Project description:High Grade Serous Ovarian Cancer (HGSOC) is a histopathological diagnosis and may represent multiple diseases at a molecular level. We investigated whether distinct molecular subgroups may influence treatment choice. The accompanying validation set of data has also been deposited in ArrayExpress under accession number E-MTAB-2570 (http://www.ebi.ac.uk/arrayexpress/experiments/E-MEXP-2570).
Project description:Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome in the management of high-grade serous ovarian cancer (HGSOC) patients. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) offers an alternate approach to management of HGSOC patients to achieve complete resection. This study assessed proteomic alterations in matched, chemotherapy naïve and NACT-treated patients tumors obtained from HGSOC patients with suboptimal (R1) versus optimal (R0) debulking at IDS. We describe distinct proteome profiles in pre- and post-NACT HGSOC tumors correlating with residual disease status providing prognostic biomarkers for residual disease at IDS as well as candidate proteins associated with NACT resistance warranting further pre-clinical investigation.
Project description:The recent introduction of poly ADP-ribose polymerase (PARP) inhibitors has significantly improved the survival outcomes of ovarian cancer. This study aimed to identify protein biomarkers and signatures predicting therapeutic responses to PARP inhibitors in high-grade serous ovarian cancer (HGSOC). To identify prognostic biomarkers, we conducted an in-depth proteomic analysis on formalin-fixed paraffin-embedded (FFPE) cancer tissues obtained from 24 HGSOC patients who received PARP inhibitor maintenance therapy for platinum-sensitive recurrence. In total, 7825 proteins were quantified with the tandem mass tag (TMT) labelling method. There were 56 and 131 proteins significantly upregulated in the good and poor response groups, respectively.
Project description:(Purpose) Biological classification of colorectal cancer (CRC) can help to understand its heterogeneous background. The purpose of this study is to classify CRC based on gene expression profiles using formalin-fixed paraffin-embedded (FFPE) samples and to correlate subgroups of CRC with biological features and clinical outcomes. (Results) CRC was clustered into four subgroups by unsupervised hierarchical clustering method. These subgroups show different biological and clinical features. (Conclusion) Gene expression profiles of CRC using FFPE samples distinguish four subgroups that had different biological features and clinical outcomes. These subgroups may explain heterogeneity of CRC and be useful biomarker for clinical. Patients and Methods: One hundred patients with unresectable and advanced or recurrent CRC who underwent the surgical resection from 1998 to 2010 were enrolled in this study. RNA extracted from FFPE samples was subjected to gene expression microarray. After comprehensive gene expression analysis, CRC were classified by an unsupervised hierarchical clustering and a principle component analysis (PCA). Mutation analysis of KRAS, BRAF, PIK3CA and TP53 genes were performed by direct DNA sequencing. Correlation between the biological information, clinicopathological factors and clinical outcomes were analyzed.
Project description:162 FFPE samples, representing six different tumour types, were profiled in triplicate across three independent laboratories. OncoScan¬ FFPE assay data was then analysed for reproducibility of genome-wide copy number, loss of heterozygosity and somatic mutations.
Project description:Different aspects of intra-tumor heterogeneity (ITH), which are associated with development of cancer and its response to treatment, have postulated prognostic value. Here we searched for the potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and the prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients that enabled their separation into two groups: with no evidence of disease (NED, n=41) and with progressive disease (PD, n=36). After the on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Furthermore, signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment. LC-MALDI-MS/MS data deposited in this repository originate from protein lysates obtained from FFPE sections consecutive to sections dedicated to MSI measurements. The hypothetical identity of the MSI components was established by assignment of a component location on the m/z scale for the measured masses of tryptic peptides identified by LC-MALDI-MS/MS allowing ±0.05% mass tolerance.
Project description:We utilize a rapid shotgun FFPE LFQ MS method to profile four regions of developing human cerebrum. Regions encompass neural precursor rich ventricular zones as well as intermediate and subplate and cortex regions accross human development from gestational weeks 16-36. Proteome signatures of the four fetal brain regions were determined using statistical tests and CMV-infected fetal brain encephalitis was analyzed to determine the region-specific effects of this neurodevelopmental disorder.
Project description:The objective of the study was to characterize hereditary breast tumors based on their miRNA expression profiles. To this end, we performed global miRNA expression analysis of more than 800 human miRNA genes in a large series of 80 FFPE breast tissue samples. The series included 66 hereditary breast primary tumors from 13 BRCA1 mutation carriers, 10 BRCA2 mutation carriers and 43 non-BRCA12 tumors denominated hereafter as BRCAX tumors. In addition we have analyzed 10 sporadic breast carcinomas and 4 normal breast tissues obtained after breast reduction surgery from healthy donors with no family history of breast cancer. To avoid contamination with normal breast tissue, tumoral area on FFPE blocks was marked by a pathologist and macrodissected for subsequent total RNA extraction. Microarray expression profiling was performed using miRCURY LNATM microRNA Array v.11 (Exiqon A/S, Denmark), in a single color experiments in a pairwise comparison experimantal design.
Project description:The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes. Keywords: Lung Cancer Prognosis, Gene Expression Signature, Formalin Fixed Paraffin Embedded Samples We micro dissected tumor area from FFPE specimen, and used Affymetrix U133 plus 2.0 arrays to obtain gene expression data.