Project description:This SuperSeries is composed of the following subset Series: GSE18916: Expression data from 42 prostate cancer samples - 16 recurrent and 26 recurrence-free GSE18917: Expression data from 22 prostate cancer samples - 6 recurrent and 16 recurrence-free from the validation dataset Refer to individual Series
Project description:We analyzed the protein-coding and non-coding gene expression profiles of 64 samples of prostate cancer primary tumors. All samples were collected between 1998 and 2001 with informed consent from patients subjected to radical prostatectomy at Hospital Sirio-Libanes in São Paulo. Selected patients were identified with clinical Stage T1-2 prostate cancer and no lymph node involvement, and received no adjuvant treatment after surgery as long as they remained recurrence-free. Biochemical recurrence was defined as an increase in patient blood PSA level to 0.2 ng per mL of blood at any time during the 5-year follow-up after prostatectomy. For this kind of experiment, also called self-self hybridization, the microarrays were cohybridized with each of Cy3- and Cy5-labeled cRNA replicates. This strategy has been used to derive intensity-dependent cutoffs to classify a gene as differentially expressed or divergent in comparative genomic hybridization (CGH) studies. The comparative analysis of constant fold change cutoffs and intensity-dependent ones has been extensively discussed, showing a superior performance of the intensity-dependent strategy. For the validation dataset processing, reference values obtained with the training dataset processin were applied to normalize the validation dataset. These values were: Average ranked intensities (quantile normalization), batch information (batch adjustment), and gene average and standard deviations (z-score transformation. Here we describe the validation of the gene expression profile comprised of 32 protein-coding mRNAs and 6 intronic non-coding RNAs (ncRNAs) in an independent set of 22 samples, 16 from recurrence-free patients and 6 recurrent patients. In order to compare the expression levels of training and independent validation samples, gene intensity levels of samples in the validation dataset were transformed using normalization factors that had been generated with the training dataset.
Project description:Current protocols for the screening of prostate cancer cannot accurately discriminate clinically indolent tumors from more aggressive ones. One reliable indicator of outcome has been the determination of organ-confined versus nonorgan-confined disease but even this determination is often only made following prostatectomy. This underscores the need to explore alternate avenues to enhance outcome prediction of prostate cancer patients. Fluids that are proximal to the prostate, such as expressed prostatic secretions (EPS), are attractive sources of potential prostate cancer biomarkers as these fluids likely bathe the tumor. Direct-EPS samples from 16 individuals with extracapsular (n = 8) or organ-confined (n = 8) prostate cancer were used as a discovery cohort, and were analyzed in duplicate by a nine-step MudPIT on a LTQ-Orbitrap XL mass spectrometer. A total of 624 unique proteins were identified by at least two unique peptides with a 0.2% false discovery rate. A semiquantitative spectral counting algorithm identified 133 significantly differentially expressed proteins in the discovery cohort. Integrative data mining prioritized 14 candidates, including two known prostate cancer biomarkers: prostate-specific antigen and prostatic acid phosphatase, which were significantly elevated in the direct-EPS from the organ-confined cancer group. These and five other candidates (SFN, MME, PARK7, TIMP1, and TGM4) were verified by Western blotting in an independent set of direct-EPS from patients with biochemically recurrent disease (n = 5) versus patients with no evidence of recurrence upon follow-up (n = 10). Lastly, we performed proof-of-concept SRM-MS-based relative quantification of the five candidates using unpurified heavy isotope-labeled synthetic peptides spiked into pools of EPS-urines from men with extracapsular and organ-confined prostate tumors. This study represents the first efforts to define the direct-EPS proteome from two major subclasses of prostate cancer using shotgun proteomics and verification in EPS-urine by SRM-MS.
Project description:We analyzed the protein-coding and non-coding gene expression profiles of 64 samples of prostate cancer primary tumors. All samples were collected between 1998 and 2001 with informed consent from patients subjected to radical prostatectomy at Hospital Sirio-Libanes in São Paulo. Selected patients were identified with clinical Stage T1-2 prostate cancer and no lymph node involvement, and received no adjuvant treatment after surgery as long as they remained recurrence-free. Biochemical recurrence was defined as an increase in patient blood PSA level to 0.2 ng per mL of blood at any time during the 5-year follow-up after prostatectomy. For this kind of experiment, also called self-self hybridization, the microarrays were cohybridized with each of Cy3- and Cy5-labeled cRNA replicates. This strategy has been used to derive intensity-dependent cutoffs to classify a gene as differentially expressed or divergent in comparative genomic hybridization (CGH) studies. The comparative analysis of constant fold change cutoffs and intensity-dependent ones has been extensively discussed, showing a superior performance of the intensity-dependent strategy. Here we describe a gene expression profile comprised of 32 protein-coding mRNAs and 6 intronic noncoding RNAs (ncRNAs) that effectively classified a set of 42 prostate cancer samples according to the patients’ biochemical recurrence status within a 5-year follow-up after radical prostatectomy.
Project description:RNA sequencing of 32 FFPE tissue samples, including 11 recurrent and 21 non-recurrent tumor specimens demonstrated higher KRT1 gene expression in the recurrence group than in non-recurrent cases. Patients with KRT1-positive immunostaining exhibited trends of worse overall survival (OS) and recurrence-free survival (RFS). In vitro studies showed that KRT1 knockdown suppressed tumor cell invasion, cell migration, and expression of epithelial-mesenchymal transition (EMT)-related genes in human head and neck squamous cell carcinoma (HNSCC) cell lines. Additionally, KRT1 knockdown enhanced tumor cell apoptosis and exhibited synergistic effects with conventional radiation and chemotherapy treatments. KRT1 may serve as a biomarker for predicting advanced laryngeal cancer recurrence and assist with selecting patients to receive concurrent chemoradiotherapy (CCRT).
Project description:We performed a mass spectrometry-based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3 to 5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow-up.
Project description:Study to identify genes associated with NSCLC recurrence in patients not receiving adjuvant chemotherapy. Purpose: Recent clinical trials suggest improvement in survival with adjuvant chemotherapy in non-small cell lung cancer (NSCLC). This study's aim is to identify genes associated with NSCLC recurrence in patients not receiving adjuvant chemotherapy. Experimental design: Banked NSCLC tumors of patients who underwent resection of stage Ia-IIIb disease were identified. Patients were stratified into two groups: recurrent (R, n=11) or non-recurrent (NR, n=16) 2 years after surgery. Microarray profiling and Cox multivariate analysis were performed. Conclusion: Increased CYP3A5 gene expression correlates with NSCLC recurrence and promotes proliferation through mechanisms that may involve, in part, CYP3A5 epoxygenase activity. Experiment Overall Design: comparison of gene expression profiles for recurrent and non-recurrent cancer
Project description:This study presents a cell-type–resolved quantitative proteomics analysis of paired primary and recurrent ascites samples from patients with high-grade serous ovarian carcinoma (HGSOC). Ascites samples were collected from three patients (IROC60, IROC65, and IROC126) at diagnosis and upon disease recurrence following platinum–taxane chemotherapy. For each sample, ascites-derived cells were fractionated into unsorted, CD45⁻ (tumor-enriched), and CD45⁺ (immune-enriched) populations using magnetic-activated cell sorting. Using label-free LC–MS/MS proteomics, we quantified proteome-wide changes associated with disease recurrence across distinct cellular compartments. Pathway-level analyses revealed consistent suppression of interferon signaling across tumor and immune fractions, alongside enhanced oxidative phosphorylation and metabolic reprogramming in recurrent tumor cells. Immune-enriched fractions exhibited signatures of immunosuppression, including reduced antigen presentation and enrichment of regulatory and monocyte-related pathways. Together, this dataset provides a comprehensive proteomic resource for investigating tumor–immune interactions and recurrence-associated molecular remodeling within the ovarian cancer ascites microenvironment.