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Gene expression analysis of whole blood samples from patients with single and double primary tumors and healthy controls

ABSTRACT: RNA samples from the blood of patients with double tumors, single tumors and from healthy control subjects are studied by gene expression analysis using the whole genome microarray platform AB1700 from Applied Biosystems. Gene expression profiles are derived from the microarray raw data by biostatistical analysis. Differential gene expression between the study subgroups and categories is assessed: On the one hand, all possible pairwise comparisons between the subgroups A, B, C, D, E and N are made in order to elucidate characteristics of the individual subgroups. On the other hand, the higher-ranked categories “double cancer” (AB, consisting of subgroups A and B) and “single cancer” (category CDE, consisting of subgroups C, D and E) are compared to each other and to the normal controls (N). Finally, the category “double cancer” is compared to the different single cancer subgroups (C, D and E). Analysis on the level of the higher ranked categories “double cancer” and “single cancer” aims at identifying the common traits of patients who have developed two independent tumors, as opposed to patients with only one tumor entity and to healthy individuals. Based on the functional annotation of the induced and repressed genes found in these comparisons, biological processes and pathways which are differentially activated in the subgroups or categories are identified, thus providing insights into their molecular characteristics. Furthermore, gene expression data are used to derive classifier rules, which are aimed at discriminating subjects from the different subgroups and categories and may constitute the basis for a future diagnostic classification tool. Keywords: microarray analysis, double-single primary malignancies

ORGANISM(S): Homo sapiens

PROVIDER: GSE11545 | GEO | 2008/05/24

SECONDARY ACCESSION(S): PRJNA106269

REPOSITORIES: GEO

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Project description:RNA samples from the blood of patients with double tumors, single tumors and from healthy control subjects are studied by gene expression analysis using the whole genome microarray platform AB1700 from Applied Biosystems. Gene expression profiles are derived from the microarray raw data by biostatistical analysis. Differential gene expression between the study subgroups and categories is assessed: On the one hand, all possible pairwise comparisons between the subgroups A, B, C, D, E and N are made in order to elucidate characteristics of the individual subgroups. On the other hand, the higher-ranked categories “double cancer” (AB, consisting of subgroups A and B) and “single cancer” (category CDE, consisting of subgroups C, D and E) are compared to each other and to the normal controls (N). Finally, the category “double cancer” is compared to the different single cancer subgroups (C, D and E). Analysis on the level of the higher ranked categories “double cancer” and “single cancer” aims at identifying the common traits of patients who have developed two independent tumors, as opposed to patients with only one tumor entity and to healthy individuals. Based on the functional annotation of the induced and repressed genes found in these comparisons, biological processes and pathways which are differentially activated in the subgroups or categories are identified, thus providing insights into their molecular characteristics. Furthermore, gene expression data are used to derive classifier rules, which are aimed at discriminating subjects from the different subgroups and categories and may constitute the basis for a future diagnostic classification tool. Keywords: microarray analysis, double-single primary malignancies A total of 66 individuals were analyzed:The primary study group consisted of 24 patients with two primary malignancies (group AB) (one of the primaries being of the breast, colon or ovary). The four control groups consisted of a total of 33 single cancer patiens: 10 with colon cancer (group C), 14 with breast cancer (group D), 9 with ovarian cancer (group E_) and 10 healthy individuals (group N). 4 samples (GECM-061_14, GECM-061_37, GECM-061_54 and GECM-061_72) were identifed as outliers by MA plots and therfore they were excluded from the study.

Project description:Male breast cancer (MBC) is a rare and inadequately characterized disease. The aim of the present study was to characterize MBC tumors transcriptionally, to classify them into comprehensive subgroups, and to compare them with female breast cancer (FBC). Methods: Sixty-six clinicopathologically well-annotated fresh frozen MBC tumors were analyzed using Illumina Human HT-12 bead arrays, and a tissue microarray with 220 MBC tumors was constructed for validation using immunohistochemistry. Two external gene expression datasets were used for comparison purposes; 37 MBCs and 359 FBCs. Results: Using an unsupervised approach, we classified the MBC tumors into two subgroups, luminal M1 and luminal M2, respectively, with differences in tumor biological features and outcome, and which differed from the intrinsic subgroups described in FBC. The two subgroups were recapitulated in the external MBCs dataset. Luminal M2 tumors were characterized by high expression of immune response genes and genes associated with estrogen receptor (ER) signaling. Luminal M1 tumors, on the other hand, despite being ER positive by immunohistochemistry showed a lower correlation to genes associated with ER signaling and displayed a more aggressive phenotype and worse prognosis. Validation of two of the most differentially expressed genes, class 1 human leukocyte antigen (HLA) and the metabolizing gene N-acetyltransferase-1 (NAT1), respectively, revealed significantly better survival associated with high expression of both markers (HLA, hazard ratio (HR) 3.6, P=0.002; NAT1, HR 2.5, P=0.033). Importantly, NAT1 remained significant in a multivariate analysis (HR 2.8, P=0.040) and may thus be a novel prognostic marker in MBC. Conclusions: We have detected two unique and stable subgroups of MBC with differences in tumor biological features and outcome. They differ from the widely acknowledged intrinsic subgroups of FBC. As such they may constitute two novel subgroups of breast cancer, occurring exclusively in men, and which may consequently require novel treatment approaches. Finally, we identified NAT1 as a possible prognostic biomarker for MBC, as suggested by NAT1 positivity corresponding to better outcome.

Project description:In order to clarify the molecular mechanisms of drought tolerance between different maize (Zea mays L.) varieties at the protein level, iTRAQ (the isobaric tags for relative and absolute quantitation) quantitative proteomics were used for the comparative analysis of protein expression in the seedling roots of the drought-tolerant Chang 7-2 and drought-sensitive TS141 maize varieties under 20% PEG 6000 (polyethylene glycol 6000)-simulated drought stress. A total of 7723 proteins were identified using iTRAQ in the maize seedling roots. We detected 39371 peptides and 30148 unique peptides. The identified protein molecular mass was mainly distributed between 10–60 kDa. COG analysis divided these proteins into 24 categories, among which general function prediction contained the largest number of proteins (19.1%), followed by posttranslational modification, protein turnover, and chaperones (10.52%). In the identified differentially expressed proteins, 1552 of which were significantly differentially expressed. Of these, 1249 were differentially expressed in Chang 7-2 following drought stress, 577 of which were up-regulated and 672 were down-regulated. Four hundred and twenty five differentially expressed proteins were identified in TS141, 249 of which were up-regulated and 176 were down-regulated. Of these proteins, 32 demonstrated opposite expression levels in the two varieties, and there were 56 up-regulated proteins that were common between the two varieties. Comparing the Chang 7-2 treatment group and control group, the DEPS in the cellular component category were mainly enriched in cytoplasmic membrane-bounded vesicles, cytoplasmic vesicles, membrane-bound vesicles and vesicles; in the molecular function category, the DEPs were mainly enriched in cation binding and metal ion binding; and in the biological process category, the major enriched categories included phosphate-containing compound metabolic process, single-organism transport cellular component organization or biogenesis, carbohydrate metabolic process, and cellular component organization. Comparing the TS141 treatment group and control group, the DEPS in the cellular component category were primarily enriched in cytoplasmic membrane-bounded vesicles, cytoplasmic vesicles, membrane-bound vesicles, and vesicle; in the molecular function category, the DEPs were mainly enriched in cation binding and metal ion binding; and in the biological process category, the major enrichment categories included oxidation-reduction process and carbohydrate metabolic process. In Chang 7-2, the differentially expressed proteins were associated with ribosome pathway, glycolysis/gluconeogenesis pathway, and amino sugar and nucleotide sugar metabolism. In TS141, the differentially expressed proteins were associated with metabolic pathway, phenylpropanoid biosynthesis pathway, and starch and sucrose metabolism.

Project description:To model the effect of Pten loss on breast cancer, we deleted Pten using a floxed allele and the deleter lines MMTV-Cre(NLST), which targets stem/bi-potent progenitor cells, and WAP-Cre, which targets CD24-positive, pregnancy-identified stem cells/alveolar progenitors. Mammary tumors were detected in WAP-Cre:Ptenf/f females with a latency of 15.2 months. By 18 months, nearly all mice had succumbed to cancer. MMTV-Cre:Ptenf/f mice developed mammary tumors after a longer latency of 26.4 months and reduced penetrance (70%) compared to WAP-Cre:Ptenf/f mice. Tumors from both models were heterogeneous, consisting primarily of differentiated adenocarcinoma (adenomyoepithelioma; ~70%) and adenosquamous carcinoma (20-25%). In addition, a small fraction of tumors was classified as acinar and poorly differentiated adenocarcinoma (4-7%) and adenosarcoma (3-4%). To test the consequences of combined Pten and p53 gene mutation on breast cancer, we deleted both genes via MMTV-Cre or WAP-Cre. Kaplan-Meier tumor free survival curves revealed that WAP-Cre:Ptenf/f:p53f/f and MMTV-Cre:Ptenf/f:p53f/f females developed tumors with reduced latency of 11.3 and 9.8 months, compared with 15.2, 26.4, and 16.9 months for single-mutant WAP-Cre:Ptenf/f, MMTV-Cre:Ptenf/f or MMTV-Cre:p53f/f mice, respectively. In contrast to the heterogeneity of Pten tumors and small percentage of adenosarcomas in these mice, ~70% of Pten:p53 lesions were histologically classified as adeno-sacrcomatoid-like or mesenchymal-like breast cancer, with the rest exhibiting mixed mesenchymal plus adenocarcinomas and differentiated adenocarcinomas. The adeno-sacrcomatoid-like tumors expressed the mesenchymal markers vimentin, K5, SMA, N-cadherin and desmin but not ER, as well as islands of luminal-like K18 expressing cells surrounded by a layer of K14-positive cells. We used microarrays to detect differentially expressed genes in the Pten:p53 double-knock-out vs Pten or p53 single deletions Total RNA was extracted from tumors developed by double Trizol method and hybridized on Affymetrix microarrays.

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Gene expression analysis of whole blood samples from patients with single and double primary tumors and healthy controls

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