFT cells gain stromal fibroblast and myofibroblast markers in tumors. Importantly, coimplantation of PFT cells with less-invasive tumor cells in mice markedly promotes tumor dissemination and invasion, leading to an increased number of circulating tumor cells and metastasis. Our findings reveal a mechanism of vascular pericytes in PDGF-BB-promoted cancer invasion and metastasis by inducing PFT, and thus targeting PFT may offer a new treatment option of cancer metastasis.pericyte | PDGF | fibroblast | metastasis | mesenchymal cell

Estrogen receptor B (ERB) is the predominant ER in the colorectal epithelium. Compared with normal colon tissue, ERB expression is reduced in colorectal cancer. Our hypothesis is that ERB inhibits proliferation of colon cancer cells. Hence, the aim of this study has been to investigate the molecular function of ERB in colon cancer cells, focusing on cell cycle regulation. SW480 colon cancer cells have been lentivirus transduced with ERB expression construct with or without mutated DNA-binding domain or an empty control vector. Expression of ERB resulted in inhibition of proliferation and G 1 phase cell cycle arrest and this effect was dependent on a functional DNA-binding region. c-Myc is overexpressed in an overwhelming majority of colorectal tumors. By Western blot and real-time PCR, we found c-Myc to be down-regulated in the ERB-expressing cells. Furthermore, the c-Myc target gene p21 (Waf1/Cip1) was induced and Cdc25A was reduced by ERB at the transcriptional level. The second cdk2-inhibitor, p27 Kip1 , was induced by ERB, but this regulation occurred at the posttranscriptional level, probably through ERB-mediated repression of the F-box protein p45 Skp2 . Expression of the ERB-variant with mutated DNA binding domain resulted in completely different cell cycle gene regulation. We performed in vivo studies with SW480 cells F ERB transplanted into severe combined immunodeficient/beige mice; after three weeks of ERB-expression, a 70% reduction of tumor volume was seen. Our results show that ERB inhibits proliferation as well as colon cancer xenograft growth, probably as a consequence of ERB-mediated inhibition of cell-cycle pathways. Furthermore, this ERB-mediated cell cycle repression is dependent on functional ERE binding. [Cancer Res 2009;69(15):6100-6]

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to improve both the volume and precision of histomorphological evaluation. Recently, machine learning, and particularly deep learning, has enabled rapid advances in computational pathology. The integration of machine learning into routine care will be a milestone for the healthcare sector in the next decade, and histopathology is right at the centre of this revolution. Examples of potential high‐value machine learning applications include both model‐based assessment of routine diagnostic features in pathology, and the ability to extract and identify novel features that provide insights into a disease. Recent groundbreaking results have demonstrated that applications of machine learning methods in pathology significantly improves metastases detection in lymph nodes, Ki67 scoring in breast cancer, Gleason grading in prostate cancer and tumour‐infiltrating lymphocyte (TIL) scoring in melanoma. Furthermore, deep learning models have also been demonstrated to be able to predict status of some molecular markers in lung, prostate, gastric and colorectal cancer based on standard HE slides. Moreover, prognostic (survival outcomes) deep neural network models based on digitized HE slides have been demonstrated in several diseases, including lung cancer, melanoma and glioma. In this review, we aim to present and summarize the latest developments in digital image analysis and in the application of artificial intelligence in diagnostic pathology.

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