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accession-icon GSE7112
Abscisic acid effect on wild type and the abh1 mutant
  • organism-icon Arabidopsis thaliana
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Analysis of the abh1 mutant Arabidopsis plants following treatment with 50 uM abscisic acid (ABA). ABH1 encodes the large (80kDa) subunit of the nuclear mRNA cap binding complex and affects early ABA signal transduction events (Hugouvieux et al., 2001, Cell 106, 477).

Publication Title

mRNA cap binding proteins: effects on abscisic acid signal transduction, mRNA processing, and microarray analyses.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP090396
Exploiting drug addiction mechanisms to select against MAPKi resistant melanoma
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Melanoma resistant to MAPK inhibitors (MAPKi) displays loss of fitness upon experimental MAPKi withdrawal and, clinically, may be resensitized to MAPKi therapy after a drug holiday. Here, we uncovered and therapeutically exploited the mechanisms of MAPKi addiction in MAPKi-resistant BRAF MUT or NRAS MUT melanoma. MAPKi-addiction phenotypes evident upon drug withdrawal spanned transient cell-cycle slowdown to cell-death responses, the latter of which required a robust phosphorylated ERK (pERK) rebound. Generally, drug withdrawal–induced pERK rebound upregulated p38–FRA1–JUNB–CDKN1A and downregulated proliferation, but only a robust pERK rebound resulted in DNA damage and parthanatos-related cell death. Importantly, pharmacologically impairing DNA damage repair during MAPKi withdrawal augmented MAPKi addiction across the board by converting a cell-cycle deceleration to a caspase-dependent cell-death response or by furthering parthanatos related cell death. Specifically in MEKi-resistant NRAS MUT or atypical BRAF MUT melanoma, treatment with a type I RAF inhibitor intensified pERK rebound elicited by MEKi withdrawal, thereby promoting a cell death–predominant MAPKi-addiction phenotype. Thus, MAPKi discontinuation upon disease progression should be coupled with specific strategies that augment MAPKi addiction. Overall design: BRAF/MEK inhibitors resistant cell lines M249DDR5 and SKMEL28DDR1 were assayed for their responses after 6 hr of BRAF/MEK inhibitor treatment and after inhibitors withdrawal (by washin) for 6 and 24 hours

Publication Title

Exploiting Drug Addiction Mechanisms to Select against MAPKi-Resistant Melanoma.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP026540
Comparative Transcriptomics of Soybean Near Isogenic Lines in Response to Phytophthora Sojae
  • organism-icon Glycine max
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIllumina HiScanSQ

Description

Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is effectively controlled by Rps genes in soybean. Rps genes are race-specific, yet the mechanism of resistance, as well as susceptibility, remains largely unclear. Taking advantage of RNA-seq technology, we sequenced the transcriptomes of 10 near isogenic lines (NIL), each with a unique Rps gene, and the recurrent susceptible parent 'Williams'. A total of 4330 differentially expressed genes (DEGs) were identified in 'Williams' while 2075 to 5499 DEGs were identified in each NIL. Comparisons between the NILs and 'Williams' allowed classification of two major groups of DEGs of interest: incompatible reaction associated genes (IRAGs) and compatible reaction associated genes (CRAGs). Hierarchical cluster analysis divided NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6). Heatmap analysis, along with GO analysis suggested that the diversity of clusters for NILs were likely due to variation of the number of DEGs and the intensity of gene expression, rather than functional differentiation. Further analysis suggested that transcription factors might play pivotal role in determination of the cluster pattern, and that WRKY family were strongly associated with incompatible reactions. Analysis of IRAGs and CRAGs with putative functions suggested that the regulation of many phytohormone signaling pathways were associated with incompatible or compatible interactions with potential crosstalk between each other. As such, our study provides an in depth view of both incompatible and compatible interactions between soybean and P. sojae, which provides further insight into the mechanisms involved in host-pathogen interactions. Overall design: 22 samples were sequenced, 11 inoculated with P. sojae, the other 11 were mock-inoculated

Publication Title

Molecular response to the pathogen Phytophthora sojae among ten soybean near isogenic lines revealed by comparative transcriptomics.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE65186
Non-genomic and Immune Evolution in Melanoma with Acquired MAPKi Resistance
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP052740
RNAseq changes in pre MAPKi treatment and post MAPKi resistance Melanomas
  • organism-icon Homo sapiens
  • sample-icon 169 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Melanoma resistance to MAPK- or T cell checkpoint-targeted therapies represents a major clinical challenge, and treatment failures of MAPK-targeted therapies due to acquired resistance often require salvage immunotherapies. We show that genomic analysis of acquired resistance to MAPK inhibitors revealed key driver genes but failedto adequately account for clinical resistance. From a large-scale comparative analysis of temporal transcriptomes from patient-matched tumor biopsies, we discovered highly recurrent differential expression and signature outputs of c-MET, LEF1 and YAP1 as drivers of acquired MAPK inhibitor resistance. Moreover, integration of gene- and signature-based transcriptomic analysis revealed profound CD8 T cell deficiency detected in half of resistant melanomas in association with downregulation of dendritic cells and antigen presentation. We also propose a major methylomic basis to transcriptomic evolution under MAPK inhibitor selection. Thus, this database provides a rich informational resource, and the current landscape represents a benchmark to understanding melanoma therapeutic resistance. Overall design: Melanoma biopsies pre and post MAPKi treatment were sent for RNAseq analysis

Publication Title

Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE65184
Expression changes in pre MAPKi treatment and post MAPKi resistance Melanomas
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

Melanoma resistance to MAPK- or T cell checkpoint-targeted therapies represents a major clinical challenge, and treatment failures of MAPK-targeted therapies due to acquired resistance often require salvage immunotherapies. We show that genomic analysis of acquired resistance to MAPK inhibitors revealed key driver genes but failedto adequately account for clinical resistance. From a large-scale comparative analysis of temporal transcriptomes from patient-matched tumor biopsies, we discovered highly recurrent differential expression and signature outputs of c-MET, LEF1 and YAP1 as drivers of acquired MAPK inhibitor resistance. Moreover, integration of gene- and signature-based transcriptomic analysis revealed profound CD8 T cell deficiency detected in half of resistant melanomas in association with downregulation of dendritic cells and antigen presentation. We also propose a major methylomic basis to transcriptomic evolution under MAPK inhibitor selection. Thus, this database provides a rich informational resource, and the current landscape represents a benchmark to understanding melanoma therapeutic resistance.

Publication Title

Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE75313
Expression changes in Melanomas pre MAPKi treatment vs. on MAPKi treatment
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Recurrent Tumor Cell-Intrinsic and -Extrinsic Alterations during MAPKi-Induced Melanoma Regression and Early Adaptation.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon SRP066571
Expression changes in Melanomas pre MAPKi treatment vs. on MAPKi treatment (RNA-seq)
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Treatment of advanced V600BRAF mutant melanoma using a BRAF inhibitor (BRAFi) or its combination with a MEKi typically elicits partial responses. We compared the transcriptomes of patient-derived tumors regressing on MAPKi therapy against MAPKi-induced temporal transcriptomic states in human melanoma cell lines or murine melanoma in immune-competent mice. Despite heterogeneous dynamics of clinical tumor regression, residual tumors displayed highly recurrent transcriptomic alterations and enriched processes, which were also observed in MAPKi-selected cell lines (implying tumor cell-intrinsic reprogramming) or in bulk mouse tumors (and the CD45-negative or -positive fractions,, implying tumor cell-intrinsic or stromal/immune alterations, respectively). Tumor cell-intrinsic reprogramming attenuated MAPK-dependency, while enhancing mesenchymal, angiogenic and IFN-inflammatory features and growth/survival dependence on multi-RTKs and PD-L2. In the immune compartment, PD-L2 upregulation in CD11c+ immunocytes drove the loss of T-cell inflammation and promoted BRAFi resistance. Thus, residual melanoma early on MAPKi therapy already displays potentially exploitable adaptive transcriptomic, epigenomic, immune-regulomic alterations. Overall design: Paired melanoma biopsies/cell lines before treatment, during treatment and after resistance to MAPKi were sent for transcriptomic analysis by paired end 2x100bp HiSeq 2000 RNAseq analysis

Publication Title

Recurrent Tumor Cell-Intrinsic and -Extrinsic Alterations during MAPKi-Induced Melanoma Regression and Early Adaptation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP070710
mRNA expressions in pre-treatment melanomas undergoing anti-PD-1 checkpoint inhibition therapy
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

PD-1 immune checkpoint blockade provides significant clinical benefits for cancer patients. However, factors influencing innate sensitivity remain incompletely catalogued. We analyzed the somatic mutanomes and transcriptomes of pretreatment melanoma biopsies. Mutations in cell adhesion genes and the DNA repair gene BRCA2 were enriched in responding tumors, and a high mutational load associated with improved survival. Innately resistant tumors displayed frequent transcriptomic up-expression of genes that enriched for mesenchymal transition, cell adhesion, ECM organization, wound-healing and angiogenesis. The transcriptomes of innate resistance also enriched for signatures indicating up-regulation of these processes. Notably, MAPK-targeted therapy (MAPKi) induced similar signatures in melanoma, suggesting that a form of MAPKi resistance mediates cross-resistance to anti-PD-1 therapy. Co-enrichment of IPRIM (Innate anti-PD-1 Resistance Induced by MAPKi) signatures defined a transcriptomic subset across advanced cancers, suggesting that attenuating processes underlying these signatures may augment anti-PD1 responses. Thus, multi-factorial determinants influence anti-PD-1 patterns in melanoma. Overall design: Melanoma biopsies pre-anti-PD-1 therapy were sent for transcriptomic analysis by paired-end RNAseq analysis to find the correlates of response vs. non-response to the therapy

Publication Title

Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE75311
Expression changes in Melanomas pre MAPKi treatment vs. on MAPKi treatment (Affymetrix)
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Treatment of advanced V600BRAF mutant melanoma using a BRAF inhibitor (BRAFi) or its combination with a MEKi typically elicits partial responses. We compared the transcriptomes of patient-derived tumors regressing on MAPKi therapy against MAPKi-induced temporal transcriptomic states in human melanoma cell lines or murine melanoma in immune-competent mice. Despite heterogeneous dynamics of clinical tumor regression, residual tumors displayed highly recurrent transcriptomic alterations and enriched processes, which were also observed in MAPKi-selected cell lines (implying tumor cell-intrinsic reprogramming) or in bulk mouse tumors (and the CD45-negative or -positive fractions,, implying tumor cell-intrinsic or stromal/immune alterations, respectively). Tumor cell-intrinsic reprogramming attenuated MAPK-dependency, while enhancing mesenchymal, angiogenic and IFN-inflammatory features and growth/survival dependence on multi-RTKs and PD-L2. In the immune compartment, PD-L2 upregulation in CD11c+ immunocytes drove the loss of T-cell inflammation and promoted BRAFi resistance. Thus, residual melanoma early on MAPKi therapy already displays potentially exploitable adaptive transcriptomic, epigenomic, immune-regulomic alterations.

Publication Title

Recurrent Tumor Cell-Intrinsic and -Extrinsic Alterations during MAPKi-Induced Melanoma Regression and Early Adaptation.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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