LUAD tumor, normal adjacent and tumoroid bulk transcriptomics
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE287471 | GEO | 2026/07/01
REPOSITORIES: GEO
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Project description:In this study, we performed spatial transcriptomics and bulk transcriptomics to profile LUAD patient samples. Next we constructed lung tumoroid from the patient and performed bulk transcriptome profiling to demonstrate its relevancy, and drug sensitivity assays
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Project description:LUAD tumor, normal adjacent and tumoroid bulk transcriptomics
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Project description:Circ101093 was knocked down in A549 LUAD cell lines, and overexpressed in H1975 LUAD cell lines. Then, downregulated proteins in A549 cell lines and upregulated proteins in H1975 cell lines were analyzed.
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Project description:Targeting protein for Xklp2 (TPX2) is a mitotic regulator frequently overexpressed in lung adenocarcinoma (LUAD), while its role in cancer stemness and autophagy remains incompletely understood. In this study, integrative bioinformatic analyses based on TCGA and GTEx datasets revealed that TPX2 overexpression in LUAD was associated with poor prognosis, elevated stemness scores, and increased expression of cancer stem cell-related markers. To investigate the molecular mechanisms underlying TPX2-mediated regulation in LUAD, RNA sequencing was performed in PC9 cells following TPX2 knockdown. Transcriptomic profiling and pathway analyses identified significant alterations in autophagy-related signaling pathways. In parallel, co-immunoprecipitation coupled with mass spectrometry (IP-MS) was conducted to characterize TPX2-associated protein interactions and explore potential regulatory networks involved in autophagy. Functional experiments further demonstrated that TPX2 depletion impaired autophagic flux and reduced stemness-associated phenotypes in LUAD cells, whereas TPX2 overexpression exerted opposite effects. These data provide transcriptomic and proteomic resources for investigating the role of TPX2-mediated autophagy in LUAD progression and cancer stemness.
2026-05-28 | GSE333531 | GEO
Project description:<p><a href="https://cptac-data-portal.georgetown.edu/study-summary/S056" target="_blank">Proteogenomics of Lung Adenocarcinoma, Gillette et al., 2020 publication is here</a><br><br>Lung cancer is a leading cause of cancer death in the United States and in 2019 it is estimated that there will be over 228,000 new cases (<a href="https://www.cancer.org/cancer/non-small-cell-lung-cancer/about/key-statistics.html" target="_blank">American Cancer Society</a>). There are two main types, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). A majority of patients (85%) have NSCLC, with a significant portion of those individuals having a histological subtype lung adenocarcinoma (LUAD) <a href="https://www.ncbi.nlm.nih.gov/pubmed/29364287" target="_blank">Herbst et al., 2018 Nature</a>. To advance the proteogenomic understanding of LUAD, the CPTAC program has investigated 111 tumors, (with 102 tumors paired with normal adjacent tissue samples) and subjected these samples to global proteome and phosphoproteome analysis. An optimized workflow for mass spectrometry of tissues using isobaric tags (TMT (tandem mass tags)-10) was used (<a href="https://www.ncbi.nlm.nih.gov/pubmed/29988108" target="_blank">Mertins et al., Nature Protocols 2018</a>). Proteome and phosphoproteome data from the LUAD discovery cohort is available below along with peptide spectrum matches (PSMs) and protein summary reports from the CPTAC common data analysis pipeline (CDAP).</p><p><em>Clinical Data</em> for LUAD tumors are provided below. Updates will be available as the LUAD cohort characterization proceeds.<br><em>Genomic Data</em> for LUAD tumors is available from the NCI Genomic Data Commons (GDC), <a href="https://portal.gdc.cancer.gov/projects/CPTAC-3" target="_blank">here</a><br><em>Imaging Data</em> for LUAD tumors is available from NCI, The Cancer Imaging Archive (TCIA), <a href="https://wiki.cancerimagingarchive.net/display/Public/CPTAC-LUAD" target="_blank">here</a><br>This release includes over 4500 files and 914 GB of data.</p>
<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/study-summary/S046">https://cptac-data-portal.georgetown.edu/study-summary/S046</a> on 01/29/21</li></ul>
2021-02-01 | MSV000086793 | MassIVE
Project description:To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we here investigated the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explored the role of epigenetic alterations in LUAD progression. We also investigated transcriptomic alterations among 36 patients tumor tissues.
| EGAS00001005132 | EGA
Project description:Background: Histone deacetylases (HDACs) drive non-small-cell lung cancer (NSCLC) progression, yet HDAC inhibitor (HDACi) responses vary by tumor subtype. We compared the pan-HDAC inhibitor SAHA (vorinostat) in two NSCLC models-HER2-mutant lung adenocarcinoma (NCI-H1299; TP53del, NRASQ61K) and EGFR/PI3K-driven squamous carcinoma (NCI-H1703; PDGFRAamp, PIK3CAE542K)-to uncover lineage-specific mechanisms. Methods: Cells were treated with SAHA (10 µM, 24 h), a clinically relevant dose yielding ~1 µM free drug in plasma. Strand-specific RNA-seq was aligned to GRCh38.p13 and analyzed with edgeR and DESeq2 (FDR < 0.05, |Log₂FC|≥ 1). Pathway, protein-interaction, apoptosis (Annexin V/PI), and migration (scratch, trans-well + mitomycin C) assays complemented transcriptomics. Clinical relevance was assessed by correlating SAHA-regulated genes with disease-free survival in TCGA-LUAD and TCGA-LUSC via GEPIA2. Results: SAHA altered 1098 genes in H1299 and 1532 in H1703, with only 437 shared. In H1299, SAHA induced EMT and MAPK-feedback genes while repressing interferon/apoptosis pathways. In H1703, SAHA activated complement/ECM remodeling and suppressed cell-cycle regulators. Class II HDACs (HDAC4/6) were downregulated only in H1703. Functionally, H1703 exhibited greater apoptosis; H1299 showed stronger migration inhibition. SAHA-reversed gene signatures (e.g., HMMR, PLK1 in LUAD; PAPPA, SAMD11 in LUSC) were significantly associated with poor disease-free survival, defining HDAC9-HMMR/PLK1 and HDAC4/6-PAPPA/SAMD11 axes. Conclusions: SAHA elicits distinct subtype-specific transcriptional and phenotypic effects in NSCLC. These findings highlight the importance of genetic context in HDACi therapy and support tailored combinations-such as SAHA with MAPK inhibitors in LUAD or HDAC4/6-targeted approaches in LUSC-and the use of SAHA-modulated biomarkers for patient stratification.
2026-02-25 | GSE302469 | GEO