GEO series

Heterogeneous tumor-immune microenvironments among differentially growing metastases in an ovarian cancer patient

GSE92780 Homo sapiens (human) Expression microarray 7 samples Submitted 2017/07/14 Platform GPL23126

At a glance

Expression microarray · human · 7 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Topic: Ovarian cancerThis series is part of our curated briefing on it.
Samples: 7 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

We present an exceptional responder case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesion during a treatment-free period. Using an immunogenomics approach, we found that progressing metastases were infiltrated by CD8+ and CD4+ T cells, exhibited oligoclonal expansion of specific T-cell subsets, and showed indications of neoepitope depletion.

Read the full summary ↓

These findings imply that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogenous fates of metastatic lesions often observed in the clinic post therapy. The goal of this particular experiment was quantify RNA expression using microarrays, and then evaluate differentially expressed genes and pathways between the different tumor samples.

This dataset

Open GSE92780 in finder → Find more human microarray datasets → Ovarian cancer landscape →

Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE92780_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA358593. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28841418) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 7 more — browse all 7 samples with per-sample file links →

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GSE268514 Integrative genomic analysis of Korean high-grade serous ovarian cancer 161 samples same disease briefing · shares ovarian
GSE314300 Rb CUT&RUN profiling in ovarian cancer cell lines following CDK2 inhibitor treatment 10 samples same disease briefing · shares ovarian
GSE135242 Hi-C identifies structural variation associated with resistance in paired patient-derived ovarian cancer models 8 samples same disease briefing · shares ovarian
GSE311212 Transcriptomic profiling in human ovarian cancer cell line OVCAR-3 following CDK2 inhibitor treatment 6 samples same disease briefing · shares ovarian
GSE128098 TET1 reprograms the epithelial ovarian cancer epigenome and reveals casein kinase 2α as a therapeutic target 4 samples same disease briefing · shares ovarian
GSE154600 Multi-omic analysis of subtype evolution and heterogeneity in high-grade serous ovarian carcinoma 5 samples same disease briefing · shares ovarian

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.