Development of a Model System to Study Expression Profile of RAC2 Gene in Breast Cancer MDA-MB-231 Cell Line.

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Oncogenic mutations in the RAC2 gene have been identified in various cancers, and extensive research is in progress to delineate its signaling pathways and identify potential therapeutic targets in breast cancers. This paper explored developing a bioinformatics model system to understand the RAC2 gene expression pattern concerning estrogenic receptor status in breast cancers. We have used the MDA-MB-231 breast cancer cell line to identify RAC2 gene expression. To simplify the development of model system with one dataset, we retrieved the microarray dataset GSE27515 from the Gene Expression Omnibus (GEO) for the differential gene expression analysis. Then, network analysis, pathway enrichment analysis, volcano plot, ORA, and the up/downregulated genes were used to highlight genes involved in signaling network pathways. We observed that the RAC2 gene is upregulated in the GSM679722, GSM676923, and GSM679724 downregulated in the samples GSM676925, GSM676926, and GSM676927 from the GEO dataset. Our observation found that the RAC2 gene is upregulated in the estrogen receptor (ER) negative breast cancers and downregulated in ER-positive breast cancer, involving pathways such as focal adhesion, MAPK signaling, axon guidance, and VEGF signaling pathway.", "claims": [{"id": "claim-method", "statement": "Filtering increases statistical power by removing unresponsive genes before differential expression analysis (DEA).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35368753", "locator": "sections[4] \"4. Results and Discussion\" paragraph 4", "quote": "Filtering increases statistical power by removing unresponsive genes before differential expression analysis (DEA)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35368753", "locator": "sections[9] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are available from the corresponding author upon request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RAC2 was upregulated in ER-negative breast cancer and downregulated in ER-positive breast cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35368753", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Our observation found that the RAC2 gene is upregulated in the estrogen receptor (ER) negative breast cancers and downregulated in ER-positive breast cancer, involving pathways such as focal adhesion, MAPK signaling, axon guidance, and VEGF signaling pathway."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RAC2 was upregulated in ER-negative breast cancer and downregulated in ER-positive breast cancer.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35368753"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE27515"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE27515"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35368753", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/2077850", "sha256": "sha256:02332330140c8ee69600ead56b38049ca1dcf92e652df17edcaf7d9a09325f1b", "bytes": 17893, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/2077850", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8970810", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE27515", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27515", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE27515", "version": null, "note": "The data used to support the findings of this study are available from the corresponding author upon request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data used to support the findings of this study are available from the corresponding author upon request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM679719", "GSM679720", "GSM679721", "GSM679722", "GSM679723", "GSM679724", "GSM679725", "GSM679726", "GSM679727"], "sample_count": 9, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Isolation and characterization of a metastatic hybrid cell line generated by ER negative and ER positive breast cancer cells in mouse bone marrow", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE27515 not downloaded", "asset:data:geo:GSE27515 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-2", "family": null, "specific": null, "label": "differential gene expression analysis (DEA)", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Filtering increases statistical power by removing unresponsive genes before differential expression analysis (DEA)."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pathway_enrich"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pathway_enrichment."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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