Transcript analysis of multi-locus sampled tumor tissue in patients with non-small cell lung cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE112996 | GEO | 2018/11/04
REPOSITORIES: GEO
Similar Datasets
Project description:In the study of DNA methylation, genetic variation between species, strains, or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that accounting for strain-specific CpGs increases power. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, and also allowing us to account for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question.
2019-05-14 | GSE87101 | GEO
Project description:The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity (ITH) regarding morphological and genetic features. To what extent the local proteome of tumors intrinsically differs remains largely unknown. Here, we used hepatocellular carcinoma (HCC) as a model system, to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution. We first defined proteomic features that robustly distinguish neoplastic from the directly adjacent non-neoplastic tissue by integrating proteomic data from human patient samples and genetically defined mouse models with available gene expression data. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution
2018-01-24 | PXD007052 | Pride
Project description:Spatial transcriptomics of six surgically-resected human brain metastasis samples
2021-08-04 | GSE179572 | GEO
Project description:We surveyed the variation and dynamics of active regulatory elements genome-wide in CD4+ T cells, using Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq) in longitudinal samples from healthy volunteers and during T cell activation. We created robust pipelines that enable accurate single molecule counting and allelic discrimination from clinical material. Over 4000 regulatory elements (7.2%) showed reproducible personal variation in activity. Gender was the most significant attributable source of regulome variation. ATAC-seq revealed novel elements that escape X chromosome inactivation and predicted gender-specific gene regulatory networks across autosomes, which coordinately impact genes with immune function. Noisy regulatory elements with personal variation in accessibility are significantly enriched for autoimmune disease loci. Over one third of regulome variation lacked genetic variation in cis, suggesting contributions from environmental or epigenetic factors. These results refine concepts of human individuality and provide foundational reference to compare disease-associated regulomes.
2015-06-23 | GSE60682 | GEO
Project description:Autophagy degrades and recycles intracellular components to sustain metabolism and survival during starvation. Tumor cells upregulate and require autophagy to support their metabolism and enhance their proliferation and malignancy, and host autophagy also promotes tumor growth by providing essential tumor nutrients such as arginine in the circulation or alanine in the local tumor microenvironment. In addition to its metabolic role, autophagy regulates immune cell homeostasis and function, and suppresses inflammation, which may also play a role in cancer. Although host autophagy does not promote a T cell anti-tumor immune response in tumors with low tumor mutational burden (TMB), whether this was the case in tumors with high TMB was not known. Here we show that in contrast to low TMB tumors, host-specific deletion of the essential autophagy gene Atg7 induces a pro-inflammatory cytokine response and limits the growth of high TMB tumors, which is rescued by T-cell depletion. Expression of immune-related genes is increased in tumors from Atg7Δ/Δ hosts in a T-cell dependent manner. Tumors from Atg7Δ/Δ hosts also have decreased T regulatory cells (Tregs), and depletion of Tregs phenocopies the reduced tumor growth observed in Atg7Δ/Δ hosts. Moreover, loss of Stimulator of interferon genes (Sting) or IFNg restores growth of high TMB tumors on Atg7Δ/Δ hosts. Finally, similar to whole-body loss of autophagy, specific loss of autophagy in the liver is sufficient to limit tumor growth. Thus, autophagy, especially in the liver, promotes tumor immune tolerance by limiting STING, T cells, and IFNg, which enables tumor growth. We have designated this: Hepatic Autophagy Immune Tolerance (HAIT). Autophagy thereby promotes tumor growth through both metabolic and immune mechanisms depending on mutational load, and autophagy inhibition is an effective means to promote an anti-tumor T-cell response in high TMB tumors.
2020-07-27 | GSE154654 | GEO
Project description:Autophagy degrades and recycles intracellular components to sustain metabolism and survival during starvation. Tumor cells upregulate and require autophagy to support their metabolism and enhance their proliferation and malignancy, and host autophagy also promotes tumor growth by providing essential tumor nutrients such as arginine in the circulation or alanine in the local tumor microenvironment. In addition to its metabolic role, autophagy regulates immune cell homeostasis and function, and suppresses inflammation, which may also play a role in cancer. Although host autophagy does not promote a T cell anti-tumor immune response in tumors with low tumor mutational burden (TMB), whether this was the case in tumors with high TMB was not known. Here we show that in contrast to low TMB tumors, host-specific deletion of the essential autophagy gene Atg7 induces a pro-inflammatory cytokine response and limits the growth of high TMB tumors, which is rescued by T-cell depletion. Expression of immune-related genes is increased in tumors from Atg7Δ/Δ hosts in a T-cell dependent manner. Tumors from Atg7Δ/Δ hosts also have decreased T regulatory cells (Tregs), and depletion of Tregs phenocopies the reduced tumor growth observed in Atg7Δ/Δ hosts. Moreover, loss of Stimulator of interferon genes (Sting) or IFNg restores growth of high TMB tumors on Atg7Δ/Δ hosts. Finally, similar to whole-body loss of autophagy, specific loss of autophagy in the liver is sufficient to limit tumor growth. Thus, autophagy, especially in the liver, promotes tumor immune tolerance by limiting STING, T cells, and IFNg, which enables tumor growth. We have designated this: Hepatic Autophagy Immune Tolerance (HAIT). Autophagy thereby promotes tumor growth through both metabolic and immune mechanisms depending on mutational load, and autophagy inhibition is an effective means to promote an anti-tumor T-cell response in high TMB tumors. Genomic DNA Profiling using Agilent SureSelect Mouse All Exon kit and sequencing using Illumina NextSeq550
2020-08-03 | GSE155556 | GEO
Project description:We surveyed the variation and dynamics of active regulatory elements genome-wide in CD4+ T cells, using Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq) in longitudinal samples from healthy volunteers and during T cell activation. We created robust pipelines that enable accurate single molecule counting and allelic discrimination from clinical material. Over 4000 regulatory elements (7.2%) showed reproducible personal variation in activity. Gender was the most significant attributable source of regulome variation. ATAC-seq revealed novel elements that escape X chromosome inactivation and predicted gender-specific gene regulatory networks across autosomes, which coordinately impact genes with immune function. Noisy regulatory elements with personal variation in accessibility are significantly enriched for autoimmune disease loci. Over one third of regulome variation lacked genetic variation in cis, suggesting contributions from environmental or epigenetic factors. These results refine concepts of human individuality and provide foundational reference to compare disease-associated regulomes. We examined chromatin structure using ATAC-seq in purified human CD4+ T cells in 33 samples from 12 healthy donors and 15 samples from 3 patients with cutaneous T cell leukemia (CTCL). For T cell activation (TCA) time course, CD4+ cells from healthy donor 1 isolated as above were stimulated with ionomycin (1 ug/mL) and Phorbol Myristate Acetate (PMA; 20 ng/mL) and collected at 0, 1, 2, 4 hours in duplicate.
2015-06-23 | E-GEOD-60682 | biostudies-arrayexpress
Project description:Spatial transcriptomics reveals the spatial context of gene expression, but current methods are limited to assaying endogenously polyadenylated (A-tailed) RNA transcripts. Here we demonstrate that enzymatic in situ polyadenylation of RNAs enables detection of the full spectrum of RNAs, expanding the scope of sequencing-based spatial transcriptomics to the total transcriptome. We apply this Spatial Total RNA-Sequencing (STRS) approach to spatially map noncoding RNAs, newly transcribed RNAs, and non-host RNAs at the tissue-scale in the study skeletal muscle regeneration and viral-induced myocarditis. Our analyses reveal the spatial patterns of noncoding RNA expression with near-cellular resolution, identify noncoding transcripts which exhibit zonal variation in skeletal muscle regeneration, and highlight host transcriptional responses highly associated with local viral RNA abundance. Our in situ polyadenylation strategy relies on a brief, low-cost add-on to a widely used protocol for spatial RNA-sequencing, and thus could be broadly and quickly adopted. Spatial RNA-sequencing of the total transcriptome will enable new insights into spatial gene regulation and biology.
2022-04-20 | GSE200481 | GEO
Project description:While mutation-derived neoantigens are well recognized in generating anti-tumor T cell responses, increasing evidences highlight the complex association between tumor mutation burden (TMB) and tumor infiltrating lymphocytes (TILs). We examined this relationship across nine major cancer types to identify non-TMB determinants of immune responses within the tumor microenvironment. TMB overall correlated poorly with both TILs and exhausted CD8+ T cells (Tex) as an indicator of tumor-specific T cells. Computational clustering analysis performed on 4,510 tumors from The Cancer Genome Atlas revealed a group of tumors with abundant Tex but low TMB. In those tumors, we observed significantly higher expression of the stimulator of interferon genes (STING) signaling. Dendritic cells, particularly those of BATF3+ lineage, were also found to be essential for accumulation of Tex within tumors. Mechanistically, loss of genomic and cellular integrity, marked by decreased DNA damage repair, defective replication stress response, and increased apoptosis were shown to drive STING activation. These results highlight that TMB alone does not fully predict tumor immune profiles, with STING signaling compensating for low TMB in non-hypermutated tumors to enhance anti-tumor immunity. We further validated these findings using clinical samples via NanoString technology and single cell RNA-seq. Translating these results, STING agonists may benefit patients with non-hypermutated tumors. STING activation may serve as an additional biomarker to predict response to immune checkpoint blockades alongside TMB. Our research also unraveled the interplay between genomic instability and STING activation, informing potential combined chemotherapy targeting the axis of genomic integrity and immunotherapy.
2024-02-10 | GSE255107 | GEO
Project description:Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or cancer genome, to identify only those variants that impact enhancer function, remains a major challenge. Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to 10 phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.
2021-03-03 | GSE159965 | GEO