Genomic Profiling in Cancer Patients (Breast Cancer Paired Tumor Samples)
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PROVIDER: PRJNA487832 | ENA |
REPOSITORIES: ENA
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Project description:Genomic Profiling in Cancer Patients (Breast Cancer Paired Tumor Samples)
| PRJNA487831 | ENA
Project description:Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that secrete the nipple aspirate fluid (NAF). In cancer patients, this breast secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging because inter-individual variability is substantial. To better address this limitation, we introduced a paired-proteomic strategy that relies on NAF sample analysis from both breasts of patients with unilateral breast cancer. We developed a software extension to the PatternLab for Proteomics software to take advantage of this setup. Briefly, the software relies on a peptide-centric approach and uses the binomial distribution to attribute a probability for each peptide as being linked to the disease or not; these probabilities are then propagated to a final protein p-value according to the Stouffer’s Z-score method. Our approach was applied to both a discovery-driven (shotgun) analysis of NAF samples and a hypothesis-driven (targeted) assessment of 19 cancer-related proteins described in the literature. Shotgun results culminated in the reliable quantitative proteomic profiling of NAF samples from healthy and cancer cohorts. A total of 1,083 proteins were identified, of which 77 were differentially abundant, being mainly involved in glycolysis (Warburg effect) and immune system activation (activated stroma). Additionally, in the estrogen receptor-positive subgroup, proteins related to the lipid metabolism and the complement cascade displayed higher abundance, as expected for this well-differentiated subtype of cancer. The targeted analysis of NAF samples from triple negative patients revealed three differentially abundant proteins related to cell migration/attraction and tumor cell differentiation. In summary, we debuted a paired differential bioinformatics workflow, performing a proof-of-principal differential proteomic analysis of NAF samples in unilateral breast cancers patients. The results revealed a promising statistical paired analysis workflow, thus validating NAF as a treasure-trove for studying this paired-organ cancer type.
2019-04-23 | PXD005157 | Pride
Project description:Background: Normal cell BRCA1 epimutations have been associated with increased risk of triple-negative breast cancer (TNBC). However, the fraction of TNBCs that may have BRCA1 epimutations as their underlying cause is unknown. Neither are the time of occurrence and the potential inheritance patterns of BRCA1 epimutations established. Methods: To address these questions, we analyzed BRCA1 methylation status in breast cancer tissue and matched white blood cells (WBC) from 408 patients with 411 primary breast cancers, including 66 TNBCs, applying a highly sensitive sequencing assay, allowing allele-resolved methylation assessment. Further, to assess the time of origin and the characteristics of normal cell BRCA1 methylation, we analyzed umbilical cord blood of 1260 newborn girls and 200 newborn boys. Finally, we assessed BRCA1 methylation status among 575 mothers and 531 fathers of girls with (n = 102) and without (n = 473) BRCA1 methylation. Results: We found concordant tumor and mosaic WBC BRCA1 epimutations in 10 out of 66 patients with TNBC and in four out of six patients with estrogen receptor (ER)-low expression (<10%) tumors (combined: 14 out of 72; 19.4%; 95% CI 11.1–30.5). In contrast, we found concordance in only three out of 220 patients with 221 ER≥10% tumors and zero out of 114 patients with 116 HER2-positive tumors. Intraindividually, BRCA1 epimutations affected the same allele in normal and tumor cells. Assessing BRCA1 methylation in umbilical WBCs from girls, we found mosaic, predominantly monoallelic BRCA1 epimutations, with qualitative features similar to those in adults, in 113/1260 (9.0%) of individuals, but no correlation to BRCA1 methylation status either in mothers or fathers. A significantly lower fraction of newborn boys carried BRCA1 methylation (9 / 200; 4.5%) as compared to girls (p = 0.038). Similarly, WBC BRCA1 methylation was found less common among fathers (16/531; 3.0%), as compared to mothers (46 / 575; 8.0%; p = 0.0003). Conclusions: Our findings suggest prenatal BRCA1 epimutations might be the underlying cause of around 20% of TNBC and low-ER expression breast cancers. Such constitutional mosaic BRCA1 methylation likely arise through gender-related mechanisms in utero, independent of Mendelian inheritance.
2023-10-26 | GSE243956 | GEO
Project description:Metastasis remains the leading cause of death in breast cancer. However, little is known about the dynamic changes during the dissemination of breast cancer. Here, we generate single-cell RNA and spatial transcriptome of primary tumors and paired metastatic lymph nodes in 4 breast cancer patients. We identified a disseminated cancer cell cluster with high levels of oxidative phosphorylation (OXPHOS). We also noticed the transition between glycolysis and OXPHOS when dissemination initiates. Furthermore, this distinct cell cluster is distributed along the tumor’s leading edge.
2023-02-19 | GSE225600 | GEO
Project description:RNAseq was done on Breast cancer PDX samples uisng Library protocol =llumina TruSeq Stranded Total RNA Kit with Ribo-Zero Gold , HiSeq 125 Cycle Paired-End Sequencing v4
2018-05-24 | GSE113476 | GEO
Project description:microRNA expression profiling of paired primary and lymph node metastatic breast cancer patients
| PRJNA625954 | ENA
Project description:Stratification of breast cancers into subtypes are generally based on immune assays on tumor cells and/or mRNA expression of tumor cell enriched tissues. Here, we have laser microdissected tumor epithelium and tumor stroma from 24 breast cancer biopsies (12 luminal-like and 12 basal-like). We hypothesized that the stromal proteome would separate patients with breast into groups independently of the traditional epithelial based subtypes.
2023-06-23 | PXD027012 | Pride
Project description:The microenvironment of lymph node metastasized tumors (LNMT) determines tumor progression and response to therapy, but a systematic study of LNMT is lacking. Here, we generate single-cell maps of primary tumors (PTs) and paired LNMTs in 8 breast cancer patients. We demonstrate that the activation, cytotoxicity, and proliferation of T cells are suppressed in LNMT compared with PT. CD4+CXCL13+ T cells in LNMT are more likely to differentiate into an exhausted state. Interestingly, LAMP3+ dendritic cells in LNMT display lower T cell priming and activating ability than in PT. Additionally, we identify a subtype of PLA2G2A+ cancer-associated fibroblasts enriched in HER2+ breast cancer patients that promotes immune infiltration. We also show that the antigen-presentation pathway is downregulated in malignant cells of the metastatic lymph node. Altogether, we characterize the microenvironment of LNMT and PT, which may shed light on the individualized therapeutic strategies for breast cancer patients with lymph node metastasis.
2022-04-30 | GSE190811 | GEO
Project description:Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization (aCGH) data to measure 1) whole arm gains and losses (WAAI) and 2) complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distribution of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relationship between structural genomic alterations, molecular subtype and clinical behavior, and provides a score of genomic complexity as a new tool for prognostication in breast cancer. Array CGH of 255 breast tumor samples vs a male skin fibroblast reference sample, in color reversal.
2009-12-15 | E-GEOD-19425 | biostudies-arrayexpress
Project description:Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization (aCGH) data to measure 1) whole arm gains and losses (WAAI) and 2) complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distribution of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relationship between structural genomic alterations, molecular subtype and clinical behavior, and provides a score of genomic complexity as a new tool for prognostication in breast cancer.
2009-12-16 | GSE19425 | GEO