A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy

Intratumoral immune cells are crucial for tumor control and antitumor responses during immunotherapy. Immune cell trafficking into tumors is mediated by binding of specific immune cell receptors to chemokines, a class of secreted chemotactic cytokines. To broadly characterize chemokine expression and function in melanoma, we used multiplexed mass cytometry-based imaging of protein markers and RNA transcripts to analyze the chemokine landscape and immune infiltration in metastatic melanoma samples. Tumors that lacked immune infiltration were devoid of most of the profiled chemokines and exhibited low levels of antigen presentation and markers of inflammation. Infiltrated tumors were characterized by expression of multiple chemokines. CXCL9 and CXCL10 were often localized in patches associated with dysfunctional T cells expressing the B lymphocyte chemoattractant CXCL13. In tumors with B cells but no B cell follicles, T cells were the sole source of CXCL13, suggesting that T cells play a role in B cell recruitment and potentially in B cell follicle formation. B cell patches and follicles were also enriched with TCF7⁺ naïve-like T cells, a cell type that is predictive of response to immune checkpoint blockade. Our data highlight the strength of targeted RNA and protein codetection to analyze tumor immune microenvironments based on chemokine expression and suggest that the formation of tertiary lymphoid structures may be accompanied by naïve and naïve-like T cell recruitment, which may contribute to antitumor activity.

Loss of Claudin-4 Reduces DNA Damage Repair and Increases Sensitivity to PARP Inhibitors

High-grade serous ovarian cancer is the deadliest gynecologic malignancy due to progression to resistant disease. Claudin-4 is classically defined as a tight junction protein and is often associated with epithelial cancers. Claudin-4 is aberrantly expressed in nearly 70% of all ovarian cancer tumors and conveys a worse overall prognosis. Elevated claudin-4 expression correlates to increased DNA repair activity and resistance to DNA damaging agents. PARP inhibitors are emerging as an effective therapeutic option for patients with ovarian cancer and function by promoting DNA damage. The study examines the relationship between claudin-4 expression and the response to PARP inhibitors using both genetic and pharmacologic inhibition of claudin-4 in in vitro and ex vivo models of ovarian cancer to examine DNA repair markers and functional activity. Genetic inhibition of claudin-4 results in the downregulation of several DNA damage repair effectors, including 53BP1 and XRCC1. Claudin-4 knockdown did not change homology-directed repair but inhibited nonhomologous end-joining and reduced 53BP1 foci formation. In 15 primary ovarian cancer tumors, higher claudin-4 expression significantly correlated to a dampened PARP inhibitor-mediated antiproliferation response. Further, claudin-4 inhibition in high claudin-4 tumors sensitized tumor sections to PARP inhibition. These data highlight that claudin-4 expression in ovarian cancer tumors could serve as both a marker of PARP inhibitor response and a therapeutic target to improve PARP inhibitor response.

Epigenetic alterations at distal enhancers are linked to proliferation in human breast cancer

Aberrant DNA methylation is an early event in breast carcinogenesis and plays a critical role in regulating gene expression. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis through the integration of DNA methylation and gene expression to identify disease-driving pathways under epigenetic control. By grouping the emQTLs using biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis including regulation of proliferation and tumor-infiltrating fibroblasts. We report genome-wide loss of enhancer methylation at binding sites of proliferation-driving transcription factors including CEBP-β, FOSL1, and FOSL2 with concomitant high expression of proliferation-related genes in aggressive breast tumors as we confirm with scRNA-seq. The identified emQTL-CpGs and genes were found connected through chromatin loops, indicating that proliferation in breast tumors is under epigenetic regulation by DNA methylation. Interestingly, the associations between enhancer methylation and proliferation-related gene expression were also observed within known subtypes of breast cancer, suggesting a common role of epigenetic regulation of proliferation. Taken together, we show that proliferation in breast cancer is linked to loss of methylation at specific enhancers and transcription factor binding and gene activation through chromatin looping.

QPCTL regulates macrophage and monocyte abundance and inflammatory signatures in the tumor microenvironment

The enzyme glutaminyl-peptide cyclotransferase-like protein (QPCTL) catalyzes the formation of pyroglutamate residues at the NH₂-terminus of proteins, thereby influencing their biological properties. A number of studies have implicated QPCTL in the regulation of chemokine stability. Furthermore, QPCTL activity has recently been shown to be critical for the formation of the high-affinity SIRPα binding site of the CD47 “don’t-eat-me” protein. Based on the latter data, interference with QPCTL activity —and hence CD47 maturation—may be proposed as a means to promote anti-tumor immunity. However, the pleiotropic activity of QPCTL makes it difficult to predict the effects of QPCTL inhibition on the tumor microenvironment (TME). Using a syngeneic mouse melanoma model, we demonstrate that QPCTL deficiency alters the intra-tumoral monocyte-to-macrophage ratio, results in a profound increase in the presence of pro-inflammatory cancer-associated fibroblasts (CAFs) relative to immunosuppressive TGF-β1-driven CAFs, and leads to an increased IFN and decreased TGF-β transcriptional response signature in tumor cells. Importantly, the functional relevance of the observed TME remodeling is demonstrated by the synergy between QPCTL deletion and anti PD-L1 therapy, sensitizing an otherwise refractory melanoma model to anti-checkpoint therapy. Collectively, these data provide support for the development of strategies to interfere with QPCTL activity as a means to promote tumor-specific immunity.

Targeting PD-L1 and TIGIT could restore intratumoral CD8 T cell function in human colorectal cancer

Microsatellite stable colorectal cancers (MSS-CRC) are resistant to anti-PD-1/PD-L1 therapy but the combination of immune checkpoints inhibitors (ICI) could be a clue to reverse resistance. Our aim was to evaluate ex vivo the capacity of the combination of atezolizumab (anti-PD-L1) and tiragolumab (anti-TIGIT) to reactivate the immune response of tumor infiltrating lymphocytes (TILs) in MSS-CRC. We analysed CRC tumor tissue and the associated blood sample in parallel. For each patient sample, extensive immunomonitoring and cytokine production were tested. We generated an ex vivo assay to study immune reactivity following immune stimulation with checkpoint inhibitors of tumor cell suspensions. Three microsatellite instable (MSI) and 13 MSS-CRC tumors were analysed. To generalize our observations, bioinformatics analyses were performed on public data of single cell RNA sequencing of CRC TILs and RNA sequencing data of TCGA. Atezolizumab alone could only reactivate T cells from MSI tumors. Atezolizumab and tiragolumab reactivated T cells in 46% of MSS-CRC samples. Reactivation by ICK was observed in patients with higher baseline frequency of Th1 and Tc1 cells, and was also associated with higher baseline T cell polyfunctionality and higher CD96 expression. We showed that a high frequency of CD96 expression on T cells could be a surrogate marker of atezolizumab and tiragolumab efficacy. Together these data suggest that the association of atezolizumab and tiragolumab could restore function of CD4 and CD8 TILs in MSS-CRC and could be tested in a clinical trial in colorectal cancer patients with MSS status.

Immunomodulation by endothelial cells - partnering up with the immune system?

Blood vessel endothelial cells (ECs) have long been known to modulate inflammation by regulating immune cell trafficking, activation status and function. However, whether the heterogeneous EC populations in various tissues and organs differ in their immunomodulatory capacity has received insufficient attention, certainly with regard to considering them for alternative immunotherapy. Recent single-cell studies have identified specific EC subtypes that express gene signatures indicative of phagocytosis or scavenging, antigen presentation and immune cell recruitment. Here we discuss emerging evidence suggesting a tissue-specific and vessel type-specific immunomodulatory role for distinct subtypes of ECs, here collectively referred to as 'immunomodulatory ECs' (IMECs). We propose that IMECs have more important functions in immunity than previously recognized, and suggest that these might be considered as targets for new immunotherapeutic approaches.

Single-Cell Transcriptome Comparison of Bladder Cancer Reveals Its Ecosystem

Bladder carcinoma (BLCA) is a highly heterogeneous disease, and the underlying biological behavior is still poorly understood. Here, single-cell RNA sequencing was performed on four clinical samples of different grades from three patients, and 26,792 cell transcriptomes were obtained revealing different tumor ecosystems. We found that N-glycan biosynthesis pathway was activated in high-grade tumor, but TNF-related pathway was activated in cystitis glandularis. The tumor microenvironment (TME) of different samples showed great heterogeneity. Notably, cystitis glandularis was dominated by T cells, low-grade and high-grade tumors by macrophages, while TME in patient with high-grade relapse by stromal cells. Our research provides single-cell transcriptome profiles of cystitis glandularis and BLCA in different clinical states, and the biological program revealed by single-cell data can be used as biomarkers related to clinical prognosis in independent cohorts.

Control of Dendritic Cell Function Within the Tumour Microenvironment

The tumour microenvironment (TME) presents a major block to anti-tumour immune responses and to effective cancer immunotherapy. The inflammatory mediators such as cytokines, chemokines, growth factors and prostaglandins generated in the TME alter the phenotype and function of dendritic cells (DCs) that are critical for a successful adaptive immune response against the growing tumour. In this mini review we discuss how tumour cells and the surrounding stroma modulate DC maturation and trafficking to impact T cell function. Fibroblastic stroma and the associated extracellular matrix around tumours can also provide physical restrictions to infiltrating DCs and other leukocytes. We discuss interactions between the inflammatory TME and infiltrating immune cell function, exploring how the inflammatory TME affects generation of T cell-driven anti-tumour immunity. We discuss the open question of the relative importance of antigen-presentation site; locally within the TME versus tumour-draining lymph nodes. Addressing these questions will potentially increase immune surveillance and enhance anti-tumour immunity.

Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy

Simple Summary

Most malignant tumours are highly heterogeneous at molecular and phenotypic levels. Tumour variability poses challenges for the management of patients, as it arises between patients and even evolves in space and time within a single patient. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of tumour diversity in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate tumour heterogeneity.

Abstract

Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrated STRIDE’s utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell types to spatial locations but also improved the identification of spatially localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/wanglabtongji/STRIDE.

Immunological control of ovarian carcinoma by chemotherapy and targeted anticancer agents

At odds with other solid tumors, epithelial ovarian cancer (EOC) is poorly sensitive to immune checkpoint inhibitors (ICIs), largely reflecting active immunosuppression despite CD8⁺ T cell infiltration at baseline. Accumulating evidence indicates that both conventional chemotherapeutics and targeted anticancer agents commonly used in the clinical management of EOC not only mediate a cytostatic and cytotoxic activity against malignant cells, but also drive therapeutically relevant immunostimulatory or immunosuppressive effects. Here, we discuss such an immunomodulatory activity, with a specific focus on molecular and cellular pathways that can be harnessed to develop superior combinatorial regimens for clinical EOC care.

Nutritional Regulation of Mammary Tumor Microenvironment

The mammary gland is a heterogeneous organ comprising of immune cells, surrounding adipose stromal cells, vascular cells, mammary epithelial, and cancer stem cells. In response to nutritional stimuli, dynamic interactions amongst these cell populations can be modulated, consequently leading to an alteration of the glandular function, physiology, and ultimately disease pathogenesis. For example, obesity, a chronic over-nutritional condition, is known to disrupt homeostasis within the mammary gland and increase risk of breast cancer development. In contrast, emerging evidence has demonstrated that fasting or caloric restriction can negatively impact mammary tumorigenesis. However, how fasting induces phenotypic and functional population differences in the mammary microenvironment is not well understood. In this review, we will provide a detailed overview on the effect of nutritional conditions (i.e., overnutrition or fasting) on the mammary gland microenvironment and its impact on mammary tumor progression.

Establish an assessment model to characterized metastasis ability Single-cell multiomics reveals heterogeneous cell states linked to metastatic potential in liver cancer cell lines

Hepatocellular carcinoma (HCC) is the most common liver cancer with a high rate of metastasis. However, the molecular mechanisms that drive metastasis remain unclear. We combined single-cell transcriptomic, proteomic, and chromatin accessibility data to investigate how heterogeneous phenotypes contribute to metastatic potential in five HCC cell lines. We confirmed that the prevalence of a mesenchymal state and levels of cell proliferation are linked to the metastatic potential. We also identified a rare hypoxic subtype that has a higher capacity for glycolysis and exhibits dormant, invasive, and malignant characteristics. This subtype has increased metastatic potential. We further identified a robust 14-gene panel representing this hypoxia signature and this hypoxia signature could serve as a prognostic index. Our data provide a valuable data resource, facilitate a deeper understanding of metastatic mechanisms, and may help diagnosis of metastatic potential in individual patients, thus supporting personalized medicine.

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Provide a high-resolution single-cell triple-omics data of five liver cancer cell lines

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Identify a robust 14-gene set representing hypoxia signature

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The hypoxia signature is associated with prognosis

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Establish an assessment model to characterized metastasis ability

Next-generation cancer organoids

Organotypic models of patient-specific tumours are revolutionizing our understanding of cancer heterogeneity and its implications for personalized medicine. These advancements are, in part, attributed to the ability of organoid models to stably preserve genetic, proteomic, morphological and pharmacotypic features of the parent tumour in vitro, while also offering unprecedented genomic and environmental manipulation. Despite recent innovations in organoid protocols, current techniques for cancer organoid culture are inherently uncontrolled and irreproducible, owing to several non-standardized facets including cancer tissue sources and subsequent processing, medium formulations, and animal-derived three-dimensional matrices. Given the potential for cancer organoids to accurately recapitulate the intra- and intertumoral biological heterogeneity associated with patient-specific cancers, eliminating the undesirable technical variability accompanying cancer organoid culture is necessary to establish reproducible platforms that accelerate translatable insights into patient care. Here we describe the current challenges and recent multidisciplinary advancements and opportunities for standardizing next-generation cancer organoid systems.

Signatures of malignant cells and novel therapeutic targets revealed by single-cell sequencing in lung adenocarcinoma

Background

Single‐cell transcriptomics has been used to investigate various tumors to elucidate the molecular distinction of all cell type compositions of a complex mix.

Aims

This study aimed to investigate malignant‐cell‐specific genes to explore diagnostic and therapeutic biomarkers using single‐cell transcriptomic data of lung adenocarcinoma.

Materials & Methods

10X single‐cell RNA‐seq data of fourteen patients with lung adenocarcinoma were analyzed. Genes that expressed differentially and those with higher confidence to distinguish tumor cells from normal cells were picked out using the ROC curves. The LASSO regression method was used to select most markedly correlated genes to predict the malignancy of every single cell within a model. We also conducted further experiments to determine their roles in lung cancer in vitro.

Results

Twenty two thousand four hundred and ninety one tumor and 181 666 normal single cells were analyzed where 369 genes were found to be specifically expressed in single malignant cells. Seventy of them, encoding secreted or membrane‐bound proteins, showed involvement in cell‐to‐cell communications in tumor biology. KRT18 and the other six genes were identified as predictors to distinguish single malignant cells and were integrated to construct an accurate (96.1%) predicting model. Notably, IRX2, SPINK13, and CAPN8 outperformed the other four genes. Further experiments confirmed the upregulation of them in lung adenocarcinoma at both tissue and cell levels. Proliferative capacities of lung adenocarcinoma cells were attenuated by knocking‐down of either of them. However, targeting CAPN8, IRX2, or SPINK13 hardly exerted a cytotoxic effect on these cells.

Discussion

Apart from the current model, similar tools were still warranted using single‐cell RNA‐seq data of more types of tumors. The three genes identified as potential therapeutic targets in the present study still need to be validated in more in lung cancer.

Conclusion

Our model can aid the analyses of single‐cell sequencing data. CAPN8, IRX2, and SPINK13 may serve as novel targets of targeted and immune‐based therapies in lung adenocarcinoma.

Dendritic Cell-Based Immunotherapy in Multiple Myeloma: Challenges, Opportunities, and Future Directions

Immunotherapeutic approaches, including adoptive cell therapy, revolutionized treatment in multiple myeloma (MM). As dendritic cells (DCs) are professional antigen-presenting cells and key initiators of tumor-specific immune responses, DC-based immunotherapy represents an attractive therapeutic approach in cancer. The past years, various DC-based approaches, using particularly ex-vivo-generated monocyte-derived DCs, have been tested in preclinical and clinical MM studies. However, long-term and durable responses in MM patients were limited, potentially attributed to the source of monocyte-derived DCs and the immunosuppressive bone marrow microenvironment. In this review, we briefly summarize the DC development in the bone marrow niche and the phenotypical and functional characteristics of the major DC subsets. We address the known DC deficiencies in MM and give an overview of the DC-based vaccination protocols that were tested in MM patients. Lastly, we also provide strategies to improve the efficacy of DC vaccines using new, improved DC-based approaches and combination therapies for MM patients.

Transcriptional census of epithelial-mesenchymal plasticity in cancer

Epithelial-mesenchymal plasticity (EMP) contributes to tumor progression, promoting therapy resistance and immune cell evasion. Definitive molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Leveraging single-cell RNA sequencing data from 266 tumors spanning eight different cancer types, we identify expression patterns associated with intratumoral EMP. Integrative analysis of these programs confirmed a high degree of diversity among tumors. These diverse programs are associated with combinations of various common regulatory mechanisms initiated from cues within the tumor microenvironment. We show that inferring regulatory features can inform effective therapeutics to restrict EMP.

Uncovering Mediators of Collagen Degradation in the Tumor Microenvironment

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Collagen cleavage in tumors is primarily mediated by FAP⁺ cancer-associated fibroblasts.

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Collagen fibers are cleaved in an MMP-dependent manner.

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Released collagen fragments are internalized by M2-like tumor-associated macrophages and cancer-associated fibroblasts.

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The mannose receptor is central in collagen internalization by tumor-associated macrophages.

Increased remodeling of the extracellular matrix in malignant tumors has been shown to correlate with tumor aggressiveness and a poor prognosis. This remodeling involves degradation of the original extracellular matrix (ECM) and deposition of a new tumor-supporting ECM. The main constituent of the ECM is collagen and collagen turnover mainly occurs in a sequential manner, where initial proteolytic cleavage of the insoluble fibers is followed by cellular internalization of large well-defined collagen fragments for lysosomal degradation. However, despite extensive research in the field, a lack of consensus on which cell types within the tumor microenvironment express the involved proteases still exists. Furthermore, the relative contribution of different cell types to collagen internalization is not well-established. Here, we developed quantitative ex vivo collagen degradation assays and show that the proteases responsible for the initial collagen cleavage in two murine syngeneic tumor models are matrix metalloproteinases produced by cancer-associated fibroblasts and that collagen degradation fragments are endocytosed primarily by tumor-associated macrophages and cancer-associated fibroblasts from the tumor stroma. Using tumors from mannose receptor-deficient mice, we show that this receptor is essential for collagen-internalization by tumor-associated macrophages. Together, these findings identify the cell types responsible for the entire collagen degradation pathway, from initial cleavage to endocytosis of fragments for intracellular degradation.

Single Nuclear RNA Sequencing Highlights Intra-Tumoral Heterogeneity and Tumor Microenvironment Complexity in Testicular Embryonic Rhabdomyosarcoma

Background

Testicular embryonic rhabdomyosarcoma (ERMS) is a rare soft tissue tumor in children featured with high intra-tumoral heterogeneity. In this study, we aimed to comprehensively delineate the testicular ERMS intra-tumoral heterogeneity and tumor microenvironment.

Methods

Cell types and the corresponding marker genes were identified by single-nuclear RNA sequencing (snRNA-seq). Functional states of different clusters were evaluated by uniform manifold approximation and projection and differentially expressed genes. Kaplan–Meier curve analysis was constructed according to the gene expression profile to determine the correlation between candidate marker genes and the overall survival and disease-free survival of patients with osteosarcoma from TCGA.

Results

A total of 8868 tumor cells and 10,147 normal cells were obtained from testicular ERMS tissues. The heterogeneous malignant subtype was composed of six subgroups (C1–C6) with differential proliferative and migratory potentials. Cell trajectory analysis revealed the C1 subgroup might be the starting cells of the tumor and transform into two different types of malignant cells, C2 and C5/6, during the development of RMS. The differentially expressed genes were closely related to cell adhesion and extracellular matrix signaling pathways. Furthermore, the interaction analysis between cell subgroups (macrophages and tumor cells, endothelial cells and tumor cells) demonstrated that collagen-related gene COL6A1 plays a key role from the initiation of ERMS to the entire process of malignant transformation.

Conclusion

Our findings provide a new insight in the understanding of the initiation and progression of testicular ERMS and have potential value in the development of markers for the diagnosis and stratification of testicular ERMS.

Interplay between Solid Tumors and Tumor Microenvironment

Over the past few decades, basic studies aimed at curing patients with cancer have been constantly evolving. A myriad of mechanistic studies on physiological changes and related factors in tumor growth and metastasis have been reported. Recently, several studies have been considerate to how tumors adapt to unfavorable environments, such as glucose deprivation, oxidative stress, hypoxic conditions, and immune responses. Tumors attempt to adapt to unfavorable environments with genetic or non-genetic changes, the alteration of metabolic signals, or the reconfiguration of their environment through migration to other organs. One of the distinct features in solid tumors is heterogeneity because their environments vary due to the characteristics of colony growth. For this reason, researchers are paying attention to the communication between growing tumors and neighboring environments, including stromal cells, immune cells, fibroblasts, and secreted molecules, such as proteins and RNAs. During cancer survival and progression, tumor cells undergo phenotype and molecular changes collectively referred to as cellular plasticity, which result from microenvironment signals, genetics and epigenetic alterations thereby contributing to tumor heterogeneity and therapy response. In this review, we herein discuss the adaptation process of tumors to adverse environments via communication with neighboring cells for overcoming unfavorable growth conditions. Understanding the physiology of these tumors and their communication with the tumor environment can help to develop promising tumor treatment strategies.

Spatial omics: Navigating to the golden era of cancer research

The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high-throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi-modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

Angiogenesis goes computational – The future way forward to discover new angiogenic targets?

Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet, computational methods have not been widely used for angiogenic target discovery and prioritization in this field, partly because (wet-lab) vascular biologists are insufficiently familiar with computational biology tools and the opportunities they may offer. With this review, written for vascular biologists who lack expertise in computational methods, we aspire to break boundaries between both fields and to illustrate the potential of these tools for future angiogenic target discovery. We provide a comprehensive survey of currently available computational approaches that may be useful in prioritizing candidate genes, predicting associated mechanisms, and identifying their specificity to endothelial cell subtypes. We specifically highlight tools that use flexible, machine learning frameworks for large-scale data integration and gene prioritization. For each purpose-oriented category of tools, we describe underlying conceptual principles, highlight interesting applications and discuss limitations. Finally, we will discuss challenges and recommend some guidelines which can help to optimize the process of accurate target discovery.

Pancreatic Cancer and Cellular Senescence: Tumor Microenvironment under the Spotlight

Pancreatic ductal adenocarcinoma (PDAC) has one of the most dismal prognoses of all cancers due to its late manifestation and resistance to current therapies. Accumulating evidence has suggested that the malignant behavior of this cancer is mainly influenced by the associated strongly immunosuppressive, desmoplastic microenvironment and by the relatively low mutational burden. PDAC develops and progresses through a multi-step process. Early in tumorigenesis, cancer cells must evade the effects of cellular senescence, which slows proliferation and promotes the immune-mediated elimination of pre-malignant cells. The role of senescence as a tumor suppressor has been well-established; however, recent evidence has revealed novel pro-tumorigenic paracrine functions of senescent cells towards their microenvironment. Understanding the interactions between tumors and their microenvironment is a growing research field, with evidence having been provided that non-tumoral cells composing the tumor microenvironment (TME) influence tumor proliferation, metabolism, cell death, and therapeutic resistance. Simultaneously, cancer cells shape a tumor-supportive and immunosuppressive environment, influencing both non-tumoral neighboring and distant cells. The overall intention of this review is to provide an overview of the interplay that occurs between senescent and non-senescent cell types and to describe how such interplay may have an impact on PDAC progression. Specifically, the effects and the molecular changes occurring in non-cancerous cells during senescence, and how these may contribute to a tumor-permissive microenvironment, will be discussed. Finally, senescence targeting strategies will be briefly introduced, highlighting their potential in the treatment of PDAC.

Decode the Stable Cell Communications Based on Neuropeptide-Receptors Network in 36746 Tumor Cells

Background: As chemical signals of hormones, neuropeptides are essential to regulate cell growth by interacting with their receptors to achieve cell communications in cancer tissues. Previously, neuropeptide transcriptome analysis was limited to tissue-based bulk expression levels. The molecular mechanisms of neuropeptides and their receptors at the single-cell level remain unclear. We conducted a systematic single-cell transcriptome data integration analysis to clarify the similarities and variations of neuropeptide-mediated cell communication between various malignancies. Methods: Based on the single-cell expression information in 72 cancer datasets across 24 cancer types, we characterized actively expressed neuropeptides and receptors as having log values of the quantitative transcripts per million ≥ 1. Then, we created the putative cell-to-cell communication network for each dataset by using the known interaction of those actively expressed neuropeptides and receptors. To focus on the stable cell communication events, we identified neuropeptide and downstream receptors whose interactions were detected in more than half of all conceivable cell-cell interactions (square of the total cell population) in a dataset. Results: Focusing on those actively expressed neuropeptides and receptors, we built over 76 million cell-to-cell communications across 70 cancer datasets. Then the stable cell communication analyses were applied to each dataset, and about 14 million stable cell-to-cell communications could be detected based on 16 neuropeptides and 23 receptors. Further functional analysis indicates these 39 genes could regulate blood pressure and are significantly associated with patients’ survival among over ten thousand The Cancer Genome Atlas (TCGA)pan-cancer samples. By zooming in lung cancer-specific clinical features, we discovered the 39 genes appeared to be enriched in the patients with smoking. In skin cancer, they may differ in the patients with the distinct histological subtype and molecular drivers. Conclusions: At the single-cell level, stable cell communications across cancer types demonstrated some common and distinct neuropeptide-receptor patterns, which could be helpful in determining the status of neuropeptide-based cell communication and developing a peptide-based therapy strategy.

Innate tumor killers in colorectal cancer

Standard treatment of colorectal cancer (CRC) improves the prognosis of CRC patients, but it is still intractable to control the progression of metastatic CRC. Immune microenvironment and immunotherapies of CRC have received extensive attention in recent years, but present immunotherapies of CRC have mainly focused on T cells and therapeutic response is only observed in a small proportion of patients. Innate immune cells are the first-line of defense in the development of malignancies. Natural killer (NK) cells, NKT cells and γδT cells are three types of innate cells of lymphoid origin and show cytotoxicity against various tumor cells including CRC. Besides, in the development of CRC, they can also be inhibited or express regulatory type, promoting tumor progression. Researches about anti-tumorigenic and pro-tumorigenic mechanisms of these cells are ongoing and regulation of these cells is also being unearthed. Meanwhile, immunotherapies using these cells more or less have shown efficacy in animal models and some of them are under exploration in clinical trials. This review provides an overview of intrinsic properties of NK cell, NKT cell and γδT cell, and summarizes current related promising treatment strategies.

Pan-cancer single-cell landscape of tumor-infiltrating T cells

[Figure: see text].

Tumor immune microenvironment lncRNAs

Long non-coding ribonucleic acids (RNAs) (lncRNAs) are key players in tumorigenesis and immune responses. The nature of their cell type-specific gene expression and other functional evidence support the idea that lncRNAs have distinct cellular functions in the tumor immune microenvironment (TIME). To date, the majority of lncRNA studies have heavily relied on bulk RNA-sequencing data in which various cell types contribute to an averaged signal, limiting the discovery of cell type-specific lncRNA functions. Single-cell RNA-sequencing (scRNA-seq) is a potential solution for tackling this limitation despite the lack of annotations for low abundance yet cell type-specific lncRNAs. Hence, updated annotations and further understanding of the cellular expression of lncRNAs will be necessary for characterizing cell type-specific functions of lncRNA genes in the TIME. In this review, we discuss lncRNAs that are specifically expressed in tumor and immune cells, summarize the regulatory functions of the lncRNAs at the cell type level and highlight how a scRNA-seq approach can help to study the cell type-specific functions of TIME lncRNAs.

Peripherally-driven myeloid NFkB and IFN/ISG responses predict malignancy risk, survival, and immunotherapy regime in ovarian cancer

Background

Tumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers’ detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification.

Methods

We used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay’s ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug–target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options.

Results

In silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an ‘in sitro’ (in vitro+in situ) sFIS assay, where human myeloid cells were exposed to patients’ serum in vitro, to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby ‘mimicking’ patients’ in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB response^HIGHsi-IFN/ISG response^LOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel–carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG response^HIGHsi-NFκB response^LOW), which aligned with high antitumor efficacy.

Conclusions

We established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies.

Multi-tumor analysis of cancer-stroma interactomes of patient-derived xenografts unveils the unique homeostatic process in renal cell carcinomas

The patient-derived xenograft (PDX) model is a versatile tool used to study the tumor microenvironment (TME). However, limited studies have described multi-tumor PDX screening strategies to detect hub regulators during cancer-stroma interaction. Transcriptomes of cancer (human) and stroma (mouse) components of 70 PDX samples comprising 9 distinctive tumor types were analyzed in this study. PDX models recapitulated the original tumors' features, including tumor composition and putative signaling. Particularly, kidney renal clear cell carcinoma (KIRC) stood out, with altered hypoxia-related pathways and a high proportion of endothelial cells in the TME. Furthermore, an integrated analysis conducted to predict paracrine effectors in the KIRC cancer-to-stroma communication detected well-established soluble factors responsible for the hypoxia-related reaction and the so-far unestablished soluble factor, apelin (APLN). Subsequent experiments also supported the potential role of APLN in KIRC tumor progression. Therefore, this paper hereby provides an analytical workflow to find hub regulators in cancer-stroma interactions.

Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer

Tumor metabolism patterns have been reported to be associated with the prognosis of many cancers. However, the metabolic mechanisms underlying prostate cancer (PCa) remain unknown. This study aimed to explore the metabolic characteristics of PCa. First, we downloaded mRNA expression data and clinical information of PCa samples from multiple databases and quantified the metabolic pathway activity level using single-sample gene set enrichment analysis (ssGSEA). Through unsupervised clustering and principal component analyses, we explored metabolic characteristics and constructed a metabolic score for PCa. Then, we independently validated the prognostic value of our metabolic score and the nomogram based on the metabolic score in multiple databases. Next, we found the metabolic score to be closely related to the tumor microenvironment and DNA mutation using multi-omics data and ssGSEA. Finally, we found different features of drug sensitivity in PCa patients in the high/low metabolic score groups. In total, 1232 samples were analyzed in the present study. Overall, an improved understanding of tumor metabolism through the characterization of metabolic clusters and metabolic score may help clinicians predict prognosis and aid the development of more personalized anti-tumor therapeutic strategies for PCa.

Macrophage-targeted therapy unlocks antitumoral crosstalk between IFN𝛾-secreting lymphocytes and IL12-producing dendritic cells

Macrophages often abound within tumors, express colony-stimulating factor 1 receptor (CSF1R), and are linked to adverse patient survival. Drugs blocking CSF1R signaling have been used to suppress tumor-promoting macrophage responses; however, their mechanisms of action remain incompletely understood. Here, we assessed the lung tumor immune microenvironment in mice treated with BLZ945, a prototypical small molecule CSF1R inhibitor, using single-cell RNA sequencing and mechanistic validation approaches. We showed that tumor control was not caused by CSF1R+ cell depletion; instead, CSF1R targeting reshaped the CSF1R+ cell landscape, which unlocked crosstalk between antitumoral CSF1R- cells. These cells included IFNγ-producing NK and T cells, and an IL12-producing dendritic cell subset, denoted as DC3, which were all necessary for CSF1R inhibitor-mediated lung tumor control. These data indicate that CSF1R targeting can activate a cardinal crosstalk between cells that are not macrophages and that are essential to mediate the effects of T cell-targeted immunotherapies and promote antitumor immunity.

A pan-cancer analysis revealing the role of TIGIT in tumor microenvironment

T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT), an immune checkpoint, plays a pivotal role in immune suppression. However its role in tumor immunity and correlation with the genetic and epigenetic alterations remains unknown. Here, we comprehensively analyzed the expression patterns of the TIGIT and its value of prognostic prediction among 33 types of cancers based on the data collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression projects (GTEx). Furthermore, the correlations of TIGIT with pathological stages, tumor-infiltrating immune cells (TIICs), signatures of T cells subtypes, immune checkpoint genes, the degree of Estimation of STromal and Immune cells in MAlignant Tumor tissues using the Expression data (ESTIMATE), tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, and DNA methyltransferases (DNMTs) were also explored. Gene functional enrichment was conducted by Gene Set Enrichment Analysis (GSEA). Our results showed that the expression of TIGIT was upregulated in most of the cancer types. Cox regression model showed that high expression of TIGIT in tumor samples correlates with poor prognosis in KIRC, KIRP, LGG, UVM, and with favorable prognosis in BRCA, CECS, HNSC, SKCM. TIGIT expression positively correlated with advanced stages, TIICs, the signatures of effector T cells, exhausted T cells, effector Tregs and the degree of ESTIMATE in KIRC, KIRP and UVM. TIGIT expression also positively correlated with CTLA4, PDCD1 (PD-1), CD274 (PD-L1), ICOS in most of the cancer types. Furthermore, the expression of TIGIT was correlated with TMB, MSI, MMR genes and DNMTs in different types of cancers. GSEA analysis showed that the expression of TIGIT was related to cytokine-cytokine receptor interaction, allograft rejection, oxidative phosphorylation. These findings suggested that TIGIT could serve as a potential biomarker for prognosis and a novel target for immunotherapies in cancers.

ImmReg: the regulon atlas of immune-related pathways across cancer types

Immune system gene regulation perturbation has been found to be a major cause of the development of various types of cancer. Numbers of mechanisms contribute to gene expression regulation, thus, systematically identification of potential regulons of immune-related pathways is critical to cancer immunotherapy. Here, we comprehensively chart the landscape of transcription factors, microRNAs, RNA binding proteins and long noncoding RNAs regulation in 17 immune-related pathways across 33 cancers. The potential immunology regulons are likely to exhibit higher expressions in immune cells, show expression perturbations in cancer, and are significantly correlated with immune cell infiltrations. We also identify a panel of clinically relevant immunology regulons across cancers. Moreover, the regulon atlas of immune-related pathways helps prioritizing cancer-related genes (i.e. ETV7, miR-146a-5p, ZFP36 and HCP5). We further identified two molecular subtypes of glioma (cold and hot tumour phenotypes), which were characterized by differences in immune cell infiltrations, expression of checkpoints, and prognosis. Finally, we developed a user-friendly resource, ImmReg (http://bio-bigdata.hrbmu.edu.cn/ImmReg/), with multiple modules to visualize, browse, and download immunology regulation. Our study provides a comprehensive landscape of immunology regulons, which will shed light on future development of RNA-based cancer immunotherapies.

Three subtypes of lung cancer fibroblasts define distinct therapeutic paradigms

Cancer-associated fibroblasts (CAFs) are highly heterogeneous. With the lack of a comprehensive understanding of CAFs' functional distinctions, it remains unclear how cancer treatments could be personalized based on CAFs in a patient's tumor. We have established a living biobank of CAFs derived from biopsies of patients' non-small lung cancer (NSCLC) that encompasses a broad molecular spectrum of CAFs in clinical NSCLC. By functionally interrogating CAF heterogeneity using the same therapeutics received by patients, we identify three functional subtypes: (1) robustly protective of cancers and highly expressing HGF and FGF7; (2) moderately protective of cancers and highly expressing FGF7; and (3) those providing minimal protection. These functional differences among CAFs are governed by their intrinsic TGF-β signaling, which suppresses HGF and FGF7 expression. This CAF functional classification correlates with patients' clinical response to targeted therapies and also associates with the tumor immune microenvironment, therefore providing an avenue to guide personalized treatment.

Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.

Application of Single-Cell Multi-Omics in Dissecting Cancer Cell Plasticity and Tumor Heterogeneity

Tumor heterogeneity, a hallmark of cancer, impairs the efficacy of cancer therapy and drives tumor progression. Exploring inter- and intra-tumoral heterogeneity not only provides insights into tumor development and progression, but also guides the design of personalized therapies. Previously, high-throughput sequencing techniques have been used to investigate the heterogeneity of tumor ecosystems. However, they could not provide a high-resolution landscape of cellular components in tumor ecosystem. Recently, advance in single-cell technologies has provided an unprecedented resolution to uncover the intra-tumoral heterogeneity by profiling the transcriptomes, genomes, proteomes and epigenomes of the cellular components and also their spatial distribution, which greatly accelerated the process of basic and translational cancer research. Importantly, it has been demonstrated that some cancer cells are able to transit between different states in order to adapt to the changing tumor microenvironment, which led to increased cellular plasticity and tumor heterogeneity. Understanding the molecular mechanisms driving cancer cell plasticity is critical for developing precision therapies. In this review, we summarize the recent progress in dissecting the cancer cell plasticity and tumor heterogeneity by use of single-cell multi-omics techniques.

Characterizing Intercellular Communication of Pan-Cancer Reveals SPP1+ Tumor-Associated Macrophage Expanded in Hypoxia and Promoting Cancer Malignancy Through Single-Cell RNA-Seq Data

Hypoxia is a characteristic of tumor microenvironment (TME) and is a major contributor to tumor progression. Yet, subtype identification of tumor-associated non-malignant cells at single-cell resolution and how they influence cancer progression under hypoxia TME remain largely unexplored. Here, we used RNA-seq data of 424,194 single cells from 108 patients to identify the subtypes of cancer cells, stromal cells, and immune cells; to evaluate their hypoxia score; and also to uncover potential interaction signals between these cells in vivo across six cancer types. We identified SPP1+ tumor-associated macrophage (TAM) subpopulation potentially enhanced epithelial–mesenchymal transition (EMT) by interaction with cancer cells through paracrine pattern. We prioritized SPP1 as a TAM-secreted factor to act on cancer cells and found a significant enhanced migration phenotype and invasion ability in A549 lung cancer cells induced by recombinant protein SPP1. Besides, prognostic analysis indicated that a higher expression of SPP1 was found to be related to worse clinical outcome in six cancer types. SPP1 expression was higher in hypoxia-high macrophages based on single-cell data, which was further validated by an in vitro experiment that SPP1 was upregulated in macrophages under hypoxia-cultured compared with normoxic conditions. Additionally, a differential analysis demonstrated that hypoxia potentially influences extracellular matrix remodeling, glycolysis, and interleukin-10 signal activation in various cancer types. Our work illuminates the clearer underlying mechanism in the intricate interaction between different cell subtypes within hypoxia TME and proposes the guidelines for the development of therapeutic targets specifically for patients with high proportion of SPP1+ TAMs in hypoxic lesions.

Significance of intratumoral infiltration of B cells in cancer immunotherapy: From a single cell perspective

Immunotherapy for cancer has provided new treatment approaches for malignant tumors, but there are low rates of response and high rates of resistance. The most recent sequencing method which is called single-cell RNA sequencing(scRNA-seq) determines the transcriptome at the single cell level, which allows high-resolution dynamic monitoring of the tumor microenvironment (TME) during immunotherapy. As an important part of humoral immunity, tumor-infiltrated B cells have been reported to have distinct functions in anti-tumor immunity, which are characterized by their RNA transcriptome, membrane surface receptors, and immunoglobulin secretion, suggesting great immunotherapeutic effects. On the basis of the important roles of B cells in immunotherapy reported in recent publications, we discuss the tumor-infiltrated B cells' subpopulations, differentiation trajectory, and interactions with other cells in the TME in this review, hoping to illustrate its significance in potential clinical application as biomarkers and therapeutic targets.

Precision diagnostics: Integration of tissue pathology and genomics in cancer

Traditionally, cancer diagnosis and management has been reactionary in that symptoms lead to investigations, then a diagnosis is followed by clinical management. This process is heavily dependent on tissue diagnosis mainly by histopathology and to a lesser extent, cytopathology. However, in recent times there has been a shift towards precision medicine to enable prevention, prediction and personalisation in healthcare. The core of precision medicine is optimising therapeutic benefit for patients, by using genomic and molecular profiling, analogously termed precision pathology. This review explores (1) the evolution of pathology from a para-clinical discipline to a mainstream medical field integral to oncology tumour boards; (2) its critical role in preventative, diagnostic, therapeutic and follow-up cancer care; (3) the future of tissue pathology in the era of precision oncology; and (4) how pathologists may evolve to future-proof their profession.

Mitogen-activated protein kinase activity drives cell trajectories in colorectal cancer

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define transcriptional states of colorectal cancer cells and signals controlling their development by performing single-cell transcriptome analysis of tumors and matched non-cancerous tissues of twelve colorectal cancer patients. We defined patient-overarching colorectal cancer cell clusters characterized by differential activities of oncogenic signaling pathways such as mitogen-activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient-derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen-activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR-BRAF-MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories. Our results highlight directional cancer cell development as a driver of non-genetic cancer cell heterogeneity and re-routing of trajectories as a response to targeted therapy.

Microdissection of the Bulk Transcriptome at Single-Cell Resolution Reveals Clinical Significance and Myeloid Cells Heterogeneity in Lung Adenocarcinoma

Background

Tumor infiltrating myeloid (TIM) cells constitute a vital element of the tumor microenvironment. The cell-type heterogeneity of TIM has yet to be fully investigated.

Methods

We used a time saving approach to generate a single-cell reference matrix, allowing quantification of cell-type proportions and cell-type-specific gene abundances in bulk RNA-seq data.

Results

Two distinct clusters, MSC1 and MSC2 (MSC subtype) were newly identified in lung adenocarcinoma (LUAD) patients, both significantly associated with overall survival and immune blockade therapy responses. Twenty myeloid cell types were detected. Thirteen of these had distinct enrichment patterns between MSC1 and MSC2. LAMP3+ dendritic cells, being a mature and transportable subtype of dendritic cell that may migrate to lymph nodes, were noted as associated with non-responsiveness to immunotargeted therapy. High infiltration level of IFIT3+ neutrophils was strongly related to the response to immune-targeted therapy and was seen to activate CD8+ T cells, partly through inflammasome activation. The infiltration levels of TIMP1+ macrophages and S100A8+ neutrophils were both significantly associated with poor prognosis. TIMP1+ macrophages were noted to recruit S100A8+ neutrophils via the CXCL5-CXCR2 axes and promote LUAD progression.

Conclusion

Altogether, we performed virtual microdissection of the bulk transcriptome at single-cell resolution and provided a promising TIM infiltration landscape that may shed new light on the development of immune therapy.

Label-free enrichment of rare unconventional circulating neoplastic cells using a microfluidic dielectrophoretic sorting device

Cellular circulating biomarkers from the primary tumor such as circulating tumor cells (CTCs) and circulating hybrid cells (CHCs) have been described to harbor tumor-like phenotype and genotype. CHCs are present in higher numbers than CTCs supporting their translational potential. Methods for isolation of CHCs do not exist and are restricted to low-throughput, time consuming, and biased methodologies. We report the development of a label-free dielectrophoretic microfluidic platform facilitating enrichment of CHCs in a high-throughput and rapid fashion by depleting healthy peripheral blood mononuclear cells (PBMCs). We demonstrated up to 96.5% depletion of PBMCs resulting in 18.6-fold enrichment of cancer cells. In PBMCs from pancreatic adenocarcinoma patients, the platform enriched neoplastic cells identified by their KRAS mutant status using droplet digital PCR with one hour of processing. Enrichment was achieved in 75% of the clinical samples analyzed, establishing this approach as a promising way to non-invasively analyze tumor cells from patients.

A single-cell tumor immune atlas for precision oncology

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

Overexpression of transposable elements is associated with immune evasion and poor outcome in colorectal cancer

AIM

High immune cell infiltration of the tumour microenvironment is generally associated with a good prognosis in solid cancers. However, a subset of patients with colorectal cancer (CRC) tumours with high immune cell infiltration have a poor outcome. These tumours have a high level of T cell infiltration and are also characterised by increased expression of programmed death-ligand 1 (PD-L1). As these tumours comprise both microsatellite instability and microsatellite stable subtypes, the mechanism underlying this phenotype is unknown.

METHODS

Using RNA-seq data from The Cancer Genome Atlas, we quantified transposable element (TE) expression and developed a TE expression score that is predictive of prognosis and immune infiltration independent of microsatellite instability status and tumour staging in CRC.

RESULTS

Tumours with the highest TE expression score showed increased immune cell infiltration with upregulation of interferon (IFN) signalling pathways and downstream activation of IFN-simulated genes. As expected, cell lines treated with DNA methyltransferase inhibitor mimicked patient tumours with increased TE expression and IFN signalling. However, surprisingly, unlike high TE expressing CRC, there is little evidence for the activation of JAK-STAT signalling and PD-L1 expression in DNA methyltransferase inhibitor-treated cells. Single-cell RNA-seq analysis of CRC samples showed that PD-L1 expression is mainly confined to tumour-associated macrophages and T cells, suggesting that TE mediated IFN signalling is triggering expression of PD-L1 in immune cells rather than in tumour cells.

CONCLUSIONS

Our study uncovers a novel mechanism of TE driven immune evasion and highlights TE expression as an important factor for patient prognosis in CRC.

Immunotherapy in rare ovarian cancer

PURPOSE OF REVIEW

Ovarian cancer (OC) is a heterogeneous disease and a mounting body of evidence shows that a 'one-size-fits-all' approach is obsolete. Differences in epidemiology, tumor biology, genetic profiles and treatment responses of these different types necessitate a tumor and patient-specific approach. Ninety percentage consists of epithelial OC with 70% being high-grade serous OC. The other rarer subtypes are low-grade serous (5%), clear cell (12%), endometrioid (11%) and mucinous carcinoma (3%). The remaining 10% are nonepithelial rare OCs: germ cell (3%) and sex-cord stromal tumors (7%).

RECENT FINDINGS

Over the past few decades, the 5-year survival rates have only improved modestly, therefore novel therapies are urgently needed. Recently, immunotherapy has been introduced into clinical practice in a number of solid tumors. Although preclinical data confirm the presence of an immunogenic microenvironment in a number of ovarian tumor types, no single-agent immune checkpoint inhibitor has been approved hitherto. Identifying suitable treatment combinations, adequate patient selection and thus correct implementation of immunotherapy remain major challenges.

SUMMARY

In this review, we focus on the rationale of incorporating immune therapy in rare OC, we summarize the recent developments with preclinical data and results of clinical trials, with particular focus on rare ovarian histological subtypes.

In Vitro Anticancer Drug Sensitivity Sensing through Single-Cell Raman Spectroscopy

Traditional in vitro anticancer drug sensitivity testing at the population level suffers from lengthy procedures and high false positive rates. To overcome these defects, we built a confocal Raman microscopy sensing system and proposed a single-cell approach via Raman-deuterium isotope probing (Raman-DIP) as a rapid and reliable in vitro drug efficacy evaluation method. Raman-DIP detected the incorporation of deuterium into the cell, which correlated with the metabolic activity of the cell. The human non-small cell lung cancer cell line HCC827 and human breast cancer cell line MCF-7 were tested against eight different anticancer drugs. The metabolic activity of cancer cells could be detected as early as 12 h, independent of cell growth. Incubation of cells in 30% heavy water (D₂O) did not show any negative effect on cell viability. Compared with traditional methods, Raman-DIP could accurately determine the drug effect, meanwhile, it could reduce the testing period from 72–144 h to 48 h. Moreover, the heterogeneity of cells responding to anticancer drugs was observed at the single-cell level. This proof-of-concept study demonstrated the potential of Raman-DIP to be a reliable tool for cancer drug discovery and drug susceptibility testing.

CXCR6 positions cytotoxic T cells to receive critical survival signals in the tumor microenvironment

Cytotoxic T lymphocyte (CTL) responses against tumors are maintained by stem-like memory cells that self-renew but also give rise to effector-like cells. The latter gradually lose their anti-tumor activity and acquire an epigenetically fixed, hypofunctional state, leading to tumor tolerance. Here, we show that the conversion of stem-like into effector-like CTLs involves a major chemotactic reprogramming that includes the upregulation of chemokine receptor CXCR6. This receptor positions effector-like CTLs in a discrete perivascular niche of the tumor stroma that is densely occupied by CCR7+ dendritic cells (DCs) expressing the CXCR6 ligand CXCL16. CCR7+ DCs also express and trans-present the survival cytokine interleukin-15 (IL-15). CXCR6 expression and IL-15 trans-presentation are critical for the survival and local expansion of effector-like CTLs in the tumor microenvironment to maximize their anti-tumor activity before progressing to irreversible dysfunction. These observations reveal a cellular and molecular checkpoint that determines the magnitude and outcome of anti-tumor immune responses.

Examining heterogeneity of stromal cells in tumor microenvironment based on pan-cancer single-cell RNA sequencing data

Tumor tissues contain both tumor and non-tumor cells, which include infiltrated immune cells and stromal cells, collectively called the tumor microenvironment (TME). Single-cell RNA sequencing (scRNAseq) enables the examination of heterogeneity of tumor cells and TME. In this review, we examined scRNAseq datasets for multiple cancer types and evaluated the heterogeneity of major cell type composition in different cancer types. We further showed that endothelial cells and fibroblasts/myofibroblasts in different cancer types can be classified into common subtypes, and the subtype composition is clearly associated with cancer characteristic and therapy response.

A Transcriptionally Distinct Subpopulation of Healthy Acinar Cells Exhibit Features of Pancreatic Progenitors and PDAC

Pancreatic ductal adenocarcinoma (PDAC) tumors can originate either from acinar or ductal cells in the adult pancreas. We re-analyze multiple pancreas and PDAC single-cell RNA-seq datasets and find a subset of nonmalignant acinar cells, which we refer to as acinar edge (AE) cells, whose transcriptomes highly diverge from a typical acinar cell in each dataset. Genes upregulated among AE cells are enriched for transcriptomic signatures of pancreatic progenitors, acinar dedifferentiation, and several oncogenic programs. AE-upregulated genes are upregulated in human PDAC tumors, and consistently, their promoters are hypomethylated. High expression of these genes is associated with poor patient survival. The fraction of AE-like cells increases with age in healthy pancreatic tissue, which is not explained by clonal mutations, thus pointing to a nongenetic source of variation. The fraction of AE-like cells is also significantly higher in human pancreatitis samples. Finally, we find edge-like states in lung, liver, prostate, and colon tissues, suggesting that subpopulations of healthy cells across tissues can exist in pre-neoplastic states. SIGNIFICANCE: These findings show "edge" epithelial cell states with oncogenic transcriptional activity in human organs without oncogenic mutations. In the pancreas, the fraction of acinar cells increases with age.