Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

MicroRNA expression profiling and its integration with mRNA in metastatic melanoma reveal associations with BRAF mutation status and patient prognosis

ABSTRACT: Objectives/experimental design Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. mRNA expression profiling information in the same samples is available: GSE54467.

ORGANISM(S): Homo sapiens

SUBMITTER: Graham Mann

PROVIDER: E-GEOD-59334 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Determination of prognosis in metastatic melanoma through integration of clinico-pathologic, mutation, mRNA, microRNA, and protein information.

Jayawardana Kaushala K Schramm Sarah-Jane SJ Haydu Lauren L Thompson John F JF Scolyer Richard A RA Mann Graham J GJ Müller Samuel S Yang Jean Yee Hwa JY

International journal of cancer 20140724 4

In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features have been evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources con ...[more]

PMID: 24975271

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Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication. Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. We previously analyzed the distribution of survival times in these samples and identified more favorable and less favorable groups as patients having time from surgery to death from melanoma greater than 4 years with no sign of relapse (n=25) or less than 1 year (n=22), respectively (Mann et al. 2013, PMID: 22931913). Since that publication, survival data have been re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset. The current survival data are considered to be more accurate. MRNA expression profiling and somatic mutation profiling, were performed as previously described in Mann et al. 2013 (PMID: 22931913).

Project description:Prediction of outcome for melanoma patients with surgically-resected macroscopic nodal metastases is very imprecise. We performed a comprehensive clinicopathologic assessment of fresh-frozen macroscopic nodal metastases and the preceding primary melanoma, somatic mutation profiling and gene expression profiling to identify determinants of outcome in 79 melanoma patients. In addition to disease stage <II at initial presentation, the following clinical and pathologic factors were independent predictors of improved outcome (ORs for survival >4yr, 90%CI): presence of a nodular component in the primary melanoma (6.8, 0.6-76.0), and small cell size (11.1, 0.8-100.0) or low pigmentation (3.0, 0.8-100.0) in the nodal metastases. Absence of BRAF mutation (20.0, 1.0-1000.0) or NRAS mutation (16.7, 0.6-1000.0) were both favourable prognostic factors. A 46-gene expression signature with strong over-representation of immune response genes was predictive of better survival (10.9, 0.4-325.6); in the full cohort median survival was >100 months in those with the signature, but 10 months in those without. This relationship was validated in two previously published independent stage III melanoma datasets. We conclude that the presence of BRAF mutation, NRAS mutation and absence of an immune-related expressed gene profile predict poor outcome in melanoma patients with macroscopic stage III disease. Samples eligible for this study (n=79) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. Total RNA was extracted from 20-30mg of fresh frozen tissue. Tissue samples were homogenized using a high-speed agitation polytron blender (Kinematica, Luzern, Switzerland) in the presence of Trizol. The RNA was isolated and purified with an RNeasy purification kit (Qiagen RNeasy purification kit- Qiagen Pty Ltd., Clifton Hill, Victoria, Australia) with DNAse I digestion on the column. The quality of the RNA preparations was assessed using the Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA, USA). RNA integrity scores were >8 for all samples analyzed. cRNA amplification and labelling with biotin were performed using Illumina TotalPrep RNA amplification kit according to the manufacturer’s directions (Ambion, Inc., Austin, TX, USA) with 250ng total RNA as input material. Gene expression analysis was performed using the Sentrix Human-6 v3 Expression BeadChips (Illumina, Inc., San Diego, CA, USA), and BeadStation system from Illumina as per manufacturer’s instructions. Expression BeadChip using array annotation based on R-2.11.0 and illuminaHumanv3.db. Quality control was performed on all chips using R/Bioconductor and the lumi package (www.bioconductor.org). Data normalization was performed using a variance-stabilizing transform (VST) and quantile normalization as implemented in the lumi package for R/Bioconductor.

Project description:Dysregulated choline metabolism is a well-known feature of breast cancer, but the underlying mechanisms are not fully understood. In this study, the metabolomic and transcriptomic characteristics of a large panel of human breast cancer xenograft models were mapped, with focus on choline metabolism. Methods: Tumor specimens from 34 patient-derived xenograft models were collected and divided in two. One part was examined using high-resolution magic angle spinning (HR-MAS) MR spectroscopy while another part was analysed using gene expression microarrays. Expression data of genes encoding proteins in the choline metabolism pathway were analysed and correlated to the levels of choline (Cho), phosphocholine (PCho) and glycerophosphocholine (GPC) using Pearson’s correlation analysis. For comparison purposes, metabolic and gene expression data were collected from human breast tumors belonging to corresponding molecular subgroups. Results: Most of the xenograft models were classified as basal-like (N=19) or luminal B (N=7). These two subgroups showed significantly different choline metabolic and gene expression profiles. The luminal B xenografts were characterized by a high PCho/GPC ratio while the basal-like xenografts were characterized by highly variable PCho/GPC ratio. Also, Cho, PCho and GPC levels were correlated to expression of several genes encoding proteins in the choline metabolism pathway, including choline kinase alpha (CHKA) and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5). These characteristics were similar to those found in human tumor samples. Discussion: The higher PCho/GPC ratio found in luminal B compared with most basal-like breast cancer xenograft models and human tissue samples do not correspond to results observed from in vitro studies. It is likely that microenvironmental factors play a role in the in vivo regulation of choline metabolism. Cho, PCho and GPC were correlated to different choline pathway-encoding genes in luminal B compared with basal-like xenografts, suggesting that regulation of choline metabolism may vary between different breast cancer subgroups. The concordance between the metabolic and gene expression profiles from xenograft models with breast cancer tissue samples from patients indicates that these xenografts are representative models of human breast cancer and represent relevant models to study tumor metabolism in vivo. Gene expression was measured in 30 human breast cancer xenografts, one sample from each model

Dataset Information

MicroRNA expression profiling and its integration with mRNA in metastatic melanoma reveal associations with BRAF mutation status and patient prognosis

Publications

Determination of prognosis in metastatic melanoma through integration of clinico-pathologic, mutation, mRNA, microRNA, and protein information.

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