Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning

Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late-stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating cancer cells, offer substantial insights into malignant tumour diagnosis, treatment and prognosis. This study aims to provide a model based on 15 types of Programmed Cell Death-Related Genes (PCDRGs) for evaluating immune microenvironment and prognosis in ccRCC patients. ccRCC patients from the TCGA and arrayexpress cohorts were grouped based on PCDRGs. A combination model using Lasso and SuperPC was constructed to identify prognostic gene features. The arrayexpress cohort validated the model, confirming its robustness. Immune microenvironment analysis, facilitated by PCDRGs, employed various methods, including CIBERSORT. Drug sensitivity analysis guided clinical treatment decisions. Single-cell data enabled Programmed Cell Death-Related scoring, subsequent pseudo-temporal and cell-cell communication analyses. A PCDRGs signature was established using TCGA-KIRC data. External validation in the arrayexpress cohort underscored the model's superiority over traditional clinical features. Furthermore, our single-cell analysis unveiled the roles of PCDRG-based single-cell subgroups in ccRCC, both in pseudo-temporal progression and intercellular communication. Finally, we performed CCK-8 assay and other experiments to investigate csf2. In conclusion, these findings reveal that csf2 inhibit the growth, infiltration and movement of cells associated with renal clear cell carcinoma. This study introduces a PCDRGs prognostic model benefiting ccRCC patients while shedding light on the pivotal role of programmed cell death genes in shaping the immune microenvironment of ccRCC patients.

Machine Learning-based Framework Develops a Tumor Thrombus Coagulation Signature in Multicenter Cohorts for Renal Cancer

Background: Renal cell carcinoma (RCC) is frequently accompanied by tumor thrombus in the venous system with an extremely dismal prognosis. The current Tumor Node Metastasis (TNM) stage and Mayo clinical classification do not appropriately identify preference-sensitive treatment. Therefore, there is an urgent need to develop a better ideal model for precision medicine. Methods: In this study, we developed a coagulation tumor thrombus signature for RCC with 10 machine-learning algorithms (101 combinations) based on a novel computational framework using multiple independent cohorts. Results: The established tumor thrombus coagulation-related risk stratification (TTCRRS) signature comprises 10 prognostic coagulation-related genes (CRGs). This signature could predict survival outcomes in public and in-house protein cohorts and showed high performance compared to 129 published signatures. Additionally, the TTCRRS signature was significantly related to some immune landscapes, immunotherapy response, and chemotherapy. Furthermore, we also screened out hub genes, transcription factors, and small compounds based on the TTCRRS signature. Meanwhile, CYP51A1 can regulate the proliferation and migration properties of RCC. Conclusions: The TTCRRS signature can complement the traditional anatomic TNM staging system and Mayo clinical stratification and provide clinicians with more therapeutic options.

Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals a tumor-associated endothelial tip cell phenotype

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer, accounting for over 75% of cases. The asymptomatic nature of the disease contributes to late-stage diagnoses and poor survival. Highly vascularized and immune infiltrated microenvironment are prominent features of ccRCC, yet the interplay between vasculature and immune cells, disease progression and response to therapy remains poorly understood. Using droplet-based single-cell RNA sequencing we profile 50,236 transcriptomes from paired tumor and healthy adjacent kidney tissues. Our analysis reveals significant heterogeneity and inter-patient variability of the tumor microenvironment. Notably, we discover a previously uncharacterized vasculature subpopulation associated with epithelial-mesenchymal transition. The cell-cell communication analysis reveals multiple modes of immunosuppressive interactions within the tumor microenvironment, including clinically relevant interactions between tumor vasculature and stromal cells with immune cells. The upregulation of the genes involved in these interactions is associated with worse survival in the TCGA KIRC cohort. Our findings demonstrate the role of tumor vasculature and stromal cell populations in shaping the ccRCC microenvironment and uncover a subpopulation of cells within the tumor vasculature that is associated with an angiogenic phenotype.

Exploring the role of coagulation-related genes in renal cell carcinoma: Implications for tumor microenvironment and prognostic biomarkers

PURPOSE

Clear cell renal cell carcinoma (ccRCC) frequently progresses to advanced stages due to tumor thrombus (TTs) formation. In this study, we aimed to investigate the role of coagulation-related pathway activation in the progression of ccRCC.

METHODS

Consensus clustering was used to identify coagulation-related molecular clusters of ccRCC patients from The Cancer Genome Atlas Program (TCGA) database. The function of coagulation and its correlation with the immune microenvironment were investigated. Protein-protein interactions and differential expression analysis were used to identify the key gene, which was verified by external experiments. The coagulation-associated risk score was constructed by cox proportional hazards regression.

RESULTS

Notable disparities were detected in immune characteristics, prognostic differentiation and drug sensitivity between two coagulation-related clusters. Through the integration of clinical stage significance and protein-protein interactions, the key gene MMP9 was screened and it was significantly correlated with CD4+T cells, CD8+T cells and Treg cells. A coagulation-related risk score prognostic model was developed in the Cancer Genome Atlas (TCGA) cohort for risk stratification and prognosis prediction. The prognostic predictive values of the coagulation-related risk score were further authenticated in both TCGA-KIRC and E-MTAB-1980 cohorts.

CONCLUSION

There is an obvious correlation between the coagulation and the tumor microenvironment in ccRCC. As a key coagulation-related gene, MMP9 may promote the progression of renal cell carcinoma by influencing immune infiltration of CD8+T cells and Treg cells. Additionally, the risk score could be used as a durable prognostic biomarker, which could assist in clinical decision making for ccRCC patients.

Single-cell transcriptomics reveal distinct immune-infiltrating phenotypes and macrophage-tumor interaction axes among different lineages of pituitary neuroendocrine tumors

BACKGROUND

Pituitary neuroendocrine tumors (PitNETs) are common gland neoplasms demonstrating distinctive transcription factors. Although the role of immune cells in PitNETs has been widely recognized, the precise immunological environment and its control over tumor cells are poorly understood.

METHODS

The heterogeneity, spatial distribution, and clinical significance of macrophages in PitNETs were analyzed using single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, spatial transcriptomics, immunohistochemistry, and multiplexed quantitative immunofluorescence (QIF). Cell viability, cell apoptosis assays, and in vivo subcutaneous xenograft experiments have confirmed that INHBA-ACVR1B influences the process of tumor cell apoptosis.

RESULTS

The present study evaluated scRNA-seq data from 23 PitNET samples categorized into 3 primary lineages. The objective was to explore the diversity of tumors and the composition of immune cells across these lineages. Analyzed data from scRNA-seq and 365 bulk RNA sequencing samples conducted in-house revealed the presence of three unique subtypes of tumor immune microenvironment (TIME) in PitNETs. These subtypes were characterized by varying levels of immune infiltration, ranging from low to intermediate to high. In addition, the NR5A1 lineage is primarily associated with the subtype characterized by limited infiltration of immune cells. Tumor-associated macrophages (TAMs) expressing CX3CR1+, C1Q+, and GPNMB+ showed enhanced contact with tumor cells expressing NR5A1 + , TBX19+, and POU1F1+, respectively. This emphasizes the distinct interaction axes between TAMs and tumor cells based on their lineage. Moreover, the connection between CX3CR1+ macrophages and tumor cells via INHBA-ACVR1B regulates tumor cell apoptosis.

CONCLUSIONS

In summary, the different subtypes of TIME and the interaction between TAM and tumor cells offer valuable insights into the control of TIME that affects the development of PitNET. These findings can be utilized as prospective targets for therapeutic interventions.

Direct contact between tumor cells and platelets initiates a FAK-dependent F3/TGF-β positive feedback loop that promotes tumor progression and EMT in osteosarcoma

Platelets have received growing attention for their roles in hematogenous tumor metastasis. However, the tumor-platelet interaction in osteosarcoma (OS) remains poorly understood. Here, using platelet-specific focal adhesion kinase (FAK)-deficient mice, we uncover a FAK-dependent F3/TGF-β positive feedback loop in OS. Disruption of the feedback loop by inhibition of F3, TGF-β, or FAK significantly suppresses OS progression. We demonstrate that OS F3 initiated the feedback loop by increasing platelet TGF-β secretion, and platelet-derived TGF-β promoted OS F3 expression in turn and modulated OS EMT process. Immunofluorescence results indicate platelet infiltration in OS niche and we verified it was mediated by platelet FAK. In addition, platelet FAK was proved to mediate platelet adhesion to OS cells, which was vital for the initiation of F3/TGF-β feedback loop. Collectively, these findings provide a rationale for novel therapeutic strategies targeting tumor-platelet interplay in metastatic OS.

Renal Cell Carcinoma With Tumor Thrombus: A Case Series in Puerto Rico

INTRODUCTION

 Renal cell carcinoma (RCC) is one of the most common types of kidney cancer. While RCC tends to present as a localized tumor, a notable proportion may present with distant metastasis. In some instances, RCC may also present with intravascular tumor extension, often called tumor thrombus (TT). Its presence confers a worse prognosis and has important implications for the tumor's staging and treatment. Despite extensive documentation of RCC TT in the US, limited data exists regarding its presentation, management, and outcomes in Puerto Rico (PR). This study aims to broaden the available information on RCC TT, emphasizing surgical management and outcomes. We also provide descriptive data on patient demographics and clinical presentation to improve decision-making among clinicians caring for Puerto Rican men and women.

METHODS

 In this single-center, retrospective study, we evaluated patients who underwent partial or total nephrectomy at Saint Luke's Episcopal Medical Center between 2018 and 2022. Data was abstracted from electronic health records (EHR). Patients without documented evidence of TT during the peri-operative period were excluded from the study. A total of 220 patient records were evaluated, of which 12 met the inclusion criteria for the study. Cases were categorized using the latest RCC TT guidelines. Central tendency measurements were used to describe the sample distribution. The mean was considered to make assumptions regarding the prevalent observations, and the median was considered to rule out possible outliers. Categorical data were evaluated using proportion analyses, including TT extension level and BMI variables. Fisher's exact test evaluated the association between the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade and TT extension level.

RESULTS

 Most patients lacked TT-related symptoms. The most severe presenting symptom was a pulmonary embolism (8.3%). Hypertension (83.3%), BMI greater than 25 at the time of diagnosis (75%), and type 2 diabetes mellitus (66.7%) were the most common comorbid conditions within our cohort. Nearly 75% of patients underwent laparoscopic radical nephrectomy with TT resection. One left-sided level III case was managed by laparoscopic-assisted open radical nephrectomy with a right subcostal incision. There were zero intraoperative complications and two postoperative complications. The histopathological reports of all cases were consistent with clear cell carcinoma, and half of the cases (n=6) were WHO/ISUP G4. All patients are alive and free of disease.

CONCLUSION

 RCC is a common renal neoplasm in PR that can present with intravascular tumor extension. Our findings do not establish a definitive association between BMI, tumor size, WHO/ISUP grading, and TT extension level. Our study shows that laparoscopic removal of RCC TT is a safe and effective approach. However, the generalizability of our findings is limited by the study's design and sample size. Future research should focus on identifying predictive markers, establishing effective screening protocols, and determining if our hybrid approach has comparable outcomes to the standard open approach.

Prognostic Significance of Grade Discrepancy Between Primary Tumor and Venous Thrombus in Nonmetastatic Clear-cell Renal Cell Carcinoma: Analysis of the REMEMBER Registry and Implications for Adjuvant Therapy

BACKGROUND

Further stratification of the risk of recurrence of clear-cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) will facilitate selection of candidates for adjuvant therapy.

OBJECTIVE

To assess the impact of tumor grade discrepancy (GD) between the primary tumor (PT) and VTT in nonmetastatic ccRCC on disease-free survival (DFS), overall survival (OS), and cancer-specific survival (CSS).

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective analysis of a multi-institutional nationwide data set for patients with pT3N0M0 ccRCC who underwent radical nephrectomy and thrombectomy.

OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS

Pathology slides were centrally reviewed. GD, a bidirectional variable (upgrading or downgrading), was numerically defined as the VTT grade minus the PT grade. Multivariable models were built to predict DFS, OS, and CSS.

RESULTS AND LIMITATIONS

We analyzed data for 604 patients with median follow-up of 42 mo (excluding events). Tumor GD between VTT and PT was observed for 47% (285/604) of the patients and was an independent risk factor with incremental value in predicting the outcomes of interest (all p < 0.05). Incorporation of tumor GD significantly improved the performance of the ECOG-ACRIN 2805 (ASSURE) model. A GD-based model (PT grade, GD, pT stage, PT sarcomatoid features, fat invasion, and VTT consistency) had a c index of 0.72 for DFS. The hazard ratios were 8.0 for GD = +2 (p < 0.001), 1.9 for GD = +1 (p < 0.001), 0.57 for GD = -1 (p = 0.001), and 0.22 for GD = -2 (p = 0.003) versus GD = 0 as the reference. According to model-converted risk scores, DFS, OS, and CSS significantly differed between subgroups with low, intermediate, and high risk (all p < 0.001).

CONCLUSIONS

Routine reporting of VTT upgrading or downgrading in relation to the PT and use of our GD-based nomograms can facilitate more informed treatment decisions by tailoring strategies to an individual patient's risk of progression.

PATIENT SUMMARY

We developed a tool to improve patient counseling and guide decision-making on other therapies in addition to surgery for patients with the clear-cell type of kidney cancer and tumor invasion of a vein.

Single-cell transcriptome analysis of epithelial, immune, and stromal signatures and interactions in human ovarian cancer

A comprehensive investigation of ovarian cancer (OC) progression at the single-cell level is crucial for enhancing our understanding of the disease, as well as for the development of better diagnoses and treatments. Here, over half a million single-cell transcriptome data were collected from 84 OC patients across all clinical stages. Through integrative analysis, we identified heterogeneous epithelial-immune-stromal cellular compartments and their interactions in the OC microenvironment. The epithelial cells displayed clinical subtype features with functional variance. A significant increase in distinct T cell subtypes was identified including Tregs and CD8+ exhausted T cells from stage IC2. Additionally, we discovered antigen-presenting cancer-associated fibroblasts (CAFs), with myofibroblastic CAFs (myCAFs) exhibiting enriched extracellular matrix (ECM) functionality linked to tumor progression at stage IC2. Furthermore, the NECTIN2-TIGIT ligand-receptor pair was identified to mediate T cells communicating with epithelial, fibroblast, endothelial, and other cell types. Knock-out of NECTIN2 using CRISPR/Cas9 inhibited ovarian cancer cell (SKOV3) proliferation, and increased T cell proliferation when co-cultured. These findings shed light on the cellular compartments and functional aspects of OC, providing insights into the molecular mechanisms underlying stage IC2 and potential therapeutic strategies for OC.

Histone demethylase KDM4B contributes to advanced clear cell renal carcinoma and association with copy number variations and cell cycle progression

Advanced renal cell carcinoma (RCC) poses a threat to patient survival. Epigenetic remodelling is the pathogenesis of renal cancer. Histone demethylase 4B (KDM4B) is overexpressed in many cancers through various pathways. However, the role of KDM4B in clear cell renal carcinoma has not yet been elucidated. The differential expression of KDM4B was first verified by analysing public databases. The expression of KDM4B in fresh tissues and pathology slides was further analysed by western blotting and immunohistochemical staining. KDM4B overexpression and knockdown cell lines were also established. Cell Counting Kit-8 (CCK-8) assay was used to detect cell growth. Transwell assays were performed to assess cell migration. Xenografts were used to evaluate tumour growth and metastasis in vivo. Finally, KDM4B expression levels associated with copy number variation (CNV) and cell cycle stage were evaluated based on single-cell RNA sequencing data. KDM4B was expressed at higher levels in tumour tissues than in the adjacent normal tissues. High levels of KDM4B are associated with worse pathological features and poorer prognosis. KDM4B also promotes cell proliferation and migration in vitro, as well as tumour growth and metastasis in vivo. Tumour cells with high KDM4B expression exhibited higher CNV levels and a greater proportion of cells in the G1/S transition phase. Our results confirm that KDM4B promotes the progression of clear cell renal carcinoma, is correlated with poor prognosis, and may be related to high levels of CNV and cell cycle progression.

Oncolytic adenoviruses expressing checkpoint inhibitors for cancer therapy

Despite the remarkable success of immune checkpoint inhibitors (ICIs), primary resistance to ICIs causes only subsets of patients to achieve durable responses due to the complex tumor microenvironment (TME). Oncolytic viruses (OVs) can overcome the immunosuppressive TME and promote systemic antitumor immunity in hosts. Engineered OVs armed with ICIs would likely have improved effectiveness as a cancer therapy. According to the diverse immune cell landscapes among different types of tumors, we rationally and precisely generated three recombinant oncolytic adenoviruses (OAds): OAd-SIRPα-Fc, OAd-Siglec10-Fc and OAd-TIGIT-Fc. These viruses were designed to locally deliver SIRPα-Fc, Siglec10-Fc or TIGIT-Fc fusion proteins recognizing CD47, CD24 or CD155, respectively, in the TME to achieve enhanced antitumor effects. Our results suggested that OAd-SIRPα-Fc and OAd-Siglec10-Fc both showed outstanding efficacy in tumor suppression of macrophage-dominated tumors, while OAd-TIGIT-Fc showed the best antitumor immunity in CD8+ T-cell-dominated tumors. Importantly, the recombinant OAds activated an inflammatory immune response and generated long-term antitumor memory. In addition, the combination of OAd-Siglec10-Fc with anti-PD-1 significantly enhanced the antitumor effect in a 4T1 tumor model by remodeling the TME. In summary, rationally designed OAds expressing ICIs tailored to the immune cell landscape in the TME can precisely achieve tumor-specific immunotherapy of cancer.

The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC

The growth and advancement of ccRCC are strongly associated with the presence of immune infiltration and the tumor microenvironment, comprising tumor cells, immune cells, stromal cells, vascular cells, myeloid-derived cells, and extracellular matrix (ECM). Nevertheless, as a result of the diverse and constantly evolving characteristics of the tumor microenvironment, prior advanced sequencing methods have frequently disregarded specific less prevalent cellular traits at varying intervals, thereby concealing their significance. The advancement and widespread use of single-cell sequencing technology enable us to comprehend the source of individual tumor cells and the characteristics of a greater number of individual cells. This, in turn, minimizes the impact of intercellular heterogeneity and temporal heterogeneity of the same cell on experimental outcomes. This review examines the attributes of the tumor microenvironment in ccRCC and provides an overview of the progress made in single-cell sequencing technology and its particular uses in the current focus of immune infiltration in ccRCC.

Spatio-temporal heterogeneity in cancer evolution and tumor microenvironment of renal cell carcinoma with tumor thrombus

Metastasis is the most fatal aspect of cancer, often preceded by a tumor thrombus (TT) which forms within the vascular system. Renal cell carcinoma (RCC), the predominant form of kidney cancer, witnesses a venous system invasion in 4-10% of cases, resulting in venous tumor thrombus (RCC-TT). This variant represents a formidable clinical challenge due to its escalated surgical complexity, heightened risk of progression and metastasis, and an adverse prognosis. However, recent trials addressing RCC-TT face significant barriers stemming from the profound inter- and intra-tumoral heterogeneity, patient-specific treatment variations, and distinct therapeutic resistance patterns between the primary tumor (PT) and the TT. This review delves into the unique evolutionary pathway of RCC-TT, the relationship between the staging and grading of RCC-TT invasion patterns, and the spatial molecular profiling of RCC-TT. Additionally, we assess the temporal heterogeneity among TT, PT, and distant metastases, as well as the functional phenotypes of TME components. An outlook for future research on RCC-TT is also provided.

Recent Advances in Single-Cell RNA-Sequencing of Primary and Metastatic Clear Cell Renal Cell Carcinoma

Over the past two decades, significant progress has been made in the treatment of clear cell renal cell carcinoma (ccRCC), with a shift towards adopting new treatment approaches ranging from monotherapy to triple-combination therapy. This progress has been spearheaded by fundamental technological advancements that have allowed a deeper understanding of the various biological components of this cancer. In particular, the rapid commercialization of transcriptomics technologies, such as single-cell RNA-sequencing (scRNA-seq) methodologies, has played a crucial role in accelerating this understanding. Through precise measurements facilitated by these technologies, the research community has successfully identified and characterized diverse tumor, immune, and stromal cell populations, uncovering their interactions and pathways involved in disease progression. In localized ccRCC, patients have shown impressive response rates to treatment. However, despite the emerging findings and new knowledge provided in the field, there are still patients that do not respond to treatment, especially in advanced disease stages. One of the key challenges lies in the limited study of ccRCC metastases compared to localized cases. This knowledge gap may contribute to the relatively low survival rates and response rates observed in patients with metastatic ccRCC. To bridge this gap, we here delve into recent research utilizing scRNA-seq technologies in both primary and metastatic ccRCC. The goal of this review is to shed light on the current state of knowledge in the field, present existing treatment options, and emphasize the crucial steps needed to improve survival rates, particularly in cases of metastatic ccRCC.

Based on disulfidptosis, revealing the prognostic and immunological characteristics of renal cell carcinoma with tumor thrombus of vena cava and identifying potential therapeutic target AJAP1

BACKGROUND

Patients with clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus have a poor prognosis, high surgical risk, and lack of targeted therapeutic agents.

METHODS

Genes with consistent differential expression trends in tumor tissues and VTT groups were first screened, and then differential genes associated with disulfidptosis were found by correlation analysis. Subsequently, identifying ccRCC subtypes and constructing risk models to compare the differences in prognosis and the tumor microenvironment in different subgroups. Finally, constructing a nomogram to predict the prognosis of ccRCC and validate key gene expression levels in cells and tissues.

RESULTS

We screened 35 differential genes related to disulfidptosis and identified 4 ccRCC subtypes. Risk models were constructed based on the 13 genes, and the high-risk group had a higher abundance of immune cell infiltration, tumor mutational load, and microsatellite instability scores, predicting high sensitivity to immunotherapy. The 1-year AUC = 0.869 for predicting OS by nomogram has a high application value. The expression level of the key gene AJAP1 was low in both tumor cell lines and cancer tissues.

CONCLUSIONS

Our study not only constructed an accurate prognostic nomogram for ccRCC patients but also identified an AJAP1 biomarker as a potential biomarker for the disease.

Integrating scRNA and bulk-RNA sequencing develops a cell senescence signature for analyzing tumor heterogeneity in clear cell renal cell carcinoma

Introduction

Cellular senescence (CS) plays a critical role in cancer development, including clear cell renal cell carcinoma (ccRCC). Traditional RNA sequencing cannot detect precise molecular composition changes within tumors. This study aimed to analyze cellular senescence's biochemical characteristics in ccRCC using single RNA sequencing (ScRNA-seq) and traditional RNA sequencing (Bulk RNA-seq).

Methods

Researchers analyzed the biochemical characteristics of cellular senescence in ccRCC using ScRNA-seq and Bulk RNA-seq. They combined these approaches to identify differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Genes from these pathways were used to identify molecular subtypes associated with senescence, and a new risk model was constructed. The function of the gene DUSP1 in ccRCC was validated through biological experiments.

Results

The combined analysis of ScRNA-seq and Bulk RNA-seq revealed significant differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Researchers identified genes from these pathways to identify molecular subtypes associated with senescence, constructing a new risk model. Different subgroups showed significant differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity.

Discussion

Senescence signature markers are practical biomarkers and predictors of molecular typing in ccRCC. Differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity between different subgroups indicate that this approach could provide valuable insights into senescence-related treatment options and prognostic assessment for patients with ccRCC. The function of the gene DUSP1 in ccRCC was validated through biological experiments, confirming its feasibility as a novel biomarker for ccRCC. These findings suggest that targeted therapies based on senescence-related mechanisms could be an effective treatment option for ccRCC.

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

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Integrative transcriptome and proteome analyses of clear cell renal cell carcinoma develop a prognostic classifier associated with thrombus

Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein-protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients' survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.

Integrated analysis of single-cell and bulk RNA sequencing data reveals an immunostimulatory microenvironment in tumor thrombus of osteosarcoma

Tumor thrombus of bone sarcomas represents a unique reservoir for various types of cancer and immune cells, however, the investigation of tumor thrombus at a single-cell level is very limited. And it is still an open question to identify the thrombus-specific tumor microenvironment that is associated with the tumor-adaptive immune response. Here, by analyzing bulk tissue and single-cell level transcriptome from the paired thrombus and primary tumor samples of osteosarcoma (OS) patients, we define the immunostimulatory microenvironment in tumor thrombus of OS with a higher proportion of tumor-associated macrophages with M1-like states (TAM-M1) and TAM-M1 with high expression of CCL4. OS tumor thrombus is found to have upregulated IFN-γ and TGF-β signalings that are related to immune surveillance of circulating tumor cells in blood circulation. Further multiplexed immunofluorescence staining of the CD3/CD4/CD8A/CD68/CCL4 markers validates the immune-activated state in the tumor thrombus samples. Our study first reports the transcriptome differences at a single-cell level between tumor thrombus and primary tumor in sarcoma.

Macrophage-Related Testicular Inflammation in Individuals with Idiopathic Non-Obstructive Azoospermia: A Single-Cell Analysis

Male infertility is a global issue that seriously affects reproductive health. This study aimed to understand the underlying causes of idiopathic non-obstructive azoospermia (iNOA), which is a type of male infertility with unknown origins that accounts for 10-15% of cases. By using single-cell analysis techniques, we aimed to uncover the mechanisms of iNOA and gain insight into the cellular and molecular changes in the testicular environment. In this study, we performed bioinformatics analysis using scRNA-seq and microarray data obtained from the GEO database. The analysis included techniques such as pseudotime analysis, cell-cell communication, and hdWGCNA. Our study showed a significant difference between the iNOA and the normal groups, indicating a disorder in the spermatogenic microenvironment in iNOA. We observed a reduction in the proportion of Sertoli cells and blocked germ cell differentiation. Additionally, we found evidence of testicular inflammation related to macrophages and identified ODF2 and CABYR as potential biomarkers for iNOA.

Integrated analysis to identify the prognostic and immunotherapeutic roles of coagulation-associated gene signature in clear cell renal cell carcinoma

The coagulation system is closely related to the physiological status and immune response of the body. Recent years, studies focusing on the association between coagulation system abnormalities and tumor progression have been widely reported. In clear cell renal cell carcinoma (ccRCC), poor prognosis often occurs in patients with venous tumor thrombosis and coagulation system abnormalities, and there is a lack of research in related fields. Significant differences in coagulation function were also demonstrated in our clinical sample of patients with high ccRCC stage or grade. Therefore, in this study, we analyzed the biological functions of coagulation-related genes (CRGs) in ccRCC patients using single-cell sequencing and TCGA data to establish the 5-CRGs based diagnostic signature and predictive signature for ccRCC. Univariate and multivariate Cox analyses suggested that prognostic signature could be an independent risk factor. Meanwhile, we applied CRGs for consistent clustering of ccRCC patients, and the two classes showed significant survival and genotype differences. The differences in individualized treatment between the two different subtypes were revealed by pathway enrichment analysis and immune cell infiltration analysis. In summary, we present the first systematic analysis of the significance of CRGs in the diagnosis, prognosis, and individualized treatment of ccRCC patients.

Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis

Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level. We validate the performance of Cottrazm along the malignant-boundary-nonmalignant spatial axis. We identify specific macrophage and fibroblast subtypes localized around tumor boundary that interacted with tumor cells to generate a structural boundary, which limits T cell infiltration and promotes immune exclusion in tumor microenvironment. In this work, Cottrazm provides an integrated tool framework to dissect the tumor spatial microenvironment and facilitates the discovery of functional biological insights, thereby identifying therapeutic targets in oncologic ST datasets.

Prognostic and immunological characteristics of CDK1 in lung adenocarcinoma: A systematic analysis

Background

Cyclin-dependent kinases (CDKs) play a key role in cell proliferation in lung adenocarcinoma (LUAD). Comprehensive analysis of CDKs to elucidate their clinical significance and interactions with the tumor immune microenvironment is needed.

Methods

RNA expression, somatic mutation, copy number variation, and single-cell RNA sequencing data were downloaded from public datasets. First, we comprehensively evaluated the expression profile and prognostic characteristics of 26 CDKs in LUAD, and CDK1 was selected as a candidate for further analysis. Then, a systematic analysis was performed to explore the relationships of CDK1 with clinical characteristics and tumor immune microenvironment factors in LUAD.

Results

CDK1 was markedly upregulated at both the mRNA and protein level in LUAD. Moreover, overexpression of CDK1 was related to poor clinical outcomes. CDK1 coexpressed genes were mainly involved in the cell cycle, the DNA repair process, and the p53 signaling pathway. In addition, CDK1 expression was found to be correlated with the expression of multiple immunomodulators and chemokines, which participate in activating and suppressing the immune microenvironment. CDK1 expression was also correlated with increased infiltration of numerous immune cells, including CD4+ T cells and M1 macrophages. Patients with high CDK1 expression tended to have a poor response to immunotherapy but were sensitive to multiple chemotherapies and targeted drugs. The MDK-NCL and SPP1-CD44 ligand-receptor pairs were markedly activated in the intercellular communication network. CDK1 was an independent prognostic factor for LUAD and improved the ability to predict overall survival when combined with tumor stage.

Conclusion

CDK1 plays an essential role in reshaping the tumor immune microenvironment and might be a prognostic and treatment biomarker in LUAD.

Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT) have poor prognosis. We aimed to reveal features of ccRCC with VTT and develop a urine-based prognostic classifier to predict ccRCC prognosis through integrative analyses of transcriptomic landscape and urinary signature.

Methods

RNA sequencing was performed in five patients with ccRCC thrombus-tumor-normal tissue triples, while mass spectrometry was performed for urine samples from 12 ccRCC and 11 healthy controls. A urine-based classifier consisting of three proteins was developed to predict patients' survival and validated in an independent cohort.

Results

Transcriptomic analysis identified 856 invasion-associated differentially expressed genes (DEGs). Furthermore, proteomic analysis showed 133 differentially expressed proteins (DEPs). Integration of transcriptomic landscape and urinary signature reveals 6 urinary detectable proteins (VSIG4, C3, GAL3ST1, TGFBI, AKR1C3, P4HB) displaying abundance changes consistent with corresponding genes in transcriptomic profiling. According to TCGA database, VSIG4, TGFBI, and P4HB were significantly overexpressed in patients with shorter survival and might be independent prognostic factors for ccRCC (all p<0.05). A prognostic classifier consisting of the three DEPs highly associated with survival performed satisfactorily in predicting overall survival (HR=2.0, p<0.01) and disease-free survival (HR=1.6, p<0.001) of ccRCC patients. The ELISA analysis of urine samples from an independent cohort confirmed the satisfied predictive power of the classifier for pathological grade (AUC=0.795, p<0.001) and stage (AUC=0.894, p<0.001).

Conclusion

Based on integrative analyses of transcriptomic landscape and urinary signature, the urine-based prognostic classifier consisting of VSIG4, TGFBI, and P4HB has satisfied predictive power of ccRCC prognosis and may facilitate ccRCC molecular subtyping and treatment.

Cellular milieu in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is globally the most prevalent renal cancer. The cells of origin in ccRCC have been identified as proximal tubular epithelial cells (PTEC); however, the transcriptomic pathways resulting in the transition from normal to malignant PTEC state have remained unclear. Immunotherapy targeting checkpoints have revolutionized the management of ccRCC, but a sustained clinical response is achieved in only a minority of ccRCC patients. This indicates that our understanding of the mechanisms involved in the malignant transition and resistance to immune checkpoint therapy in ccRCC is unclear. This review examines recent single-cell transcriptomics studies of ccRCC to clarify the transition of PTEC in ccRCC development, and the immune cell types, states, and interactions that may limit the response to targeted immune therapy, and finally suggests stromal cells as key drivers in recurrent and locally invasive ccRCC. These and future single-cell transcriptomics studies will continue to clarify the cellular milieu in the ccRCC microenvironment, thus defining actional clinical, therapeutic, and prognostic characteristics of ccRCC.

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

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