Trastuzumab Priming on aggregate formation, Intracellular signaling, and the Tumor Microenvironment
RNA-seq (gene expression) · human · 21 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 21 samples: 7 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, 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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE245593_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1029040 and SRA study SRP466843. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 21 samples.
How we read this: 7 replicated groups read from 21 sample titles; they account for 21 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7845405 AU565 2D with TZM_1 AU565 2D with TZM
- GSM7845406 AU565 2D with TZM_2 AU565 2D with TZM
- GSM7845407 AU565 2D with TZM_3 AU565 2D with TZM
- GSM7845408 AU565 2D_1 AU565 2D
- GSM7845409 AU565 2D_2 AU565 2D
- GSM7845410 AU565 2D_3 AU565 2D
- GSM7845411 AU565 Sph with TZM_1 AU565 Sph with TZM
- GSM7845412 AU565 Sph with TZM_2 AU565 Sph with TZM
- GSM7845413 AU565 Sph with TZM_3 AU565 Sph with TZM
- GSM7845414 AU565 Sph_1 AU565 Sph
- GSM7845415 AU565 Sph_2 AU565 Sph
- GSM7845416 AU565 Sph_3 AU565 Sph
- GSM7845417 AU565 2D with primed TZM_1 AU565 2D with primed TZM
- GSM7845418 AU565 2D with primed TZM_2 AU565 2D with primed TZM
- GSM7845419 AU565 2D with primed TZM_3 AU565 2D with primed TZM
- GSM7845420 AU565 Sph with Treated TZM_1 AU565 Sph with Treated …
- GSM7845421 AU565 Sph with Treated TZM_2 AU565 Sph with Treated …
- GSM7845422 AU565 Sph with Treated TZM_3 AU565 Sph with Treated …
- GSM7845423 AU565 Sph with Primed+Treated TZM_1 AU565 Sph with Primed+T…
- GSM7845424 AU565 Sph with Primed+Treated TZM_2 AU565 Sph with Primed+T…
- GSM7845425 AU565 Sph with Primed+Treated TZM_3 AU565 Sph with Primed+T…
- GSE291206 Spatial crosstalk modeling of the tumor microenvironment uncovers CCR5-mediated glia-to-glia signaling as a key regulator of brain metastases 18 samples shares microenvironment
- GSE242271 Prostaglandin E2-EP4 signaling shapes immunosuppressive tumor microenvironment in human tumors by suppressing bioenergetics and ribosome biogenesis in infiltrating immune cells [scRNA-seq] 15 samples shares microenvironment
- GSE270296 TGF-β Signaling Pathway and Cell-Cell Interactions in the Tumor Microenvironment Drive Bladder Cancer Progression after BCG Instillation Treatment: Insights from longitudinal Single-Nucleus RNA-Seq 14 samples shares microenvironment
- GSE309595 Longitudinal Analysis of Multiple Myeloma: Therapeutic Response and Immune Microenvironment Dynamics in the Context of Tumor Heterogeneity [scRNA-seq] 270 samples shares microenvironment
- GSE310388 In situ multi-modal characterization of pancreatic cancer reveals tumor cell identity as a defining factor of the surrounding microenvironment. [RNA-Seq] 171 samples shares microenvironment
- GSE269629 Metabolic programs drive function of therapeutic natural killer (NK) cells in low oxygen tumor microenvironments 63 samples shares microenvironment
- GSE120926 Single-cell RNA sequencing defines the interplay between tumor cells, virus and microenvironment in nasopharyngeal carcinoma 56 samples shares microenvironment
- GSE314812 Divergent clonal evolution and tumor microenvironment remodeling shape gastric cancer peritoneal metastasis 55 samples shares microenvironment
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.