Rat somatic genome editing enables ER+ breast cancer modeling
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE307807 | GEO | 2026/06/10
REPOSITORIES: GEO
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Project description:Genetically engineered mouse models have advanced cancer research but often fail to capture key features of certain human tumors. Rats, with distinct physiology and tumor biology, offer a powerful alternative, yet their use has been constrained by technical barriers to genome editing. Here, we report efficient somatic genome editing in rats, enabling both Indel and substitution mutations. We then apply this approach to model estrogen receptor (ER)-positive breast cancer, which accounts for ~70% of human cases but remains poorly represented in mice. The resulting rat tumors reproduce hallmarks of human ER+ breast cancer, including ductal histology, hormone responsiveness, and immune-microenvironmental features. By contrast, identical genetic alterations in mice failed to yield ER+ tumors, underscoring critical species differences in tumorigenesis. Together, this work establishes a versatile platform for rapid generation of clinically relevant rat tumor models, opening new avenues to dissect tumor biology, therapeutic response, and immune interactions in previously inaccessible cancer subtypes.
2026-04-01 | GSE326238 | GEO
Project description:Rat somatic genome editing enables ER+ breast cancer modeling
| PRJNA1444180 | ENA
Project description:Rat somatic genome editing enables ER+ breast cancer modeling
| PRJNA1327354 | ENA
Project description:To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups. Frozen breast cancer tissues that were excised from patients with Stage 1-3 disease prior to treatment (n=103) were retrieved from Surgical Pathology at Johns Hopkins Hospital (Baltimore, Maryland) and confirmed to contain > 50% epithelial cells. Normal breast organoids were prepared by enzymatic digestion of reduction mammoplasty specimens (n=15; median patient age = 52 years, range 47 to 71). Normal ducts from breast tissue > 2 cm away from the tumor (n=6) were isolated from cryosections using laser-capture micro-dissection (PALM MicroBeam, Carl Zeiss Microimaging, North America). To determine the differences in breast cancer biology/behavior between ER subtypes, we characterized methylation patterns at 8376 selected CpG loci according to ER status. These loci met two criteria: 1) showed the most variation across primary tumors (SD >0.100) and 2) had probe detection p-values <0.0001. To develop an epigenomic signature that predicts outcome in patients with breast cancer, we conducted differential methylation analysis on primary tumors from recurrent versus non-recurrent breast cancers. We used a subgroup of 82 well-annotated, invasive breast tumors derived from the discovery set of 103 tumors that included 44 ER-positive (7 recurrences) and 38 ER-negative (11 recurrences) breast cancers and independently queried the ER-positive and ER-negative tumor groups
2011-09-08 | E-GEOD-31979 | biostudies-arrayexpress
Project description:Purpose To develop a radiosensitivity gene expression assay to predict the response to adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in breast cancer. Patients and methods Fresh frozen primary tumors from 336 patients operated with BCS with or without RT were collected. Patients were split in a discovery cohort (N=172) and a validation cohort (N=164). Genes predicting ipsilateral breast tumor recurrence (IBTR) in an Illumina HT12 v4 whole transcriptome analysis were combined with genes from the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single sample predictors (SSPs) for IBTR based on a k-top scoring pairs algorithm were trained stratified for estrogen receptor (ER) status and RT. Two previously published profiles (radiosensitivity index, RSI, and radiosensitivity score, RSS) were also tested in our data Results The SSPs were prognostic for IBTR in ER+RT- patients (AUC 0.67, p=0.005), ER+RT- patients (AUC=0.89, p=0.015) and ER-RT+ patients (AUC=0.78, p<0.001). Among ER+ patients, radiosensitive tumors had an excellent effect of RT (p<0.001), while radioresistant tumors had no effect of RT (p=0.4) and a high risk of IBTR (55% at 10 years). Our SSPs developed in ER+ tumors and the RSS correlated with proliferation, while SSPs developed in ER- tumors correlated with immune response. RSI negatively correlated with both proliferation and immune response. Conclusions Our targeted SSPs were prognostic for IBTR and has the potential to stratify patients for RT. The biology behind models may explain the different performance in subgroups of breast cancer. Purpose To develop a radiosensitivity gene expression assay to predict the response to adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in breast cancer. Patients and methods Fresh frozen primary tumors from 336 patients operated with BCS with or without RT were collected. Patients were split in a discovery cohort (N=172) and a validation cohort (N=164). Genes predicting ipsilateral breast tumor recurrence (IBTR) in an Illumina HT12 v4 whole transcriptome analysis were combined with genes from the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single sample predictors (SSPs) for IBTR based on a k-top scoring pairs algorithm were trained stratified for estrogen receptor (ER) status and RT. Two previously published profiles (radiosensitivity index, RSI, and radiosensitivity score, RSS) were also tested in our data Results The SSPs were prognostic for IBTR in ER+RT- patients (AUC 0.67, p=0.005), ER+RT- patients (AUC=0.89, p=0.015) and ER-RT+ patients (AUC=0.78, p<0.001). Among ER+ patients, radiosensitive tumors had an excellent effect of RT (p<0.001), while radioresistant tumors had no effect of RT (p=0.4) and a high risk of IBTR (55% at 10 years). Our SSPs developed in ER+ tumors and the RSS correlated with proliferation, while SSPs developed in ER- tumors correlated with immune response. RSI negatively correlated with both proliferation and immune response. Conclusions Our targeted SSPs were prognostic for IBTR and has the potential to stratify patients for RT. The biology behind models may explain the different performance in subgroups of breast cancer.
2018-07-01 | GSE103745 | GEO
Project description:In the present study approximately 1 to 2 mm3 prostate tumor AT1 was inoculated subcutaneously in the right hind leg of adult male Copenhagen rats. When the tumor diameter exceeded 15 mm, tumors of 5 and 4 rats were irradiated with carbon ion radiation of 37 or 16Gy respectively. Tumors of 5 other rats were irradiated with photon radiation of 37Gy. One animal irradiated with 37 Gy carbon ion radiation and one animal irradiated with photon radiation was sacrificed 12h, 30h, 72h, 7d and 14d after irradiation respectively. One animal irradiated with 16 Gy photon radiation was sacrificed 12h, 60h, 7d and 14d after irradiation respectively. Non-irradiated animals were sacrificed at 60h time point. Tumors were dissected and frozen in liquid nitrogen immediately. Total RNA from tumor material was isolated using the NucleoSpin RNA L kit (#740962.20, Macherey-Nagel). Differential gene expression analysis was performed on the Agilent whole rat genome Oligo Microarray (44k) platform by comparative two dye hybridisation with dye-swaps.
2008-07-18 | E-TABM-481 | biostudies-arrayexpress
Project description:Solid tumors are complex organs comprising neoplastic cells and stroma, yet cancer cell lines remain widely used to study tumor biology, biomarkers and experimental therapy. Here, we performed a fully integrative analysis of global proteomic data comparing human colorectal cancer (CRC) cell lines to primary tumors and normal tissues. We found a significant, systematic difference between cell line and tumor proteomes, with a major contribution from tumor stroma proteomes. Nevertheless, cell lines overall mirrored the proteomic differences observed between tumors and normal tissues, in particular for genetic information processing and metabolic pathways, indicating that cell lines provide a system for the study of the intrinsic molecular programs in cancer cells. Intersection of cell line data with tumor data provided insights into tumor cell specific proteome alterations driven by genomic alterations. Our integration of cell line proteogenomic data with drug sensitivity data highlights the potential of proteomic data in predicting therapeutic response. We identified representative cell lines for the proteomic subtypes of primary tumors, and linked these to drug sensitivity data to identify subtype-specific drug candidates.
2016-12-01 | MSV000080374 | GNPS
Project description:Purpose To develop a radiosensitivity gene expression assay to predict the response to adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in breast cancer. Patients and methods Fresh frozen primary tumors from 336 patients operated with BCS with or without RT were collected. Patients were split in a discovery cohort (N=172) and a validation cohort (N=164). Genes predicting ipsilateral breast tumor recurrence (IBTR) in an Illumina HT12 v4 whole transcriptome analysis were combined with genes from the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single sample predictors (SSPs) for IBTR based on a k-top scoring pairs algorithm were trained stratified for estrogen receptor (ER) status and RT. Two previously published profiles (radiosensitivity index, RSI, and radiosensitivity score, RSS) were also tested in our data Results The SSPs were prognostic for IBTR in ER+RT- patients (AUC 0.67, p=0.005), ER+RT- patients (AUC=0.89, p=0.015) and ER-RT+ patients (AUC=0.78, p<0.001). Among ER+ patients, radiosensitive tumors had an excellent effect of RT (p<0.001), while radioresistant tumors had no effect of RT (p=0.4) and a high risk of IBTR (55% at 10 years). Our SSPs developed in ER+ tumors and the RSS correlated with proliferation, while SSPs developed in ER- tumors correlated with immune response. RSI negatively correlated with both proliferation and immune response. Conclusions Our targeted SSPs were prognostic for IBTR and has the potential to stratify patients for RT. The biology behind models may explain the different performance in subgroups of breast cancer.
2018-07-01 | GSE103744 | GEO
Project description:The number of relevant and well-characterized cell lines and xenograft models for studying human breast cancer are few, and may represent a limitation for this field of research. With the aim of developing new breast cancer model systems for in vivo studies of hormone dependent and independent tumor growth, progression and invasion, and for in vivo experimental therapy studies, we collected primary mammary tumor specimens from patients, and implanted them in immunodeficient mice. Primary tumor tissue from 29 patients with breast cancer was implanted subcutaneously with matrigel in SCID mice, in the presence of continuous release of estradiol. The tumors were transferred into new animals when reaching a diameter of 15mm and engrafted tumors were harvested for morphological and molecular characterization from passage six. Further, gene expression profiling was performed using Agilent Human Whole Genome Oligo Microarrays, as well as DNA copy number analysis using Agilent Human Genome CGH 244K Microarrays. Of the 30 primary tumors implanted into mice (including two implants from the same patient), two gave rise to viable tumors beyond passage ten. One showed high expression levels of estrogen receptor-alpha protein (ER) while the other was negative. Histopathological evaluation of xenograft tumors was carried out at passage 10-12; both xenografts maintained the morphological characteristics of the original tumors (classified as invasive grade III ductal carcinomas). The genomic profile of the ER-positive xenograft tumor resembled the profile of the primary tumor, while the profile obtained from the ER-negative parental tumor was different from the xenograft. However, the ER-negative parental tumor and xenograft clustered on the same branch using unsupervised hierarchical clustering analysis on RNA microarray expression data of "intrinsic genes". A significant variation was observed in the expression of extracellular matrix (ECM)-related genes, which were found downregulated in the engrafted tumors compared to the primary tumor. By IHC and qRT-PCR we found that the downregulation of stroma-related genes was compensated by the overexpression of such molecules by the mouse host tissue. The two established breast cancer xenograft models showed different histopathological characteristics and profound diversity in gene expression patterns that in part can be associated to their ER status and here described as basal-like and luminal-like phenotype, respectively. These two new breast cancer xenografts represent useful preclinical tools for developing and testing of new therapies and improving our knowledge on breast cancer biology. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc.
2010-07-22 | E-GEOD-23041 | biostudies-arrayexpress
Project description:Adenosine-to-inosine (A-to-I) RNA editing is an epigenetic modification catalyzed by adenosine deaminases acting on RNA (ADARs), and is especially prevalent in the brain. Using microfluidics-based multiplex PCR sequencing (mmPCR-seq) to assess A-to-I editing at 146 pre-selected, conserved sites, we found that editing was generally higher in adult compared to neonatal rat brain, and that at birth, global editing was lower in prefrontal cortex than in amygdala. Prereproductive stress (PRS) affected editing at the serotonin receptor 2c, and editing at this site was significantly altered in offspring of PRS rats across two generations. Changes in ADAR expression did not correlate with editing changes induced by development or stress. Our findings indicate that mmPCR-seq can accurately detect RNA editing in rat brain samples, and confirm previous accounts of a developmental increase in RNA editing rates. Altered RNA editing rates in offspring of stress-exposed rats complements growing literature on the transgenerational effects of stress.
2017-05-24 | GSE99214 | GEO