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Gene expression analysis of cervical cancer progression

ABSTRACT: Affymetrix-U133-plus2.0-based gene expression analysis of laser-captured epithelium from 128 cervical tissue specimens from women enrolled in SUCCEED Cervical cancer (CC) is the second most frequent cancer in women and the third leading cause of cancer death in women worldwide. Our analysis of normal, precancerous, and cancerous cervical tissue shows that progress of the disease is a cascade of increased DNA replication/repair and cell proliferation followed by substantial metabolic shifts. The data show a sharp decrease in estrogen receptor alpha (ERα) in tumor cells, and ranking tissue specimens by estrogen-responsive gene expression correlates remarkably closely with histological pathology. Johan, den Boon, Morgridge Institute for Research at University of Wisconsin-Madison Paul, Ahlquist, Howard Hughes Medical Institute and Morgridge Institute for Research at University of Wisconsin-Madison Nicolas, Wentzensen, National Cancer Institute

ORGANISM(S): Homo sapiens

PROVIDER: GSE63514 | GEO | 2015/07/01

SECONDARY ACCESSION(S): PRJNA268109

REPOSITORIES: GEO

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Gene expression analysis of cervical cancer progression

Project description:Affymetrix-U133-plus2.0-based gene expression analysis of laser-captured epithelium from 128 cervical tissue specimens from women enrolled in SUCCEED Cervical cancer (CC) is the second most frequent cancer in women and the third leading cause of cancer death in women worldwide. Our analysis of normal, precancerous, and cancerous cervical tissue shows that progress of the disease is a cascade of increased DNA replication/repair and cell proliferation followed by substantial metabolic shifts. The data show a sharp decrease in estrogen receptor alpha (ER?) in tumor cells, and ranking tissue specimens by estrogen-responsive gene expression correlates remarkably closely with histological pathology. Johan, den Boon, Morgridge Institute for Research at University of Wisconsin-Madison Paul, Ahlquist, Howard Hughes Medical Institute and Morgridge Institute for Research at University of Wisconsin-Madison Nicolas, Wentzensen, National Cancer Institute 24 normal, 14 CIN1 lesions, 22 CIN2 lesions, 40 CIN3 lesions, and 28 cancers specimens were cryosecrtioned and used for laser-capture, RNA extraction, two rounds of T7-mediated amplification, and cRNA biotinylation. Bio-cRNA was hybridized to Affymetrix U133-Plus2.0 arrays, scanned signals were processed through GC-RMA

2015-07-01 | E-GEOD-63514 | biostudies-arrayexpress

Epigenome analysis of normal and cancer tissue from the uterine cervix

Project description:The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs in normal and cancer tissue from the uterine cervix. There are a total of 63 samples, 15 samples of normal histology and 48 cervical cancers. The normal cervical samples were from women who underwent a hysterectomy for uterine fibroids. The 48 cervical cancers were from women who were treated at the Innsbruck Medical University between 1990 and 2006.

2012-02-23 | GSE30759 | GEO

Comparison between matched microdissected and whole tissue breast cancer specimen

Project description:A total of 38 flash-frozen breast cancer tissues were collected from three medical centers in the Netherlands (i.e. National Cancer institute: n=19; Radboud University Medical Center: n=4; Erasmus University Medical Center: n=15). All tissues were analyzed as laser capture microdissected (LCM) and whole samples (whole tissue lysate: WTL). All gathered samples were primary estrogen receptor (ER) tumors, which were subdivided in two patient groups according to outcome to first line (i.e. recurrent disease setting) tamoxifen therapy based on time-to-progression (TTP): patients which manifested progression of disease before (i.e. TTP <=) 6 months were defined as "poor outcome", while patients which manifested progression after (i.e. TTP>) 6 months were defined as "good outcome". All patients did not receive adjuvant hormonal therapy (i.e. tamoxifen or aromatase inhibitors post-surgical resection of primary tumor). The LCM subset derives from PXD000484 (Erasmus Medical Center samples) and PXD000485 (National Cancer Institute and Radboud University Medical Center).

2016-03-31 | PXD002381 | Pride

Epigenome analysis of normal and cancer tissue from the uterine cervix

2012-02-23 | E-GEOD-30759 | biostudies-arrayexpress

Mufudza2012 - Estrogen effect on the dynamics of breast cancer

Project description:Mufudza2012 - Estrogen effect on the dynamics of breast cancer This deterministic model shows the dynamics of breast cancer with immune response. The effects of estrogen are incorporated to study its effects as a risk factor for the disease. This model is described in the article: Assessing the effects of estrogen on the dynamics of breast cancer. Mufudza C, Sorofa W, Chiyaka ET. Comput Math Methods Med 2012; 2012: 473572 Abstract: Worldwide, breast cancer has become the second most common cancer in women. The disease has currently been named the most deadly cancer in women but little is known on what causes the disease. We present the effects of estrogen as a risk factor on the dynamics of breast cancer. We develop a deterministic mathematical model showing general dynamics of breast cancer with immune response. This is a four-population model that includes tumor cells, host cells, immune cells, and estrogen. The effects of estrogen are then incorporated in the model. The results show that the presence of extra estrogen increases the risk of developing breast cancer. This model is hosted on BioModels Database and identified by: BIOMD0000000642. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

2017-07-26 | BIOMD0000000642 | BioModels

The different genes profiles in NASH-HCC specimens

Project description:Paraffin-embedded paired tumor and peri-carcinoma tissues (n=4) were obtained from the Biorepository of Fudan University Institute of Liver Cancer, which were used for the Affymetrix microarray analysis To investigate the progression of NASH to HCC, we established a differential gene expression profile by analyzing significant expression changes in pathologically confirmed NASH-HCC and peri-carcinoma specimens using Affymetrix microarrays.

2020-06-01 | GSE99807 | GEO

Whole transcriptome analysis of breast tissues prior to breast cancer diagnosis [RNA-seq]

Project description:The Susan G. Komen Tissue Bank at Indiana University Simon Cancer Center (KTB) is the only repository of normal breast tissues donated by healthy women. As expected, a relatively small number of KTB donors (≈5%) diagnosed with breast cancer a few years post-donation. The specimens originally donated by these women (here labeled “susceptible normal tissue”) provide a window into the earliest phases of breast cancer development. Here, we investigated the transcriptomic changes in the histologically normal breast tissues donated by women 2-8 years prior to their diagnosis of breast cancer (mostly DCIS), as compared with breasts from age-matched healthy subjects.

2021-09-30 | GSE166044 | GEO

Whole methylome analysis of breast tissues prior to breast cancer diagnosis [methyl-capture]

Project description:The Susan G. Komen Tissue Bank at Indiana University Simon Cancer Center (KTB) is the only repository of normal breast tissues donated by healthy women. As expected, a relatively small number of KTB donors (≈5%) diagnosed with breast cancer a few years post-donation. The specimens originally donated by these women (here labeled “susceptible normal tissue”) provide a window into the earliest phases of breast cancer development. Here, we investigated the DNA metylation changes in the histologically normal breast tissues donated by women 2-8 years prior to their diagnosis of breast cancer (mostly DCIS), as compared with breasts from age-matched healthy subjects.

2021-09-30 | GSE166045 | GEO

LIF-dependent gene expression in human neural stem cell cultures

Project description:Human cortical neural stem cells, provided by Dr. Clive Svendsen (Waisman Center, University of Wisconsin at Madison), were generated from human fetal cortex (9 weeks post conception) and grown as free-floating neurospheres as previously detailed (Wright, et al 2003. Journal of Neurochemistry 86, 179-195). At 15 weeks of growth, 10 ng/ml LIF was added to the cultures. In cases where LIF was withdrawn, neurospheres were collected, medium removed, and neurospheres washed three times with 1% N2 supplemented with 20 ng/ml EGF, and cultured into the same. Total RNA was prepared from a single human neural progenitor cell grown long-term LIF collected at 3 time points: early passage (GSM51360-GSM51362), mid passage (GSM51363-GSM51365), and late passage (GSM51366-GSM51368). Keywords: parallel sample

2005-05-17 | GSE2663 | GEO

RNA sequencing (RNA-SEQ) of ER-α36 knockdown by siRNA in cervical cancer cells

Project description:Estrogen is proven to promote the malignant behaviors of many cancers via its receptors. Estrogen receptor alfa 36(ER-α36) is a newly identified isoform of estrogen receptor alfa （ERα）, which is different from the 66 kDa estrogen receptor alpha (ER-α66).However, the role of ER-α36 in regulating the effects of estrogen and its potential impact on human cervical cancer is poorly understood. In this study, we found that ER-α36 was over-expressed in cervical cancer tissues and elevated ER-α36 expression was associated with poor prognosis in cervical cancer patients. High expression of ER-α36 promotes the proliferation, invasion and metastasis of cervical cancer cells mediated by estrogen, while silencing ER-α36 had the opposite effects. Further research showed that high mobility group A2 (HMGA2) identified as a down-target of ER-α36 in cervical cancer cells. The oncogenic effect of ER-α36 was attenuated after HMGA2 knockdown. In conclusion, high expression of ER-α36 was correlated with a poor prognosis and metastasis in cervical cancer by regulating HMGA2.ER-α36 might serve as a prognostic biomarker and a target for cervical cancer treatment.

2021-04-23 | GSE173120 | GEO

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