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accession-icon GSE55503
Effects of siRNA targeting PRKCD in breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The aim was to identify genes that were commonly influenced by a siRNA targeting PRKCD in breast cancer cell lines.

Publication Title

Down Regulation of CLDND1 Induces Apoptosis in Breast Cancer Cells.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE40222
A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Extracellular matrix interactions play essential roles in normal physiology and many pathological processes. Here, we report a novel screening platform capable of measuring phenotypic responses to combinations of ECM molecules. While the importance of ECM interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Using a genetic mouse model of lung adenocarcinoma, we measured the ECM-dependent adhesion of tumor-derived cells. Hierarchical clustering of adhesion profiles generated using this platform differentially segregated metastatic cell lines from primary tumor lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8, or laminin. These interactions appear to be mediated in part by 31 integrin both in vitro and in vivo. We show that these galectins also correlate with human disease at both a transcriptional and histological level. Thus, our in vitro platform allowed us to interrogate the interactions of metastatic cells with their surrounding environment, and identified ECM and integrin interactions that could lead to therapeutic targets for metastasis prevention.

Publication Title

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis.

Sample Metadata Fields

Specimen part

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accession-icon SRP078563
Unbiased genomic analysis of multiple stages of lung cancer development
  • organism-icon Mus musculus
  • sample-icon 50 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To uncover the gene expression alterations that occur during lung cancer progression, we interrogated the gene expression state of neoplastic cells at different stages of malignant progression. We initiated tumors in KrasLSL-G12D/+;p53flox/flox;R26LSL-tdTomato (KPT) mice with a pool of barcoded lentiviral-Cre vectors and purified Tomatopositive cancer cells away from the diverse and variable stromal cell populations. Five to nine months after tumor initiation, cancer cells were isolated from individual primary tumors and metastases using fluorescence-activated cell sorting. Sequencing of the barcode region of the integrated lentiviral vectors established primary tumor-metastasis and metastasis-metastasis relationships. Tumor barcoding allowed us to unequivocally distinguish non-metastatic primary tumors (TnonMet) from those primary tumors that had seeded metastases (TMet). We profiled 10 TnonMet samples as well as TMet and metastasis (Met) samples representing 12 metastatic events. To examine additional earlier stages of lung cancer development, we also analyzed premalignant cells from hyperplasias that develop in KPT mice shortly after tumor initiation (KPT-Early; KPT-E), as well as tumors from KrasG12D;R26LSL-tdTomato (KT) mice which rarely gain metastatic ability Overall design: This study includes 52 samples: 3 KP late samples, 3KPT early samples,10 non-metastatic primary tumors, 9 metastatic primary tumors, and 27 metastasis in different organs. total RNA was isolated and prepared for sequencing using the Ovation® RNA-Seq system and Illumina TruSeq DNA kit (v2) to generate 100bp paired end reads. Reads were aligned to mm10.

Publication Title

Molecular definition of a metastatic lung cancer state reveals a targetable CD109-Janus kinase-Stat axis.

Sample Metadata Fields

Subject

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accession-icon SRP153147
Inter-tumoral heterogeneity in SCLC is influenced by the cell-type of origin
  • organism-icon Mus musculus
  • sample-icon 41 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 4000

Description

We describe two different routes of SCLC metastatic progression Overall design: We performed RNA-seq on primary tumors and metastasis from SCLC mouse model (Rb/p53/p130/mTmG) transduced by Ad-CMV-Cre or Ad-CGRP-Cre

Publication Title

Axon-like protrusions promote small cell lung cancer migration and metastasis.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE23875
Stage-specific sensitivity to p53 restoration in lung cancer
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Stage-specific sensitivity to p53 restoration during lung cancer progression.

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon GSE23874
Stage-specific sensitivity to p53 restoration in lung cancer: tumor data
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Tumorigenesis is a multistep process that results from the sequential accumulation of mutations in key oncogene and tumor-suppressor pathways. The quest to personalize cancer medicine based on targeting these underlying genetic abnormalities presupposes that sustained inactivation of tumor suppressors and activation of oncogenes are required for tumor maintenance. Mutations in the p53 tumor-suppressor pathway are a hallmark of cancer and significant efforts toward pharmaceutical reactivation of mutant p53 pathways are underway1-3. Here we show that restoration of p53 in established murine lung tumors leads to significant but incomplete tumor cell loss specifically in malignant adenocarcinomas but not in adenomas. Also, we define amplification of MAPK signaling as a critical determinant of malignant progression. The differential response to p53 restoration depends on activation of the Arf tumor suppressor downstream of hyperactive MAPK signaling. We propose that p53 naturally limits malignant progression by responding to increased oncogenic signaling, but is unresponsive to low levels of oncogene activity that are sufficient for early stages of lung tumor development. These data suggest that restoration of pathways important in tumor progression, as opposed to initiation, may lead to incomplete tumor regression due to the stage-heterogeneity of tumor cell populations.

Publication Title

Stage-specific sensitivity to p53 restoration during lung cancer progression.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE23873
Stage-specific sensitivity to p53 restoration in lung cancer: cell line data
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Tumorigenesis is a multistep process that results from the sequential accumulation of mutations in key oncogene and tumor-suppressor pathways. The quest to personalize cancer medicine based on targeting these underlying genetic abnormalities presupposes that sustained inactivation of tumor suppressors and activation of oncogenes are required for tumor maintenance. Mutations in the p53 tumor-suppressor pathway are a hallmark of cancer and significant efforts toward pharmaceutical reactivation of mutant p53 pathways are underway1-3. Here we show that restoration of p53 in established murine lung tumors leads to significant but incomplete tumor cell loss specifically in malignant adenocarcinomas but not in adenomas. Also, we define amplification of MAPK signaling as a critical determinant of malignant progression. The differential response to p53 restoration depends on activation of the Arf tumor suppressor downstream of hyperactive MAPK signaling. We propose that p53 naturally limits malignant progression by responding to increased oncogenic signaling, but is unresponsive to low levels of oncogene activity that are sufficient for early stages of lung tumor development. These data suggest that restoration of pathways important in tumor progression, as opposed to initiation, may lead to incomplete tumor regression due to the stage-heterogeneity of tumor cell populations.

Publication Title

Stage-specific sensitivity to p53 restoration during lung cancer progression.

Sample Metadata Fields

Cell line

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accession-icon SRP063609
Global transcriptome profiling of the 482N1 mouse metastasis-derived cell line, with or without Arntl2 knockdown
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

In order to determine the role of the transcription factor Arntl2 in regulating metastatic ability and identify Arntl2-dependent transcriptonal targets in metastatic lung adenocarcinoma, we sequenced the mRNA from 3 mouse metastasis cell lines. Each of these cell lines (482N1shLuciferase, 482N1shArntl2#1, and 482N1shArntl2#2) were derived from the same parental cell line, 482N1. 482N1 was derived from a lymph node metastasis of a Kras LSL G12D, p53 flox/flox 129S1/SvlmJ mouse model of metastatic lung adenocarcinoma. A comparison of shLuciferase and shArntl2 cell lines reveals Arntl2-dependent changes in the metastatic transcriptome. Overall design: This study includes 6 samples: 2 biological replicates of 482N1 shLuciferase, 2 biological replicates of 482N1 shArntl2#1, and 2 biological replicates of 482N1shArntl2#2. Poly-A RNA was isolated and prepared for sequencing using the Illumina TruSeq RNA kit (v2) to generate 100bp paired end reads. Reads were aligned to mm10.

Publication Title

An Arntl2-Driven Secretome Enables Lung Adenocarcinoma Metastatic Self-Sufficiency.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE29533
Nuclear Factor I/B is an Oncogene in Small Cell Lung Cancer
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Small cell lung cancer (SCLC) is an aggressive cancer often diagnosed only after it has metastasized to distant sites (Meuwissen and Berns 2005; Cooper and Spiro 2006). Despite the need to better understand this disease, SCLC remains poorly characterized at the molecular and genomic levels (Forgacs et al. 2001; Pleasance et al. 2010). Using a genetically-engineered mouse model of SCLC driven by conditional deletion of Trp53 and Rb1 in the lung (Jonkers et al. 2001; Vooijs et al. 2002; Meuwissen et al. 2003; Sage et al. 2003), we identified several frequent, high-magnitude focal DNA copy number alterations in SCLC. We uncovered amplification of a novel, oncogenic transcription factor, Nuclear Factor I/B (Nfib) in the mouse SCLC model and in human SCLC. Functional studies indicate that NFIB regulates cell viability and proliferation during transformation.

Publication Title

Nuclear factor I/B is an oncogene in small cell lung cancer.

Sample Metadata Fields

Cell line

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accession-icon SRP094490
Blimp1 induces transient metastatic heterogeneity in pancreatic cancer [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 37 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Purpose: Due to its high metastatic proclivity, pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly types of cancer. Therefore, it is imperative to better understand how the disease spreads as it progresses. Using a novel genetically engineered mouse model that allows us to isolate a subpopulation of cancer cells with superior metastatic capacity, we show that this aggressive phenotype correlates exclusively with a strong hypoxia signature. We subsequently identified the novel hypoxia-inducible gene Blimp1, which appears to play a critical role in regulating the hypoxic response upon its induction. Furthermore, genetic ablation of Blimp1 greatly reduces the level of metastasis in a PDAC mouse model. The nature of this Blimp1-regulated hypoxia signature is very unstable, since the seeded metastatic lesions mostly re-adopt similar transcriptomic profiles as the primary tumors. In conclusion, our results offer a potential mechanistic insight into how hypoxia drives metastasis in PDAC. Methods: Pure, paired GFP-negative/Tomato-positive and GFP-positive/Tomato-positive cancer cells or pure Tomato-positive cancer cells were sorted from primary PDAC samples from 6 KPC-colors mice or KPCT mice, respectively, with the following criteria: single cell based on FSC-A/H; CD45-negative; CD31-negative; Ter119-negative; F4/80-negative; DAPI-negative; and Tomato-positive. RNA were extracted from 10^4 to 5x10^4 freshly sorted cancer cells using AllPrep DNA/RNA Micro Kit (Qiagen). RNA quality was assessed with the RNA6000 PicoAssay kit by using the Bioanalyzer 2100 (Agilent). All ex vivo RNA samples used for RNA-seq analyses had an RIN > 8.0. Total RNA (15 ng/sample) was used for cDNA synthesis and amplification with the Ovation RNA-Seq system (NuGEN Technologies, Inc.). Subsequently, the amplified DNA samples were fragmented through sonication (Covaris model S1) and subjected to library preparation using the Illumina TruSeqTM DNA sample preparation kit (Low-Throughput protocol) according to manufacturer''s protocol. The quality of purified cDNA library products was confirmed by bioanalyzer and prepared for cluster generation on HiSeq paired-end flow cells using the CBot automated cluster generation system followed by sequencing on HiSeq 2000 machines. We obtained 101bp, paired-end reads from fragments of an average length of 250bp. Subsequently, RNA-Seq reads were aligned to the mouse genome (mm10) using the STAR aligner with standard input parameters (Dobin et al., 2013). The number of reads uniquely aligned to exons of individual genes were counted with HTSeq against the UCSC KnownGene (mm10) transcriptome (Anders et al., 2015). Results: Compared to the GFP-negative counterparts, GFP-positive pure PDAC cancer cells express higher levels of genes that are highly enriched with hypoxia signature. Additionally, compared to the GFP-negative counterparts, GFP-positive pure PDAC cancer cells express lower levels of cell cycle-related genes. In contrast, pure cancer cells isolated based on locations reveal few consistent differentially expressed genes between primary tumor and liver metastases; no consistent differentially expressed gene between primary tumor and lymph node metastases. Conclusions: Transcriptome profiles of both GFP-negative/positive PDAC cancer cells suggest that Hmga2/GFP-expressing cancer cells are highly enriched for signatures that correspond to cells residing within hypoxic enrivonment. Overall design: Freshly sorted GFP/Hmga2-positive and GFP/Hmga2-negative PDAC cancer cells derived from tumors of 6 KPCT;Hmga2-CK/+ (KPC-colors) mice were subjected to transcriptome profiling by paired-end RNA-Seq (total of 6 pairs of samples with overall 12 samples). Additionally, pure Tomato-positive PDAC cancer cells isolated from different anatomical locations were also subjected to transcriptome profiling by paired-end RNA-Seq (n = 23, not including technical replicates).

Publication Title

BLIMP1 Induces Transient Metastatic Heterogeneity in Pancreatic Cancer.

Sample Metadata Fields

Specimen part, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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