Deciphering functional tumor states at single-cell resolution

Pericyte phenotype switching alleviates immunosuppression and sensitizes vascularized tumors to immunotherapy in preclinical models

T cell-based immunotherapies are a promising therapeutic approach for multiple malignancies, but their efficacy is limited by tumor hypoxia arising from dysfunctional blood vessels. Here, we report that cell-intrinsic properties of a single vascular component, namely the pericyte, contribute to the control of tumor oxygenation, macrophage polarization, vessel inflammation, and T cell infiltration. Switching pericyte phenotype from a synthetic to a differentiated state reverses immune suppression and sensitizes tumors to adoptive T cell therapy, leading to regression of melanoma in mice. In melanoma patients, improved survival is correlated with enhanced pericyte maturity. Importantly, pericyte plasticity is regulated by signaling pathways converging on Rho kinase activity, with pericyte maturity being inducible by selective low-dose therapeutics that suppress pericyte MEK, AKT, or notch signaling. We also show that low-dose targeted anticancer therapy can durably change the tumor microenvironment without inducing adaptive resistance, creating a highly translatable pathway for redosing anticancer targeted therapies in combination with immunotherapy to improve outcome.

Tipping points in epithelial-mesenchymal lineages from single-cell transcriptomics data

Understanding cell fate decision-making during complex biological processes is an open challenge that is now aided by high-resolution single-cell sequencing technologies. Specifically, it remains challenging to identify and characterize transition states corresponding to "tipping points" whereby cells commit to new cell states. Here, we present a computational method that takes advantage of single-cell transcriptomics data to infer the stability and gene regulatory networks (GRNs) along cell lineages. Our method uses the unspliced and spliced counts from single-cell RNA sequencing data and cell ordering along lineage trajectories to train an RNA splicing multivariate model, from which cell-state stability along the lineage is inferred based on spectral analysis of the model's Jacobian matrix. Moreover, the model infers the RNA cross-species interactions resulting in GRNs and their variation along the cell lineage. When applied to epithelial-mesenchymal transition in ovarian and lung cancer-derived cell lines, our model predicts a saddle-node transition between the epithelial and mesenchymal states passing through an unstable, intermediate cell state. Furthermore, we show that the underlying GRN controlling epithelial-mesenchymal transition rearranges during the transition, resulting in denser and less modular networks in the intermediate state. Overall, our method represents a flexible tool to study cell lineages with a combination of theory-driven modeling and single-cell transcriptomics data.

Spatial transcriptomics profiling of gallbladder adenocarcinoma: a detailed two-case study of progression from precursor lesions to cancer

BACKGROUND

Most studies on tumour progression from precursor lesion toward gallbladder adenocarcinoma investigate lesions sampled from distinct patients, providing an overarching view of pathogenic cascades. Whether this reflects the tumourigenic process in individual patients remains insufficiently explored. Genomic and epigenomic studies suggest that a subset of gallbladder cancers originate from biliary intraepithelial neoplasia (BilIN) precursor lesions, whereas others form independently from BilINs. Spatial transcriptomic data supporting these conclusions are missing. Moreover, multiple areas with precursor or adenocarcinoma lesions can be detected within the same pathological sample. Yet, knowledge about intra-patient variability of such lesions is lacking.

METHODS

To characterise the spatial transcriptomics of gallbladder cancer tumourigenesis in individual patients, we selected two patients with distinct cancer aetiology and whose samples simultaneously displayed multiple areas of normal epithelium, BilINs and adenocarcinoma. Using GeoMx digital spatial profiling, we characterised the whole transcriptome of a high number of regions of interest (ROIs) per sample in the two patients (24 and 32 ROIs respectively), with each ROI covering approximately 200 cells of normal epithelium, low-grade BilIN, high-grade BilIN or adenocarcinoma. Human gallbladder organoids and cell line-derived tumours were used to investigate the tumour-promoting role of genes.

RESULTS

Spatial transcriptomics revealed that each type of lesion displayed limited intra-patient transcriptomic variability. Our data further suggest that adenocarcinoma derived from high-grade BilIN in one patient and from low-grade BilIN in the other patient, with co-existing high-grade BilIN evolving via a distinct process in the latter case. The two patients displayed distinct sequences of signalling pathway activation during tumour progression, but Semaphorin 4 A (SEMA4A) expression was repressed in both patients. Using human gallbladder-derived organoids and cell line-derived tumours, we provide evidence that repression of SEMA4A promotes pseudostratification of the epithelium and enhances cell migration and survival.

CONCLUSION

Gallbladder adenocarcinoma can develop according to patient-specific processes, and limited intra-patient variability of precursor and cancer lesions was noticed. Our data suggest that repression of SEMA4A can promote tumour progression. They also highlight the need to gain gene expression data in addition to histological information to avoid understimating the risk of low-grade preneoplastic lesions.

A comparison of scRNA-seq annotation methods based on experimentally labeled immune cell subtype dataset

Cell-type annotation is a critical step in single-cell data analysis. With the development of numerous cell annotation methods, it is necessary to evaluate these methods to help researchers use them effectively. Reference datasets are essential for evaluation, but currently, the cell labels of reference datasets mainly come from computational methods, which may have computational biases and may not reflect the actual cell-type outcomes. This study first constructed an experimentally labeled immune cell-subtype single-cell dataset of the same batch and systematically evaluated 18 cell annotation methods. We assessed those methods under five scenarios, including intra-dataset validation, immune cell-subtype validation, unsupervised clustering, inter-dataset annotation, and unknown cell-type prediction. Accuracy and ARI were evaluation metrics. The results showed that SVM, scBERT, and scDeepSort were the best-performing supervised methods. Seurat was the best-performing unsupervised clustering method, but it couldn't fully fit the actual cell-type distribution. Our results indicated that experimentally labeled immune cell-subtype datasets revealed the deficiencies of unsupervised clustering methods and provided new dataset support for supervised methods.

RNA regulatory mechanisms controlling TGF-β signaling and EMT in cancer

Epithelial-mesenchymal transition (EMT) is a major contributor to metastatic progression and is prominently regulated by TGF-β signalling. Both EMT and TGF-β pathway components are tightly controlled by non-coding RNAs - including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) - that collectively have major impacts on gene expression and resulting cellular states. While miRNAs are the best characterised regulators of EMT and TGF-β signaling and the miR-200-ZEB1/2 feedback loop plays a central role, important functions for lncRNAs and circRNAs are also now emerging. This review will summarise our current understanding of the roles of non-coding RNAs in EMT and TGF-β signaling with a focus on their functions in cancer progression.

The integrate profiling of single-cell and spatial transcriptome RNA-seq reveals tumor heterogeneity, therapeutic targets, and prognostic subtypes in ccRCC

Clear-cell renal cell carcinoma (ccRCC) is the most common type of RCC; however, the intratumoral heterogeneity in ccRCC remains unclear. We first identified markers and biological features of each cell cluster using bioinformatics analysis based on single-cell and spatial transcriptome RNA-sequencing data. We found that gene copy number loss on chromosome 3p and amplification on chromosome 5q were common features in ccRCC cells. Meanwhile, NNMT and HILPDA, which are associated with the response to hypoxia and metabolism, are potential therapeutic targets for ccRCC. In addition, CD8+ exhausted T cells (LAG3+ HAVCR2+), CD8+ proliferated T cells (STMN+), and M2-like macrophages (CD68+ CD163+ APOC1+), which are closely associated with immunosuppression, played vital roles in ccRCC occurrence and development. These results were further verified by whole exome sequencing, cell line and xenograft experiments, and immunofluorescence staining. Finally, we divide patients with ccRCC into three subtypes using unsupervised cluster analysis. and generated a classifier to reproduce these subtypes using the eXtreme Gradient Boosting algorithm. Our classifier can help clinicians evaluate prognosis and design personalized treatment strategies for ccRCC. In summary, our work provides a new perspective for understanding tumor heterogeneity and will aid in the design of antitumor therapeutic strategies for ccRCC.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

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.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Mesothelial cells with mesenchymal features enhance peritoneal dissemination by forming a protumorigenic microenvironment

Malignant ascites accompanied by peritoneal dissemination contain various factors and cell populations as well as cancer cells; however, how the tumor microenvironment is shaped in ascites remains unclear. Single-cell proteomic profiling and a comprehensive proteomic analysis are conducted to comprehensively characterize malignant ascites. Here, we find defects in immune effectors along with immunosuppressive cell accumulation in ascites of patients with gastric cancer (GC) and identify five distinct subpopulations of CD45(-)/EpCAM(-) cells. Mesothelial cells with mesenchymal features in CD45(-)/EpCAM(-) cells are the predominant source of chemokines involved in immunosuppressive myeloid cell (IMC) recruitment. Moreover, mesothelial-mesenchymal transition (MMT)-induced mesothelial cells strongly express extracellular matrix (ECM)-related genes, including tenascin-C (TNC), enhancing metastatic colonization. These findings highlight the definite roles of the mesenchymal cell population in the development of a protumorigenic microenvironment to promote peritoneal dissemination.

BRCA1/2 Haploinsufficiency: Exploring the Impact of Losing one Allele

Since their discovery in the late 20th century, significant progress has been made in elucidating the functions of the tumor suppressor proteins BRCA1 and BRCA2. These proteins play vital roles in maintaining genome integrity, including DNA repair, replication fork protection, and chromosome maintenance. It is well-established that germline mutations in BRCA1 and BRCA2 increase the risk of breast and ovarian cancer; however, the precise mechanism underlying tumor formation in this context is not fully understood. Contrary to the long-standing belief that the loss of the second wild-type allele is necessary for tumor development, a growing body of evidence suggests that tumorigenesis can occur despite the presence of a single functional allele. This entails that heterozygosity in BRCA1/2 confers haploinsufficiency, where a single copy of the gene is not sufficient to fully suppress tumor formation. Here we provide an overview of the findings and the ongoing debate regarding BRCA haploinsufficiency. We further put out the challenges in studying this topic and discuss its potential relevance in the prevention and treatment of BRCA-related cancers.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Development and validation of cuproptosis-related lncRNAs associated with pancreatic cancer immune microenvironment based on single-cell

Background

Cuproptosis, a novel mode of cell death associated with the tricarboxylic acid (TCA) cycle, is relevant to the development of cancer. However, the impact of single-cell-based Cuproptosis-associated lncRNAs on the Tumor immune microenvironment (TIME) of Pancreatic adenocarcinoma (PAAD) and its potential value for individualized immunotherapy has not been clarified.

Methods

14 immune-related CRGs were screened by exploring the interaction between differentially expressed Immune-Related Genes (IRGs) and Cuproptosis-Related Genes (CRGs) in PAAD. Next, the expression amount and expression distribution of CRGs in single-cell samples were analyzed by focusing on 7-CRGs with significant expressions. On the one hand, MAP2K2, SOD1, and VEGFA, which were significantly differentially expressed between PAAD sites and normal tissues adjacent to them, were subjected to immunohistochemical validation and immune landscape analysis. On the other hand, from these 7-CRGs, prognostic signatures of lncRNAs were established by co-expression and LASSO-COX regression analysis, and their prognostic value and immune relevance were assessed. In addition, this study not only validated the hub CRGs and the lncRNAs constituting the signature in a PAAD animal model treated with immunotherapy-based combination therapy using immunohistochemistry and qRT-PCR but also explored the potential value of the combination of targeted, chemotherapy and immunotherapy.

Results

Based on the screening of 7-CRGs significantly expressed in a PAAD single-cell cohort and their co-expressed Cuproptosis-Related lncRNAs (CRIs), this study constructed a prognostic signature of 4-CRIs named CIR-score. A Nomogram integrating the CIR-score and clinical risk factors was constructed on this basis to predict the individualized survival of patients. Moreover, high and low-risk groups classified according to the median of signatures exhibited significant differences in clinical prognosis, immune landscape, bioenrichment, tumor burden, and drug sensitivity. And the immunohistochemical and qRT-PCR results of different mouse PAAD treatment strategies were consistent with the trend of inter-group variability in drug sensitivity of hub CRGs and CIR-score. The combination of immunotherapy, targeted therapy, and chemotherapy exhibited a better tumor suppression effect.

Conclusion

CIR-score, as a Cuproptosis-related TIME-specific prognostic signature based on PAAD single cells, not only predicts the prognosis and immune landscape of PAAD patients but also provides a new strategy for individualized immunotherapy-based combination therapy.

Non-Coding RNAs: Foes or Friends for Targeting Tumor Microenvironment

Non-coding RNAs (ncRNAs) are a group of molecules critical for cell development and growth regulation. They are key regulators of important cellular pathways in the tumor microenvironment. To analyze ncRNAs in the tumor microenvironment, the use of RNA sequencing technology has revolutionized the field. The advancement of this technique has broadened our understanding of the molecular biology of cancer, presenting abundant possibilities for the exploration of novel biomarkers for cancer treatment. In this review, we will summarize recent achievements in understanding the complex role of ncRNA in the tumor microenvironment, we will report the latest studies on the tumor microenvironment using RNA sequencing, and we will discuss the potential use of ncRNAs as therapeutics for the treatment of cancer.

Gene expression networks involved in multiple cellular programs coexist in individual hepatocellular cancer cells

The gene expression networks of a single cell can be used to reveal cell type- and condition-specific patterns that account for cell states, cell identity, and its responses to environmental changes. We applied single cell sequencing datasets to define mRNA patterns and visualized potential cellular capacities among hepatocellular cancer cells. The expressing numbers and levels of genes were highly heterogenous among the cancer cells. The cellular characteristics were dependent strongly on the expressing numbers and levels of genes, especially oncogenes and anti-oncogenes, in an individual cancer cell. The transcriptional activations of oncogenes and anti-oncogenes were strongly linked to inherent multiple cellular programs, some of which oppose and contend against other processes, in a cancer cell. The gene expression networks of multiple cellular programs proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, ATP production, and neurogenesis coexisted in an individual cancer cell. The findings give rise a hypothesis that a cancer cell expresses balanced combinations of genes and undergoes a given biological process by rapidly transmuting gene expressing networks.

Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing

The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.

Reversible transitions between noradrenergic and mesenchymal tumor identities define cell plasticity in neuroblastoma

Noradrenergic and mesenchymal identities have been characterized in neuroblastoma cell lines according to their epigenetic landscapes and core regulatory circuitries. However, their relationship and relative contribution in patient tumors remain poorly defined. We now document spontaneous and reversible plasticity between the two identities, associated with epigenetic reprogramming, in several neuroblastoma models. Interestingly, xenografts with cells from each identity eventually harbor a noradrenergic phenotype suggesting that the microenvironment provides a powerful pressure towards this phenotype. Accordingly, such a noradrenergic cell identity is systematically observed in single-cell RNA-seq of 18 tumor biopsies and 15 PDX models. Yet, a subpopulation of these noradrenergic tumor cells presents with mesenchymal features that are shared with plasticity models, indicating that the plasticity described in these models has relevance in neuroblastoma patients. This work therefore emphasizes that intrinsic plasticity properties of neuroblastoma cells are dependent upon external cues of the environment to drive cell identity.

Addressing Tumor Heterogeneity by Sensitizing Resistant Cancer Cells to T cell-Secreted Cytokines

Tumor heterogeneity is a major barrier to cancer therapy, including immunotherapy. Activated T cells can efficiently kill tumor cells following recognition of MHC class I (MHC-I)-bound peptides, but this selection pressure favors outgrowth of MHC-I-deficient tumor cells. We performed a genome-scale screen to discover alternative pathways for T cell-mediated killing of MHC-I-deficient tumor cells. Autophagy and TNF signaling emerged as top pathways, and inactivation of Rnf31 (TNF signaling) and Atg5 (autophagy) sensitized MHC-I-deficient tumor cells to apoptosis by T cell-derived cytokines. Mechanistic studies demonstrated that inhibition of autophagy amplified proapoptotic effects of cytokines in tumor cells. Antigens from apoptotic MHC-I-deficient tumor cells were efficiently cross-presented by dendritic cells, resulting in heightened tumor infiltration by IFNγ-and TNFα-producing T cells. Tumors with a substantial population of MHC-I-deficient cancer cells could be controlled by T cells when both pathways were targeted using genetic or pharmacologic approaches.

SIGNIFICANCE

Tumor heterogeneity is a major barrier to immunotherapy. We show that MHC-I-deficient tumor cells are forced into apoptosis by T cell-derived cytokines when TNF signaling and autophagy pathways are targeted. This approach enables T cell-mediated elimination of tumors with a substantial population of resistant, MHC-I-deficient tumor cells. This article is highlighted in the In This Issue feature, p. 1027.

Designing Cancer Immunotherapies That Engage T Cells and NK Cells

T cells and natural killer (NK) cells have complementary roles in tumor immunity, and dual T cell and NK cell attack thus offers opportunities to deepen the impact of immunotherapy. Recent work has also shown that NK cells play an important role in recruiting dendritic cells to tumors and thus enhance induction of CD8 T cell responses, while IL-2 secreted by T cells activates NK cells. Targeting of immune evasion mechanisms from the activating NKG2D receptor and its MICA and MICB ligands on tumor cells offers opportunities for therapeutic intervention. Interestingly, T cells and NK cells share several important inhibitory and activating receptors that can be targeted to enhance T cell- and NK cell-mediated immunity. These inhibitory receptor-ligand systems include CD161-CLEC2D, TIGIT-CD155, and NKG2A/CD94-HLA-E. We also discuss emerging therapeutic strategies based on inhibitory and activating cytokines that profoundly impact the function of both lymphocyte populations within tumors.

Development of a coupled modeling for tumor growth, angiogenesis, oxygen delivery, and phenotypic heterogeneity

Analysis of the evolution and growth dynamics of tumors is crucial for understanding cancer and the development of individually optimized therapies. During tumor growth, a hypoxic microenvironment around cancer cells caused by excessive non-vascular tumor growth induces tumor angiogenesis that plays a key role in the ensuing tumor growth and its progression into higher stages. Various mathematical simulation models have been introduced to simulate these biologically and physically complex hallmarks of cancer. Here, we developed a hybrid two-dimensional computational model that integrates spatiotemporally different components of the tumor system to investigate both angiogenesis and tumor growth/proliferation. This spatiotemporal evolution is based on partial diffusion equations, the cellular automation method, transition and probabilistic rules, and biological assumptions. The new vascular network provided by angiogenesis affects tumor microenvironmental conditions and drives individual cells to adapt themselves to spatiotemporal conditions. Furthermore, some stochastic rules are involved besides microenvironmental conditions. Overall, the conditions promote some commonly observed cellular states, i.e., proliferative, migrative, quiescent, and cell death, depending on the condition of each cell. Altogether, our results offer a theoretical basis for the biological evidence that regions of the tumor tissue near blood vessels are densely populated by proliferative phenotypic variants, while poorly oxygenated regions are sparsely populated by hypoxic phenotypic variants.

Harnessing epithelial-mesenchymal plasticity to boost cancer immunotherapy

Immune checkpoint blockade (ICB) therapy is a powerful option for cancer treatment. Despite demonstrable progress, most patients fail to respond or achieve durable responses due to primary or acquired ICB resistance. Recently, tumor epithelial-to-mesenchymal plasticity (EMP) was identified as a critical determinant in regulating immune escape and immunotherapy resistance in cancer. In this review, we summarize the emerging role of tumor EMP in ICB resistance and the tumor-intrinsic or extrinsic mechanisms by which tumors exploit EMP to achieve immunosuppression and immune escape. We discuss strategies to modulate tumor EMP to alleviate immune resistance and to enhance the efficiency of ICB therapy. Our discussion provides new prospects to enhance the ICB response for therapeutic gain in cancer patients.

Tumor stemness score to estimate epithelial-to-mesenchymal transition (EMT) and cancer stem cells (CSCs) characterization and to predict the prognosis and immunotherapy response in bladder urothelial carcinoma

BACKGROUND

A growing number of investigations have suggested a close link between cancer stem cells (CSCs), epithelial-to-mesenchymal transition (EMT), and the tumor microenvironment (TME). However, the relationships between these physiological processes in bladder urothelial carcinoma (BLCA) remain unclear.

METHODS

We first explored biomarkers of tumor stemness (TS) by single-cell sequencing analysis. Then, subtypes of bladder urothelial carcinoma (BLCA) were identified using clustering analysis based on TS biomarkers. The TS score was constructed using principal component analysis to quantify tumor stemness in BLCA. Then, meta-analysis was performed to measure the hazard ratio of the TS score in BLCA cohorts. Moreover, we evaluated the clinical value of the TS score for predicting the response to tumor immunotherapy using immunotherapy cohorts. Finally, we built an EMT cell model by treating T24 cells with TGF-β and validated the relationship between the TS score and the EMT process in tumors by real-time quantitative PCR, cell invasion assays, and RNA-seq. In total, 3846 BLCA cells, 6 cell lines, 1627 BLCA samples, and 9858 samples from 32 other types of tumors were included in our study.

RESULTS

Three TS clusters and two TS-related gene clusters were identified with differential EMT activity status, CSC features, and TME characteristics in BLCA. Then, a TS scoring system was established with 61 TS-related genes to quantify the TS. The prognostic value of the TS score was then confirmed in multiple independent cohorts. A high TS score was associated with high EMT activity, CSC characteristics, high stromal cell content, high TP53 mutation rate, poor prognosis, and high tumor immunotherapy tolerance. The cell line experiment and RNA-seq further validated that our TS score can reflect the EMT and CSC characterization of tumor cells.

CONCLUSION

Overall, this research provides a better understanding of tumor invasion and metastasis mechanisms through an analysis of TS patterns with different EMT processes and CSC characteristics. The TS score provides an index for EMT and CSC research and helps clinicians develop treatment plans and predict outcomes for patients.

In vivo 3D profiling of site-specific human cancer cell morphotypes in zebrafish

Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a challenge. We present a quantitative high-resolution imaging assay of single cancer cells in zebrafish xenografts to probe functional adaptation to variable cell-extrinsic cues and molecular interventions. Using cell morphology as a surrogate readout of cell functional states, we examine environmental influences on the morphotype distribution of Ewing Sarcoma, a pediatric cancer associated with the oncogene EWSR1-FLI1 and whose plasticity is thought to determine disease outcome through non-genomic mechanisms. Computer vision analysis reveals systematic shifts in the distribution of 3D morphotypes as a function of cell type and seeding site, as well as tissue-specific cellular organizations that recapitulate those observed in human tumors. Reduced expression of the EWSR1-FLI1 protein product causes a shift to more protrusive cells and decreased tissue specificity of the morphotype distribution. Overall, this work establishes a framework for a statistically robust study of cancer cell plasticity in diverse tissue microenvironments.

Comprehensive analysis of potential cellular communication networks in advanced osteosarcoma using single-cell RNA sequencing data

Osteosarcoma (OS) is a common bone cancer in children and adolescents, and metastasis and recurrence are the major causes of poor treatment outcomes. A better understanding of the tumor microenvironment is required to develop an effective treatment for OS. In this paper, a single-cell RNA sequencing dataset was taken to a systematic genetic analysis, and potential signaling pathways linked with osteosarcoma development were explored. Our findings revealed 25 clusters across 11 osteosarcoma tissues, with 11 cell types including “Chondroblastic cells”, “Osteoblastic cells”, “Myeloid cells”, “Pericytes”, “Fibroblasts”, “Proliferating osteoblastic cells”, “Osteoclasts”, “TILs”, “Endothelial cells”, “Mesenchymal stem cells”, and “Myoblasts”. The results of Cell communication analysis showed 17 potential cellular communication networks including “COLLAGEN signaling pathway network”, “CD99 signaling pathway network”, “PTN signaling pathway network”, “MIF signaling pathway network”, “SPP1 signaling pathway network”, “FN1 signaling pathway network”, “LAMININ signaling pathway network”, “FGF signaling pathway network”, “VEGF signaling pathway network”, “GALECTIN signaling pathway network”, “PERIOSTIN signaling pathway network”, “VISFATIN signaling pathway network”, “ITGB2 signaling pathway network”, “NOTCH signaling pathway network”, “IGF signaling pathway network”, “VWF signaling pathway network”, “PDGF signaling pathway network”. This research may provide novel insights into the pathophysiology of OS’s molecular processes.

Single-cell analysis of a high-grade serous ovarian cancer cell line reveals transcriptomic changes and cell subpopulations sensitive to epigenetic combination treatment

Ovarian cancer (OC) is a lethal gynecological malignancy with a five-year survival rate of only 46%. Development of resistance to platinum-based chemotherapy is a common cause of high mortality rates among OC patients. Tumor and transcriptomic heterogeneity are drivers of platinum resistance in OC. Platinum-based chemotherapy enriches for ovarian cancer stem cells (OCSCs) that are chemoresistant and contribute to disease recurrence and relapse. Studies examining the effect of different treatments on subpopulations of HGSOC cell lines are limited. Having previously demonstrated that combined treatment with an enhancer of zeste homolog 2 inhibitor (EZH2i) and a RAC1 GTPase inhibitor (RAC1i) inhibited survival of OCSCs, we investigated EZH2i and RAC1i combination effects on HGSOC heterogeneity using single cell RNA sequencing. We demonstrated that RAC1i reduced expression of stemness and early secretory marker genes, increased expression of an intermediate secretory marker gene and induced inflammatory gene expression. Importantly, RAC1i alone and in combination with EZH2i significantly reduced oxidative phosphorylation and upregulated Sirtuin signaling pathways. Altogether, we demonstrated that combining a RAC1i with an EZH2i promoted differentiation of subpopulations of HGSOC cells, supporting the future development of epigenetic drug combinations as therapeutic approaches in OC.