Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology.

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet's ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

Combinatorial treatment rescues tumour-microenvironment-mediated attenuation of MALT1 inhibitors in B-cell lymphomas.

Activated B-cell-like diffuse large B-cell lymphomas (ABC-DLBCLs) are characterized by constitutive activation of nuclear factor κB driven by the B-cell receptor (BCR) and Toll-like receptor (TLR) pathways. However, BCR-pathway-targeted therapies have limited impact on DLBCLs. Here we used >1,100 DLBCL patient samples to determine immune and extracellular matrix cues in the lymphoid tumour microenvironment (Ly-TME) and built representative synthetic-hydrogel-based B-cell-lymphoma organoids accordingly. We demonstrate that Ly-TME cellular and biophysical factors amplify the BCR-MYD88-TLR9 multiprotein supercomplex and induce cooperative signalling pathways in ABC-DLBCL cells, which reduce the efficacy of compounds targeting the BCR pathway members Bruton tyrosine kinase and mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1). Combinatorial inhibition of multiple aberrant signalling pathways induced higher antitumour efficacy in lymphoid organoids and implanted ABC-DLBCL patient tumours in vivo. Our studies define the complex crosstalk between malignant ABC-DLBCL cells and Ly-TME, and provide rational combinatorial therapies that rescue Ly-TME-mediated attenuation of treatment response to MALT1 inhibitors.

Spatially variant immune infiltration scoring in human cancer tissues.

The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients' tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors' immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients' tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor's immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.

Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics.

Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. Although tumors comprise ample cell types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond.

Multiplex Spatial Bioimaging for Combination Therapy Design.

Multiplex spatial analyses dissect the heterogeneous cellular abundances and interactions in tumors. Single-cell bioimaging profiles many disease-associated protein biomarkers in patient biopsies to inform the design of cancer therapies. Guided by the mechanistic insights from spatial cellular maps, combination therapy can efficiently eliminate cancers with reduced off-targets, resistance, and relapse.

The role of tumor-stroma interactions on desmoplasia and tumorigenicity within a microengineered 3D platform.

The tumor microenvironment has been demonstrated to play a crucial role in modulating cancer progression. Amongst various cell types within the tumor microenvironment, cancer associated fibroblasts (CAFs) are in abundance, serving to modulate the biophysical properties of the stromal matrix, through excessive deposition of extracellular matrix (ECM) proteins that leads to enhanced tumor progression. There is still a critical need to develop a fundamental framework on the role of tumor-stromal cell interactions on desmoplasia and tumorigenicity. Herein, we developed a 3D microengineered organotypic tumor-stroma model incorporated with breast cancer cells surrounded by CAF-embedded collagen matrix. We further integrated our platform with atomic force microscopy (AFM) to study the dynamic changes in stromal stiffness during active tumor invasion. Our findings primarily demonstrated enhanced tumor progression in the presence of CAFs. Furthermore, we highlighted the crucial role of crosstalk between tumor cells and CAFs on stromal desmoplasia, where we identified the role of tumor-secreted PDGF-AA/-BB on elevated matrix stiffness. Inhibition of the activity of PDGFRs in CAFs led to attenuation of stromal stiffness. Overall, our work presents a well-controlled tumor microenvironment model capable of dissecting specific biophysical and biochemical signaling cues which lead to stromal desmoplasia and tumor progression.

The Role of Desmoplasia and Stromal Fibroblasts on Anti-cancer Drug Resistance in a Microengineered Tumor Model.

INTRODUCTION: Cancer associated fibroblasts (CAFs) are known to participate in anti-cancer drug resistance by upregulating desmoplasia and pro-survival mechanisms within the tumor microenvironment. In this regard, anti-fibrotic drugs (i.e., tranilast) have been repurposed to diminish the elastic modulus of the stromal matrix and reduce tumor growth in presence of chemotherapeutics (i.e., doxorubicin). However, the quantitative assessment on impact of these stromal targeting drugs on matrix stiffness and tumor progression is still missing in the sole presence of CAFs. METHODS: We developed a high-density 3D microengineered tumor model comprised of MDA-MB-231 (highly invasive breast cancer cells) embedded microwells, surrounded by CAFs encapsulated within collagen I hydrogel. To study the influence of tranilast and doxorubicin on fibrosis, we probed the matrix using atomic force microscopy (AFM) and assessed matrix protein deposition. We further studied the combinatorial influence of the drugs on cancer cell proliferation and invasion. RESULTS: Our results demonstrated that the combinatorial action of tranilast and doxorubicin significantly diminished the stiffness of the stromal matrix compared to the control. The two drugs in synergy disrupted fibronectin assembly and reduced collagen fiber density. Furthermore, the combination of these drugs, condensed tumor growth and invasion. CONCLUSION: In this work, we utilized a 3D microengineered model to tease apart the role of tranilast and doxorubicin in the sole presence of CAFs on desmoplasia, tumor growth and invasion. Our study lay down a ground work on better understanding of the role of biomechanical properties of the matrix on anti-cancer drug efficacy in the presence of single class of stromal cells.