Project description:Lung tumors, as well as normal tumor-adjacent (NTA) tissue of non-small cell lung cancer (NSCLC) patients, were collected and subjected label-free quantitation shotgun proteomics in data-independent mode to identify differences between the tumors and adjacent tissue. By employing in-depth proteomics, we identified several pathways that are up- or downregulated in the tumors of non-small cell lung cancer patients.
Project description:We report the association between CpG islander methylator phenotype (CIMP) and the gut microbiome in human colorectal cancer tumor and adjacent normal tissue.
Project description:We report the association between CpG islander methylator phenotype (CIMP) and the gut microbiome in human colorectal cancer tumor and adjacent normal tissue.
Project description:Tumor tissue of lung carcinoid tumors (pulmonary neuroendocrine tumors) and adjacent normal lung tissue was profiled using scRNA-seq
Project description:Proteome characterization of gland confined prostate tumors and non-malignant prostate tissue. Whole cell protein extracts were purified from FFPE radical prostatectomy specimens for a total of 28 tumor samples and 8 adjacent non-malignant prostate tissues. Associated ProteomeXchange identifiers: PXD003430, PXD003452, PXD003515, PXD004132, PXD003615, PXD003636. Quantitative proteomic analysis of adjacent non-malignant prostate tissue (n=8) and gland confined prostate tumors (n=28) obtained from radical prostatectomy procedures; and bone metastatic prostate tumors (n=22) obtained from patients operated to relief spinal cord compression. At the time of surgery, most metastatic patients had relapsed after androgen-deprivation therapy, while 5 were previously untreated.
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 137 total samples: 43 mammaplastic reduction, 47 breast adenocarcinoma, 47 paired adjacent normal breast tissue
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 296 total samples: 148 breast adenocarcinoma, 148 paired adjacent normal breast tissue
Project description:We generated large-scale proteome data for 65 human breast tumors and 53 paired adjacent non-cancerous tissue and performed an integrated proteotranscriptomic characterization. To our best knowledge, the study is one of the largest quantitative proteomic study of human breast tissues, including the analysis of 118 tissue samples from 65 patients with long-term survival outcomes. Our data show that protein expression describes a tumor biology that is only partly captured by the transcriptome, with mRNA abundance incompletely predicting protein abundance in tumors, and even less so in non-cancerous tissue. Furthermore, the tumor proteome described disease pathways and subgroups that were only partially captured by the tumor transcriptome.