GEO 数据集

主题由标题与摘要自动归类；样本量为数据集标注之和，SuperSeries 可能与其 SubSeries 重复计算。

• Baseline immune transcriptional states predict future HIV-1 acquisition in individuals at risk of sexual infection
  GSE352331Homo sapiens104 个样本2026-10-31

  Natural resistance to HIV-1 acquisition in highly exposed seronegative (HESN) individuals suggests the existence of pre-existing host states associated with reduced susceptibility. However, the baseline molecular determinants of susceptibility remain poorly understood. We analyzed PBMC transcriptomes by RNA sequencing in 104 HIV-1-seronegative men who have sex with men (MSM) at high risk of sexual exposure, including 65 HESN and 39 who subsequently seroconverted. Differential expression, functional enrichment, and spatial genomic clustering analyses were integrated with Elastic Net regularized logistic regression. HESN individuals showed enrichment of sensory receptor (p.adj=2×10⁻¹⁶) and cell-adhesion pathways (p.adj=9×10⁻³), together with non-random genomic clustering (p.adj=1×10⁻⁴) of differentially expressed genes at immune-related loci, including TCR, IGH, KIR, and MHC/HLA regions. In contrast, future seroconverters exhibited increased mRNA metabolism (p.adj=1.5×10⁻¹⁴), immune activation (p.adj=0.01), and type I interferon signaling (p.adj=0.02). A 14-gene risk score showed an out-of-fold AUC of 0.888. Cross-cohort transportability was evaluated in an independent ectocervical RNA-seq dataset. Applied without refitting, the signature showed moderate discrimination between long-term HESN and HIV-negative women at high risk of acquisition (AUC=0.689). The out-of-fold molecular risk score was also associated with time to HIV-1 seroconversion in MSM (log-rank p=7.1×10⁻¹¹; score×time interaction p=0.0086). These findings identify distinct pre-infection transcriptional states associated with HIV-1 acquisition and support partially transportable transcriptional architecture across blood and genital mucosal compartments.

  空间转录组
• Genomic and Immune Profiling Characterizes Immune Heterogeneity and a TIGIT-Associated Subtype in Intrahepatic Cholangiocarcinoma
  GSE350183Homo sapiens164 个样本2026-10-27

  Background and Aims: Intrahepatic cholangiocarcinoma (iCCA) is characterised by marked molecular and microenvironmental heterogeneity and moderate response to immunotherapy. We aimed to define the genomic and spatial determinants of immune checkpoint activity in iCCA and their association with clinical outcome. Approach and Results: We performed integrated transcriptomic, DNA panel sequencing, and multiplex immunohistochemistry analyses in a cohort of 144 patients with iCCA. Tumors were classified according to STIM-defined microenvironmental subtypes. Spatially resolved immune profiling was conducted across tumor core, stroma, invasive margin, and adjacent liver. Immune checkpoint expression, cellular proximity, and clinical outcome were analysed using Cox regression and Kaplan-Meier methods. TIGIThigh tumors were further characterised by differential gene expression and pathway enrichment analyses. STIM classification stratified tumors into inflamed (47%) and non-inflamed (53%) subtypes with distinct survival outcomes and genomic profiles. Recurrent alterations in CDKN2A/B, TP53, MTAP, and BAP1 showed subtype-specific enrichment and prognostic relevance. Spatial immune profiling revealed compartment-specific distributions of T cells and immune checkpoints, with predominance of TIGIT and PD-1 expression in stromal and marginal regions. Most tumor-infiltrating T cells lacked inhibitory receptor expression, while co-expression of multiple checkpoints was uncommon. TIGIThigh tumors displayed coordinated activation of immune effector, antigen presentation, and interferon signalling pathways, alongside enrichment of distinct genomic alterations, defining an immune-activated molecular subtype. Conclusions: Integrated genomic and spatial immune profiling reveals pronounced context-dependent heterogeneity of immune checkpoint regulation in iCCA. TIGIT delineates an immune-activated subtype with distinct molecular features, providing a potential biomarker framework for patient stratification and rational immunotherapeutic targeting.

  空间转录组