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Breast Cancer Gene Expression Analysis

ABSTRACT: Analysis of 104 breast cancer biopsies (removed prior to any treatment with tamoxifen or chemotherapeutic agents) from patients aged between 31 years and 89 years at the time of diagnosis (mean age = 58 years). Twenty were less than 50 years and seventy-seven women were 50 years, or older, at diagnosis. The size of the tumours ranged between 0.6 cm and 8.0 cm (mean = 2.79 cm). Eighteen tumours were T1 (<2 cm) in maximal dimension; 83 were T2 (2–5 cm) and 3 tumours were T3 (>5 cm). Eighty-two were invasive ductal carcinoma, 17 were invasive lobular and five were tumours of special type (two tubular and three mucinous). Eleven tumours were grade 1; 40 were grade 2; and 53 were grade 3. Sixty-seven tumours were oestrogen receptor (ER) positive and 34 were ER negative (ER status was determined by Enzyme Immuno-Assay (EIA); a positive result was defined as more than 200 fmol/g protein). ER status was not available for 3 patients. Forty-five tumours had no axillary metastases and 59 tumours had metastasised to axillary lymph nodes. Sixty-nine women were treated with post-operative tamoxifen; 26 did not receive tamoxifen. Fifty patients were treated with adjuvant systemic chemotherapy (CMF +/− adriamycin); 45 patients did not receive chemotherapy. Details regarding tamoxifen and systemic chemotherapy were not available for 9 patients. Maximal follow-up was 3,026 days with a mean follow-up of 1,887 days. 17 normal breast tissues were also assayed.

ORGANISM(S): Homo sapiens

PROVIDER: GSE42568 | GEO | 2013/05/26

SECONDARY ACCESSION(S): PRJNA182286

REPOSITORIES: GEO

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Project description:Adrenocortical carcinoma (ACC) is a rare endocrine malignancy accounting for between 0.02 and 0.2 percent of all cancer deaths. Surgical removal offers the only current potential for cure. Unfortunately, ACC has undergone metastatic spread in approximately 40-70 percent of patients at the time of diagnosis. Standard chemotherapy with mitotane containing regimens is often ineffective and associated with intolerable side-effects. Modern molecular technologies now allow the examination of germ-line and somatic DNA for chromosomal alterations which can give biological insight into cancer processes. Using an array-based high density comparative genomic hybridization (CGH) screen, genomic aberrations within 25 ACC patients were assessed to identify genomic characteristic of this cancer. Genomes were queried with >44,000 probes on the Agilent Human Genome CGH array detecting regions of chromosomal gain and loss within the tumor population. Statistical analysis of this genetic landscape reveals a set of chromosomal aberrations strongly associated with survival in an accumulation dependent fashion. These regions may hold prognostic indicators and offer therapeutic targets that can be used to develop novel treatments for aggressive tumors. Experiment Overall Design: Array-based high density comparative genomic hybridization (CGH) screen was utilized to identify genomic aberrations within 25 ACC patients. Thirteen tumor samples are from male and 12 are from female patients. The mean age of patients is 51.8 years (range, 23.3-77.7 years) with a median of 54.2 years. The mean tumor physical measurements for the ACC set are a mean weight of 536.3 grams (range, 20.5-2880 grams) and size of 10.7 cm (range, 3-21.5 cm). The clinical data also includes functional status of the tumor which is based on clinical parameters and confirmed by biochemical analysis. Nonfunctional tumors or those that do not over-produce hormones represent 48% of the tumor set. The localization of each tumor is a measure of the tumor metastatic characteristic at time of operation while tumor grade is a histologically based rating system for tumor progression. Sixty percent of the tumors (15 of 25) were localized to the adrenal area with no indication of metastatic spread. The majority of tumors were grade 3 and 4 at time of diagnosis (17 of 25) indicating necrosis and atypical mitosis of >21/50 hpf. Genomes were queried with >44,000 probes on the Agilent Human Genome CGH array detecting regions of chromosomal gain and loss within the tumor population.

Project description:Ribba2012 - Low-grade gliomas, tumour growth inhibition model Using longitudinal mean tumour diameter (MTD) data, this model describe the size evolution of low-grade glioma (LGG) in patients treated with chemotherapy or radiotherapy. This model is described in the article: A tumour growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy Ribba B, Kaloshi G, Peyre M, Ricard D, Calvez V, Tod M, Cajavec-Bernard B, Idbaih A, Psimaras D, Dainese L, Pallud J, Cartalat-Carel S, Delattre JY, Honnorat J, Grenier E, Ducray F. Clin. Cancer Res. 2012 Sep; 18(18): 5071-5080 Abstract: PURPOSE: To develop a tumor growth inhibition model for adult diffuse low-grade gliomas (LGG) able to describe tumor size evolution in patients treated with chemotherapy or radiotherapy. EXPERIMENTAL DESIGN: Using longitudinal mean tumor diameter (MTD) data from 21 patients treated with first-line procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine (PCV) chemotherapy, we formulated a model consisting of a system of differential equations, incorporating tumor-specific and treatment-related parameters that reflect the response of proliferative and quiescent tumor tissue to treatment. The model was then applied to the analysis of longitudinal tumor size data in 24 patients treated with first-line temozolomide (TMZ) chemotherapy and in 25 patients treated with first-line radiotherapy. RESULTS: The model successfully described the MTD dynamics of LGG before, during, and after PCV chemotherapy. Using the same model structure, we were also able to successfully describe the MTD dynamics in LGG patients treated with TMZ chemotherapy or radiotherapy. Tumor-specific parameters were found to be consistent across the three treatment modalities. The model is robust to sensitivity analysis, and preliminary results suggest that it can predict treatment response on the basis of pretreatment tumor size data. CONCLUSIONS: Using MTD data, we propose a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model might be used to predict treatment efficacy in LGG patients and could constitute a rational tool to conceive more effective chemotherapy schedules. This model is hosted on BioModels Database and identified by: BIOMD0000000521 . 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.

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Breast Cancer Gene Expression Analysis

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