文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

SOURCE

Title: A Single-Cell Tumor Immune Atlasfor Precision Oncology
Date: 2020-10-26
Team: Barcelona Institute of Science and Technology (BIST), Barcelona,Spain
Paper Link: https://www.biorxiv.org/content/10.1101/2020.10.26.354829v1
Data Link (Restricted Access): https://zenodo.org/record/4036020#.X5uoHlMzaHF
Code Link: https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/Tumor-Immune-Cell-Atlas

WHY?

  • Immune microenvironments vary profoundly between patients and biomarkers for prognosis and treatment response lack precision
  • To pinpoint predictive cellular states of tumor immune cells and their spatial localization

HOW?

  • Analyzing>500,000cells from217patients and13cancer types
  • Data projection: Seurat's anchor-transferring method
  • UsingSPOTlightto combine single-cell and spatial transcriptomics data and identifying striking spatial immune cell patterns in tumor sections
  • ShinyApp(in progress) to project external data and to apply the immune classifier

GET WHAT?

GET 1: Generating a tumor immune cell atlas

  • Collected scRNA-seq datasets from13 different cancer types, 217 patients and 526,261 cells
文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology
  • Immune cells clustered by cell identity rather than patient origin: integrated317,111immune cells usingcanonical correlation analysis=> 25clusters文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

Get 2: Tumor subtype classifier

For Current:to establish a pan-cancer immune classification system

  • usedimmune cell type and state frequenciesof the reference atlas as input for similarity assessment across the 13 cancer types文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology
  • Ahierarchical k-means clusteringusing immune cell proportions as features defined six clusters with largely different compositions (almost all cancer types were presented in each cluster)
文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

For future: to facilitate the classification of immune profiles

  • trained aRF(random forest) classifierwith the 25 immune cell population achieving a highly accurate classification
  • using the classifier, the pan-cancer immune classification system could be extended toadditional cancer types

GET 3: A resource for immune cell annotation

To demonstrate the potential value of the atlas

文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

The applicability of the atlas as referenceacross different cancer types

  • First:Project cells onto atlas using a reference-based projection (Fig. A)

Next: Typical clustering matching (Fig. B)

文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology
  • Third: Check correlation (Fig. C)文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

The applicability of the atlas as referenceacross species

  • two liver metastases derived frommouse CRC organoids
  • main subtypes and specific subpopulations could also be assignedusing the human reference文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

GET 4: Spatial localization of immune cells in tumor sections

Spatialdistribution of immune cells is important forICI (immune checkpoint inhibitors) response

Single-cell reference atlas immune profiles + Spatial transcriptome data

SPOTlight: non-negative matrix factorization (NMF) based spatial deconvolution framework

Analysis of oropharyngeal squamous cell carcinoma (SCC)

  • cluster 1/2(cancer cells) is surrounded bycluster 0(stroma) andcluster 3(immune cells)

文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

  • cluster1/2presented a similar immune infiltration pattern, with an enrichment of proliferativeT-cellsandSPP1 macrophages

  • cluster 3presented a distinct immune infiltration pattern characterized by an enriched presence of (proliferative)B-cells

    cluster 0harbored regulatory T-cells and terminally exhausted CD8 T-cells and was specifically enriched inM2 macrophagesandnaive T-cells.

    文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

Analysis of ductal breast carcinoma (BC)

  • also get a cancer-specific regional distribution:文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

  • subclonal was directly associated with local enrichment of distinct immune cell states文献解读,单细胞肿瘤免疫图谱 A Single-Cell Tumor Immune Atlas for Precision Oncology

  • Foreseethe regional distribution of immune cell types to become an important feature for the prediction of immuno-therapy outcome.

相关文章

暂无评论

暂无评论...