hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy

Brief Bioinform. 2022 Mar 10;23(2):bbab575. doi: 10.1093/bib/bbab575.


There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Keywords: Pareto optimization; projection-free single-cell modeling; response to immune checkpoint blockade; single-cell RNA sequencing (scRNA-seq); single-cell mass cytometry (CyTOF).

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers
  • Humans
  • Immunotherapy*
  • Melanoma* / drug therapy
  • Melanoma* / genetics
  • T-Lymphocytes


  • Biomarkers