Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures.

Cells within the tumour microenvironment (TME) can impact tumour development and influence treatment response. Computational approaches have been developed to deconvolve the TME from bulk RNA-seq. Using scRNA-seq profiling from breast tumours we simulate thousands of bulk mixtures, representing tumour purities and cell lineages, to compare the performance of nine TME deconvolution methods (BayesPrism, Scaden, CIBERSORTx, MuSiC, DWLS, hspe, CPM, Bisque, and EPIC). Some methods are more robust in deconvolving mixtures with high tumour purity levels. Most methods tend to mis-predict normal epithelial for cancer epithelial as tumour purity increases, a finding that is validated in two independent datasets. The breast cancer molecular subtype influences this mis-prediction. BayesPrism and DWLS have the lowest combined numbers of false positives and false negatives, and have the best performance when deconvolving granular immune lineages. Our findings highlight the need for more single-cell characterisation of rarer cell types, and suggest that tumour cell compositions should be considered when deconvolving the TME.

Reversal of Lactate and PD-1-mediated Macrophage Immunosuppression Controls Growth of PTEN/p53-deficient Prostate Cancer.

PURPOSE: Phosphatase and tensin homolog (PTEN) loss of function occurs in approximately 50% of patients with metastatic castrate-resistant prostate cancer (mCRPC), and is associated with poor prognosis and responsiveness to standard-of-care therapies and immune checkpoint inhibitors. While PTEN loss of function hyperactivates PI3K signaling, combinatorial PI3K/AKT pathway and androgen deprivation therapy (ADT) has demonstrated limited anticancer efficacy in clinical trials. Here, we aimed to elucidate mechanism(s) of resistance to ADT/PI3K-AKT axis blockade, and to develop rational combinatorial strategies to effectively treat this molecular subset of mCRPC. EXPERIMENTAL DESIGN: Prostate-specific PTEN/p53-deficient genetically engineered mice (GEM) with established 150-200 mm3 tumors, as assessed by ultrasound, were treated with either ADT (degarelix), PI3K inhibitor (copanlisib), or anti-PD-1 antibody (aPD-1), as single agents or their combinations, and tumors were monitored by MRI and harvested for immune, transcriptomic, and proteomic profiling, or ex vivo co-culture studies. Single-cell RNA sequencing on human mCRPC samples was performed using 10X Genomics platform. RESULTS: Coclinical trials in PTEN/p53-deficient GEM revealed that recruitment of PD-1-expressing tumor-associated macrophages (TAM) thwarts ADT/PI3Ki combination-induced tumor control. The addition of aPD-1 to ADT/PI3Ki combination led to TAM-dependent approximately 3-fold increase in anticancer responses. Mechanistically, decreased lactate production from PI3Ki-treated tumor cells suppressed histone lactylation within TAM, resulting in their anticancer phagocytic activation, which was augmented by ADT/aPD-1 treatment and abrogated by feedback activation of Wnt/ß-catenin pathway. Single-cell RNA-sequencing analysis in mCRPC patient biopsy samples revealed a direct correlation between high glycolytic activity and TAM phagocytosis suppression. CONCLUSIONS: Immunometabolic strategies that reverse lactate and PD-1-mediated TAM immunosuppression, in combination with ADT, warrant further investigation in patients with PTEN-deficient mCRPC.

STAT3 gain-of-function mutations connect leukemia with autoimmune disease by pathological NKG2Dhi CD8+ T cell dysregulation and accumulation.

The association between cancer and autoimmune disease is unexplained, exemplified by T cell large granular lymphocytic leukemia (T-LGL) where gain-of-function (GOF) somatic STAT3 mutations correlate with co-existing autoimmunity. To investigate whether these mutations are the cause or consequence of CD8+ T cell clonal expansions and autoimmunity, we analyzed patients and mice with germline STAT3 GOF mutations. STAT3 GOF mutations drove the accumulation of effector CD8+ T cell clones highly expressing NKG2D, the receptor for stress-induced MHC-class-I-related molecules. This subset also expressed genes for granzymes, perforin, interferon-γ, and Ccl5/Rantes and required NKG2D and the IL-15/IL-2 receptor IL2RB for maximal accumulation. Leukocyte-restricted STAT3 GOF was sufficient and CD8+ T cells were essential for lethal pathology in mice. These results demonstrate that STAT3 GOF mutations cause effector CD8+ T cell oligoclonal accumulation and that these rogue cells contribute to autoimmune pathology, supporting the hypothesis that somatic mutations in leukemia/lymphoma driver genes contribute to autoimmune disease.

DNA barcoding reveals ongoing immunoediting of clonal cancer populations during metastatic progression and immunotherapy response.

Cancers evade the immune system through the process of cancer immunoediting. While immune checkpoint inhibitors are effective for reactivating tumour immunity in some cancer types, many other solid cancers, including breast cancer, remain largely non-responsive. Understanding how non-responsive cancers evade immunity and whether this occurs at the clonal level will improve immunotherapeutic design. Here we use DNA barcoding to track murine mammary cancer cell clones during immunoediting and determine clonal transcriptional profiles that allow immune evasion following anti-PD1 plus anti-CTLA4 immunotherapy. Clonal diversity is significantly restricted by immunotherapy treatment in both primary tumours and metastases, demonstrating selection for pre-existing breast cancer cell populations and ongoing immunoediting during metastasis and treatment. Immunotherapy resistant clones express a common gene signature associated with poor survival of basal-like breast cancer patient cohorts. At least one of these genes has an existing small molecule that can potentially be used to improve immunotherapy response.

Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions.

In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases.

A single-cell and spatially resolved atlas of human breast cancers.

Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of their cellular composition and organization is limited. Here we present a single-cell and spatially resolved transcriptomics analysis of human breast cancers. We developed a single-cell method of intrinsic subtype classification (SCSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) provides high-resolution immune profiles, including new PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell-surface protein expression through differentiation within three major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into antitumor immune regulation. Using single-cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed 'ecotypes', with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer.

Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease.

Mononuclear phagocytes (MNPs) encompass dendritic cells, monocytes, and macrophages (MoMac), which exhibit antimicrobial, homeostatic, and immunoregulatory functions. We integrated 178,651 MNPs from 13 tissues across 41 datasets to generate a MNP single-cell RNA compendium (MNP-VERSE), a publicly available tool to map MNPs and define conserved gene signatures of MNP populations. Next, we generated a MoMac-focused compendium that revealed an array of specialized cell subsets widely distributed across multiple tissues. Specific pathological forms were expanded in cancer and inflammation. All neoplastic tissues contained conserved tumor-associated macrophage populations. In particular, we focused on IL4I1+CD274(PD-L1)+IDO1+ macrophages, which accumulated in the tumor periphery in a T cell-dependent manner via interferon-γ (IFN-γ) and CD40/CD40L-induced maturation from IFN-primed monocytes. IL4I1_Macs exhibited immunosuppressive characteristics through tryptophan degradation and promoted the entry of regulatory T cell into tumors. This integrated analysis provides a robust online-available platform for uniform annotation and dissection of specific macrophage functions in healthy and pathological states.

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis.

BACKGROUND: High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. METHODS: Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. RESULTS: Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. CONCLUSIONS: We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

Stromal cell diversity associated with immune evasion in human triple-negative breast cancer.

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single-cell RNA sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states: the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes.

High-throughput single-cell RNA sequencing is a powerful technique but only generates short reads from one end of a cDNA template, limiting the reconstruction of highly diverse sequences such as antigen receptors. To overcome this limitation, we combined targeted capture and long-read sequencing of T-cell-receptor (TCR) and B-cell-receptor (BCR) mRNA transcripts with short-read transcriptome profiling of barcoded single-cell libraries generated by droplet-based partitioning. We show that Repertoire and Gene Expression by Sequencing (RAGE-Seq) can generate accurate full-length antigen receptor sequences at nucleotide resolution, infer B-cell clonal evolution and identify alternatively spliced BCR transcripts. We apply RAGE-Seq to 7138 cells sampled from the primary tumor and draining lymph node of a breast cancer patient to track transcriptome profiles of expanded lymphocyte clones across tissues. Our results demonstrate that RAGE-Seq is a powerful method for tracking the clonal evolution from large numbers of lymphocytes applicable to the study of immunity, autoimmunity and cancer.