Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer

Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.

35 Chemokine-driven spatial organization of immune cell microaggregates marks oropharyngeal squamous cell carcinomas containing tumor-specific T cells

Background

Oropharyngeal squamous cell carcinoma (OPSCC) is the most prevalent type of head and neck cancer. The survival of patients with OPSCC is tightly linked to the intratumoral presence of tumor-specific CD4+ and CD8+ T cells. Yet, immunotherapy is currently far from effective in OPSCC partly due to our limited understanding of its immune microenvironment.

Methods

Here a multi-modal, high-dimensional approach was used to dissect the immune landscape in a unique cohort of pre-therapy OPSCC patient samples (n=20) in which intratumoral tumor-specific T cells were either detected (immune response positive, IR+) or not (IR-). This included imaging mass cytometry (Hyperion) for high-dimensional phenotyping, spatial localization and interaction analyses of the cells in the tumor mircoenvironment with our newly developed imaging processing pipeline employing machine learning, Nanostring PanCancer IO360 panel analysis of immune signaling pathways, and combined single-cell gene expression profiling and T cell receptor sequencing (scRNAseq) to characterize the transcriptional states of clonally expanded tumor-infiltrating T cells.

Results

Immune cell infiltration in IR+ tumors is stronger and highly coordinated, with a distinct spatial phenotypic signature characterized by microaggregates of tumor-resident (CD103+) CD8+ and CD4+ T cells and dendritic cells within the tumor cell beds, which retained after permutation based correction for differences in cell frequencies. Furthermore, the increased expression of CXCL12 and LTB produced by CD4+ T cells, both involved in the spatial organization of immune cell infiltration, and the clonal expansion of CD8+ T cells producing the DC-attracting chemokines CCL4 or XCL1 in IR+ OPSCC, indicate that tumor-reactive T cells act as a positive feedback loop in the formation of these aggregates. The impact of these chemokines on local immunity and clinical outcome was confirmed in an independent TCGA OPSCC cohort. In contrast, the IR- OPSCC signature comprised spatial interactions between lymphocytes and different subpopulations of immunosuppressive myeloid cells.

Conclusions

Our study reveals that the chemokine-driven spatial immune signature of OPSCC has strong potential as a prognostic and predictive biomarker. While the immune signature of IR+ OPSCC suggests potential benefit from neoadjuvant immunotherapeutic approaches to limit the side effects of current radio(chemo)therapy, that of IR- OPSCC calls for strategies focused on stimulating T cells and counteracting immune suppressive mechanisms.

Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, and immunohistochemistry data.quanTIseq analysis of 8000 tumor samples revealed that cytotoxic T cell infiltration is more strongly associated with the activation of the CXCR3/CXCL9 axis than with mutational load and that deconvolution-based cell scores have prognostic value in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture and to reveal immune-cell types that underlie differential patients' responses to checkpoint blockers.Availability: quanTIseq is available at http://icbi.at/quantiseq .