Project description:Cortical thickness has been investigated since the beginning of the 20th century, but we do not know how similar the cortical thickness profiles among humans are. In this study, the local similarity of cortical thickness profiles was investigated using sliding window methods. Here, we show that approximately 5% of the cortical thickness profiles are similarly expressed among humans while 45% of the cortical thickness profiles show a high level of heterogeneity. Therefore, heterogeneity is the rule, not the exception. Cortical thickness profiles of somatosensory homunculi and the anterior insula are consistent among humans, while the cortical thickness profiles of the motor homunculus are more variable. Cortical thickness profiles of homunculi that code for muscle position and skin stimulation are highly similar among humans despite large differences in sex, education, and age. This finding suggests that the structure of these cortices remains well preserved over a lifetime. Our observations possibly relativize opinions on cortical plasticity.
Project description:The use of cultured cell lines as model systems for normal tissue is limited by the molecular alterations accompanying the immortalisation process, including changes in the mRNA and microRNA (miRNA) repertoire. Therefore, identification of cell lines with normal-like expression profiles is of paramount importance in studies of normal gene regulation.The mRNA and miRNA expression profiles of several breast cell lines of cancerous or normal origin were measured using printed slide arrays, Luminex bead arrays, and real-time reverse transcription-polymerase chain reaction.We demonstrate that the mRNA expression profiles of two breast cell lines are similar to that of normal breast tissue: HB4a, immortalised normal breast epithelium, and PMC42, a breast cancer cell line that retains progenitor pluripotency allowing in-culture differentiation to both secretory and myoepithelial fates. In contrast, only PMC42 exhibits a normal-like miRNA expression profile. We identified a group of miRNAs that are highly expressed in normal breast tissue and PMC42 but are lost in all other cancerous and normal-origin breast cell lines and observed a similar loss in immortalised lymphoblastoid cell lines compared with healthy uncultured B cells. Moreover, like tumour suppressor genes, these miRNAs are lost in a variety of tumours. We show that the mechanism leading to the loss of these miRNAs in breast cancer cell lines has genomic, transcriptional, and post-transcriptional components.We propose that, despite its neoplastic origin, PMC42 is an excellent molecular model for normal breast epithelium, providing a unique tool to study breast differentiation and the function of key miRNAs that are typically lost in cancer.
Project description:BACKGROUND:Precision oncology seeks to integrate multiple layers of data from a patient's cancer to effectively tailor therapy. Conventional chemotherapies are sometimes effective but accompanied by adverse events, warranting the identification of a biomarker of chemosensitivity. OBJECTIVE:Identify an mRNA biomarker that predicts chemosensitivity across solid tumor subtypes. METHODS:We performed a pan-solid tumor analysis integrating gene expression and drug sensitivity profiles from 3 cancer cell line datasets to identify transcripts correlated with sensitivity to a panel of chemotherapeutics. We then tested the ability of an mRNA biomarker to predictive clinical outcomes in cohorts of patients with breast, lung, or ovarian cancer. RESULTS:Expression levels of several mRNA transcripts were significantly correlated with sensitivity or resistance chemotherapeutics in cancer cell line datasets. The only mRNA transcript significantly correlated with sensitization to multiple classes of DNA-damaging chemotherapeutics in all 3 cell line datasets was encoded by Schlafen Family Member 11 (SLFN11). Analyses of multiple breast, lung, and ovarian cancer patient cohorts treated with chemotherapy confirmed SLFN11 mRNA expression as a predictive biomarker of longer overall survival and improved tumor response. CONCLUSIONS:Tumor SLFN11 mRNA expression is a biomarker of sensitivity to an array of DNA-damaging chemotherapeutics across solid tumor subtypes.
Project description:BACKGROUND: Endocrine therapies of breast cancer are effective but ultimately fail because of the development of treatment resistance. We have previously revealed several genes leading to tamoxifen resistance in vitro by retroviral insertion mutagenesis. To understand the manner in which these genes yield tamoxifen resistance, their effects on global gene expression were studied and those genes resulting in a distinct gene expression profile were further investigated for their clinical relevance. METHODS: Gene expression profiles of 69 human breast cancer cell lines that were made tamoxifen resistant through retroviral insertion mutagenesis were obtained using oligonucleotide arrays and analysed with bioinformatic tools. mRNA levels of NCOR2 and CITED2 in oestrogen receptor-positive breast tumours were determined by quantitative RT-PCR. mRNA levels were evaluated for association with metastasis-free survival (MFS) in 620 patients with lymph node-negative primary breast cancer who did not receive systemic adjuvant therapy, and with clinical benefit in 296 patients receiving tamoxifen therapy for recurrent breast cancer. RESULTS: mRNA expression profiles of most tamoxifen-resistant cell lines were strikingly similar, except for the subgroups of cell lines in which NCOR2 or CITED2 were targeted by the retrovirus. Both NCOR2 and CITED2 mRNA levels were associated with MFS, that is, tumour aggressiveness, independently of traditional prognostic factors. In addition, high CITED2 mRNA levels were predictive for a clinical benefit from first-line tamoxifen treatment in patients with advanced disease. CONCLUSIONS: Most retrovirally targeted genes yielding tamoxifen resistance in our cell lines do not impose a distinctive expression profile, suggesting that their causative role in cell growth may be accomplished by post-transcriptional processes. The associations of NCOR2 and CITED2 with outcome in oestrogen receptor-positive breast cancer patients underscore the clinical relevance of functional genetic screens to better understand disease progression, which may ultimately lead to the development of improved treatment options.
Project description:Studies indicate that stathmin expression associates with PI3K activation in breast cancer, suggesting stathmin as a marker for targetable patient subgroups. Here we assessed stathmin in relation to tumour proliferation, vascular and immune responses, BRCA1 germline status, basal-like differentiation, clinico-pathologic features, and survival. Immunohistochemical staining was performed on breast cancers from two series (cohort 1, n?=?187; cohort 2, n?=?198), and mass spectrometry data from 24 cases and 12 breast cancer cell lines was examined for proteomic profiles. Open databases were also explored (TCGA, METABRIC, Oslo2 Landscape cohort, Cancer Cell Line Encyclopedia). High stathmin expression associated with tumour proliferation, p53 status, basal-like differentiation, BRCA1 genotype, and high-grade histology. These patterns were confirmed using mRNA data. Stathmin mRNA further associated with tumour angiogenesis, immune responses and reduced survival. By logistic regression, stathmin protein independently predicted a BRCA1 genotype (OR 10.0, p?=?0.015) among ER negative tumours. Cell line analysis (Connectivity Map) implied PI3K inhibition in tumours with high stathmin. Altogether, our findings indicate that stathmin might be involved in the regulation of tumour angiogenesis and immune responses in breast cancer, in addition to tumour proliferation. Cell data point to potential effects of PI3K inhibition in tumours with high stathmin expression.
Project description:BACKGROUND:Proper cell models for breast cancer primary tumors have long been the focal point in the cancer's research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented. RESULTS:Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C?>?T and C?>?G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors. CONCLUSIONS:The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research.
Project description:Human papillomaviruses (HPVs) are the most common on sexually transmitted viruses in the world. HPVs are responsible for a large spectrum of deseases, both benign and malignant. The certain types of HPV are involved in the development of cervical cancer. In attemps to find additional drugs in the treatment of cervical cancer, inhibitors of the histone deacetylases (HDAC) have received much attention due to their low cytotoxic profiles and the E6/E7 oncogene function of human papilomavirus can be completely by passed by HDAC inhibition. The histone deacetylase inhibitors can induce growth arrest, differentiation and apoptosis of cancer cells. HDAC class I and class II are considered the main targets for cancer. Therefore, the six HDACs class II was modeled and about two inhibitors (SAHA and TSA) were docked using AutoDock4.2, to each of the inhibitor in order to identify the pharmacological properties. Based on the results of docking, SAHA and TSA were able to bind with zinc ion in HDACs models as a drug target. SAHA was satisfied almost all the properties i.e., binding affinity, the Drug-Likeness value and Drug Score with 70% oral bioavailability and the carbonyl group of these compound fits well into the active site of the target where the zinc is present. Hence, SAHA could be developed as potential inhibitors of class II HDACs and valuable cervical cancer drug candidate.