Single-cell RNA sequencing reveals the tumor microenvironment and facilitates strategic choices to circumvent treatment failure in a chemorefractory bladder cancer patient

Recent contributions of single-cell and spatial profiling to the understanding of bladder cancer

PURPOSE OF REVIEW

Current risk stratification and treatment decision-making for bladder cancer informed by histopathology as well as molecular diagnostics face limitations. This review summarizes recent advancements in single-cell and spatial omics methodologies for understanding bladder cancer biology and their potential impact on development of novel therapeutic strategies.

RECENT FINDINGS

Single-cell RNA sequencing and spatial omics techniques offer unprecedented insights into various aspects of tumor microenvironment (TME), bladder cancer heterogeneity, cancer stemness, and cellular plasticity. Studies have identified multiple malignant cell subpopulations within tumors, revealing diverse transcriptional states and clonal evolution. Additionally, intratumor heterogeneity has been linked to tumor progression and therapeutic response. Immune cell composition analysis has revealed immunosuppressive features in the TME, impacting treatment response. Furthermore, studies have elucidated the role of cancer-associated fibroblasts and endothelial cells in shaping the tumor immune landscape and response to therapy.

SUMMARY

Single-cell and spatial omics technologies have revolutionized our understanding of bladder cancer biology, uncovering previously unseen complexities. These methodologies provide valuable insights into tumor heterogeneity and microenvironmental interactions, with implications for therapeutic development. However, challenges remain in translating research findings into clinical practice and implementing personalized treatment strategies. Continued interdisciplinary collaboration and innovation are essential for overcoming these challenges and leveraging the full potential of single-cell and spatial omics in improving bladder cancer diagnosis and treatment.

Developing and experimental validating a B cell exhaustion-related gene signature to assess prognosis and immunotherapeutic response in bladder cancer

BACKGROUND

B cell exhaustion (BEX) refers to the impairment of normal B cell functions and decreased proliferation capability. However, the prognostic value of BEX-related genes in bladder cancer (BLCA) remains unclear.

METHODS

BLCA cases from TCGA were used for training, while GSE5287, GSE13507, GSE31684, and GSE32894 cohorts from GEO were used for external validation. BEX-related genes were identified through literature retrieval, unsupervised clustering, and genomic difference detection. Gene pairing, LASSO, random forest, and Cox regression were employed to construct a predictive model. B cell samples from scRNAseqDB, GSE111636, and IMvigor210 were utilized to explore immunoprofiles and the predictive ability of the model in immunotherapeutic response. Additionally, 21 pairs of BLCA and paracarcinoma samples from Nanfang Hospital were used to re-confirm our findings through RT-qPCR, immunofluorescence, and flow cytometry.

RESULTS

39 BEX-related genes were identified. A 4-gene-pair signature was constructed and served as a reliable prognostic predictor across multiple datasets (pooled HR = 2.32; 95 % CI = 1.81-2.98). The signature reflected the BEX statuses of B cells (FDR < 0.05) and showed promise in evaluating immunotherapeutic sensitivity (P < 0.001). In the local cohort, CD52, TUBB6, and CAV1 were down-regulated in BLCA tissues, while TGFBI, UBE2L6, TINAGL1, and IL32 were up-regulated (all P < 0.05). Furthermore, the infiltration levels of CD19 + CD52 + and CD19 + TUBB6 + B cells in paracarcinoma samples were higher than those in BLCA samples (all P < 0.05).

CONCLUSION

A BEX-related gene signature was developed to predict prognosis and immunotherapeutic sensitivity in BLCA, providing valuable guidance for personalized treatment.

The predictive value of PFKFB3 in bladder cancer prognosis

6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3 (PFKFB3) influences cancer progression via participating in tumor aerobic glycolysis. In this study, we aimed to evaluate the prognostic significance of PFKFB3 in bladder cancer (BLCA) patients by analyzing a combination of publicly available databases, clinical patient data, and bladder tumor samples from our hospital. Single-cell and bulk RNA-seq data of bladder cancer, obtained from ENA, GEO, and TCGA databases, were utilized for our analysis. The results indicated that PFKFB3 mRNA expression was markedly elevated in bladder cancer compared to paired normal tissue. Furthermore, BLCA patients with high PFKFB3 expression exhibited a significantly worse prognosis (P < 0.05). To validate these findings, clinical data and immunohistochemistry staining were performed on specimens obtained from 89 BLCA patients who underwent radical cystectomy at either Qingdao University Affiliated Hospital or Peking Union Medical College Hospital. The findings from this verification process confirmed that high expression of PFKFB3 serves as a biomarker for predicting worse prognosis in BLCA patients (OR: 2.462, 95 % CI: 1.202-5.042, P = 0.012). To facilitate clinical application, we developed a nomogram based on four variables, including PFKFB3 expression, to predict the survival of BLCA patients. Importantly, this nomogram demonstrated a low mean prediction error of 0.03. Taken together, our findings suggest that PFKFB3 has the potential to serve as both a prognostic biomarker and a therapeutic target for BLCA patients.

Exploring the impact of PDGFD in osteosarcoma metastasis through single-cell sequencing analysis

PURPOSE

The overall survival rate for metastatic osteosarcoma hovers around 20%. Responses to second-line chemotherapy, targeted therapies, and immunotherapies have demonstrated limited efficacy in metastatic osteosarcoma. Our objective is to validate differentially expressed genes and signaling pathways between non-metastatic and metastatic osteosarcoma, employing single-cell RNA sequencing (scRNA-seq) and additional functional investigations. We aim to enhance comprehension of metastatic mechanisms and potentially unveil a therapeutic target.

METHODS

scRNA-seq was performed on two primary osteosarcoma lesions (1 non-metastatic and 1 metastatic). Seurat package facilitated dimensionality reduction and cluster identification. Copy number variation (CNV) was predicted using InferCNV. CellChat characterized ligand-receptor-based intercellular communication networks. Differentially expressed genes underwent GO function enrichment analysis and GSEA. Validation was achieved through the GSE152048 dataset, which identified PDGFD-PDGFRB as a common ligand-receptor pair with significant contribution. Immunohistochemistry assessed PDGFD and PDGFRB expression, while multicolor immunofluorescence and flow cytometry provided insight into spatial relationships and the tumor immune microenvironment. Kaplan-Meier survival analysis compared metastasis-free survival and overall survival between high and low levels of PDGFD and PDGFRB. Manipulation of PDGFD expression in primary osteosarcoma cells examined invasion abilities and related markers.

RESULTS

Ten clusters encompassing osteoblasts, osteoclasts, osteocytes, fibroblasts, pericytes, endothelial cells, myeloid cells, T cells, B cells, and proliferating cells were identified. Osteoblasts, osteoclasts, and osteocytes exhibited heightened CNV levels. Ligand-receptor-based communication networks exposed significant fibroblast crosstalk with other cell types, and the PDGF signaling pathway was activated in non-metastatic osteosarcoma primary lesion. These results were corroborated by the GSE152048 dataset, confirming the prominence of PDGFD-PDGFRB as a common ligand-receptor pair. Immunohistochemistry demonstrated considerably greater PDGFD expression in non-metastatic osteosarcoma tissues and organoids, correlating with extended metastasis-free and overall survival. PDGFRB expression showed no significant variation between non-metastatic and metastatic osteosarcoma, nor strong correlations with survival times. Multicolor immunofluorescence suggested co-localization of PDGFD with PDGFRB. Flow cytometry unveiled a highly immunosuppressive microenvironment in metastatic osteosarcoma. Manipulating PDGFD expression demonstrated altered invasive abilities and marker expressions in primary osteosarcoma cells from both non-metastatic and metastatic lesions.

CONCLUSIONS

scRNA-seq illuminated the activation of the PDGF signaling pathway in primary lesion of non-metastatic osteosarcoma. PDGFD displayed an inhibitory effect on osteosarcoma metastasis, likely through the suppression of the EMT signaling pathway.

The Genomic, Transcriptomic, and Immunologic Landscape of HRAS Mutations in Solid Tumors

Tipifarnib is the only targeted therapy breakthrough for HRAS-mutant (HRASmt) recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). The molecular profiles of HRASmt cancers are difficult to explore given the low frequency of HRASmt. This study aims to understand the molecular co-alterations, immune profiles, and clinical outcomes of 524 HRASmt solid tumors including urothelial carcinoma (UC), breast cancer (BC), non-small-cell lung cancer (NSCLC), melanoma, and HNSCC. HRASmt was most common in UC (3.0%), followed by HNSCC (2.82%), melanoma (1.05%), BC (0.45%), and NSCLC (0.44%). HRASmt was absent in Her2+ BC regardless of hormone receptor status. HRASmt was more frequently associated with squamous compared to non-squamous NSCLC (60% vs. 40% in HRASwt, p = 0.002). The tumor microenvironment (TME) of HRASmt demonstrated increased M1 macrophages in triple-negative BC (TNBC), HNSCC, squamous NSCLC, and UC; increased M2 macrophages in TNBC; and increased CD8+ T-cells in HNSCC (all p < 0.05). Finally, HRASmt was associated with shorter overall survival in HNSCC (HR: 1.564, CI: 1.16-2.11, p = 0.003) but not in the other cancer types examined. In conclusion, this study provides new insights into the unique molecular profiles of HRASmt tumors that may help to identify new targets and guide future clinical trial design.

Unraveling the causal role of immune cells in gastrointestinal tract cancers: insights from a Mendelian randomization study

Background

Despite early attempts, the relationship between immune characteristics and gastrointestinal tract cancers remains incompletely elucidated. Hence, rigorous and further investigations in this domain hold significant clinical relevance for the development of novel potential immunotherapeutic targets.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis using the tools available in the "TwoSampleMR" R package. The GWAS data for these 731 immune traits were sourced from the GWAS Catalog database. Concurrently, data on gastrointestinal tract cancers, encompassing malignant tumors in the esophagus, stomach, small intestine, colon, and rectum, were extracted from the FinnGen database. The immune traits subjected to MR analysis predominantly fall into four categories: median fluorescence intensities (MFI), relative cell (RC), absolute cell (AC), and morphological parameters (MP). To ensure the reliability of our findings, sensitivity analyses were implemented to address robustness, account for heterogeneity, and alleviate the impact of horizontal pleiotropy.

Results

A total of 78 immune traits causally linked to gastrointestinal tract cancers were identified, encompassing esophageal cancer (12 traits), gastric cancer (13 traits), small intestine cancer (22 traits), colon cancer (12 traits), and rectal cancer (19 traits). Additionally, 60 immune traits were recognized as protective factors associated with gastrointestinal tract cancers, distributed across esophageal cancer (14 traits), gastric cancer (16 traits), small intestine cancer (7 traits), colon cancer (14 traits), and rectal cancer (9 traits). Furthermore, it was observed that seven immune traits are causally related to gastrointestinal tract cancers in at least two locations. These traits include "CCR2 on CD14- CD16+ monocyte," "CD19 on IgD+ CD38-," "CD19 on IgD+ CD38- naive," "CD25hi CD45RA+ CD4 not Treg AC," "CD27 on unsw mem," "CD28 on CD39+ activated Treg," and "CD45 on CD4+."

Conclusion

This study elucidates a causal link between immune cells and gastrointestinal tract cancers at various sites through genetic investigation. The findings of this research open up new perspectives and resources for exploring tumor prevention strategies and immunotherapeutic targets.

Single-cell transcriptomics dissects premalignant progression in proliferative verrucous leukoplakia

OBJECTIVE

Proliferative verrucous leukoplakia (PVL) is characterized by a spectrum of clinicopathological features and a high risk of malignant transformation. In this study, we aimed to delineate the dynamic changes in molecular signature during PVL progression and identify the potential cell subtypes that play a key role in the premalignant evolution of PVL.

METHODS

We performed single-cell RNA sequencing on three biopsy samples from a large PVL lesion. These samples exhibited a histopathological continuum of PVL progression.

RESULTS

By analyzing the transcriptome profiles of 27,611 cells from these samples, we identified ten major cell lineages and revealed that cellular remodeling occurred during the progression of PVL lesions, including epithelial, stromal, and immune cells. Epithelial cells are shifted to tumorigenic states and secretory patterns at the premalignant stage. Immune cells showed growing immunosuppressive phenotypes during PVL progression. Remarkably, two novel cell subtypes INSR+ endothelial cells and ASPN+ fibroblasts, were discovered and may play vital roles in microenvironment remodeling, such as angiogenesis and stromal fibrosis, which are closely involved in malignant transformation.

CONCLUSION

Our work is the first to depict the cellular landscape of PVL and speculate that disease progression may be driven by functional remodeling of multiple cell subtypes.

Single-cell integrated transcriptomics reveals the role of keratinocytes in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignant tumor with significant morbidity and mortality. Understanding the molecular mechanisms of HNSCC and identifying prognostic markers and therapeutic targets are crucial for improving patient outcomes. In this study, we utilized single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data to comprehensively analyze HNSCC at the cellular level. We identified keratinocytes as the predominant cell type in tumor samples, suggesting their potential role in HNSCC development. Through hdWGCNA co-expression network analysis, we identified gene modules associated with HNSCC progression. Furthermore, we constructed a prognostic model based on specific genes and demonstrated its robust predictive performance in multiple datasets. The model exhibited strong correlations with immune cell infiltration patterns and signaling pathways related to tumor progression. Additionally, drug sensitivity analysis revealed potential chemotherapeutic targets for HNSCC treatment. Our findings provide valuable insights into the molecular characteristics and immune microenvironment of HNSCC, offering new perspectives for prognosis prediction and therapeutic interventions in clinical practice. Further research is warranted to validate and expand upon these findings, ultimately improving patient outcomes in HNSCC.

Cell-cell communication network-based interpretable machine learning predicts cancer patient response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, only some patients respond to ICIs, and current biomarkers for ICI efficacy have limited performance. Here, we devised an interpretable machine learning (ML) model trained using patient-specific cell-cell communication networks (CCNs) decoded from the patient's bulk tumor transcriptome. The model could (i) predict ICI efficacy for patients across four cancer types (median AUROC: 0.79) and (ii) identify key communication pathways with crucial players responsible for patient response or resistance to ICIs by analyzing more than 700 ICI-treated patient samples from 11 cohorts. The model prioritized chemotaxis communication of immune-related cells and growth factor communication of structural cells as the key biological processes underlying response and resistance to ICIs, respectively. We confirmed the key communication pathways and players at the single-cell level in patients with melanoma. Our network-based ML approach can be used to expand ICIs' clinical benefits in cancer patients.

Expression of PD-1 mitigates phagocytic activities TAM in osteosarcoma

The high expression of programmed death 1 (PD-1) is a hallmark of T cell exhaustion, consequently inhibiting the anti-tumor immunity, tumor-associated macrophages (TAMs) aggravate Osteosarcoma (OS) progression. However, PD-1 expression on TAMs in OS metastasis remains unclear. Here, we used scRNA-Seq of 15500 individual cells from human OS lung metastatic lesion, identified thirteen major cell clusters. Our data revealed that tumor-infiltrating lymphocytes (TILs) OS lung metastatic accompanied by accumulation of exhausted T cells and regulatory T cells (Tregs). CD3+ T cells from human OS lung metastatic exhibited lower proliferation than in primary tissue. Importantly, TAMs mainly comprise immunosuppressive M2 phenotype in OS metastasis. Mechanistically, we found that PD-1 of TAMs inhibits the phagocytic potency, further promoting the progression of OS metastasis. Therefore, the study provides a strong technical support for OS immunotherapy based on PD-1 inhibitors.

Single-cell Sequencing Data Reveals Aggressive CD68-type Macrophages and Prognostic Models in Bladder Cancer

BACKGROUND

The highly heterogeneous, complex pathological histology, and clinical phenotype in bladder cancer (BC) plague the prognostic management of BC to the present day.

METHODS

This study was conducted using single-cell sequencing data from the gene expression omnibus (GEO) database (GSE135337). A descending, annotated analysis was performed to identify the cell types contributing to BC aggressiveness. BC cell sequencing data from The Cancer Genome Atlas (TCGA) database were then combined with univariate, least absolute shrinkage and selection operator (LASSO), multivariate COX regression analysis to identify biomarkers of BC prognosis to construct a BC. We identified biomarkers of BC prognosis to construct a prognostic risk guidance system for BC. The feedback of patients in different risk strata to immunotherapy was analyzed. Finally, the regulation of prognostic genes on cancer cell activity was verified in vitro by Western blot and cell counting kit-8 (CCK8) assays.

RESULTS

Macrophages specifically expressing CD68 in BC were the cell type with the highest AUCell score, and CD68 was the biomarker of Tumor-associated macrophages (TAMs). CD68 macrophages were potentially the critical cell type in the aggressive BC subtype. Through univariate, LASSO, multivariate COX-based regression analysis. CTSS, GMFG, ANXA5, GSN, SLC2A3, and FTL were authenticated as prognostic biomarkers (p < 0.05) and composed the Risk Score. Patients in the low-risk group showed an excellent survival advantage (p < 0.01) and immunotherapy feedback. Additionally, inhibition of GSN expression decreased EMT activity to inhibit bladder cancer cell viability.

CONCLUSION

In conclusion, this study provided feedback on the immune cell types associated with aggressiveness in BC. Importantly, a prognostic management system for BC was created based on the genes involved, providing more insight into the aggressive pathological phenotype as well as the prognosis of BC.

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.

BLCA prognostic model creation and validation based on immune gene-metabolic gene combination

BACKGROUND

Bladder cancer (BLCA) is a prevalent urinary system malignancy. Understanding the interplay of immunological and metabolic genes in BLCA is crucial for prognosis and treatment.

METHODS

Immune/metabolism genes were extracted, their expression profiles analyzed. NMF clustering found prognostic genes. Immunocyte infiltration and tumor microenvironment were examined. Risk prognostic signature using Cox/LASSO methods was developed. Immunological Microenvironment and functional enrichment analysis explored. Immunotherapy response and somatic mutations evaluated. RT-qPCR validated gene expression.

RESULTS

We investigated these genes in 614 BLCA samples, identifying relevant prognostic genes. We developed a predictive feature and signature comprising 7 genes (POLE2, AHNAK, SHMT2, NR2F1, TFRC, OAS1, CHKB). This immune and metabolism-related gene (IMRG) signature showed superior predictive performance across multiple datasets and was independent of clinical indicators. Immunotherapy response and immune cell infiltration correlated with the risk score. Functional enrichment analysis revealed distinct biological pathways between low- and high-risk groups. The signature demonstrated higher prediction accuracy than other signatures. qRT-PCR confirmed differential gene expression and immunotherapy response.

CONCLUSIONS

The model in our work is a novel assessment tool to measure immunotherapy's effectiveness and anticipate BLCA patients' prognosis, offering new avenues for immunological biomarkers and targeted treatments.

Single-cell sequencing in pancreatic cancer research: A deeper understanding of heterogeneity and therapy

Pancreatic cancer, including pancreatic ductal adenocarcinomas (PDACs), is a malignant tumor with characteristics of tumor-stroma interactions. Patients often have a poor prognosis and a poor long-term survival rate. In recent years, rapidly-developing single-cell sequencing techniques have been used to analyze cell populations at a single-cell resolution, so that it is now possible to have a more in-depth and clearer understanding of the genetic composition of pancreatic cancer. In this review, we provide an overview of the current single-cell sequencing techniques and their applications in the exploration of intratumoral heterogeneity, the tumor microenvironment, therapy resistance, and novel treatments. Our hope is to provide new insight into the potential of precision therapy, which will perhaps one day lead to significant advances in PDAC treatment.

Identification of tumor immunophenotypes associated with immunotherapy response in bladder cancer

OBJECTIVES

This study aims to reveal immunophenotypes associated with immunotherapy response in bladder cancer, identify the signature genes of immune subtypes, and provide new molecular targets for improving immunotherapy response.

METHODS

Bladder cancer immunophenotypes were characterized in the bulk RNA sequencing dataset GSE32894 and Imvigor210, and gene expression signatures were established to identify the immunophenotypes. Expression of gene signatures were validated in single-cell RNA sequencing dataset GSE145140 and human proteins expression data source. Investigation of Immunotherapy Response was performed in IMvigor210 dataset. Prognosis of tumor immunophenotypes was further analyzed.

RESULTS

Inflamed and immune-excluded immunophenotypes were characterized based on the tumor immune cell scores. Risk score models that were established rely on RNA sequencing profiles and overall survival of bladder cancer cohorts. The inflamed tumors had lower risk scores, and the low-risk tumors were more likely to respond to atezolizumab, receiving complete response/partial response (CR/PR). Patients who responded to atezolizumab had higher SRRM4 and lower NPHS1 and TMEM72 expression than the non-responders. SRRM4 expression was a protective factor for bladder cancer prognosis, while the NPHS1 and TMEM72 showed the opposite pattern.

CONCLUSION

This study provided a novel classification method for tumor immunophenotypes. Bladder cancer immunophenotypes can predict the response to immune checkpoint blockade. The immunophenotypes can be identified by the expression of signature genes.

Quenching thirst with poison? Paradoxical effect of anticancer drugs

Anticancer drugs have been developed with expectations to provide long-term or at least short-term survival benefits for patients with cancer. Unfortunately, drug therapy tends to provoke malignant biological and clinical behaviours of cancer cells relating not only to the evolution of resistance to specific drugs but also to the enhancement of their proliferation and metastasis abilities. Thus, drug therapy is suspected to impair long-term survival in treated patients under certain circumstances. The paradoxical therapeutic effects could be described as 'quenching thirst with poison', where temporary relief is sought regardless of the consequences. Understanding the underlying mechanisms by which tumours react on drug-induced stress to maintain viability is crucial to develop rational targeting approaches which may optimize survival in patients with cancer. In this review, we describe the paradoxical adverse effects of anticancer drugs, in particular how cancer cells complete resistance evolution, enhance proliferation, escape from immune surveillance and metastasize efficiently when encountered with drug therapy. We also describe an integrative therapeutic framework that may diminish such paradoxical effects, consisting of four main strategies: (1) targeting endogenous stress response pathways, (2) targeting new identities of cancer cells, (3) adaptive therapy- exploiting subclonal competition of cancer cells, and (4) targeting tumour microenvironment.

Effective Antitumor Immunity Can Be Triggered by Targeting VISTA in Combination with a TLR3-Specific Adjuvant

Resistance to anti-PD-1/PD-L1 treatment is often associated with accumulation of intratumoral inhibitory macrophages. V-domain immunoglobulin suppressor of T-cell activation (VISTA) is a nonredundant immune checkpoint that can induce both T-cell and myeloid-cell immunosuppression. In this study, we found that high levels of VISTA+ immune cells were associated with advanced stage bladder cancer and predicted poor survival in patients. A combination of high infiltration of VISTA+ immune cells and PD-L1+ immune cells or PD-1+ T cells predicted the worst survival. Flow cytometry and multiplex immunofluorescence analyses confirmed that VISTA expression was higher in macrophages than in T cells or neutrophils, and only VISTA+CD163+ macrophage density predicted poor prognosis in patients with bladder cancer. Toll-like receptor (TLR) agonists are known to trigger the innate immune response in macrophages. We found that the VISTA-specific mAb 13F3 augmented the ability of a TLR3-specific adjuvant to induce macrophage activation in vitro. In the MB49 syngeneic mouse model of bladder cancer, treatment with 13F3 curbed tumor growth and prolonged survival when combined with a TLR3-specific adjuvant. The combination treatment reduced the intratumoral frequency of CD206+ anti-inflammatory macrophages and levels of the immunosuppressive molecule TGFβ1, but it upregulated expression of immunostimulatory molecules (Ifna, Ifnb, and Trail) and increased the CD8+ T cell/regulatory T-cell ratio. These findings indicate that elevated VISTA expression in immune cells, particularly macrophages, is associated with an unfavorable prognosis in patients with bladder cancer and suggest that targeting VISTA in combination with a TLR3-specific adjuvant has translational potential.

Single-nucleus RNA sequencing reveals heterogenous microenvironments and specific drug response between cervical squamous cell carcinoma and adenocarcinoma

BACKGROUND

Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAde) are two major pathological types of cervical cancer (CC), but their high-resolution heterogeneity of tumor and immune microenvironment remains elusive.

METHODS

Here, we performed single-nucleus RNA sequencing (snRNA-seq) from five CSCC and three CAde samples, and systematically outlined their specific transcriptome atlas.

FINDINGS

We found CD8+ T cells in CSCC were more cytotoxic but lower exhausted compared to those in CAde, and phagocytic MRC1+ macrophages were specifically enriched in CSCC. Interestingly, we discovered that pro-tumoral cancer-associated myofibroblasts (myoCAFs) and cancer-associated vascular-fibroblasts (vCAFs) were more abundant in CSCC, and further verified their pro-metastatic roles in vitro. Furthermore, we also identified some specific chemotherapy drugs for CSCC (Dasatinib and Doramapimod) and CAde (Pyrimethamine and Lapatinib) by revealing their heterogeneity in transcriptomic profiles of malignant epithelial cells, and further verified their specific sensitivity in cell lines and constructed CC-derived organoids. Cell-cell communication networks revealed that the pathways of NRG1-ERBB2, and FN1-ITAG3 were specific for CAde and CSCC, respectively, which may partly explain the specificities of identified chemotherapy drugs.

INTERPRETATION

Our study described the immune heterogeneity and specific cellular interactions between CSCC and CAde, which could provide insights for uncovering pathogenesis and designing personalized treatment.

FUNDINGS

National Key R&D Program of China (2021YFC2701201), National Natural Science Foundation of China (82072895, 82141106, 82103134, 81903114).

IL-8 is a novel prometastatic chemokine in intrahepatic cholangiocarcinoma that induces CXCR2-PI3K/AKT signaling upon CD97 activation

Intrahepatic cholangiocarcinoma (ICC) is a rare but highly aggressive malignant tumor arising within the liver, with a 5-year survival rate of only 20-40% after surgery. The role of interleukin-8 (IL-8) in ICC progression remains elusive. A transcriptomic approach based on IL-8 stimulation first revealed significant upregulation of the prometastatic gene CD97 and key epithelial-mesenchymal transition (EMT) factors E-cadherin and vimentin. Immunohistochemistry of 125 ICC tissues confirmed the positive correlation between IL-8 and CD97. Multivariable Cox regression indicated that they are both independent predictors of ICC prognosis. Mechanistically, IL-8 treatment induced CD97 expression at 50 and 100 ng/ml in QBC-939 and QBE cells, respectively. Moreover, the induction of cell migration and invasion upon IL-8 treatment was attenuated by CD97 RNA interference, and the expression of EMT-associated genes was dramatically inhibited. To determine whether CXCR1 or CXCR2 are downstream effectors of IL-8, siCXCR2 was applied and shown to significantly attenuate the oncogenic effects of IL-8 by inhibiting the phosphorylation of PI3K/AKT. Finally, the induction of CD97 expression by the PI3K pathway was verified by treatment with the inhibitor LY294002. In vivo, the significant tumor growth and lung metastasis effects induced by intraperitoneal injection of IL-8 were greatly inhibited by silencing CD97 in nude mice. Collectively, the study presents a novel mechanism of the IL-8-CXCR2-PI3K/AKT axis in regulating CD97 expression, which leads to ICC metastasis mainly through EMT. The study may provide alternatives for targeting the tumor microenvironment in metastatic ICC.

SIGANEO: Similarity network with GAN enhancement for immunogenic neoepitope prediction

Target selection of the personalized cancer neoantigen vaccine, which is highly dependent on computational prediction algorithms, is crucial for its clinical efficacy. Due to the limited number of experimentally validated immunogenic neoepitopes as well as the complexity of neoantigens in eliciting T cell response, the accuracy of neoepitope immunogenicity prediction methods requires persistent efforts for improvement. We present a deep learning framework for neoepitope immunogenicity prediction - SIGANEO by integrating GAN-like network with similarity network to address issues of missing values and limited data concerning neoantigen prediction. This framework exhibits superior performance over competing machine-learning-based neoantigen prediction algorithms over an independent test dataset from TESLA consortium. Particularly for the clinical setting of neoantigen vaccine where only the top 10 and 20 predictions are selected for vaccine production, SIGANEO achieves significantly better accuracy for predicting experimentally validated neoepitopes. Our work demonstrates that deep learning techniques can greatly boost the accuracy of target identification for cancer neoantigen vaccine.

Reconstructing disease dynamics for mechanistic insights and clinical benefit

Diseases change over time, both phenotypically and in their underlying molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult due to their complexity and the high heterogeneity in disease development between individuals. We present TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional, short time-series data. We demonstrate the utility of TimeAx by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identify a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiates between early and late tumors within the same tumor subtype, uncovering molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics-providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

Identification of tryptophan metabolism- and immune-related genes signature and prediction of immune infiltration landscape in bladder urothelial carcinoma

Introduction

Tryptophan metabolism is indirectly involved in immune tolerance and promotes response to anticancer drugs. However, the mechanisms underlying tryptophan metabolism and immune landscape in bladder urothelial carcinoma (BLCA) are not fully understood.

Methods

A BLCA dataset containing 406 tumor samples with clinical survival information and 19 normal samples were obtained from the Cancer Genome Atlas database. The validation set, GSE32894, contained 223 BLCA tumor samples with survival information, and the single-cell dataset, GSE135337, included seven BLCA tumor samples; both were obtained from the gene expression omnibus database. Univariate and multivariate Cox regression analyses were conducted to evaluate clinical parameters and risk scores. Immune infiltration and checkpoint analyses were performed to explore the immune landscape of BLCA. Single-cell analysis was conducted to further identify the roles of model genes in BLCA. Finally, NAMPT expression in BLCA and adjacent tissues was detected using RT-qPCR, CCK-8 and Transwell assays were conducted to determine the role of NAMPT in BLCA cells.

Results

Six crossover genes (TDO2, ACAT1, IDO1, KMO, KYNU, and NAMPT) were identified by overlap analysis of tryptophan metabolism-related genes, immune-related genes, and differentially expressed genes (DEGs). Three biomarkers, NAMPT, IDO1, and ACAT1, were identified using Cox regression analysis. Accordingly, a tryptophan metabolism- and immune-related gene risk model was constructed, and the patients were divided into high- and low-risk groups. There were significant differences in the clinical parameters, prognosis, immune infiltration, and immunotherapy response between the risk groups. RT-qPCR revealed that NAMPT was upregulated in BLCA samples. Knocking down NAMPT significantly inhibited BLCA cell proliferation, migration, and invasion.

Discussion

In our study, we constructed a tryptophan metabolism- and immune-related gene risk model based on three biomarkers, namely NAMPT, IDO1, and ACAT1, that were significantly associated with the progression and immune landscape of BLCA. The risk model could effectively predict patient prognosis and immunotherapy response and can guide individualized immunotherapy.

Single-cell dissection of tumor microenvironmental response and resistance to cancer therapy

Cancer treatment strategies have evolved significantly over the years, with chemotherapy, targeted therapy, and immunotherapy as major pillars. Each modality leads to unique treatment outcomes by interacting with the tumor microenvironment (TME), which imposes a fundamental selective pressure on cancer progression. The advent of single-cell profiling technologies has revolutionized our understanding of the intricate and heterogeneous nature of the TME at an unprecedented resolution. This review delves into the commonalities and differential manifestations of how cancer therapies reshape the microenvironment in diverse cancer types. We highlight how groundbreaking immune checkpoint blockade (ICB) strategies alone or in combination with tumor-targeting treatments are endowed with comprehensive mechanistic insights when decoded at the single-cell level, aiming to drive forward future research directions on personalized treatments.

Combination of multiple omics techniques for a personalized therapy or treatment selection

Despite targeted therapies and immunotherapies have revolutionized the treatment of cancer patients, only a limited number of patients have long-term responses. Moreover, due to differences within cancer patients in the tumor mutational burden, composition of the tumor microenvironment as well as of the peripheral immune system and microbiome, and in the development of immune escape mechanisms, there is no "one fit all" therapy. Thus, the treatment of patients must be personalized based on the specific molecular, immunologic and/or metabolic landscape of their tumor. In order to identify for each patient the best possible therapy, different approaches should be employed and combined. These include (i) the use of predictive biomarkers identified on large cohorts of patients with the same tumor type and (ii) the evaluation of the individual tumor with "omics"-based analyses as well as its ex vivo characterization for susceptibility to different therapies.

Single-cell profiling of murine bladder cancer identifies sex-specific transcriptional signatures with prognostic relevance

Bladder cancer (BLCA) is more common in men but more aggressive in women. Sex-based differences in cancer biology are commonly studied using a murine model with BLCA generated by N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN). While tumors in the BBN model have been profiled, these profiles provide limited information on the tumor microenvironment. Here, we applied single-cell RNA sequencing to characterize cell-type specific transcriptional differences between male and female BBN-induced tumors. We found proportional and gene expression differences in epithelial and non-epithelial subpopulations between male and female tumors. Expression of several genes predicted sex-specific survival in several human BLCA datasets. We identified novel and clinically relevant sex-specific transcriptional signatures including immune cells in the tumor microenvironment and it validated the relevance of the BBN model for studying sex differences in human BLCA. This work highlights the importance of considering sex as a biological variable in the development of new and accurate cancer markers.

S100A5 Attenuates Efficiency of Anti-PD-L1/PD-1 Immunotherapy by Inhibiting CD8+ T Cell-Mediated Anti-Cancer Immunity in Bladder Carcinoma

Although immune checkpoint blockade (ICB) therapies have been approved for bladder cancer (BLCA), only a minority of patients respond to these therapies, and there is an urgent need to explore combined therapies. Systematic multi-omics analysis identified S100A5 as a novel immunosuppressive target for BLCA. The expression of S100A5 in malignant cells inhibited CD8+ T cell recruitment by decreasing pro-inflammatory chemokine secretion. Furthermore, S100A5 attenuated effector T cell killing of cancer cells by inhibiting CD8+ T cell proliferation and cytotoxicity. In addition, S100A5 acted as an oncogene, thereby promoting tumor proliferation and invasion. Targeting S100A5 synergized with the efficacy of anti-PD-1 treatment by enhancing infiltration and cytotoxicity of CD8+ T cells in vivo. Clinically, there was a spatially exclusive relationship between S100A5+ tumor cells and CD8+ T cells in tissue microarrays. Moreover, S100A5 negatively correlated with immunotherapy efficacy in our real-world and several public immunotherapy cohorts. In summary, S100A5 shapes a non-inflamed tumor microenvironment in BLCA by inhibiting the secretion of pro-inflammatory chemokines and the recruitment and cytotoxicity of CD8+ T cells. Targeting S100A5 converts cold tumors into hot tumors, thus enhancing the efficacy of ICB therapy in BLCA.

A novel metabolic subtype with S100A7 high expression represents poor prognosis and immuno-suppressive tumor microenvironment in bladder cancer

BACKGROUND

Bladder cancer (BLCA) represents a highly heterogeneous disease characterized by distinct histological, molecular, and clinical features, whose tumorigenesis and progression require aberrant metabolic reprogramming of tumor cells. However, current studies have not expounded systematically and comprehensively on the metabolic heterogeneity of BLCA.

METHODS

The UCSC XENA portal was searched to obtain the expression profiles and clinical annotations of BLCA patients in the TCGA cohort. A total of 1,640 metabolic-related genes were downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, consensus clustering was performed to divide the BLCA patients into two metabolic subtypes according to the expression of metabolic-related genes. Kaplan-Meier analysis was used to measure the prognostic values of the metabolic subtypes. Subsequently, comparing the immune-related characteristics between the two metabolic subtypes to describe the immunological difference. Then, the Scissor algorithm was applied to link the metabolic phenotypes and single-cell transcriptome datasets to determine the biomarkers associated with metabolic subtypes and prognosis. Finally, the clinical cohort included 63 BLCA and 16 para-cancerous samples was used to validate the prognostic value and immunological correlation of the biomarker.

RESULTS

BLCA patients were classified into two heterogeneous metabolic-related subtypes (MRSs) with distinct features: MRS1, the subtype with no active metabolic characteristics but an immune infiltration microenvironment; and MRS2, the lipogenic subtype with upregulated lipid metabolism. These two subtypes had distinct prognoses, molecular subtypes distributions, and activations of therapy-related pathways. MRS1 BLCAs preferred to be immuno-suppressive and up-regulated immune checkpoints expression, suggesting the well-therapeutic response of MRS1 patients to immunotherapy. Based on the Scissor algorithm, we found that S100A7 both specifically up-regulated in the MRS1 phenotype and MRS1-tumor cells, and positively correlated with immunological characteristics. In addition, in the clinical cohort included 63 BLCA and 16 para-cancerous samples, S100A7 was obviously associated with poor prognosis and enhanced PD-L1 expression.

CONCLUSIONS

The metabolic subtype with S100A7 high expression recognizes the immuno-suppressive tumor microenvironment and predicts well therapeutic response of immunotherapy in BLCA. The study provides new insights into the prognostic and therapeutic value of metabolic heterogeneity in BLCA.

Bioinformatics analysis and single-cell RNA sequencing: elucidating the ubiquitination pathways and key enzymes in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a prevalent subtype of lung cancer associated with high mortality rates. We aimed to utilize single-cell multiomics analysis to identify the key molecules involved in ubiquitination modification, which plays a role in LUAD development and progression.

METHODS

We use a systematic approach to analyze LUAD-related single-cell and bulk transcriptome datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Single-cell RNA sequencing (scRNA-seq) data were normalized, clustered, and annotated with the Seurat package in R. InferCNV was used to distinguish malignant from epithelial cells, and AUCell evaluated the area under the curve (AUC) score of ubiquitination-related enzymes. Survival and differential analyses identified significant molecular markers associated with ubiquitination. PSMD14 expression was confirmed using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) and Western blot assays, and its knockdown cell lines were assessed for effects on cellular processes and tumor formation in mice. PSMD14's interacting proteins were predicted, and its impact on AGR2 protein half-life and ubiquitination was evaluated. Rescue experiments involving PSMD14 overexpression and AGR2 silencing assessed their impact on malignant behaviors.

RESULTS

By means of single-cell sequencing analysis, we probed the ubiquitination modification landscape in the LUAD microenvironment. Malignant cells had elevated scores for enzymes and ubiquitin-binding domains compared to normal epithelial cells, with 53 ubiquitination-related molecules showing prognostic disparities. FGR, PSMD14, and ZBTB16 were identified as genes with prognostic significance, with PSMD14 showing higher expression in epithelial and malignant cells. Two missense mutation sites were identified in PSMD14, which had a high copy number amplification ratio and positive correlation with messenger RNA (mRNA) expression. PSMD14 expression and tumor stage were found to be independent prognostic factors, and interfering with PSMD14 expression reduced the malignant behavior of LUAD cells. PSMD14 was found to bind to AGR2 protein and reduce its ubiquitination, leading to increased AGR2 stability. Knockdown of AGR2 inhibited the enhancement of cell viability, invasion, and migration resulting from PSMD14 overexpression.

CONCLUSIONS

This study examined ubiquitination modifications in LUAD using sequencing data, identifying PSMD14's critical role in malignancy regulation and its potential as a prognostic and therapeutic biomarker. These insights enhance understanding of LUAD mechanisms and treatment.

Construction and experimental validation of a B cell-related gene signature to predict the prognosis and immunotherapeutic sensitivity in bladder cancer

BACKGROUND

B cells are essential components of tumor microenvironment and exert important functions in anti-tumor immune response. However, the prognosis value of B cell-related genes in bladder cancer (BLCA) remains obscure.

MATERIALS AND METHODS

The infiltrating levels of B cells were measured via the CD20 staining in the local samples and the computational biology analyses in the TCGA-BLCA cohort. The single-cell RNA sequencing analysis, gene-pair strategy, LASSO regression, random forest, and Cox regression were used for B cell-related signature construction. TCGA-BLCA cohort was chosen as the training cohort, and three independent cohorts from GEO and the local cohort were used for external validation. 326 B cells were adopted to explore the association between the model and B cells' biological processes. TIDE algorithm and two BLCA cohorts receiving anti-PD1/PDL1 treatment were utilized to detect its predictive ability to the immunotherapeutic response.

RESULTS

High infiltration levels of B cells heralded favorable prognosis, both in the TCGA-BLCA cohort and the local cohort (all P < 0.05). A 5-gene-pair model was established and served as a significant prognosis predictor across multiple cohorts (pooled hazard ratio = 2.79, 95% confidence interval = 2.22-3.49). The model could evaluate the prognosis effectively in 21 of 33 cancer types (P < 0.05). The signature was negatively associated with B cells' activation, proliferation, and infiltrating levels, and could serve as a potential predictor of immunotherapeutic outcomes.

CONCLUSIONS

A B cell-related gene signature was constructed to predict the prognosis and immunotherapeutic sensitivity in BLCA, helping to guide the personalized treatment.

Epigenetic and Immunological Features of Bladder Cancer

Bladder cancer (BLCA) is one of the most common types of malignant tumors of the urogenital system in adults. Globally, the incidence of BLCA is more than 500,000 new cases worldwide annually, and every year, the number of registered cases of BLCA increases noticeably. Currently, the diagnosis of BLCA is based on cystoscopy and cytological examination of urine and additional laboratory and instrumental studies. However, cystoscopy is an invasive study, and voided urine cytology has a low level of sensitivity, so there is a clear need to develop more reliable markers and test systems for detecting the disease with high sensitivity and specificity. Human body fluids (urine, serum, and plasma) are known to contain significant amounts of tumorigenic nucleic acids, circulating immune cells and proinflammatory mediators that can serve as noninvasive biomarkers, particularly useful for early cancer detection, follow-up of patients, and personalization of their treatment. The review describes the most significant advances in epigenetics of BLCA.

Single-cell RNA sequencing revealed subclonal heterogeneity and gene signatures of gemcitabine sensitivity in pancreatic cancer

Introduction: Resistance to gemcitabine is common and critically limits its therapeutic efficacy in pancreatic ductal adenocarcinoma (PDAC). Methods: We constructed 17 patient-derived xenograft (PDX) models from PDAC patient samples and identified the most notable responder to gemcitabine by screening the PDX sets in vivo. To analyze tumor evolution and microenvironmental changes pre- and post-chemotherapy, single-cell RNA sequencing (scRNA-seq) was performed. Results: ScRNA-seq revealed that gemcitabine promoted the expansion of subclones associated with drug resistance and recruited macrophages related to tumor progression and metastasis. We further investigated the particular drug-resistant subclone and established a gemcitabine sensitivity gene panel (GSGP) (SLC46A1, PCSK1N, KRT7, CAV2, and LDHA), dividing PDAC patients into two groups to predict the overall survival (OS) in The Cancer Genome Atlas (TCGA) training dataset. The signature was successfully validated in three independent datasets. We also found that 5-GSGP predicted the sensitivity to gemcitabine in PDAC patients in the TCGA training dataset who were treated with gemcitabine. Discussion and conclusion: Our study provides new insight into the natural selection of tumor cell subclones and remodeling of tumor microenvironment (TME) cells induced by gemcitabine. We revealed a specific drug resistance subclone, and based on the characteristics of this subclone, we constructed a GSGP that can robustly predict gemcitabine sensitivity and prognosis in pancreatic cancer, which provides a theoretical basis for individualized clinical treatment.

Focusing on scRNA-seq-Derived T Cell-Associated Genes to Identify Prognostic Signature and Immune Microenvironment Status in Low-Grade Glioma

Background

The clinical outcomes of low-grade glioma (LGG) are associated with T cell infiltration, but the specific contribution of heterogeneous T cell types remains unclear.

Method

To study the different functions of T cells in LGG, we mapped the single-cell RNA sequencing results of 10 LGG samples to obtain T cell marker genes. In addition, bulk RNA data of 975 LGG samples were collected for model construction. Algorithms such as TIMER, CIBERSORT, QUANTISEQ, MCPCOUTER, XCELL, and EPIC were used to depict the tumor microenvironment landscape. Subsequently, three immunotherapy cohorts, PRJEB23709, GSE78820, and IMvigor210, were used to explore the efficacy of immunotherapy.

Results

The Human Primary Cell Atlas was used as a reference dataset to identify each cell cluster; a total of 15 cell clusters were defined and cells in cluster 12 were defined as T cells. According to the distribution of T cell subsets (CD4+ T cell, CD8+ T cell, Naïve T cell, and Treg cell), we selected the differentially expressed genes. Among the CD4+ T cell subsets, we screened 3 T cell-related genes, and the rest were 28, 4, and 13, respectively. Subsequently, according to the T cell marker genes, we screened six genes for constructing the model, namely, RTN1, HERPUD1, MX1, SEC61G, HOPX, and CHI3L1. The ROC curve showed that the predictive ability of the prognostic model for 1, 3, and 5 years was 0.881, 0.817, and 0.749 in the TCGA cohort, respectively. In addition, we found that risk scores were positively correlated with immune infiltration and immune checkpoints. To this end, we obtained three immunotherapy cohorts to verify their predictive ability of immunotherapy effects and found that high-risk patients had better clinical effects of immunotherapy.

Conclusion

This single-cell RNA sequencing combined with bulk RNA sequencing may elucidate the composition of the tumor microenvironment and pave the way for the treatment of low-grade gliomas.

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

N7-methylguanosine (m7G) modification signature has recently emerged as a crucial regulator of tumor progression and treatment in cancer. However, there is limited information available on the genomic profile of lower-grade gliomas (LGGs) related to m7G methylation modification genes' function in tumorigenesis and progression. In this study, we employed bioinformatics methods to characterize m7G modifications in individuals with LGG from The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). We used gene set enrichment analysis (GSEA), single sample GSEA (ssGSEA), CIBERSORT algorithm, ESTIMATE algorithm, and TIDE to evaluate the association between m7G modification patterns, tumor microenvironment (TME) cell infiltration properties, and immune infiltration markers. The m7G scoring scheme using principal component analysis (PCA) was employed to investigate the m7G modification patterns quantitatively. We examined the m7G modification hub genes' expression levels in normal samples, refractory epilepsy samples, and LGG samples using immunohistochemistry, western-blotting, and qRT-PCR. Our findings revealed that individuals with LGG could be categorized into two groups based on m7G scores (high and low) according to the properties of m7G. Moreover, we observed that high m7G score was associated with significant clinical benefit and prolonged survival duration in the anti-PD-1 cohort, while low m7G score was associated with improved prognostic outcomes and increased likelihood of complete or partial response in the anti-PD-L1 cohort. Different m7G subtypes also showed varying Tumor Mutational Burden (TMB) and immune profiles and might have distinct responses to immunotherapy. Furthermore, we identified five potential genetic markers that were highly correlated with the m7G score signature index. These findings provide insight into the features and classification associated with m7G methylation modifications and may aid in improving the clinical outcome of LGG.

Digital Twins for Predictive, Preventive Personalized, and Participatory Treatment of Immune-Mediated Diseases

Digital twins are computational models of complex systems, which aim to understand and optimize those systems more effectively than would be possible in real life. Ideally, digital twins can be translated to individual patients, to characterize and computationally treat their diseases with thousands of drugs, to select the drug or drugs that cure the patients. The background problem is that many patients do not respond adequately to drug treatment. This problem reflects a wide gap between the complexity of diseases and clinical practice. Each disease may involve altered interactions between thousands of genes that vary between different cell types in different organs. To our knowledge, these altered interactions have not been characterized on a genome-, cellulome-, and organ-wide scale in any disease. Thus, clinical translation of the digital twin ideal for predictive, preventive, personalized and participatory treatment involves formidable challenges, which are close to the limits of, or beyond today's technologies. Here, I discuss recent developments and challenges in relation to that ideal focusing on immune-mediated inflammatory diseases, as well as examples from other diseases.

Single-cell RNA-seq Reveals Intratumoral Heterogeneity in Osteosarcoma Patients: A Review

While primary bone malignancies make up just 0.2% of all cancers, osteosarcoma (OS) is the third most common cancer in adolescents. Due to its highly complex and heterogeneous tumor microenvironment (TME), OS has proven difficult to treat. There has been little to no improvement in therapy for this disease over the last 40 years. Even the recent success of immunotherapies in other blood-borne and solid malignancies has not translated to OS. With frequent recurrence and lung metastases continuing to pose a challenge in the clinic, recent advancements in molecular profiling, such as single-cell RNA sequencing (scRNA-seq), have proven useful in identifying novel biomarkers of OS tumors while providing new insight into this TME that could potentially lead to new therapeutic options. This review combines the analyses of over 150,000 cells from 18 lesions ranging from primary, recurrent, and metastatic OS lesions, revealing distinct cellular populations and gene signatures that exist between them. Here, we detail these previous findings and ultimately convey the intratumoral heterogeneity that exists within OS tumor specimens.

Exploring heterogeneity of tumor immune cells and adrenal cells in aldosterone-producing adenomas using single-cell RNA-seq and investigating differences by sex

The mechanism behind the higher incidence of aldosterone-producing adenoma (APA) in women compared to men is not yet understood. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to investigate the immune cell infiltration and adrenal cell characteristics in APA. Our findings revealed a high presence of immune cells in the tumor microenvironment, with macrophages and T lymphocytes being the most prevalent. Comparison of infiltrating cells between males and females showed that female CD8+T cells had stronger cytotoxic and inflammation-related functions, while female myeloid cells had more enrichment in inflammatory pathways. Additionally, we found that female adrenal cells had greater upregulation of immune-related and antigen presentation pathways. Furthermore, our analysis revealed that zona glomerulosa (ZG) cells had a higher capability for aldosterone synthesis. These results provide a deeper understanding of the APA microenvironment in patients of different sexes and offer new insights into the onset of APA.

C1Q labels a highly aggressive macrophage-like leukemia population indicating extramedullary infiltration and relapse

Extramedullary infiltration (EMI) is a concomitant manifestation that may indicate poor outcome of acute myeloid leukemia (AML). The underlying mechanism remains poorly understood and therapeutic options are limited. Here, we employed single-cell RNA sequencing on bone marrow (BM) and EMI samples from a patient with AML presenting pervasive leukemia cutis. A complement C1Q+ macrophage-like leukemia subset, which was enriched within cutis and existed in BM before EMI manifestations, was identified and further verified in multiple patients with AML. Genomic and transcriptional profiling disclosed mutation and gene expression signatures of patients with EMI that expressed high levels of C1Q. RNA sequencing and quantitative proteomic analysis revealed expression dynamics of C1Q from primary to relapse. Univariate and multivariate analysis demonstrated adverse prognosis significance of C1Q expression. Mechanistically, C1Q expression, which was modulated by transcription factor MAF BZIP transcription factor B, endowed leukemia cells with tissue infiltration ability, which could establish prominent cutaneous or gastrointestinal EMI nodules in patient-derived xenograft and cell line-derived xenograft models. Fibroblasts attracted migration of the C1Q+ leukemia cells through C1Q-globular C1Q receptor recognition and subsequent stimulation of transforming growth factor β1. This cell-to-cell communication also contributed to survival of C1Q+ leukemia cells under chemotherapy stress. Thus, C1Q served as a marker for AML with adverse prognosis, orchestrating cancer infiltration pathways through communicating with fibroblasts and represents a compelling therapeutic target for EMI.

IP-score correlated to endogenous tumour antigen peptide processing: A candidate clinical response score algorithm of immune checkpoint inhibitors therapy in multiple cohorts

The processing of endogenous tumour antigen peptides was essential for anti-tumour immunity in the tumour microenvironment. A high degree of Endogenous tumour antigen peptide processing has been demonstrated to improve the prognosis of carcinoma patients. However, there is insufficient evidence to prove its effect on the clinical response to immune checkpoint inhibitor therapy. To undertake a more in-depth analysis of the effects of the aforementioned genes on immunotherapy, we constructed a gene set evaluation score system relevant to tumour endogenous antigen peptide therapy using the GSVA approach. This rating mechanism is known as IP score (IPs). Immediately afterwards, we used the TCGA pan-cancer cohorts to conduct a comprehensive analysis of 6 genes in the IPs, and the analysis results showed that these six genes were related to the proportion of CD8⁺ T lymphocytes in a variety of solid tumours. As a prognostic protective factor for solid tumours, patients had better prognosis outcomes in the group with high expression levels of the above genes. We analysed the differential expression of six genes between immune checkpoint inhibitor treatment response and disease progression groups using several treatment cohorts. The results revealed that after treatment with PD-1 or CTLA4 inhibitors, the expression levels of the above six genes were comparatively high in the effective group, but the expression of the signature genes was dramatically downregulated in the ICI-insensitive groups. This indicates that the 6 genes are related to the clinical response to ICI treatment. Finally, we used the GSVA method to evaluate the above signatures, and the results showed that PDCD1, CTAL4, CD274 and LAG3 were significantly higher expressed in the IPs high-expression group; therefore, based on the processing of endogenous antigenic peptides in tumours, a predictive score of clinical response to immune checkpoint inhibitor therapy composed of 6 genes(PSMB8/PSMB9/PSMB10/PSME1/PSME2/IRF1) was constructed, and the role of each independent variable in the signature in the solid tumour microenvironment and the impact on ICI treatment were comprehensively analysed. This study provides a candidate evaluation score for predicting clinical response to immune checkpoint inhibitor therapy.

Up-Regulation of SH3TC2 Induced by YTHDF1 Predicts Poor Outcome and Facilitates Cell-Cycle Progress in Colorectal Cancer

N6-methyladenosine (m6A) modification plays a crucial role in determining the fate and function of RNA transcripts in tumor cells. Nevertheless, how m6A regulates the expression of key molecules and coordinates its involvement in the development of colorectal cancer (CRC) remains largely unclear. Here, we report that the m6A reading protein YTHDF1-mediated up-regulation of SH3TC2 promotes CRC growth both in vitro and in vivo. In a pan-cancer analysis across more than thirty types of cancer, we found that SH3TC2 was dysregulated in nine cancers, including BLCA, CHOL, COAD, LAML, PAAD, READ, SKCM, BRCA, and TGCT, and was closely associated with patient prognosis in four cancers, including COAD, MESO, PAAD, and READ. In particular, SH3TC2 was overexpressed in CRC as confirmed by six independent study cohorts. Clinically, high expression of SH3TC2 predicted worse disease-free survival (DFS) in CRC patients. SH3TC2 showed fascinating diagnostic value and was correlated with immunosuppression in CRC. Functionally, RNA-sequencing combined with experiments revealed that knockdown of SH3TC3 significantly inhibited cell-cycle progress of CRC, impairing cell growth. Mechanistically, YTHDF1 protein directly binds with SH3TC2 mRNA and promotes its elevation in an m6A-dependent manner. Thus, our findings provide a mechanism to target the YTHDF1/SH3TC2 axis for CRC therapy.

Single-cell sequencing reveals the landscape of the tumor microenvironment in a skeletal undifferentiated pleomorphic sarcoma patient

Skeletal undifferentiated pleomorphic sarcoma (SUPS) is an invasive pleomorphic soft tissue sarcoma with a high degree of malignancy and poor prognosis. It is prone to recur and metastasize. The tumor microenvironment (TME) and the pathophysiology of SUPS are barely described. Single-cell RNA sequencing (scRNA-seq) provides an opportunity to dissect the landscape of human diseases at an unprecedented resolution, particularly in diseases lacking animal models, such as SUPS. We performed scRNA-seq to analyze tumor tissues and paracancer tissues from a SUPS patient. We identified the cell types and the corresponding marker genes in this SUPS case. We further showed that CD8+ exhausted T cells and Tregs highly expressed PDCD1, CTLA4 and TIGIT. Thus, PDCD1, CTLA4 and TIGIT were identified as potential targets in this case. We applied copy number karyotyping of aneuploid tumors (CopyKAT) to distinguish malignant cells from normal cells in fibroblasts. Our study identified eight malignant fibroblast subsets in SUPS with distinct gene expression profiles. C1-malignant Fibroblast and C6-malignant Fibroblast in the TME play crucial roles in tumor growth, angiogenesis, metastasis and immune response. Hence, targeting malignant fibroblasts could represent a potential strategy for this SUPS therapy. Intervention via tirelizumab enabled disease control, and immune checkpoint inhibitors (ICIs) of PD-1 may be considered as the first-line option in patients with SUPS. Taken together, scRNA-seq analyses provided a powerful basis for this SUPS treatment, improved our understanding of complex human diseases, and may afforded an alternative approach for personalized medicine in the future.

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Bladder cancer is among the most common malignant tumors with highly heterogeneous molecular characteristics. Despite advancements of the available therapeutic options, several bladder cancer patients exhibit unsatisfactory clinical outcomes. The lack of specific biomarkers for effective targeted therapy or immunotherapy remains a major obstacle in treating bladder cancer. The rapid development of single-cell techniques is transforming our understanding of the intra-tumoral heterogeneity, thereby providing us with a powerful high-throughput sequencing tool that can reveal tumorigenesis, progression, and invasion in bladder tumors. In this review, we summarise and discuss how single-cell sequencing technologies have been applied in bladder cancer research, to advance our collective knowledge on the heterogeneity of bladder tumor cells, as well as to provide new insights into the complex ecosystem of the tumor microenvironment. The application of single-cell approaches also uncovers the therapeutic resistance mechanism in bladder cancer and facilitates the detection of urinary-exfoliated tumor cells. Moreover, benefiting from the powerful technical advantages of single-cell techniques, several key therapeutic targets and prognostic models of bladder cancer have been identified. It is hoped that this paper can provide novel insights into the precision medicine of bladder cancer.

Identification of a six-gene prognostic signature for bladder cancer associated macrophage

As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

Integrative and comparative single-cell analysis reveals transcriptomic difference between human tumefactive demyelinating lesion and glioma

Tumefactive demyelinating lesion (TDL) is an immune-mediated disease which can be misdiagnosed as glioma. At present, there is no study comparing difference between the two disorders at the cellular level. Here, we perform integrative and comparative single-cell RNA sequencing (ScRNA-seq) transcriptomic analysis on TDL and glioma lesions. At single-cell resolution, TDL is comprised primarily of immune cells, which is completely different from glioma. The integrated analysis reveals a TDL-specific microglial subset involving in B cell activation and proliferation. Comparative analysis highlights remyelination function of glial cells and demyelination function of T cells in TDL. Subclustering and pseudotime trajectory analysis of T cells in TDL reveal their heterogeneity and diverse functions involving in TDL pathogenesis and recovery process. Our study identifies substantial differences between TDL and glioma at single-cell resolution. The observed heterogeneity and potentially diverse functions of cells in TDL may be critical in disease progression.

Integrative and comparative single-cell analysis reveals transcriptomic difference between human tumefactive demyelinating lesion and glioma.

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer

BACKGROUNDS

Breast cancer (BC) is the most frequent cancer diagnosed in women throughout the world. The purpose of this study was to explore new biomarkers for breast cancer diagnosis. CyclinB1 (CCNB1) is found in abundance in a wide range of human malignancies.

MATERIAL AND METHODS

We evaluated the transcriptional, survival data and expression levels in tissue data of CCNB1 in patients with breast cancer from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The Human Protein Atlas (THAP) and Genome Tissue Expression (GTEx) database. A series of in silico analyses were used to investigate at noncoding RNAs (ncRNAs), gene ontology (GO) annotation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Protein-Protein Interaction (PPI) network. A quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate CCNB1 in BC cell lines.

RESULTS

CCNB1 expression was higher in BC tissues than in normal breast tissues. It was significantly related to survival time, tumor mutation burden (TMB), methylated, immune cell infiltration, and the expressed in estrogen receptor (ER) (-), lymphnode (+), and p53 (+) groups in BC. Moreover, The AC026401.3/CCNB1-miR-139-5p axis was discovered as the most promising upstream ncRNA-related pathway of CCNB1 in BC.

CONCLUSION

CCNB1 can be used as an independent predictive factor for BC, indicating that this would be a target for highly precise therapy and a biomarker for the disease.

Subsequent Systemic Therapy following Platinum and Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma

Treatment of metastatic urothelial carcinoma (mUC) after failure with platinum-based chemotherapy and immune checkpoint inhibitors (ICIs) remains controversial. To explore the role of subsequent systemic therapy, medical records from 436 patients who were consecutively treated with chemotherapy for mUC between May 2017 and April 2021 were collected from a single-center cancer registry. The primary endpoint was overall survival (OS), and progression-free survival (PFS) and response rate (RR) were also assessed. Among the 318 patients who failed both platinum and ICIs, subsequent therapy was delivered to 166 (52%) patients: taxanes (n = 56), platinum rechallenge (n = 46), pemetrexed (n = 39), and clinical trials (n = 25). Objective responses to third-line therapy were noted in 50 patients (RR, 30%; 95% CI, 23–37%). The patients who were enrolled in clinical trials and treated with platinum rechallenge were significantly more likely to respond than those treated with taxanes or pemetrexed. The median PFS and OS were 3.5 months (95% CI, 2.9–4.2 months) and 9.5 months (95% CI, 8.1–11.0 months), respectively. Similar to RR, PFS and OS were longer for the patients who were enrolled in clinical trials. Based on multivariate analyses, good performance status and enrollment in clinical trials are associated with benefits from subsequent therapy for pretreated mUC.

The significance of m6A RNA methylation modification in prognosis and tumor microenvironment immune infiltration of cervical cancer

Recent studies have highlighted that N6-methyladenosine (m6A) plays a significant role in tumorigenicity and progression. However, the mechanism of m6A modifications in the tumor microenvironment (TME) immune cell infiltration in cervical cancer (CC) remains unclear. Clinical and RNA sequencing data of 25 m6A RNA methylation regulators were acquired from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO Cox regression analysis was used to generate a prognostic risk signature. m6A modification patterns were identified based on the expression of 25 m6A regulators, and their correlation with TME immune cell-infiltrating characterization was analyzed. Principal component analysis was used to construct an m6A-scoring signature (m6A score) to evaluate the m6A modification patterns of individual CC samples and guide the selection of more effective immunotherapeutic strategies. Genetic and expression alterations of 25 m6A regulators were highly heterogeneous between CC and normal tissues. METTL14 and IGF2BP1 were selected to conduct the prognostic risk signature. Three m6A modification patterns were identified in 659 CC samples, which were associated with distinct clinical outcomes and biological pathways. The TME immune cell-infiltrating characterization of the three m6A modification patterns was highly consistent with 3 tumor immune phenotypes, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Due to the heterogeneity of m6A modification patterns, an m6A scoring signature was established to evaluate the m6A modification patterns of individual CC samples. Univariate and multivariate Cox regression analyses revealed that the m6A score is a robust and independent prognostic biomarker for assessing the prognosis of CC patients. A low m6A score, characterized by higher somatic mutation and higher expression of proliferation-related and DNA repair-related genes, indicated poor overall survival. Activation of immune infiltration was exhibited by the high m6A score, which was likely to have a good response and clinical benefits to antiPD-1/L1 immunotherapy. This study highlights the prognostic value of 25 m6A regulators in CC. The m6A modification is related to immune regulation and the formation of TME heterogeneity and complexity. An m6A scoring signature to clarify the individual m6A modification pattern could enhance our understanding of TME immune cell-infiltrating characterization and guide immunotherapy strategies.

Application and prospect of single-cell sequencing in cancer metastasis

Cancer metastasis is a complicated process driven by internal genetic variations and developed through interactions with the external environment. This process usually causes therapeutic resistance and results in a low survival rate. In recent years, single-cell sequencing has become a popular method for revealing the tumor evolutionary genetic lineage, intra-tumoral heterogeneity and tumor microenvironment of the metastasis process. So as to find more therapeutic targets for clinical application, the spatial transcriptomics method has become a new rising field of cancer studies, which promotes the combination between clinical medicine and molecular biology. In future prospects, more accurate and personalized treatment models will come into reality.

Single-cell sequencing: expansion, integration and translation

With the rapid advancement in sequencing technologies, the concept of omics has revolutionized our understanding of cellular behaviors. Conventional omics investigation approaches measure the averaged behaviors of multiple cells, which may easily hide signals represented by a small-cell cohort, urging for the development of techniques with enhanced resolution. Single-cell RNA sequencing, investigating cell transcriptomics at the resolution of a single cell, has been rapidly expanded to investigate other omics such as genomics, proteomics and metabolomics since its invention. The requirement for comprehensive understanding of complex cellular behavior has led to the integration of multi-omics and single-cell sequencing data with other layers of information such as spatial data and the CRISPR screening technique towards gained knowledge or innovative functionalities. The development of single-cell sequencing in both dimensions has rendered it a unique field that offers us a versatile toolbox to delineate complex diseases, including cancers.

N6-Methyladenosine Modification Patterns and Tumor Microenvironment Immune Characteristics Associated With Clinical Prognosis Analysis in Stomach Adenocarcinoma

Background: N6-methyladenosine (m6A) modification is a part of epigenetic research that has gained increasing attention in recent years. m6A modification is widely involved in many biological behaviors of intracellular RNA by regulating mRNA, thus affecting disease progression and tumor occurrence. However, the effects of m6A modification on immune cell infiltration of the tumor microenvironment (TME) are uncertain in stomach adenocarcinoma (STAD).

Methods: The Cancer Genome Map (TCGA) database was used to download transcriptome data, clinicopathological data, and survival data for m6A-regulated genes in 433 STAD tissues that meet the requirements of this study. GSE84437 data were obtained from the Gene Expression Omnibus (GEO) database. The correlation between 23 m6A regulated genes was analyzed using R software. Sample clustering analysis was carried out on the genes of the m6A regulatory factor, and survival analysis and differentiation comparison were made for patients in clustering grouping. Then, the Gene Set Enrichment Analysis (GSEA), the single-sample GSEA (ssGSEA), and other methods were conducted to assess the correlation among m6A modification patterns, TME cell infiltration characteristics, and immune infiltration markers. The m6A modification pattern of individual tumors was quantitatively evaluated using the m6A score scheme of the principal component analysis (PCA).

Results: From the TCGA database, 94/433 (21.71%) samples were somatic cell mutations, and ZC3H13 mutations are the most common. Based on the consensus, matrix k-3 is an optimal clustering stability value to identify three different clusters. Three types of m6A methylation modification patterns were significantly different in immune infiltration. Thus, 1028 differentially expressed genes (DEGs) were identified. The survival analysis of the m6A score found that patients in the high m6A score group had a better prognosis than those in the low m6A score group. Further analysis of the survival curve combining tumor mutation burden (TMB) and m6A scores revealed that patients had a significantly lower prognosis in the low tumor mutant group and the low m6A score group (p = 0.003). The results showed that PD-L1 was significantly higher in the high m6A score group than in the low score group (p < 2.22e-16). The high-frequency microsatellite instability (MSI-H) subtype score was significantly different from the other two groups.

Conclusions: This study systematically evaluated the modification patterns of 23 m6A regulatory factors in STAD. The m6A modification pattern may be a critical factor leading to inhibitory changes and heterogeneity in TME. This elucidated the TME infiltration characteristics in patients with STAD through the evaluation of the m6A modification pattern.