Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Single-cell and spatial transcriptomics reveals the key role of MCAM+ tip-like endothelial cells in osteosarcoma metastasis

Osteosarcoma, the most common primary malignant bone tumor in children and adolescents, is highly aggressive and prone to metastasis. Endothelial cells (ECs) are involved in angiogenesis and play a key role in promoting the metastasis of tumor. However, research on tip-like ECs within osteosarcoma was extremely rare. In this study, a single-cell atlas of ECs was constructed using single-cell transcriptomic data. It was found that tip-like ECs were abundant in the primary tumors and metastatic foci. Gene sets score analysis indicated their enrichment in pathways associated with angiogenesis and metastasis. What's more, MCAM was highly expressed in tip-like ECs and was likely to promote the metastasis of osteosarcoma. MCAM was also found to be highly expressed in the ECs of metastatic lymph nodes when compared to normal lymph node samples. Meanwhile, spatial transcriptomics data confirmed the presence of MCAM-positive ECs in metastatic lymph node, closely localized to osteoblasts. In vitro assays, including qRT-PCR, tube formation, and immunofluorescence, validated the role of the MCAM gene in promoting angiogenesis. In conclusion, tip-like ECs may promote tumor metastasis by enhancing angiogenesis. MCAM was a functional gene for tip-like ECs and could serve as a target for the treatment of osteosarcoma.

A single-cell atlas of bladder cancer unveils dynamic cellular composition and endothelial functional shifts during progression

PURPOSE

Bladder cancer (BC) is characterized by high heterogeneity, with non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) stages differing significantly in clinical behavior and outcomes. The transition from NMIBC to MIBC involves extensive tumor microenvironment (TME) remodeling, particularly in endothelial cells (ECs), which drive angiogenesis and modulate immune and extracellular matrix (ECM) interactions. However, the precise roles of ECs in this progression remain poorly defined.

METHODS

Public single-cell RNA sequencing (scRNA-seq) datasets from 47 BC patients were analyzed to characterize endothelial cell heterogeneity and functional states across NMIBC and MIBC. Computational tools such as CellChat were applied to reconstruct cell-cell communication networks, focusing on pathways related to angiogenesis, immune crosstalk, and ECM remodeling.

RESULTS

Twelve major cell types were identified, with endothelial cells exhibiting distinct transcriptional profiles between NMIBC and MIBC. NMIBC-associated ECs promoted adhesion and migration through HMGB1 and CXCL12 signaling. In contrast, MIBC was enriched in an ADAM10+ endothelial subset associated with vascular remodeling and activation of Wnt signaling via CTNNB1. Key ligand-receptor interactions highlighted the dynamic roles of ECs in TME modulation during BC progression.

CONCLUSIONS

This study reveals stage-specific endothelial cell phenotypes and signaling networks in BC. The identification of an MIBC-specific ADAM10+ endothelial subset underscores its potential role in driving tumor progression and highlights opportunities for stage-adapted vascular-targeted therapies. These findings advance our understanding of BC pathogenesis and provide the foundation for novel therapeutic strategies.

Mitigating ambient RNA and doublets effects on single cell transcriptomics analysis in cancer research

In cancer biology, where understanding the tumor microenvironment at high resolution is vital, ambient RNA contamination becomes a considerable problem. This hinders accurate delineation of intratumoral heterogeneity, complicates the identification of potential biomarkers, and decelerates advancements in precision oncology. To solve this problem, several computational approaches are created to determine the ambient RNA contribution from scRNA-seq datasets. Techniques like SoupX and DecontX assist in assessing and eliminating ambient RNA contamination from primary gene expression profiles. Practical solutions like CellBender employ deep learning techniques to concurrently address ambient RNA contamination and background noise, offering a contemporary end-to-end strategy for data preparation. This high-quality, reliable data enables clinicians and researchers to make effective decisions that will help ensure interventions are rooted in reproducible evidence, giving hope for developing more effective targeted therapies.

Role of Radiomics-based Multiomics Panel in the Microenvironment and Prognosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent form of liver tumor, characterized by restricted therapeutic options and typically low long-term survival rates. Recently, immunotherapy has revolutionized HCC treatment, making the tumor microenvironment (TME) a research focus. Radiomics is increasingly crucial in HCC clinical decisions, offering advanced tools for TME characterization and prognosis assessment. Meanwhile, advancements in pathomics provide new insights into HCC's comprehensive traits and details. Advancements in genomics and transcriptomics enable the integration of radiomics and pathomics with genetic data to better understand HCC heterogeneity and its microenvironment, aiding prognostic assessments. This review provides a comprehensive overview of pivotal radiomics studies focused on TME prediction, underscoring the synergistic effects of integrating multiomics approaches for TME analysis and HCC outcome prediction. It critically examines the challenges and opportunities inherent in multiomics research, emphasizing its substantial significance in both research and clinical contexts.

Embryonic reprogramming of the tumor vasculature reveals targets for cancer therapy

A sustained blood supply is critical for tumor growth, as it delivers the nutrients and oxygen required for development. Targeting of blood vessel formation via immunotherapies is an area of great importance. Knowing that certain embryonic genes, such as carcinoembryonic antigens (CEA) and oncofetal fibronectin, become reexpressed in malignant transformation, we hypothesized that a similar phenomenon holds true for tumor endothelial cells (TECs) as well. An approach for identification of highly selective tumor endothelial markers was conducted to develop targeted antiangiogenic immunotherapies. We first queried the transcriptome that is present during embryo development. We then performed a systematic search for genes selectively expressed in the mouse embryo at days E11 and E18, as compared to the transcriptome of the adult mouse. Subsequently, we queried for expression of these embryonic genes in sorted murine TECs. This approach identified among others the tumor endothelial antigens fibrillin-2 (Fbn2), elastin microfibril interface-located protein 2 (Emilin2) as well as the tumor endothelial antigens lysyl oxidase (Lox) and serine/cysteine protease inhibitor, clade E, member 1 (Serpine1; Pai-1). For these selected genes, functional involvement in angiogenesis was confirmed in in vitro bioassays. We subsequently used iBoost conjugate vaccine technology to develop vaccines against the selected targets. For all four targets, vaccination readily induced target-specific antibody responses in mice, resulting in inhibition of tumor growth. Access to highly specific tumor endothelial markers provides opportunities for direct targeting of the tumor vasculature with high specificity, without affecting healthy vasculature.

Dissecting endothelial cell heterogeneity with new tools

The formation of a blood vessel network is crucial for organ development and regeneration. Over the past three decades, the central molecular mechanisms governing blood vessel growth have been extensively studied. Recent evidence indicates that vascular endothelial cells-the specialized cells lining the inner surface of blood vessels-exhibit significant heterogeneity to meet the specific needs of different organs. This review focuses on the current understanding of endothelial cell heterogeneity, which includes both intra-organ and inter-organ heterogeneity. Intra-organ heterogeneity encompasses arterio-venous and tip-stalk endothelial cell specialization, while inter-organ heterogeneity refers to organ-specific transcriptomic profiles and functions. Advances in single-cell RNA sequencing (scRNA-seq) have enabled the identification of new endothelial subpopulations and the comparison of gene expression patterns across different subsets of endothelial cells. Integrating scRNA-seq with other high-throughput sequencing technologies promises to deepen our understanding of endothelial cell heterogeneity at the epigenetic level and in a spatially resolved context. To further explore human endothelial cell heterogeneity, vascular organoids offer powerful tools for studying gene function in three-dimensional culture systems and for investigating endothelial-tissue interactions using human cells. Developing organ-specific vascular organoids presents unique opportunities to unravel inter-organ endothelial cell heterogeneity and its implications for human disease. Emerging technologies, such as scRNA-seq and vascular organoids, are poised to transform our understanding of endothelial cell heterogeneity and pave the way for innovative therapeutic strategies to address human vascular diseases.

Endothelial-like cancer-associated fibroblasts facilitate pancreatic cancer metastasis via vasculogenic mimicry and paracrine signalling

BACKGROUND

Cancer-associated fibroblasts (CAFs) are highly heterogeneous in the progression of pancreatic ductal adenocarcinoma (PDAC) and vasculogenic mimicry (VM) refers to a phenomenon in which cancer cells adopt endothelial-like characteristics.

OBJECTIVE

To identify a novel protumoural CAF subtype undertaking VM.

DESIGN

We used single-cell RNA sequencing and mIHC to identify FAPα+CD144+ endothelial-like CAFs (endoCAFs) and combined prospective and retrospective analyses to assess its clinical outcomes. Tube formation, proliferation and invasion assay were conducted on cell lines, organoids, the orthotopic tumour model and LSL-KrasG12D/+, LSL-Trp53R172H/+ and Pdx1-Cre (KPC) mouse model. Mechanically, we performed cytokine array assays, RNA-sequencing, IP-mass spectrometry, ChIP and luciferase analyses. Importantly, an siRNA delivery nanosystem was developed to precisely target FAPα+CD144+endoCAFs in vivo.

RESULTS

FAPα+CD144+endoCAFs were present in the tumour microenvironment of PDAC, and patients with a higher CD144+CAFs proportion displayed poor prognosis of PDAC. FAPα+CD144+endoCAFs not only acquired a VM phenotype to provide metastatic conduits but also promoted the proliferation and invasion of tumour cells in situ through paracrine signalling, thereby actively facilitating the metastasis of tumour cells. The CD144-β-catenin-STAT3 signalling axis was activated, and CD144 and downstream secreted cytokines were transcriptionally upregulated to maintain the dual roles of endoCAFs. A CAF-targeting siRNA delivery nanosystem, via loading FAPα and siCD144, was administered to precisely target FAPα+CD144+ endoCAFs, which substantially inhibited their protumoural roles in vivo.

CONCLUSION

FAPα+CD144+endoCAFs can promote metastasis of PDAC via undertaking VM and paracrine through activation of the CD144-β-catenin-STAT3 signalling axis. CAF-targeting siRNA delivery nanosystem can inhibit tumour progression by precisely targeting FAPα+CD144+endoCAFs.

Immune-featured stromal niches associate with response to neoadjuvant immunotherapy in oral squamous cell carcinoma

Tumor stromal cells (TSCs) play a crucial yet underexplored role in the tumor microenvironment (TME). This study uses single-cell sequencing and spatial transcriptomics on paired tumor specimens from 22 patients with oral squamous cell carcinoma (OSCC) enrolled in a randomized two-arm phase 2 trial, receiving neoadjuvant anti-PD-1 mono-immunotherapy or anti-PD-1 plus docetaxel-cisplatin-5-fluorouracil (TPF) immunochemotherapy. Single-cell analysis reveals increased TSCs within the TME of responders in immunochemotherapy. Notably, significant post-treatment upregulation of SELP+ high endothelial venules (HEVs) and APOD+ myofibroblastic cancer-associated fibroblasts (myCAFs), alongside a decline in STMN1+ capillary endothelial cells (cECs), is specific to the immunochemotherapy cohort. In contrast, MYF5+ muscle satellite cells (MSCs) are upregulated in non-responders to mono-immunotherapy. SELP+ HEVs and APOD+ myCAFs foster favorable immunomodulatory stromal niches for improved outcomes, while STMN1+ cECs and MYF5+ MSCs form immunosuppressive niches in tumor invasion regions, highlighting therapeutic targets. The trial was registered at ClinicalTrials.gov, and the registration number is NCT04649476.

Cross-Talk Between Cancer and Its Cellular Environment-A Role in Cancer Progression

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective

The development of single-cell and spatial transcriptomics has revolutionized our capacity to investigate cellular properties, functions, and interactions in both cellular and spatial contexts. Despite this progress, the analysis of single-cell and spatial omics data remains challenging. First, single-cell sequencing data are high-dimensional and sparse, and are often contaminated by noise and uncertainty, obscuring the underlying biological signal. Second, these data often encompass multiple modalities, including gene expression, epigenetic modifications, metabolite levels, and spatial locations. Integrating these diverse data modalities is crucial for enhancing prediction accuracy and biological interpretability. Third, while the scale of single-cell sequencing has expanded to millions of cells, high-quality annotated datasets are still limited. Fourth, the complex correlations of biological tissues make it difficult to accurately reconstruct cellular states and spatial contexts. Traditional feature engineering approaches struggle with the complexity of biological networks, while deep learning, with its ability to handle high-dimensional data and automatically identify meaningful patterns, has shown great promise in overcoming these challenges. Besides systematically reviewing the strengths and weaknesses of advanced deep learning methods, we have curated 21 datasets from nine benchmarks to evaluate the performance of 58 computational methods. Our analysis reveals that model performance can vary significantly across different benchmark datasets and evaluation metrics, providing a useful perspective for selecting the most appropriate approach based on a specific application scenario. We highlight three key areas for future development, offering valuable insights into how deep learning can be effectively applied to transcriptomic data analysis in biological, medical, and clinical settings.

Single-Cell RNA Sequencing Reveals the Tumor Heterogeneity and Immunosuppressive Microenvironment in Urothelial Carcinoma

Urothelial carcinoma (UC) can arise from either the lower urinary tract or the upper tract; they represent different disease entities and require different clinical treatment strategies. A full understanding of the cellular characteristics in UC may guide the development of novel therapies. Here, we performed single-cell transcriptome analysis from four patients with UC of the bladder (UCB), five patients with UC of the ureter (UCU), and four patients with UC of the renal pelvis (UCRP) to develop a comprehensive cell atlas of UC. We found the rare epithelial cell subtype EP9 with epithelial-to-mesenchymal transition (EMT) and cancer stem cell (CSC) features, and specifically expressed SOX6, which was associated with poor prognosis. We also found that ACKR1+ endothelial cells and inflammatory cancer-associated fibroblasts (iCAFs) were more enriched in UCU, which may promote pathogenesis. While ESM1+ endothelial cells may more actively participate in UCB and UCRP tumorigenesis by promoting angiogenesis. Additionally, CD8 + effector T cells were more enriched in UCU and UCRP patients, while Tregs were mainly enriched in UCB tumors. C1QC+ macrophages and LAMP3+ dendritic cells were more enriched in UCB, which is closely related to the formation of the heterogeneous immunosuppressive microenvironment. Furthermore, we found strong interactions between iCAFs, EP9, and Endo_ESM1, and different degrees of activation of the FGF-FGFR3 axis and immune checkpoint pathway were observed in different UC subtypes. Our study elucidated the cellular heterogeneity and the components of the microenvironment in UC arising from the upper and lower urinary tracts and provided novel therapeutic targets.

Automated Laser-Assisted Single-Cell Sorting for Cell Functional and RNA Sequencing

Accurate and efficient sorting of single target cells is crucial for downstream single-cell analysis, such as RNA sequencing, to uncover cellular heterogeneity and functional characteristics. However, conventional single-cell sorting techniques, such as manual micromanipulation or fluorescence-activated cell sorting, do not match current demands and are limited by low throughput, low sorting efficiency and precision, or limited cell viability. Here, we report an automated, highly efficient single-cell sorter, integrating laser-induced forward transfer (LIFT) with a high-throughput picoliter micropore array. The micropore array was surface-functionalized to manipulate liquid surface tension, facilitating the formation of single-cell picoliter droplets in the micropores to realize automated and highly efficient (>80%) single-cell isolation. Using an in-house built microscopic system, rare target cells were identified and automatically retrieved by LIFT with precise sorting efficiency (about 100%) for downstream single-cell analysis while maintaining high cell viability (about 80%). As a case demonstration, we demonstrated the accurate sorting of rare transfected PC-9 cells and post-transfection cell culture, minimizing cell loss and the risk of contamination. Furthermore, we performed single-cell RNA sequencing and showed that high-quality single-cell transcriptome information was efficiently and reliably obtained during cell sorting, preventing additional costs due to low sorting accuracy. The single-cell sorter will become invaluable for single-cell analysis, laying the foundation for multiomics analysis and precision medicine research.

An endothelial SOX18-mevalonate pathway axis enables repurposing of statins for infantile hemangioma

Infantile hemangioma (IH) is the most common tumor in children and a paradigm for pathological vasculogenesis, angiogenesis, and regression. Propranolol, the mainstay of treatment, inhibits IH vessel formation via a β-adrenergic receptor-independent off-target effect of its R(+) enantiomer on endothelial SOX18 - a member of the SOX (SRY-related HMG-box) family of transcription factors. Transcriptomic profiling of patient-derived hemangioma stem cells uncovered the mevalonate pathway (MVP) as a target of R(+) propranolol. Loss and gain of function of SOX18 confirmed it is both necessary and sufficient for R(+) propranolol suppression of the MVP, including regulation of sterol regulatory element-binding protein 2 (SREBP2) and the rate-limiting enzyme HMG-CoA reductase (HMGCR). A biological relevance of the endothelial SOX18-MVP axis in IH patient tissue was demonstrated by nuclear colocalization of SOX18 and SREBP2. Functional validation in a preclinical IH xenograft model revealed that statins - competitive inhibitors of HMGCR - efficiently suppress IH vessel formation. We propose an endothelial SOX18-MVP axis as a central regulator of IH pathogenesis and suggest statin repurposing to treat IH. The pleiotropic effects of R(+) propranolol and statins along the SOX18-MVP axis to disable an endothelial cell-specific program may have therapeutic implications for other vascular disease entities involving pathological vasculogenesis and angiogenesis.

SELP+ TEC:CD8+ T cell crosstalk associates with improved radiotherapy efficacy in cervical cancer

P-selectin (SELP) expression in tumor cells has been implicated in promoting tumor progression and treatment resistance across various cancers. However, our prior study identified SELP expression in a specific subpopulation of endothelial cells within cervical cancer (CC) and potentially linked to anti-cancer immune response. The precise mechanisms by which SELP influences anti-cancer immunity and its involvement in radiotherapy response in CC, however, remain elusive. To address these gaps, this study analyzed tumor tissue samples from 205 CC patients undergoing radiotherapy, scRNA-seq data from 42,159 cells of eight patients, and bulk RNA-sequencing data from 187 radiotherapy-treated patients. The results revealed that elevated SELP expression in tumor endothelial cells (TECs) was significantly correlated with improved survival outcomes in patients treated with radiotherapy. The SELPhigh group exhibited a prominent enrichment of immune-related pathways, coupled with a diminished enrichment in epithelial cell proliferation and angiogenesis pathways. Notably, this group demonstrated increased infiltration of CD8+ T cells and enhanced expression of chemokine receptors, including ACKR1. Furthermore, our data suggest that SELP+ TECs engage in crosstalk with CD8+ T cells via the ACKR1-CCL5 axis, which is associated with improved radiotherapy efficacy. In conclusion, these findings underscore the pivotal role of SELP+ TEC:CD8+ T cell interactions through the ACKR1-CCL5 pathway in enhancing radiotherapy response in CC. Targeting this crosstalk may offer novel therapeutic strategies to mitigate treatment resistance and improve patient survival.

Isolation of Biomolecules Using MXenes

Biomolecule isolation is a crucial process in diverse biomedical and biochemical applications, including diagnostics, therapeutics, research, and manufacturing. Recently, MXenes, a novel class of two-dimensional nanomaterials, have emerged as promising adsorbents for this purpose due to their unique physicochemical properties. These biocompatible and antibacterial nanomaterials feature a high aspect ratio, excellent conductivity, and versatile surface chemistry. This timely review explores the potential of MXenes for isolating a wide range of biomolecules, such as proteins, nucleic acids, and small molecules, while highlighting key future research trends and innovative applications poised to transform the field. This review provides an in-depth discussion of various synthesis methods and functionalization techniques that enhance the specificity and efficiency of MXenes in biomolecule isolation. In addition, the mechanisms by which MXenes interact with biomolecules are elucidated, offering insights into their selective adsorption and customized separation capabilities. This review also addresses recent advancements, identifies existing challenges, and examines emerging trends that may drive the next wave of innovation in this rapidly evolving area.

Advancements in programmed cell death research in antitumor therapy: a comprehensive overview

Cell death is a normal physiological process within cells that involves multiple pathways, such as normal DNA damage, cell cycle arrest, and programmed cell death (PCD). Cell death has been a hot spot of research in tumor-related fields, especially programmed cell death, which is a key form of cell death and is classified into different types according to the mechanism of occurrence, such as apoptosis, autophagy, necroptosis, pyroptosis, ferroptosis, and disulfidptosis. Given the important role of PCD in maintaining tissue homeostasis and inhibiting tumorigenesis and development, more and more basic and clinical studies are devoted to revealing its potential application in anti-tumor strategies. The purpose of this review is to systematically review the regulatory mechanisms of PCD and to summarize the latest research progress of anti-tumor treatment strategies based on PCD.

Single-cell RNA sequencing and spatial transcriptomics of esophageal squamous cell carcinoma with lymph node metastases

Esophageal squamous cell carcinoma (ESCC) patients often face a grim prognosis due to lymph node metastasis. However, a comprehensive understanding of the cellular and molecular characteristics of metastatic lymph nodes in ESCC remains elusive. In this study involving 12 metastatic ESCC patients, we employed single-cell sequencing, spatial transcriptomics (ST), and multiplex immunohistochemistry (mIHC) to explore the spatial and molecular attributes of primary tumor samples, adjacent tissues, metastatic and non-metastatic lymph nodes. The analysis of 161,333 cells revealed specific subclusters of epithelial cells that were significantly enriched in metastatic lymph nodes, suggesting pro-metastatic characteristics. Furthermore, stromal cells in the tumor microenvironment, including MMP3+IL24+ fibroblasts, APLN+ endothelial cells, and CXCL12+ pericytes, were implicated in ESCC metastasis through angiogenesis, collagen production, and inflammatory responses. Exhausted CD8+ T cells in a cycling status were notably prevalent in metastatic lymph nodes, indicating their potential role in facilitating metastasis. We identified distinct cell-cell communication networks and specific ligand-receptor pathways. Our findings were validated through a spatial transcriptome map and mIHC. This study enhances our comprehension of the cellular and molecular aspects of metastatic lymph nodes in ESCC patients, offering potential insights into novel therapeutic strategies for these individuals.

A deconvolution framework that uses single-cell sequencing plus a small benchmark data set for accurate analysis of cell type ratios in complex tissue samples

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we utilize an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using this well-matched, that is, benchmark, data. Built upon a novel weighted nonnegative least-squares framework, DeMixSC identifies and adjusts genes with high technological discrepancy and aligns the benchmark data with large patient cohorts of matched-tissue-type for large-scale deconvolution. Our results using two benchmark data sets of healthy retinas and ovarian cancer tissues suggest much-improved deconvolution accuracy. Leveraging tissue-specific benchmark data sets, we applied DeMixSC to a large cohort of 453 age-related macular degeneration patients and a cohort of 30 ovarian cancer patients with various responses to neoadjuvant chemotherapy. Only DeMixSC successfully unveiled biologically meaningful differences across patient groups, demonstrating its broad applicability in diverse real-world clinical scenarios. Our findings reveal the impact of technological discrepancy on deconvolution performance and underscore the importance of a well-matched data set to resolve this challenge. The developed DeMixSC framework is generally applicable for accurately deconvolving large cohorts of disease tissues, including cancers, when a well-matched benchmark data set is available.

Weakly Supervised Nuclei Segmentation with Point-Guided Attention and Self-Supervised Pseudo-Labeling

Due to the labor-intensive manual annotations for nuclei segmentation, point-supervised segmentation based on nuclei coordinate supervision has gained recognition in recent years. Despite great progress, two challenges hinder the performance of weakly supervised nuclei segmentation methods: (1) The stable and effective segmentation of adjacent cell nuclei remains an unresolved challenge. (2) Existing approaches rely solely on initial pseudo-labels generated from point annotations for training, and inaccurate labels may lead the model to assimilate a considerable amount of noise information, thereby diminishing performance. To address these issues, we propose a method based on center-point prediction and pseudo-label updating for precise nuclei segmentation. First, we devise a Gaussian kernel mechanism that employs multi-scale Gaussian masks for multi-branch center-point prediction. The generated center points are utilized by the segmentation module to facilitate the effective separation of adjacent nuclei. Next, we introduce a point-guided attention mechanism that concentrates the segmentation module's attention around authentic point labels, reducing the noise impact caused by pseudo-labels. Finally, a label updating mechanism based on the exponential moving average (EMA) and k-means clustering is introduced to enhance the quality of pseudo-labels. The experimental results on three public datasets demonstrate that our approach has achieved state-of-the-art performance across multiple metrics. This method can significantly reduce annotation costs and reliance on clinical experts, facilitating large-scale dataset training and promoting the adoption of automated analysis in clinical applications.

Single-cell transcriptome analysis reveals reciprocal epithelial and endothelial cell evolution in ovarian cancer

Tumor neovascularization mediated by endothelial cells (ECs) is essential for ovarian cancer (OC) progression, but interactions between epithelial cells and ECs are not well understood. Here, we analyze single-cell transcriptome of 87,847 epithelial cells and 11,696 ECs from fallopian tubes, primary and metastatic ovarian tumors. Cell differentiation trajectory analysis reveals that fallopian tube cells exhibit a potential development trend toward primary OC epithelial cells. We identify a sub-population of fallopian tube epithelial cells (FTSEC3), which highly express tumor cell markers and are enriched in vascular endothelial growth factor production. Two neovascularization-related EC phenotypes (MKI67+ proliferating ECs and ESM1+ tip cells) are specially found in ovarium tumors, which exhibit strong interactions with FTSEC3. We validate that genetic disruption of LAMININ and TGF-β with CRISPR in ECs inhibits sprouting angiogenesis. In summary, this study reveals a reciprocal evolution and interaction between epithelial and ECs in OC development and progression.

Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy

A comprehensive understanding of tumor heterogeneity, tumor microenvironment and the mechanisms of drug resistance is fundamental to advancing breast cancer research. While single-cell RNA sequencing has resolved the issue of "temporal dynamic expression" of genes at the single-cell level, the lack of spatial information still prevents us from gaining a comprehensive understanding of breast cancer. The introduction and application of spatial transcriptomics addresses this limitation. As the annual technical method of 2020, spatial transcriptomics preserves the spatial location of tissues and resolves RNA-seq data to help localize and differentiate the active expression of functional genes within a specific tissue region, enabling the study of spatial location attributes of gene locations and cellular tissue environments. In the context of breast cancer, spatial transcriptomics can assist in the identification of novel breast cancer subtypes and spatially discriminative features that show promise for individualized precise treatment. This article summarized the key technical approaches, recent advances in spatial transcriptomics and its applications in breast cancer, and discusses the limitations of current spatial transcriptomics methods and the prospects for future development, with a view to advancing the application of this technology in clinical practice.

CD34+CLDN5+ tumor associated senescent endothelial cells through IGF2-IGF2R signaling increased cholangiocellular phenotype in hepatocellular carcinoma

INTRODUCTION

The heterogeneity of hepatocellular carcinoma (HCC) is linked to tumor malignancy and poor prognosis. Nevertheless, the precise mechanisms underlying the development of the cholangiocellular phenotype (CCA) within HCC remain unclear. Emerging studies support that the cross-talk among the host cells within tumor microenvironment (TME) sustains the cancer cell plasticity.

OBJECTIVES

This study sought to identify the specific cell types involved in the formation of CCA and to elucidate their functional roles in the progression of HCC.

METHODS

Single-cell RNA sequencing was employed to identify the specific cell types involved in the formation of CCA. Both in vitro and vivo analyses were used to identify the tumor-associated senescent ECs and investigate the function in TME. The diethylnitrosamine-induced model was utilized to investigate the interaction between senescent ECs and MSCs, aiming to elucidate their synergistic contributions to the progression of CCA.

RESULTS

Using single-cell RNA sequencing, we identified a distinct senescent-associated subset of endothelial cells (ECs), namely CD34+CLDN5+ ECs, which mainly enriched in tumor tissue. Further, the senescent ECs were observed to secrete IGF2, which recruited mesenchymal stem cells (MSCs) into the TME through IGF2R/MAPK signaling. In primary liver cancer model, MSCs exhibited a strong tumor-promoting effect, increasing the CCA and tumor malignancy after HCC formation. Interestingly, knockdown of IGF2R expression in MSCs inhibited the increase of CCA caused by MSCs in HCC. Meanwhile, it was revealed that MSCs released multiple inflammatory and trophic-related cytokines to enhance the cancer stem cell-like characteristics in HCC cells. Finally, we demonstrated that CEBPβ up-regulated IGF2 expression in tumor senescent ECs by combining with Igf2-promtor-sequence.

CONCLUSIONS

Together, our findings illustrated that tumor associated senescent ECs in HCC recruited the MSCs into TME, enhancing cancer stem cell (CSC)-like features of HCC cells and contributing to the CCA formation.

Droplet-based single-cell sequencing: Strategies and applications

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

Multiple RNA Rapid In Situ Imaging Based on Cas9 Code Key System

Existing RNA in situ imaging strategies mostly utilize parallel repetitive nucleic acid self-assembly to achieve multiple analysis, with limitations of complicated systems and cumbersome steps. Here, a Cas9 code key system with key probe (KP) encoder and CRISPR/Cas9 signal exporter is developed. This system triggers T-protospacer adjacent motif (T-PAM structural transitions of multiple KP encoders to form coding products with uniform single-guide RNA (sgRNA) target sequences as tandem nodes. Only single sgRNA/Cas9 complex is required to cleave multiple coding products, enabling efficient "many-to-one" tandem signaling, and non-collateral cleavage activity-dependent automatic signaling output through active introduction of mismatched bases. Compared with conventional parallel multiple signaling analysis model, the proposed system greatly simplifies reaction process and enhances detection efficiency. Further, a rapid multiple RNA in situ imaging system is developed by combining the Cas9 code key system with a T-strand displacement amplification (T-SDA) signal amplifier. The constructed system is applied to tumor cells and clinicopathology slices, generating clear multi-mRNA imaging profiles in less than an hour with just one step. Therefore, this work provides reliable technical support for clinical tumor typing and molecular mechanism investigation.

Tumor microenvironment remodeling after neoadjuvant chemoradiotherapy in local advanced rectal cancer revealed by single-cell RNA sequencing

BACKGROUND

The use of neoadjuvant chemoradiotherapy (neoCRT) followed by surgery has markedly enhanced the quality of survival in patients suffering from local advanced rectal cancer (LARC). Enhancing this treatment requires a deep understanding of its underlying mechanism. The heterogeneous nature of the tumor microenvironment (TME) significantly impacts therapeutic responses, presenting complex therapeutic challenges.

METHODS

In this comprehensive study, we explored the intricate cellular and molecular shifts within the TME of LARC after neoCRT administration. Using single-cell transcriptomic analysis, we meticulously examined 32,417 cells sourced from six samples, each representing different tumor regression grades (TRG: 0 versus 2). This detailed analysis enabled us to characterize the various cell subpopulations, encompassing epithelial cells, lymphocytes, myeloid cells, endothelial cells, and fibroblasts. Additionally, we identified their marker genes for deconvolution calculation in the READ cohort of the TCGA project. And we obtain their marker genes for deconvolution calculation in the READ cohort of the TCGA project.

RESULTS

Through cluster analysis and pathway comparisons of malignant tumor cells, we discerned that samples with poor tumor regression exhibit enhanced metabolic versatility and adaptability, enabling them to counteract the impacts of both radiotherapy and chemotherapy. Interestingly, within the TRG2 cohort, we observed a predominant immunosuppressive state in the TME, characterized by the activation of CD4 + regulatory T cells, maintained CD8 + T cell functionality, and a heightened M1 to M2 macrophage ratio. Moreover, the differing outcomes of neoCRT were reflected in the varying interaction dynamics between macrophages (M1 and M2) and CD4+/CD8 + T cells. Furthermore, our data reveal that neoCRT intricately modulates fibroblasts and endothelial cells, primarily through the extracellular matrix remodeling pathway, which orchestrates tumor angiogenesis. All changes were validated through immunofluorescence staining on intraoperative samples before and after treatment. To summarize, our investigation presents a comprehensive exploration of the cellular and molecular metamorphoses within the TME post-neoCRT.

CONCLUSIONS

By unveiling the sophisticated interaction between the multifaceted cells within the TME and their respective reactions to neoCRT, we establish a robust platform for ensuing future investigations. This study paves the way for novel therapeutic strategies that leverage these insights to bolster the efficacy of neoCRT in managing LARC.

Integration of single-cell and spatial transcriptome sequencing identifies CDKN2A as a senescent biomarker in endothelial cells implicating hepatocellular carcinoma malignancy

PURPOSE

Highly complex tumor microenvironment makes hepatocellular carcinoma (HCC) as one of the most malignant tumors worldwide. The role of cellular senescence in HCC has been gradually recognized. The present study aimed to comprehensively elucidate the senescence-related features of HCC in single-cell and spatial dimension.

METHODS

Single-cell RNA sequencing (scRNA-Seq) data was used to clarify the heterogeneity of senescence-related genes (SRGs) among multiple cell types within HCC. Spatial transcriptome RNA sequencing (stRNA-Seq) data was used for depicting SRGs features in spatial dimension. A prognostic model based on SRGs was constructed by using of bulk sequencing (bulk-Seq) data of HCC. The cell-cell interaction of senescent endothelial cells (ECs) in tumor microenvironment was analyzed. Then, the role of senescent ECs was verified through in vitro and in vivo experiments.

RESULTS

The level of senescence demonstrated substantial heterogeneity among different cell types within tumor microenvironment of HCC, where ECs exhibited the most prominent senescent phenotype. Senescent ECs activated specific regulatory pathways through communicating with other cell types, with a potential impact on tumor progression. Spatial analysis revealed senescent ECs mainly located in the core region of HCC. The interaction of senescent ECs and immune cells implicated their role in tumor progression and immunotherapeutic response. In addition, CDKN2A was identified as an independent risk factor for HCC prognosis by constructing a prognostic model. Patients with high risk displayed an even worse outcome. The experimental verification indicated senescence of ECs determined by CDKN2A exhibited a secretory phenotype. Furthermore, senescent ECs with CDKN2A overexpression promote the proliferation and migration of HCC.

CONCLUSION

The present study recognizes the critical effect of senescent ECs defined by CDKN2A in the promotion of tumor progression, which sheds new light on the investigation of ECs senescence in HCC.

The Pan-Tumor Vasculature under the Transcriptomic Magnifying Glass

In the first pan-cancer analysis of the tumor vasculature, Pan and colleagues profile nearly 200,000 endothelial cells (EC) and mural cells, identifying novel subclusters and cell states using consensus trajectory inference. They identify differentiation trajectories in vascular and lymphatic ECs and subtype the pericyte (PC) population. During sprouting angiogenesis, venous cells dedifferentiate and transition to capillary and, finally, arterial ECs. Capillary ECs transition via "three angiogenic stages" (SI-SIII), during which APLN+ TipS1 cells were identified as potential modulators of tumor-induced neovascularization and antiangiogenic therapy response. In lymphatic ECs, differentiation was inversely correlated between the lymphangiogenic (T1) and antigen-presenting (T2) trajectories, with T2 associated with a better prognosis. Although several PC clusters were identified, BASP1+ matrix-associated PCs were associated with APLN+ TipS1 cells and had a worse prognosis. These findings present transcriptional validation of previous experimental findings and serve as a resource to examine the tumor vascular microenvironment in detail.

Immunomodulation by endothelial cells: prospects for cancer therapy

Growing evidence highlights the importance of tumor endothelial cells (TECs) in the tumor microenvironment (TME) for promoting tumor growth and evading immune responses. Immunomodulatory endothelial cells (IMECs) represent a distinct plastic phenotype of ECs that exerts the ability to modulate immunity in health and disease. This review discusses our current understanding of IMECs in cancer biology, scrutinizing insights from single-cell reports to compare their characteristics and function dynamics across diverse tumor types, conditions, and species. We investigate possible implications of exploiting IMECs in the context of cancer treatment, particularly examining their influence on the efficacy of existing therapies and the potential to leverage them as targets in optimizing immunotherapeutic strategies.

Microfluidic Chip-Based Automatic System for Sequencing Patient-Derived Organoids at the Single-Cell Level

Genetically sequencing patient-derived organoids (PDOs) at the single-cell level has emerged as a promising method to infer cell-level heterogeneity of original organs and improve cancer precision medicine. Unfortunately, because of the limited starting quantity and uncontrolled establishing process of PDOs, the existing single-cell sequencing technologies, either manual-operation-based or microfluid-based, are inefficient in processing PDOs originating from clinical tissue samples. To address such issues, this study presents a microfluidic chip-based automatic system for sequencing organoids at the single-cell level, named as MASSO. By performing all required procedures, including PDO establishment/culturing/digesting and single-cell isolation/lysis/whole-genome amplification, in a single microfluidic chip, the possible loss of precious PDO is avoided, and the high quality of on-chip whole-genome amplification of a single PDO cell is ensured. By automating the entire operation process, possible human error is eliminated, and the data repeatability is improved, therefore bridging the technical gap between laboratorial proof-of-concept studies and clinical practices. After characterizing the organoid single-cell whole-genome amplification chip (named as OSA-Chip) and the MASSO, the first successful attempt, to the best of our knowledge, on whole-genome sequencing lung cancer PDO at the single-cell level was performed by MASSO. The results reveal that the MASSO is capable of not only identifying common cancer-related mutations but also discovering specific mutations that affect drug responses, therefore laying the technical foundation for efficiently understanding the cell-level heterogeneities of PDOs and corresponding original organs.

Integrative multi-omics analysis reveals the role of tumor-associated endothelial cells and their signature in prognosis of intrahepatic cholangiocarcinoma

This study aims to investigate the interplay between tumor-associated endothelial cells (TECs) and immune cells within the tumor microenvironment (TME) and its impact on tumor prognosis. We conducted single-cell RNA sequencing (scRNA-seq) of tumor, normal, and lymph node tissues obtained from intrahepatic cholangiocarcinoma (ICC) patients to reveal the role of TECs in tumor angiogenesis and their significant heterogeneity. Meanwhile, we identified genes highly expressed in TECs and constructed TEC signatures (TEC.Sig). Next, we calculated TEC scores of samples based on TEC.Sig. Patients with higher TEC scores exhibited a higher frequency of KRAS mutations, which was associated with increased infiltration of neutrophils and immature dendritic cells (iDCs), and decreased numbers of natural killer (NK), CD4 + T, and CD8 + T effector memory (Tem) cells, indicating an inflammation-dominated immunosuppressive phenotype. In contrast, BAP1 mutations and CXCL12 overexpression showed a contrasting trend. Spatial transcriptomics analysis and histological experiments further confirmed that TECs interacted with various tumor-killing immune cells through the CXCL12/CXCR4 axis. Multiple tumor immunotherapy datasets confirmed that the TEC.Sig could predict patient responses to immunotherapy. The TEC score is a promising and reliable biomarker for predicting genetic mutations and prognosis in ICC patients. Enhancing the regulation of the CXCL12/CXCR4 signaling pathway may represent a potential novel therapeutic target for ICC treatment.

Targeting the tumour vasculature: from vessel destruction to promotion

As angiogenesis was recognized as a core hallmark of cancer growth and survival, several strategies have been implemented to target the tumour vasculature. Yet to date, attempts have rarely been so diverse, ranging from vessel growth inhibition and destruction to vessel normalization, reprogramming and vessel growth promotion. Some of these strategies, combined with standard of care, have translated into improved cancer therapies, but their successes are constrained to certain cancer types. This Review provides an overview of these vascular targeting approaches and puts them into context based on our subsequent improved understanding of the tumour vasculature as an integral part of the tumour microenvironment with which it is functionally interlinked. This new knowledge has already led to dual targeting of the vascular and immune cell compartments and sets the scene for future investigations of possible alternative approaches that consider the vascular link with other tumour microenvironment components for improved cancer therapy.

Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies

As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

The burgeoning spatial multi-omics in human gastrointestinal cancers

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

A systems view of the vascular endothelium in health and disease

The dysfunction of blood-vessel-lining endothelial cells is a major cause of mortality. Although endothelial cells, being present in all organs as a single-cell layer, are often conceived as a rather inert cell population, the vascular endothelium as a whole should be considered a highly dynamic and interactive systemically disseminated organ. We present here a holistic view of the field of vascular research and review the diverse functions of blood-vessel-lining endothelial cells during the life cycle of the vasculature, namely responsive and relaying functions of the vascular endothelium and the responsive roles as instructive gatekeepers of organ function. Emerging translational perspectives in regenerative medicine, preventive medicine, and aging research are developed. Collectively, this review is aimed at promoting disciplinary coherence in the field of angioscience for a broader appreciation of the importance of the vasculature for organ function, systemic health, and healthy aging.

Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC

BACKGROUND AND AIMS

Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues.

APPROACH AND RESULTS

We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC.

CONCLUSIONS

Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

Pan-cancer integrative analyses dissect the remodeling of endothelial cells in human cancers

Therapeutics targeting tumor endothelial cells (TECs) have been explored for decades, with only suboptimal efficacy achieved, partly due to an insufficient understanding of the TEC heterogeneity across cancer patients. We integrated single-cell RNA-seq data of 575 cancer patients from 19 solid tumor types, comprehensively charting the TEC phenotypic diversities. Our analyses uncovered underappreciated compositional and functional heterogeneity in TECs from a pan-cancer perspective. Two subsets, CXCR4 + tip cells and SELE + veins, represented the prominent angiogenic and proinflammatory phenotypes of TECs, respectively. They exhibited distinct spatial organization patterns, and compared to adjacent non-tumor tissues, tumor tissue showed an increased prevalence of CXCR4 + tip cells, yet with SELE + veins depleted. Such functional and spatial characteristics underlie their differential associations with the response of anti-angiogenic therapies and immunotherapies. Our integrative resources and findings open new avenues to understand and clinically intervene in the tumor vasculature.

Deciphering tertiary lymphoid structure heterogeneity reveals prognostic signature and therapeutic potentials for colorectal cancer: a multicenter retrospective cohort study

BACKGROUND

Tertiary lymphoid structures (TLSs) exert a crucial role in the tumor microenvironment (TME), impacting tumor development, immune escape, and drug resistance. Nonetheless, the heterogeneity of TLSs in colorectal cancer (CRC) and their impact on prognosis and treatment response remain unclear.

METHODS

The authors collected genome, transcriptome, clinicopathological information, and digital pathology images from multiple sources. An unsupervised clustering algorithm was implemented to determine diverse TLS patterns in CRC based on the expression levels of 39 TLS signature genes (TSGs). Comprehensive explorations of heterogeneity encompassing mutation landscape, TME, biological characteristics, response to immunotherapy, and drug resistance were conducted using multiomics data. TLSscore was then developed to quantitatively assess TLS patterns of individuals for further clinical applicability.

RESULTS

Three distinct TLS patterns were identified in CRC. Cluster 1 exhibited upregulation of proliferation-related pathways, high metabolic activity, and intermediate prognosis, while Cluster 2 displayed activation of stromal and carcinogenic pathways and a worse prognosis. Both Cluster 1 and Cluster 2 may potentially benefit from adjuvant chemotherapy. Cluster 3, characterized by the activation of immune regulation and activation pathways, demonstrated a favorable prognosis and enhanced responsiveness to immunotherapy. The authors subsequently employed a regularization algorithm to construct the TLSscore based on nine core genes. Patients with lower TLSscore trended to prolonged prognosis and a more prominent presence of TLSs, which may benefit from immunotherapy. Conversely, those with higher TLSscore exhibited increased benefits from adjuvant chemotherapy.

CONCLUSIONS

The authors identified distinct TLS patterns in CRC and characterized their heterogeneity through multiomics analyses. The TLSscore held promise for guiding clinical decision-making and further advancing the field of personalized medicine in CRC.

Single-cell RNA sequencing of cystic fibrosis liver disease explants reveals endothelial complement activation

BACKGROUND & AIMS

Cystic fibrosis (CF) is considered a multisystemic disorder in which CF-associated liver disease (CFLD) is the third most common cause of mortality. Currently, no effective treatment is available for CFLD because its pathophysiology is still unclear. Interestingly, CFLD exhibits identical vascular characteristics as non-cirrhotic portal hypertension, recently classified as porto-sinusoidal vascular disorders (PSVD).

METHODS

Since endothelial cells (ECs) are an important component in PSVD, we performed single-cell RNA sequencing (scRNA-seq) on four explant livers from CFLD patients to identify differential endothelial characteristics which could contribute to the disease. We comprehensively characterized the endothelial compartment and compared it with publicly available scRNA-seq datasets from cirrhotic and healthy livers. Key gene signatures were validated ex vivo on patient tissues.

RESULTS

We found that ECs from CF liver explants are more closely related to healthy than cirrhotic patients. In CF patients we also discovered a distinct population of liver sinusoidal ECs-coined CF LSECs-upregulating genes involved in the complement cascade and coagulation. Finally, our immunostainings further validated the predominant periportal location of CF LSECs.

CONCLUSIONS

Our work showed novel aspects of human liver ECs at the single-cell level thereby supporting endothelial involvement in CFLD, and reinforcing the hypothesis that ECs could be a driver of PSVD. Therefore, considering the vascular compartment in CF and CFLD may help developing new therapeutic approaches for these diseases.

Biphasic co-detection of melanoma aneuploid tumor cells and tumor endothelial cells in guidance of specifying the field cancerized surgical excision margin and administering immunotherapy

An optimum safety excision margin (EM) delineated by precise demarcation of field cancerization along with reliable biomarkers that enable predicting and timely evaluating patients' response to immunotherapy significantly impact effective management of melanoma. In this study, optimized biphasic "immunofluorescence staining integrated with fluorescence insitu hybridization" (iFISH) was conducted along the diagnosis-metastasis-treatment-cellular MRD axis to longitudinally co-detect a full spectrum of intact CD31- aneuploid tumor cells (TCs), CD31+ aneuploid tumor endothelial cells (TECs), viable and necrotic circulating TCs (CTCs) and circulating TECs (CTECs) expressing PD-L1, Ki67, p16 and Vimentin in unsliced specimens of the resected primary tumor, EM, dissected sentinel lymph nodes (SLNs) and peripheral blood in an early-stage melanoma patient. Numerous PD-L1+ aneuploid TCs and TECs were detected at the conventional safety EM (2 cm), quantitatively indicating the existence of a field cancerized EM for the first time. Contrary to highly heterogeneous PD-L1 expression and degrees of Chr8 aneuploidy in TCs and TECs in the primary lesions as well as CTCs and CTECs in peripheral blood, almost all TCs and TECs in SLNs and EM were homogeneously PD-L1+ haploid cells. Dynamic monitoring and cellular MRD assessment revealed that, in contrast to PD-L1+ CTCs being responsive to the immune checkpoint inhibitor (ICI-anti-PD-1), multiploid (≥pentasomy 8) PD-L1+ and Ki67+ CTECs were respectively resistant to ICI-sensitized T cells. In therapeutically stressed lymphatic and hematogenous metastatic cascades, stratified phenotypic and karyotypic profiling of iFISH tissue and liquid biopsied TCs, TECs, CTCs and CTECs in future large-cohort studies will enable appropriate re-specification of the optimal safety EM and distribution mapping of in-depth characterized, subcategorized target cells to help illustrate their metastatic relevance, ultimately improving risk stratification and clinical intervention of tumor progression, metastases, therapy resistance and cancer relapse.

Multicellular 3D bioprinted human gallbladder carcinoma forin vitromimicry of tumor microenvironment and intratumoral heterogeneity

Gallbladder carcinoma (GBC) is a malignant hepatobiliary cancer characterized by an intricate tumor microenvironments (TME) and heterogeneity. The traditional GBC 2D culture models cannot faithfully recapitulate the characteristics of the TME. Three-dimensional (3D) bioprinting enables the establishment of high-throughput and high-fidelity multicellular GBC models. In this study, we designed a concentric cylindrical tetra-culture model to reconstitute the spatial distribution of cells in tumor tissue, with the inner portion containing GBC cells, and the outer ring containing a mixture of endothelial cells, fibroblasts, and macrophages. We confirmed the survival, proliferation, biomarker expression and gene expression profiles of GBC 3D tetra-culture models. Hematoxylin-eosin (HE) and immunofluorescence staining verified the morphology and robust expression of GBC/endothelial/fibroblast/macrophage biomarkers in GBC 3D tetra-culture models. Single-cell RNA sequencing revealed two distinct subtypes of GBC cells within the model, glandular epithelial and squamous epithelial cells, suggesting the mimicry of intratumoral heterogeneity. Comparative transcriptome profile analysis among variousin vitromodels revealed that cellular interactions and the TME in 3D tetra-culture models reshaped the biological processes of tumor cells to a more aggressive phenotype. GBC 3D tetra-culture models restored the characteristics of the TME as well as intratumoral heterogeneity. Therefore, this model is expected to have future applications in tumor biology research and antitumor drug development.

Single-cell transcriptome profiles the heterogeneity of tumor cells and microenvironments for different pathological endometrial cancer and identifies specific sensitive drugs

Endometrial cancer (EC) is a highly heterogeneous malignancy characterized by varied pathology and prognoses, and the heterogeneity of its cancer cells and the tumor microenvironment (TME) remains poorly understood. We conducted single-cell RNA sequencing (scRNA-seq) on 18 EC samples, encompassing various pathological types to delineate their specific unique transcriptional landscapes. Cancer cells from diverse pathological sources displayed distinct hallmarks labeled as immune-modulating, proliferation-modulating, and metabolism-modulating cancer cells in uterine clear cell carcinomas (UCCC), well-differentiated endometrioid endometrial carcinomas (EEC-I), and uterine serous carcinomas (USC), respectively. Cancer cells from the UCCC exhibited the greatest heterogeneity. We also identified potential effective drugs and confirmed their effectiveness using patient-derived EC organoids for each pathological group. Regarding the TME, we observed that prognostically favorable CD8+ Tcyto and NK cells were prominent in normal endometrium, whereas CD4+ Treg, CD4+ Tex, and CD8+ Tex cells dominated the tumors. CXCL3+ macrophages associated with M2 signature and angiogenesis were exclusively found in tumors. Prognostically relevant epithelium-specific cancer-associated fibroblasts (eCAFs) and SOD2+ inflammatory CAFs (iCAFs) predominated in EEC-I and UCCC groups, respectively. We also validated the oncogenic effects of SOD2+ iCAFs in vitro. Our comprehensive study has yielded deeper insights into the pathogenesis of EC, potentially facilitating personalized treatments for its varied pathological types.

Advancing precision medicine in gliomas through single-cell sequencing: unveiling the complex tumor microenvironment

Glioblastoma (GBM) displays an infiltrative growth characteristic that recruits neighboring normal cells to facilitate tumor growth, maintenance, and invasion into the brain. While the blood-brain barrier serves as a critical natural defense mechanism for the central nervous system, GBM disrupts this barrier, resulting in the infiltration of macrophages from the peripheral bone marrow and the activation of resident microglia. Recent advancements in single-cell transcriptomics and spatial transcriptomics have refined the categorization of cells within the tumor microenvironment for precise identification. The intricate interactions and influences on cell growth within the tumor microenvironment under multi-omics conditions are succinctly outlined. The factors and mechanisms involving microglia, macrophages, endothelial cells, and T cells that impact the growth of GBM are individually examined. The collaborative mechanisms of tumor cell-immune cell interactions within the tumor microenvironment synergistically promote the growth, infiltration, and metastasis of gliomas, while also influencing the immune status and therapeutic response of the tumor microenvironment. As immunotherapy continues to progress, targeting the cells within the inter-tumor microenvironment emerges as a promising novel therapeutic approach for GBM. By comprehensively understanding and intervening in the intricate cellular interactions within the tumor microenvironment, novel therapeutic modalities may be developed to enhance treatment outcomes for patients with GBM.

CAFs vs. TECs: when blood feuds fuel cancer progression, dissemination and therapeutic resistance

Neoplastic progression involves complex interactions between cancer cells and the surrounding stromal milieu, fostering microenvironments that crucially drive tumor progression and dissemination. Of these stromal constituents, cancer-associated fibroblasts (CAFs) emerge as predominant inhabitants within the tumor microenvironment (TME), actively shaping multiple facets of tumorigenesis, including cancer cell proliferation, invasiveness, and immune evasion. Notably, CAFs also orchestrate the production of pro-angiogenic factors, fueling neovascularization to sustain the metabolic demands of proliferating cancer cells. Moreover, CAFs may also directly or indirectly affect endothelial cell behavior and vascular architecture, which may impact in tumor progression and responses to anti-cancer interventions. Conversely, tumor endothelial cells (TECs) exhibit a corrupted state that has been shown to affect cancer cell growth and inflammation. Both CAFs and TECs are emerging as pivotal regulators of the TME, engaging in multifaceted biological processes that significantly impact cancer progression, dissemination, and therapeutic responses. Yet, the intricate interplay between these stromal components and the orchestrated functions of each cell type remains incompletely elucidated. In this review, we summarize the current understanding of the dynamic interrelationships between CAFs and TECs, discussing the challenges and prospects for leveraging their interactions towards therapeutic advancements in cancer.

Identification of adipocyte infiltration-related gene subtypes for predicting colorectal cancer prognosis and responses of immunotherapy/chemotherapy

Colorectal cancer (CRC) is a prevalent and aggressive malignancy characterized by a complex tumor microenvironment (TME). Given the variations in the level of adipocyte infiltration in TME, the prognosis may differ among CRC patients. Thus, there is an urgent need to establish a reliable method for identifying adipocyte subtypes in CRC in order to elucidate the impact of adipocyte infiltration on CRC treatment and prognosis. Herein, 144 adipocyte-infiltration-related genes (AIRGs) were identified as predictive markers for the immune-associated features and prognosis of CRC patients. Based on the 144 genes, the unsupervised clustering algorithm identified two distinct clusters of CRC patients with variations in molecular and signaling pathways, clinicopathological characteristics and responses to CRC chemotherapy and immunotherapy. Furthermore, an AIRG prognostic signature was constructed and validated in independent datasets. Overall, this study developed a prognostic signature based on AIRGs in CRC, which may contribute to the development of personalized treatment strategies and enhance prognostic prediction for CRC patients.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

Near-infrared-II responsive ovalbumin functionalized gold-genipin nanosystem cascading photo-immunotherapy of cancer

Synergistic cancer therapies have attracted wide attention owing to their multi-mode tumor inhibition properties. Especially, photo-responsive photoimmunotherapy demonstrates an emerging cancer treatment paradigm that significantly improved treatment efficiency. Herein, near-infrared-II responsive ovalbumin functionalized Gold-Genipin nanosystem (Au-G-OVA NRs) was designed for immunotherapy and deep photothermal therapy of breast cancer. A facile synthesis method was employed to prepare the homogeneous Au nanorods (Au NRs) with good dispersion. The nanovaccine was developed further by the chemical cross-linking of Au-NRs, genipin and ovalbumin. The Au-G-OVA NRs outstanding aqueous solubility, and biocompatibility against normal and cancer cells. The designed NRs possessed enhanced localized surface plasmon resonance (LSPR) effect, which extended the NIR absorption in the second window, enabling promising photothermal properties. Moreover, genipin coating provided complimentary red fluorescent and prepared Au-G-OVA NRs showed significant intracellular encapsulation for efficient photoimmunotherapy outcomes. The designed nanosystem possessed deep photothermal therapy of breast cancer and 90% 4T1 cells were ablated by Au-G-OVA NRs (80μg ml-1concentration) after 1064 nm laser irradiation. In addition, Au-G-OVA NRs demonstrated outstanding vaccination phenomena by facilitating OVA delivery, antigen uptake, maturation of bone marrow dendritic cells, and cytokine IFN-γsecretion for tumor immunosurveillance. The aforementioned advantages permit the utilization of fluorescence imaging-guided photo-immunotherapy for cancers, demonstrating a straightforward approach for developing nanovaccines tailored to precise tumor treatment.