Dataset Information

Intraductal patient-derived xenografts of estrogen receptor ?-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions.

ABSTRACT: Estrogen receptor ?-positive (ER-positive) or 'luminal' breast cancers were notoriously difficult to establish as patient-derived xenografts (PDXs). We and others recently demonstrated that the microenvironment is critical for ER-positive tumor cells; when grafted as single cells into milk ducts of NOD Scid gamma females, >90% of ER-positive tumors can be established as xenografts and recapitulate many features of the human disease in vivo. This intraductal approach holds promise for personalized medicine, yet human and murine stroma are organized differently and this and other species specificities may limit the value of this model. Here, we analyzed 21 ER-positive intraductal PDXs histopathologically. We found that intraductal PDXs vary in extent and define four histopathological patterns: flat, lobular, in situ and invasive, which occur in pure and combined forms. The intraductal PDXs replicate earlier stages of tumor development than their clinical counterparts. Micrometastases are already detected when lesions appear in situ. Tumor extent, histopathological patterns and micrometastatic load correlate with biological properties of their tumors of origin. Our findings add evidence to the validity of the intraductal model for in vivo studies of ER-positive breast cancer and raise the intriguing possibility that tumor cell dissemination may occur earlier than currently thought. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

SUBMITTER: Fiche M

PROVIDER: S-EPMC6590246 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Intraductal patient-derived xenografts of estrogen receptor α-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions.

Fiche Maryse M Scabia Valentina V Aouad Patrick P Battista Laura L Treboux Assia A Stravodimou Athina A Zaman Khalil K Dormoy Valerian V Ayyanan Ayyakkannu A Sflomos George G Brisken Cathrin C

The Journal of pathology 20181227 3

Estrogen receptor α-positive (ER-positive) or 'luminal' breast cancers were notoriously difficult to establish as patient-derived xenografts (PDXs). We and others recently demonstrated that the microenvironment is critical for ER-positive tumor cells; when grafted as single cells into milk ducts of NOD Scid gamma females, >90% of ER-positive tumors can be established as xenografts and recapitulate many features of the human disease in vivo. This intraductal approach holds promise for personalize ...[more]

PMID: 30430577

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Project description:BackgroundExisting studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer.MethodsAn established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis.ResultsUsing canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features.ConclusionThis integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets.

Project description:Endometriosis is a common gynaecological condition characterised by the growth of endometrial tissue outside the uterus and is associated with pain and infertility. Currently, the gold standard for endometriosis diagnosis is laparoscopic excision and histological identification of endometrial epithelial and stromal cells. There is, however, currently no known association between the histological appearance, size, morphology, or subtype of endometriosis and disease prognosis. In this study, we used histopathological software to identify and quantify the number of endometrial epithelial and stromal cells within excised endometriotic lesions and assess the relationship between the cell contents and lesion subtypes. Prior to surgery for suspected endometriosis, patients provided menstrual and abdominal pain and dyspareunia scores. Endometriotic lesions removed during laparoscopic surgery were collected and prepared for immunohistochemistry from 26 patients. Endometrial epithelial and stromal cells were identified with Cytokeratin and CD10 antibodies, respectively. Whole slide sections were digitised and the QuPath software was trained to automatically detect and count epithelial and stromal cells across the whole section. Using this classifier, we identified a significantly larger number of strongly labelled CD10 stromal cells (p = 0.0477) in deeply infiltrating lesions (99,970 ± 2962) compared to superficial lesions (2456 ± 859). We found the ratio of epithelial to stromal cells was inverted in deeply infiltrating endometriosis lesions compared to superficial peritoneal and endometrioma lesions and we subsequently identified a correlation between total endometrial cells and abdominal pain (p = 0.0005) when counted via the automated software. Incorporating histological software into current standard diagnostic pipelines may improve endometriosis diagnosis and provide prognostic information in regards to severity and symptoms and eventually provide the potential to personalise adjuvant treatment decisions.

Dataset Information

Intraductal patient-derived xenografts of estrogen receptor ?-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions.

Publications

Intraductal patient-derived xenografts of estrogen receptor α-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions.

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