Project description:Gene expressional analysis with single cell scale by next generation sequencer revealed clonal dissemination in cancer metastasis. To reveal expressional heterogeneity and cell-cell interaction in the primary tumor and the metastasis, we performed transcriptome analysis of micro-tissues dissected from triple negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model by our automated tissue micro-dissection punching technology. This “multiple micro-tissue transcriptome analysis” revealed that there existed three clusters in primary tumor and axillary lymph-node metastasis, two of which were cancer stem cell-like clusters (CD44/MYC-high, HMGA1-high).
2022-04-22 | GSE184720 | GEO
Project description:Intra-tumor Genetic Heterogeneity in Rectal Cancer
Project description:Meningiomas are one of the most common adult brain tumors. For most patients, surgical excision is curative. However, up to 20% recur. Currently, the molecular determinants predicting recurrence and malignant transformation are lacking. We performed global genetic and genomic analysis of 85 meningioma samples of various grades. Copy number alterations were assessed by 100K SNP arrays and correlated with gene expression, proliferation indices, and clinical outcome. In addition to chromosome 22q loss, which was detected in the majority of clinical samples, chromosome 18q and 6q loss significantly predicted recurrence and was associated with anaplastic histology. Five classes of meningiomas were detected by gene expression analysis that correlated with copy number alterations, recurrence risk, and malignant histology. These classes more accurately predicted tumor recurrence than Ki-67 index, the gold standard for determining risk of recurrence, and highlight substantial expression heterogeneity between meningiomas. These data offer the most complete description of the genomic landscape of meningiomas and provide a set of tools that could be used to more accurately stratify meningioma patients into prognostic risk groups. Tumor biopsies from 43 female and 25 male subjects with sporadic meningioma were identified from the UCLA Neuro-oncology Program Tissue Bank through institutional review board approved protocols. 43 tumors were designated "benign" WHO I, 19 tumors were "atypical" WHO II, and 6 were "anaplastic" WHO III. Gene expression analysis was performed on the 68 tumor biopsies.
Project description:Here we characterize an association between disease progression and DNA methylation in Diffuse Large B cell Lymphoma (DLBCL). By profiling genome-wide DNA methylation at single base-pair resolution in thirteen DLBCL diagnosis-relapse sample pairs, we show DLBCL patients exhibit heterogeneous evolution of tumor methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse–associated methylation signature converging on key pathways such as transforming growth factor beta (TGF-beta) receptor activity. We also observe decreased intra-tumor methylation heterogeneity from diagnosis to relapsed tumor samples. Relapse-free patients display lower intra-tumor methylation heterogeneity at diagnosis compared to relapsed patients in an independent validation cohort. Furthermore, intra-tumor methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse. Using ERRBS, we profiled genome-wide DNA methylation patterns of non-relapse DLBCL tumor samples at diagnosis, relaspe DLBCL patient samples at diagnosis and relaspe.
Project description:Intra-tumor heterogeneity (ITH) has been studied at the morphologic, genomic, and transcriptomic level, but not proteomic level. Recent advances in mass spectrometric (MS) proteome quantification techniques, exemplified by SWATH-MS, a massively parallel targeting method, now also support precise quantitative proteomic comparisons across multiple samples, thus identifying molecular and implied functional differences. Here we used SWATH-MS to analyze the proteome profiles of a set of fresh-frozen prostate tissue samples derived from radical prostatectomy specimens. A high confidence set of 1,906 proteins were consistently quantified across 60 biopsy-level tissue samples from three prostatectomy patients, each consisting of 1.0 mm punch biopsies from histologically malignant (acinar and ductal adenocarcinoma) and matching benign prostatic hyperplasia tissues. The quantitative protein profiles allowed independent quantification of the degree of intra-tumor heterogeneity for each protein in benign and malignant tissues. We found that while majority of the proteins showed comparably low intra-tumor variability, 122 proteins were highly variable in malignant and/or matching benign tissues. We observed that proteins that varied between patients or tissue types also tended to be highly variable within prostate tissues, suggesting that these variability patterns will be a critical selection criterion in future protein biomarker studies. The data also permitted investigation of the heterogeneity of multiple biochemical pathways. The high variability of several of the pathways, including Glypican-1 network, alpha-linolenic acid metabolism and celecoxib pathway, explained contradictory results regarding them in the literature. In conclusion, we demonstrated a methodology for investigating proteomic intra-tumor heterogeneity from biopsy-level tissue samples, and quantified the degree of intra-tumor heterogeneity of 1,906 proteins in prostate tumors. The method and data presented here have advanced our understanding of tumor biology and offered critical insights for future biomarker development.
Project description:We have analyzed transcriptomic intra-tumor heterogeneity among 2-4 multiregional samples from each of 98 primary colorectal cancers. We investigated the level and prognostic value of intra-tumor heterogeniety of the consensus molecular subtypes, and identified subtypes more robust to heterogeneity based on genes with uniform expression levels across tumor regions.
Project description:Meningiomas are one of the most common adult brain tumors. For most patients, surgical excision is curative. However, up to 20% recur. Currently, the molecular determinants predicting recurrence and malignant transformation are lacking. We performed global genetic and genomic analysis of 85 meningioma samples of various grades. Copy number alterations were assessed by 100K SNP arrays and correlated with gene expression, proliferation indices, and clinical outcome. In addition to chromosome 22q loss, which was detected in the majority of clinical samples, chromosome 18q and 6q loss significantly predicted recurrence and was associated with anaplastic histology. Five "classes" of meningiomas were detected by gene expression analysis that correlated with copy number alterations, recurrence risk, and malignant histology. These classes more accurately predicted tumor recurrence than Ki-67 index, the gold standard for determining risk of recurrence, and highlight substantial expression heterogeneity between meningiomas. These data offer the most complete description of the genomic landscape of meningiomas and provide a set of tools that could be used to more accurately stratify meningioma patients into prognostic risk groups. Tumor biopsies from 53 female and 32 male subjects with sporadic meningioma were identified from the UCLA Neuro-oncology Program Tissue Bank through institutional review board approved protocols. 57 tumors were designated "benign" WHO I, 20 tumors were "atypical" WHO II, and 8 were "anaplastic" WHO III. Affymetrix SNP arrays were performed according to the manufacturer's instructions on DNA extracted from flash frozen meningioma tumors.