RESUMO
Fluorescence microscopy data describe protein localization patterns at single-cell resolution and have the potential to reveal whole-proteome functional information with remarkable precision. Yet, extracting biologically meaningful representations from cell micrographs remains a major challenge. Existing approaches often fail to learn robust and noise-invariant features or rely on supervised labels for accurate annotations. We developed PIFiA (Protein Image-based Functional Annotation), a self-supervised approach for protein functional annotation from single-cell imaging data. We imaged the global yeast ORF-GFP collection and applied PIFiA to generate protein feature profiles from single-cell images of fluorescently tagged proteins. We show that PIFiA outperforms existing approaches for molecular representation learning and describe a range of downstream analysis tasks to explore the information content of the feature profiles. Specifically, we cluster extracted features into a hierarchy of functional organization, study cell population heterogeneity, and develop techniques to distinguish multi-localizing proteins and identify functional modules. Finally, we confirm new PIFiA predictions using a colocalization assay, suggesting previously unappreciated biological roles for several proteins. Paired with a fully interactive website ( https://thecellvision.org/pifia/ ), PIFiA is a resource for the quantitative analysis of protein organization within the cell.
Assuntos
Microscopia de Fluorescência , Saccharomyces cerevisiae , Análise de Célula Única , Análise de Célula Única/métodos , Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/genética , Microscopia de Fluorescência/métodos , Proteínas de Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Processamento de Imagem Assistida por Computador/métodos , Anotação de Sequência Molecular , Proteínas de Fluorescência Verde/metabolismo , Proteínas de Fluorescência Verde/genéticaRESUMO
BACKGROUND: World Health Organization grade II/III meningiomas frequently recur despite maximal safe surgical resection and adjuvant radiation. Notoriously resistant to medical therapy, no well-established guidelines for pharmacologic treatment currently exist. In recent years, a small number of clinical trials have investigated immune checkpoint inhibitors (ICIs) for patients with recurrent grade II/III meningiomas. We reviewed the existing literature to 1) summarize the clinical responses that have been observed and 2) identify tumor genomic characteristics that may predict a better response to ICI therapy. METHODS: PubMed was searched following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to include studies reporting clinical data for recurrent grade II or grade III meningiomas treated with ICIs. Clinical features, available tumor genomics, and outcomes were analyzed. RESULTS: Four studies were included comprising 59 patients; 74.6% had World Health Organization grade II meningiomas and 25.4% had grade III meningiomas. Thirt-two patients (54%) received nivolumab, 26 (44%) received pembrolizumab, and 1 (2%) received an ICI not named. While tumor genomic data was not consistently reported across studies, favorable response was most associated with mismatch repair deficiency and high tumor mutational burden. Common adverse effects included liver/pancreas enzyme elevations (11.5%), fatigue (11.5%), and leukopenia/infection (9%). CONCLUSIONS: Checkpoint inhibitors represent a promising investigational therapy for patients with recurrent grade II/III meningiomas. These drugs may be more efficacious for tumors with mismatch repair deficiency or high tumor mutational burden. Future investigations would benefit from research consortia with prospective enrollments of patients, descriptive characterization of tumor genomics, and standardized assessment of radiographic response.
RESUMO
Progression through the G1 phase of the cell cycle is the most highly regulated step in cellular division. We employed a chemogenomics approach to discover novel cellular networks that regulate cell cycle progression. This approach uncovered functional clusters of genes that altered sensitivity of cells to inhibitors of the G1/S transition. Mutation of components of the Polycomb Repressor Complex 2 rescued growth inhibition caused by the CDK4/6 inhibitor palbociclib, but not to inhibitors of S phase or mitosis. In addition to its core catalytic subunits, mutation of the PRC2.1 accessory protein MTF2, but not the PRC2.2 protein JARID2, rendered cells resistant to palbociclib treatment. We found that PRC2.1 (MTF2), but not PRC2.2 (JARID2), was critical for promoting H3K27me3 deposition at CpG islands genome-wide and in promoters. This included the CpG islands in the promoter of the CDK4/6 cyclins CCND1 and CCND2, and loss of MTF2 lead to upregulation of both CCND1 and CCND2. Our results demonstrate a role for PRC2.1, but not PRC2.2, in promoting G1 progression.