Poor patient outcome correlates with active engulfment of cytokeratin positive CTCs within cancer-associated monocyte population in lung cancer.

High rates of mortality in non-small cell lung cancer lung cancer is due to inherent and acquired resistance to systemic therapies and subsequent metastatic burden. Metastasis is supported by suppression of the immune system at secondary organs and within the circulation. Modulation of the immune system is now being exploited as a therapeutic target with immune checkpoint inhibitors. The tracking of therapeutic efficacy in a real-time can be achieved with liquid biopsy, and evaluation of circulating tumour cells and the associated immune cells. A stable liquid biopsy biomarker for non-small cell lung cancer lung cancer has yet to be approved for clinical use. We performed a cross-sectional single-site study, and collected liquid biopsies from patients diagnosed with early, locally advanced, or metastatic lung cancer, undergoing surgery, or systemic therapy (chemotherapy/checkpoint inhibitors). Evaluation of overall circulating tumour cell counts, or cluster counts did not correlate with patient outcome. Interestingly, the numbers of Pan cytokeratin positive circulating tumour cells engulfed by tumour associated monocytes correlated strongly with patient outcome independent of circulating tumour cell counts and the use of checkpoint inhibitors. We suggest that Pan cytokeratin staining within monocytes is an important indicator of tumour-associated inflammation post-therapy and an effective biomarker with strong prognostic capability for patient outcome.

A robust experimental and computational analysis framework at multiple resolutions, modalities and coverages.

The ability to study cancer-immune cell communication across the whole tumor section without tissue dissociation is needed, especially for cancer immunotherapy development, which requires understanding of molecular mechanisms and discovery of more druggable targets. In this work, we assembled and evaluated an integrated experimental framework and analytical process to enable genome-wide scale discovery of ligand-receptors potentially used for cellular crosstalks, followed by targeted validation. We assessed the complementarity of four different technologies: single-cell RNA sequencing and Spatial transcriptomic (measuring over >20,000 genes), RNA In Situ Hybridization (RNAscope, measuring 4-12 genes) and Opal Polaris multiplex protein staining (4-9 proteins). To utilize the multimodal data, we implemented existing methods and also developed STRISH (Spatial TRanscriptomic In Situ Hybridization), a computational method that can automatically scan across the whole tissue section for local expression of gene (e.g. RNAscope data) and/or protein markers (e.g. Polaris data) to recapitulate an interaction landscape across the whole tissue. We evaluated the approach to discover and validate cell-cell interaction in situ through in-depth analysis of two types of cancer, basal cell carcinoma and squamous cell carcinoma, which account for over 70% of cancer cases. We showed that inference of cell-cell interactions using scRNA-seq data can misdetect or detect false positive interactions. Spatial transcriptomics still suffers from misdetecting lowly expressed ligand-receptor interactions, but reduces false discovery. RNAscope and Polaris are sensitive methods for defining the location of potential ligand receptor interactions, and the STRISH program can determine the probability that local gene co-expression reflects true cell-cell interaction. We expect that the approach described here will be widely applied to discover and validate ligand receptor interaction in different types of solid cancer tumors.