Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response

The implications for urological malignancies of non-coding RNAs in the the tumor microenvironment

Urological malignancies are a major global health issue because of their complexity and the wide range of ways they affect patients. There's a growing need for in-depth research into these cancers, especially at the molecular level. Recent studies have highlighted the importance of non-coding RNAs (ncRNAs) – these don't code for proteins but are crucial in controlling genes – and the tumor microenvironment (TME), which is no longer seen as just a background factor but as an active player in cancer progression. Understanding how ncRNAs and the TME interact is key for finding new ways to diagnose and predict outcomes in urological cancers, and for developing new treatments. This article reviews the basic features of ncRNAs and goes into detail about their various roles in the TME, focusing specifically on how different ncRNAs function and act in urological malignancies.

Potential protumor function of CD74 in clear cell renal cell carcinoma

CD74 is a transmembrane protein that functions as a specialized chaperone of HLA class II and CD74 in tumor cells was suggested to be involved in cell proliferation in several kinds of malignant tumors. CD74 is also known to be expressed in macrophages, therefore, we investigated the CD74 expression in clear cell renal cell carcinoma (ccRCC). Immunohistochemistry of CD74 indicated that CD74 was expressed not only in cancer cells but also macrophages. CD74 was detected in surface membrane and cytoplasm of cancer cells in 92 of 94 cases (98%) and of 87 of 94 cases (93%). CD74 was expressed both in cancer cells and TAMs in 86 of 94 cases (91%). In vitro studies using cancer cell lines and monocyte-derived macrophages stimulated by anti-CD74 antibodies showed that CD74 signal accelerated cancer cell proliferation and macrophage activation. However, macrophage activation via CD74 signal did not influence macrophage-mediated cancer cell growth. RNA-sequence of macrophages stimulated by anti-CD74 antibodies indicated that CD74 signal was associated to inflammatory responses in macrophages. In conclusion, we examined the expression and functional significance of CD74 in ccRCC using tissue specimens and cell culture studies. The function of CD74 was suggested to be different in cancer cells and in macrophages, and further studies are necessary to clarify the functional significance of CD74 in ccRCC.

An 18-gene signature of recurrence-associated endothelial cells predicts tumor progression and castration resistance in prostate cancer

BACKGROUND

The prognostic and therapeutic implications of endothelial cells (ECs) heterogeneity in prostate cancer (PCa) are poorly understood.

METHODS

We investigated associations of EC heterogeneity with PCa recurrence and castration resistance in 8 bulk transcriptomic and 4 single-cell RNA-seq cohorts. A recurrence-associated EC (RAEC) signature was constructed by comparing 11 machine learning algorithms through nested cross-validation. Functional relevances of RAEC-specific genes were also tested.

RESULTS

A subset of ECs was significantly associated with recurrence in primary PCa and named RAECs. RAECs were characteristic of tip and immature cells and were enriched in migration, angiogenesis, and collagen-related pathways. We then developed an 18-gene RAEC signature (RAECsig) representative of RAECs. Higher RAECsig scores independently predicted tumor recurrence and performed better or comparably compared to clinicopathological factors and commercial gene signatures in multiple PCa cohorts. Of the 18 RAECsig genes, FSCN1 was upregulated in ECs from PCa with higher Gleason scores; and the silencing of FSCN1, TMEME255B, or GABRD in ECs either attenuated tube formation or inhibited PCa cell proliferation. Finally, higher RAECsig scores predicted castration resistance in both primary and castration-resistant PCa.

CONCLUSION

This study establishes an endothelial signature that links a subset of ECs to prostate cancer recurrence and castration resistance.

scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate rare cell types and achieve accurate identification. We benchmark scCAD on 25 real-world scRNA-seq datasets, demonstrating its superior performance compared to 10 state-of-the-art methods. In-depth case studies across diverse datasets, including mouse airway, brain, intestine, human pancreas, immunology data, and clear cell renal cell carcinoma, showcase scCAD's efficiency in identifying rare cell types in complex biological scenarios. Furthermore, scCAD can correct the annotation of rare cell types and identify immune cell subtypes associated with disease, thereby offering valuable insights into disease progression.

Expression of L1 Cell Adhesion Molecule, a Nephronal Principal Cell Marker, in Nephrogenic Adenoma

Nephrogenic adenoma (NA) is a benign, reactive lesion seen predominantly in the urinary bladder and often associated with antecedent inflammation, instrumentation, or an operative history. Its histopathologic diversity can create diagnostic dilemmas and pathologists use morphologic evaluation along with available immunohistochemical (IHC) markers to navigate these challenges. IHC assays currently do not designate or specify NA's potential putative cell of origin. Leveraging single-cell RNA-sequencing technology, we nominated a principal (P) cell-collecting duct marker, L1 cell adhesion molecule (L1CAM), as a potential biomarker for NA. IHC characterization revealed L1CAM to be positive in all 35 (100%) patient samples of NA; negative expression was seen in the benign urothelium, benign prostatic glands, urothelial carcinoma (UCA) in situ, prostatic adenocarcinoma, majority of high-grade UCA, and metastatic UCA. In the study, we also used single-cell RNA sequencing to nominate a novel compendium of biomarkers specific for the proximal tubule, loop of Henle, and distal tubule (DT) (including P and intercalated cells), which can be used to perform nephronal mapping using RNA in situ hybridization and IHC technology. Employing this technique on NA we found enrichment of both the P-cell marker L1CAM and, the proximal tubule type-A and -B cell markers, PDZKI1P1 and PIGR, respectively. The cell-type markers for the intercalated cell of DTs (LINC01187 and FOXI1), and the loop of Henle (UMOD and IRX5), were found to be uniformly absent in NA. Overall, our findings show that based on cell type-specific implications of L1CAM expression, the shared expression pattern of L1CAM between DT P cells and NA. L1CAM expression will be of potential value in assisting surgical pathologists toward a diagnosis of NA in challenging patient samples.

Single-cell sequencing reveals novel proliferative cell type: a key player in renal cell carcinoma prognosis and therapeutic response

Renal cell carcinoma (RCC) is characterized by a variety of subtypes, each defined by unique genetic and morphological features. This study utilizes single-cell RNA sequencing to explore the molecular heterogeneity of RCC. A highly proliferative cell subset, termed as "Prol," was discovered within RCC tumors, and its increased presence was linked to poorer patient outcomes. An artificial intelligence network, encompassing traditional regression, machine learning, and deep learning algorithms, was employed to develop a Prol signature capable of predicting prognosis. The signature demonstrated superior performance in predicting RCC prognosis compared to other signatures and exhibited pan-cancer prognostic capabilities. RCC patients with high Prol signature scores exhibited resistance to targeted therapies and immunotherapies. Furthermore, the key gene CEP55 from the Prol signature was validated by both proteinomics and quantitative real time polymerase chain reaction. Our findings may provide new insights into the molecular and cellular mechanisms of RCC and facilitate the development of novel biomarkers and therapeutic targets.

CXCL3/TGF-β-mediated crosstalk between CAFs and tumor cells augments RCC progression and sunitinib resistance

Cancer-associated fibroblasts (CAFs) play a significant role in tumor development and treatment failure, yet the precise mechanisms underlying their contribution to renal cell carcinoma (RCC) remains underexplored. This study explored the interaction between CAFs and tumor cells, and related mechanisms. CAFs isolated from tumor tissues promoted the tumor progression and drugs resistance both in vivo and in vitro. Mechanistically, chemokine (C-X-C motif) ligand (CXCL) 3 secreted from CAFs mediated its effects. CXCL3 activated its receptor CXCR2 to active the downstream ERK1/2 signaling pathway, subsequently promoting epithelial-mesenchymal transition and cell stemness. Blocking the crosstalk between CAFs and tumor cells by CXCR2 inhibitor SB225002 attenuated the functions of CAFs. Furthermore, Renca cells facilitated the transformation of normal interstitial fibroblasts (NFs) into CAFs and the expression of CXCL3 through TGF-β-Smad2/3 signaling pathway. In turn, transformed NFs promoted the tumor progression and drug resistance of RCC. These findings may constitute potential therapeutic strategies for RCC treatment.

Decoding ecosystem heterogeneity and transcriptional regulation characteristics of multi-subtype renal cell carcinoma

Background

Renal cell carcinoma (RCC) is characterized by its heterogeneity and the complexity of its tumor microenvironment. This study addresses the need to understand RCC at a cellular level, with a focus on its three main subtypes: clear cell (ccRCC), chromophobe (chRCC), and papillary renal cell carcinoma (pRCC).

Objective

This study aims to comprehensively characterize the cellular diversity and intercellular communication networks of RCC subtypes using scRNA-seq technology. By focusing on macrophages and cancer-associated fibroblasts (CAFs), we seek to reveal their functional states, developmental trajectories, and signaling pathways.

Methodology

We utilized single-cell RNA sequencing (scRNA-seq) data from various kidney cancer subtypes. Advanced analytical techniques, including Uniform Manifold Approximation and Projection (UMAP) and Reactome Gene Set Variation Analysis (ReactomeGSA), were employed to assess cellular heterogeneity and pathway activities. The developmental dynamics of macrophages were studied using CytoTRACE, and cell-to-cell communication was analyzed to identify subtype-specific interaction networks.

Results

Our comprehensive analysis revealed significant cellular diversity within RCC. Distinct macrophage and CAF subpopulations were identified, each exhibiting unique gene expression profiles and pathway activities. Notably, ccRCC showed prominent bidirectional communication between macrophages and CAFs, while chRCC and pRCC displayed disrupted signaling pathways. Metabolic pathway analysis reflected the adaptability of macrophages and CAFs to the tumor microenvironment, and the MIF signaling pathway was identified as a key mediator of cellular interactions.

Conclusion

The study highlights the cellular heterogeneity and the intricate communication networks within RCC subtypes, underscoring the complexity of the tumor microenvironment. Our findings suggest that targeting specific cellular interactions and pathways may offer new avenues for therapeutic intervention in RCC. The unique macrophage and CAF profiles across RCC subtypes provide valuable insights for the development of personalized and targeted treatment strategies.

Single-cell resolution characterization of myeloid-derived cell states with implication in cancer outcome

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.

YAP represses the TEAD-NF-κB complex and inhibits the growth of clear cell renal cell carcinoma

The Hippo pathway is generally understood to inhibit tumor growth by phosphorylating the transcriptional cofactor YAP to sequester it to the cytoplasm and reduce the formation of YAP-TEAD transcriptional complexes. Aberrant activation of YAP occurs in various cancers. However, we found a tumor-suppressive function of YAP in clear cell renal cell carcinoma (ccRCC). Using cell cultures, xenografts, and patient-derived explant models, we found that the inhibition of upstream Hippo-pathway kinases MST1 and MST2 or expression of a constitutively active YAP mutant impeded ccRCC proliferation and decreased gene expression mediated by the transcription factor NF-κB. Mechanistically, the NF-κB subunit p65 bound to the transcriptional cofactor TEAD to facilitate NF-κB-target gene expression that promoted cell proliferation. However, by competing for TEAD, YAP disrupted its interaction with NF-κB and prompted the dissociation of p65 from target gene promoters, thereby inhibiting NF-κB transcriptional programs. This cross-talk between the Hippo and NF-κB pathways in ccRCC suggests that targeting the Hippo-YAP axis in an atypical manner-that is, by activating YAP-may be a strategy for slowing tumor growth in patients.

Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs' signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, 'Cellchat' revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

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.

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms

BACKGROUNDS

A growing number of expression quantitative trait loci (eQTLs) have been found to be linked with tumorigenesis. In this article, we employed integrated Mendelian randomization (MR) analyses to identify novel susceptibility genes in renal cancer (RC) and reveal their potential mechanisms.

METHODS

Two-sample MR analyses were performed to infer causal relationships between eQTLs, metabolites, and RC risks through the "TwoSampleMR" R package. Sensitivity analyses, such as heterogeneity, pleiotropy, and leave-one-out analysis, were used to assess the stability of our outcomes. Summary-data-based MR (SMR) analyses were used to verify the causal relationships among cis-eQTLs and RC risks via the SMR 1.3.1 software.

RESULTS

Our results provided the first evidence for AFF3 eQTL elevating RC risks, suggesting its oncogenic roles (IVW method; odds ratio (OR) = 1.0005; 95% confidence interval (CI) = 1.0001-1.0010; P = 0.0285; heterogeneity = 0.9588; pleiotropy = 0.8397). Further SMR analysis validated the causal relationships among AFF3 cis-eQTLs and RC risks (P < 0.05). Moreover, the TCGA-KIRC, the ICGC-RC, and the GSE159115 datasets verified that the AFF3 gene was more highly expressed in RC tumors than normal control via scRNA-sequencing and bulk RNA-sequencing (P < 0.05). Gene set enrichment analysis (GSEA) analysis identified six potential biological pathways of AFF3 involved in RC. As for the potential mechanism of AFF3 in RC, we concluded in this article that AFF3 eQTL could negatively modulate the levels of the X-11,315 metabolite (IVW method; OR = 0.9127; 95% CI = 0.8530-0.9765; P = 0.0081; heterogeneity = 0.4150; pleiotropy = 0.8852), exhibiting preventive effects against RC risks (IVW method; OR = 0.9987; 95% CI = 0.9975-0.9999; P = 0.0380; heterogeneity = 0.5362; pleiotropy = 0.9808).

CONCLUSIONS

We concluded that AFF3 could serve as a novel eQTL-mediated susceptibility gene in RC and reveal its potential mechanism of elevating RC risks via negatively regulating the X-11,315 metabolite levels.

Development of prognostic signatures and risk index related to lipid metabolism in ccRCC

Background

Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment.

Methods

We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives.

Results

Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens.

Conclusion

Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.

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

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

Single-cell transcriptomics reveals antigen-presenting capacity and therapeutic resistance potential of immunomodulatory endothelial cells in colorectal cancer

BACKGROUND

The heterogeneity of tumor endothelial cells (TECs) hinders the efficacy of antiangiogenic therapies (AATs). Only a small percentage of angiogenic TECs are considered effective targets for AATs. Immunomodulatory ECs (IMECs), as a newly focused functional subgroup of endothelial cells (ECs), are being evaluated for their ability to regulate tumor immune balance and influence existing AATs.

METHODS

Based on single-cell transcriptome data from colorectal cancer in a publicly available database, we conducted a wide array of bioinformatic approaches to study EC subsets that meet the IMECs definition. Our investigation encompassed the gene expression signatures of these subsets, cellular composition differences, cell-cell interactions.

RESULTS

Two subsets that meet the IMECs definition were found in tumors and para-cancerous tissues. Combined with the results of gene ontological analysis and interaction with CD4+ T cells, we found that IMECs can present MHC-II antigens to mature CD4+ T cells. There were differences in the level of interaction between IMECs and different types of mature CD4+ T cell subsets. In addition, IMEC subsets had different expression levels of angiogenesis related genes. The angiogenesis score of IMECs decreased after patients received immunotherapy. IMEC subsets do not depend on a single proangiogenic receptor and are involved in regulating angiogenesis, which may reduce the efficacy of AATs. The adverse effects of specific IMEC subsets on AATs were validated in the RNA-seq dataset of the bevacizumab treatment group.

CONCLUSION

Our study suggests the potential MHC-II antigen presentation capacity of IMECs and the enhanced angiogenesis characteristics within tumors. The function of IMECs in the vascular network may have a potentially adverse effect on AATs. Controlling the functional properties of IMECs may be a new angle for tumor therapy.

PABPC1L Induces IDO1 to Promote Tryptophan Metabolism and Immune Suppression in Renal Cell Carcinoma

The tumor microenvironment (TME) in renal cell carcinomas (RCC) is marked by substantial immunosuppression and immune resistance despite having extensive T-cell infiltration. Elucidation of the mechanisms underlying immune evasion could help identify therapeutic strategies to boost the efficacy of immune checkpoint blockade (ICB) in RCC. This study uncovered a mechanism wherein the polyadenylate-binding protein PABPC1L modulates indoleamine 2,3-dioxygenase 1 (IDO1), a prospective target for immunotherapy. PABPC1L was markedly upregulated in RCC, and high PABPC1L expression correlated with unfavorable prognosis and resistance to ICB. PABPC1L bolstered tryptophan metabolism by upregulating IDO1, inducing T-cell dysfunction and Treg infiltration. PABPC1L enhanced the stability of JAK2 mRNA, leading to increased JAK2-STAT1 signaling that induced IDO1 expression. Additionally, PABPC1L-induced activation of the JAK2-STAT1 axis created a positive feedback loop to promote PABPC1L transcription. Conversely, loss of PABPC1L diminished IDO1 expression, mitigated cytotoxic T-cell suppression, and enhanced responsiveness to anti-PD-1 therapy in patient-derived xenograft models. These findings reveal the crucial role of PABPC1L in facilitating immune evasion in RCC and indicate that inhibiting PABPC1L could be a potential immunotherapeutic approach in combination with ICB to improve patient outcomes.

SIGNIFICANCE

PABPC1L functions as a key factor in renal cell carcinoma immune evasion, enhancing IDO1 and impeding T-cell function, and represents a potential target to enhance the efficacy of immune checkpoint blockade therapy.

Molecular mechanisms and clinical relevance of endothelial cell cross-talk in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults and stands out as one of the most vascularized and immune-infiltrated solid tumors. Overproduction of vascular endothelial growth factor A promotes uncontrolled growth of abnormal vessels and immunosuppression, and the tumor microenvironment (TME) has a prominent role in disease progression, drug targeting and drug response, and for patient outcome.

Methods

Studies of experimental models, large-scale omics approaches, and patient prognosis and therapy prediction, using gene expression signatures and tissue biomarker analysis, have been reviewed for enhanced understanding of the endothelium in ccRCC and the interplay with the surrounding TME.

Results

Preclinical and clinical studies have discovered molecular mechanisms of endothelial cross-talk of relevance for disease progression, patient prognosis, and therapy prediction. There is, however, a lack of representative ccRCC experimental models. Omics approaches have identified clinically relevant subsets of angiogenic and immune-infiltrated tumors with distinct molecular signatures and distinct endothelial cell and immune cell populations in patients.

Conclusions

Recent genetically engineered ccRCC mouse models together with emerging evidence from single cell RNA sequencing data open up for future validation studies, including multiplex imaging of ccRCC patient cohorts. These studies are of importance for therapy benefit and personalized treatment of ccRCC patients.

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma

BACKGROUND

Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP.

METHODS

RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors.

RESULTS

In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP.

CONCLUSIONS

We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

L1 Cell Adhesion Molecule (L1CAM) Expression and Molecular Alterations Distinguish Low-Grade Oncocytic Tumor From Eosinophilic Chromophobe Renal Cell Carcinoma

Renal low-grade oncocytic tumor (LOT) is a recently recognized renal cell neoplasm designated within the "other oncocytic tumors" category in the 2022 World Health Organization classification system. Although the clinicopathologic, immunohistochemical, and molecular features reported for LOT have been largely consistent, the data are relatively limited. The morphologic overlap between LOT and other low-grade oncocytic neoplasms, particularly eosinophilic chromophobe renal cell carcinoma (E-chRCC), remains a controversial area in renal tumor classification. To address this uncertainty, we characterized and compared large cohorts of LOT (n = 67) and E-chRCC (n = 69) and revealed notable differences between the 2 entities. Clinically, LOT predominantly affected women, whereas E-chRCC showed a male predilection. Histologically, although almost all LOTs were dominated by a small-nested pattern, E-chRCC mainly showed solid and tubular architectures. Molecular analysis revealed that 87% of LOT cases harbored mutations in the tuberous sclerosis complex (TSC)-mTOR complex 1 (mTORC1) pathway, most frequently in MTOR and RHEB genes; a subset of LOT cases had chromosomal 7 and 19q gains. In contrast, E-chRCC lacked mTORC1 mutations, and 60% of cases displayed chromosomal losses characteristic of chRCC. We also explored the cell of origin for LOT and identified L1 cell adhesion molecule (L1CAM), a collecting duct and connecting tubule principal cell marker, as a highly sensitive and specific ancillary test for differentiating LOT from E-chRCC. This distinctive L1CAM immunohistochemical labeling suggests the principal cells as the cell of origin for LOT, unlike the intercalated cell origin of E-chRCC and oncocytoma. The ultrastructural analysis of LOT showed normal-appearing mitochondria and intracytoplasmic lumina with microvilli, different from what has been described for chRCC. Our study further supports LOT as a unique entity with a benign clinical course. Based on the likely cell of origin and its clinicopathologic characteristics, we propose that changing the nomenclature of LOT to "Oncocytic Principal Cell Adenoma of the Kidney" may be a better way to define and describe this entity.

PTK6: An emerging biomarker for prognosis and immunotherapeutic response in clear cell renal carcinoma (KIRC)

Kidney renal clear cell carcinoma (KIRC), one of the most prevalent form of kidney carcinoma, is highly aggressive cancer known for significant immune infiltration and high mortality rates. The absence of sensitivity to traditional therapy has spurred the search for new treatments. Protein Tyrosine Kinase 6 (PTK6) is implicated in promoting cancer growth, spread, and metastasis. Our review of The Cancer Genome Atlas database revealed PTK6 overexpression in KIRC, though its specific role in this cancer type was unclear. We investigated PTK6's cancer-promoting roles in KIRC using the database and confirmed our findings with patient-derived tissues. Our analysis showed that elevated PTK6 expression is linked to worse outcomes and higher levels of immune infiltration. It also correlates positively with neo-antigens (NEO) and DNA ploidy changes in KIRC. This research delves into PTK6's role in KIRC development, suggesting PTK6 as a possible biomarker for prognosis and treatment in KIRC.

Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

Harnessing atomic force microscopy-based single-cell analysis to advance physical oncology

Single-cell analysis is an emerging and promising frontier in the field of life sciences, which is expected to facilitate the exploration of fundamental laws of physiological and pathological processes. Single-cell analysis allows experimental access to cell-to-cell heterogeneity to reveal the distinctive behaviors of individual cells, offering novel opportunities to dissect the complexity of severe human diseases such as cancers. Among the single-cell analysis tools, atomic force microscopy (AFM) is a powerful and versatile one which is able to nondestructively image the fine topographies and quantitatively measure multiple mechanical properties of single living cancer cells in their native states under aqueous conditions with unprecedented spatiotemporal resolution. Over the past few decades, AFM has been widely utilized to detect the structural and mechanical behaviors of individual cancer cells during the process of tumor formation, invasion, and metastasis, yielding numerous unique insights into tumor pathogenesis from the biomechanical perspective and contributing much to the field of cancer mechanobiology. Here, the achievements of AFM-based analysis of single cancer cells to advance physical oncology are comprehensively summarized, and challenges and future perspectives are also discussed. RESEARCH HIGHLIGHTS: Achievements of AFM in characterizing the structural and mechanical behaviors of single cancer cells are summarized, and future directions are discussed. AFM is not only capable of visualizing cellular fine structures, but can also measure multiple cellular mechanical properties as well as cell-generated mechanical forces. There is still plenty of room for harnessing AFM-based single-cell analysis to advance physical oncology.

An integrative pan-cancer analysis of the molecular characteristics of dietary restriction in tumour microenvironment

BACKGROUND

Dietary restriction (DR), a general term for dieting, has been demonstrated as an effective intervention in reducing the occurrence of cancers. Molecular activities associated with DR are crucial in mediating its anti-cancer effects, yet a comprehensive exploration of the landscape of these activities at the pan-cancer level is still lacking.

METHODS

We proposed a computational approach for quantifying DR-related molecular activities and delineating the landscape of these activities across 33 cancer types and 30 normal tissues within 27,320 samples. We thoroughly examined the associations between DR-related molecular activities and various factors, including the tumour microenvironment, immunological phenotypes, genomic features, and clinical prognosis. Meanwhile, we identified two DR genes that show potential as prognostic predictors in hepatocellular carcinoma and verified them by immunohistochemical assays in 90 patients.

FINDINGS

We found that DR-related molecular activities showed a close association with tumour immunity and hold potential for predicting immunotherapy responses in various cancers. Importantly, a higher level of DR-related molecular activities is associated with improved overall survival and cancer-specific survival. FZD1 and G6PD are two DR genes that serve as biomarkers for predicting the prognosis of patients with hepatocellular carcinoma.

INTERPRETATION

This study presents a robust link between DR-related molecular activities and tumour immunity across multiple cancer types. Our research could open the path for further investigation of DR-related molecular processes in cancer treatment.

FUNDING

National Natural Science Foundation of China (Grant No. 82000628) and the Guangdong-Hong Kong-Macao University Joint Laboratory of Interventional Medicine Foundation of Guangdong Province (Grant No. 2023LSYS001).

Exosomes in renal cell carcinoma: challenges and opportunities

Renal cell carcinoma (RCC) is the most common type of kidney cancer that accounts for approximately 2-3% of adult malignancies. Among the primary treatment methods for this type of cancer are surgery and targeted treatment. Still, due to less than optimal effectiveness, there are problems such as advanced distant metastasis, delayed diagnosis, and drug resistance that continue to plague patients. In recent years, therapeutic advances have increased life expectancy and effective treatment in renal cell carcinoma patients. One of these methods is the use of stem cells. Although the therapeutic effects of stem cells, especially mesenchymal stem cells, are still impressive, today, extracellular vesicles (EVs) as carrying molecules and various mediators in intercellular communications, having a central role in tumorigenesis, metastasis, immune evasion, and drug response, and on the other hand, due to its low immunogenicity and strong regulatory properties of the immune system, has received much attention from researchers and doctors. Despite the increasing interest in exosomes as the most versatile type of EVs, the heterogeneity of their efficacy presents challenges and, on the other hand, exciting opportunities for diagnostic and clinical interventions.In the upcoming article, we will review the various aspects of exosomes' effects in the prevention, treatment, and progress of renal cell carcinoma and also ways to optimize them to strengthen their positive sides.

Sarcoid-like reaction and hypothyroidism induced by PD-1 inhibitor treatment in metastatic renal cell carcinoma: a case report and literature review

BACKGROUND

Pembrolizumab is among the approved treatments for a variety of cancer types, including clear cell renal cell carcinoma (ccRCC). It has contributed to enhancing the prognosis of renal cell carcinoma. However, it is essential to be aware of the numerous potential immune-related side effects associated with its use.

CASE PRESENTATION

A 69-year-old patient with a history of metastatic renal cell carcinoma has been undergoing treatment with Pembrolizumab, an immune checkpoint inhibitor. The medication has led to the development of a sarcoid-like reaction, initially misinterpreted as cancer recurrence and progression. Additionally, the patient has experienced new-onset hypothyroidism, which has been attributed to the immunotherapy.

CONCLUSION

Clinicians, including oncologists, endocrinologists, and radiologists, should maintain a high level of suspicions and awareness regarding the potential adverse events associated with newly introduced immunotherapies like pembrolizumab. This knowledge is crucial for the accurate diagnosis and appropriate management of patients receiving these treatments.

Rebuilding the microenvironment of primary tumors in humans: a focus on stroma

Conventional tumor models have critical shortcomings in that they lack the complexity of the human stroma. The heterogeneous stroma is a central compartment of the tumor microenvironment (TME) that must be addressed in cancer research and precision medicine. To fully model the human tumor stroma, the deconstruction and reconstruction of tumor tissues have been suggested as new approaches for in vitro tumor modeling. In this review, we summarize the heterogeneity of tumor-associated stromal cells and general deconstruction approaches used to isolate patient-specific stromal cells from tumor tissue; we also address the effect of the deconstruction procedure on the characteristics of primary cells. Finally, perspectives on the future of reconstructed tumor models are discussed, with an emphasis on the essential prerequisites for developing authentic humanized tumor models.

Metabolic heterogeneity in clear cell renal cell carcinoma revealed by single-cell RNA sequencing and spatial transcriptomics

BACKGROUND

Clear cell renal cell carcinoma is a prototypical tumor characterized by metabolic reprogramming, which extends beyond tumor cells to encompass diverse cell types within the tumor microenvironment. Nonetheless, current research on metabolic reprogramming in renal cell carcinoma mostly focuses on either tumor cells alone or conducts analyses of all cells within the tumor microenvironment as a mixture, thereby failing to precisely identify metabolic changes in different cell types within the tumor microenvironment.

METHODS

Gathering 9 major single-cell RNA sequencing databases of clear cell renal cell carcinoma, encompassing 195 samples. Spatial transcriptomics data were selected to conduct metabolic activity analysis with spatial localization. Developing scMet program to convert RNA-seq data into scRNA-seq data for downstream analysis.

RESULTS

Diverse cellular entities within the tumor microenvironment exhibit distinct infiltration preferences across varying histological grades and tissue origins. Higher-grade tumors manifest pronounced immunosuppressive traits. The identification of tumor cells in the RNA splicing state reveals an association between the enrichment of this particular cellular population and an unfavorable prognostic outcome. The energy metabolism of CD8+ T cells is pivotal not only for their cytotoxic effector functions but also as a marker of impending cellular exhaustion. Sphingolipid metabolism evinces a correlation with diverse macrophage-specific traits, particularly M2 polarization. The tumor epicenter is characterized by heightened metabolic activity, prominently marked by elevated tricarboxylic acid cycle and glycolysis while the pericapsular milieu showcases a conspicuous enrichment of attributes associated with vasculogenesis, inflammatory responses, and epithelial-mesenchymal transition. The scMet facilitates the transformation of RNA sequencing datasets sourced from TCGA into scRNA sequencing data, maintaining a substantial degree of correlation.

CONCLUSIONS

The tumor microenvironment of clear cell renal cell carcinoma demonstrates significant metabolic heterogeneity across various cell types and spatial dimensions. scMet exhibits a notable capability to transform RNA sequencing data into scRNA sequencing data with a high degree of correlation.

Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic

The incidence of renal cell carcinoma (RCC) is increasing worldwide, yet research within this field is lagging behind other cancers. Despite increased detection of early disease as a consequence of the widespread use of diagnostic CT scans, 25% of patients have disseminated disease at diagnosis. Similarly, around 25% progress to metastatic disease following curatively intended surgery. Surgery is the cornerstone in the treatment of RCC; however, when the disease is disseminated, immunotherapy or immunotherapy in combination with a tyrosine kinase inhibitor is the patient's best option. Immunotherapy is a potent treatment, with durable treatment responses and potential to cure the patient, but only half of the patients benefit from the administered treatment, and there are currently no methods that can identify which patients will respond to immunotherapy. Moreover, there is a need to identify the patients in greatest risk of relapsing after surgery for localized disease and direct adjuvant treatment there. Even though several molecular biomarkers have been published to date, we are still lacking routinely used biomarkers to guide optimal clinical management. The purpose of this review is to highlight some of the most promising biomarkers, discuss the efforts made within this field to date, and describe the barriers needed to be overcome to have reliable and robust predictive and prognostic biomarkers in the clinic for renal cancer.

Hybrid Oncocytic Tumors (HOTs) in Birt-Hogg-Dubé Syndrome Patients-A Tale of Two Cities: Sequencing Analysis Reveals Dual Lineage Markers Capturing the 2 Cellular Populations of HOT

Birt-Hogg-Dubé (BHD) syndrome is associated with an increased risk of multifocal renal tumors, including hybrid oncocytic tumor (HOT) and chromophobe renal cell carcinoma (chRCC). HOT exhibits heterogenous histologic features overlapping with chRCC and benign renal oncocytoma, posing challenges in diagnosis of HOT and renal tumor entities resembling HOT. In this study, we performed integrative analysis of bulk and single-cell RNA sequencing data from renal tumors and normal kidney tissues, and nominated candidate biomarkers of HOT, L1CAM, and LINC01187 , which are also lineage-specific markers labeling the principal cell and intercalated cell lineages of the distal nephron, respectively. Our findings indicate the principal cell lineage marker L1CAM and intercalated cell lineage marker LINC01187 to be expressed mutually exclusively in a unique checkered pattern in BHD-associated HOTs, and these 2 lineage markers collectively capture the 2 distinct tumor epithelial populations seen to co-exist morphologically in HOTs. We further confirmed that the unique checkered expression pattern of L1CAM and LINC01187 distinguished HOT from chRCC, renal oncocytoma, and other major and rare renal cell carcinoma subtypes. We also characterized the histopathologic features and immunophenotypic features of oncocytosis in the background kidney of patients with BHD, as well as the intertumor and intratumor heterogeneity seen within HOT. We suggest that L1CAM and LINC01187 can serve as stand-alone diagnostic markers or as a panel for the diagnosis of HOT. These lineage markers will inform future studies on the evolution and interaction between the 2 transcriptionally distinct tumor epithelial populations in such tumors.

Mosaic loss of Y chromosome is associated with aging and epithelial injury in chronic kidney disease

BACKGROUND

Mosaic loss of Y chromosome (LOY) is the most common chromosomal alteration in aging men. Here, we use single-cell RNA and ATAC sequencing to show that LOY is present in the kidney and increases with age and chronic kidney disease.

RESULTS

The likelihood of a cell having LOY varies depending on its location in the nephron. Cortical epithelial cell types have a greater proportion of LOY than medullary or glomerular cell types, which may reflect their proliferative history. Proximal tubule cells are the most abundant cell type in the cortex and are susceptible to hypoxic injury. A subset of these cells acquires a pro-inflammatory transcription and chromatin accessibility profile associated with expression of HAVCR1, VCAM1, and PROM1. These injured epithelial cells have the greatest proportion of LOY and their presence predicts future kidney function decline. Moreover, proximal tubule cells with LOY are more likely to harbor additional large chromosomal gains and express pro-survival pathways. Spatial transcriptomics localizes injured proximal tubule cells to a pro-fibrotic microenvironment where they adopt a secretory phenotype and likely communicate with infiltrating immune cells.

CONCLUSIONS

We hypothesize that LOY is an indicator of increased DNA damage and potential marker of cellular senescence that can be applied to single-cell datasets in other tissues.

Integration of Pan-Cancer Single-Cell and Spatial Transcriptomics Reveals Stromal Cell Features and Therapeutic Targets in Tumor Microenvironment

Stromal cells are physiologically essential components of the tumor microenvironment (TME) that mediates tumor development and therapeutic resistance. Development of a logical and unified system for stromal cell type identification and characterization of corresponding functional properties could help design antitumor strategies that target stromal cells. Here, we performed a pan-cancer analysis of 214,972 nonimmune stromal cells using single-cell RNA sequencing from 258 patients across 16 cancer types and analyzed spatial transcriptomics from 16 patients across seven cancer types, including six patients receiving anti-PD-1 treatment. This analysis uncovered distinct features of 39 stromal subsets across cancer types, including various functional modules, spatial locations, and clinical and therapeutic relevance. Tumor-associated PGF+ endothelial tip cells with elevated epithelial-mesenchymal transition features were enriched in immune-depleted TME and associated with poor prognosis. Fibrogenic and vascular pericytes (PC) derived from FABP4+ progenitors were two distinct tumor-associated PC subpopulations that strongly interacted with PGF+ tips, resulting in excess extracellular matrix (ECM) abundance and dysfunctional vasculature. Importantly, ECM-related cancer-associated fibroblasts enriched at the tumor boundary acted as a barrier to exclude immune cells, interacted with malignant cells to promote tumor progression, and regulated exhausted CD8+ T cells via immune checkpoint ligand-receptors (e.g., LGALS9/TIM-3) to promote immune escape. In addition, an interactive web-based tool (http://www.scpanstroma.yelab.site/) was developed for accessing, visualizing, and analyzing stromal data. Taken together, this study provides a systematic view of the highly heterogeneous stromal populations across cancer types and suggests future avenues for designing therapies to overcome the tumor-promoting functions of stromal cells.

SIGNIFICANCE

Comprehensive characterization of tumor-associated nonimmune stromal cells provides a robust resource for dissecting tumor microenvironment complexity and guiding stroma-targeted therapy development across multiple human cancer types.

Decoder-seq enhances mRNA capture efficiency in spatial RNA sequencing

Spatial transcriptomics technologies with high resolution often lack high sensitivity in mRNA detection. Here we report a dendrimeric DNA coordinate barcoding design for spatial RNA sequencing (Decoder-seq), which offers both high sensitivity and high resolution. Decoder-seq combines dendrimeric nanosubstrates with microfluidic coordinate barcoding to generate spatial arrays with a DNA density approximately ten times higher than previously reported methods while maintaining flexibility in resolution. We show that the high RNA capture efficiency of Decoder-seq improved the detection of lowly expressed olfactory receptor (Olfr) genes in mouse olfactory bulbs and contributed to the discovery of a unique layer enrichment pattern for two Olfr genes. The near-cellular resolution provided by Decoder-seq has enabled the construction of a spatial single-cell atlas of the mouse hippocampus, revealing dendrite-enriched mRNAs in neurons. When applying Decoder-seq to human renal cell carcinomas, we dissected the heterogeneous tumor microenvironment across different cancer subtypes and identified spatial gradient-expressed genes related to epithelial-mesenchymal transition with the potential to predict tumor prognosis and progression.

Predictive value of SIRI and SII for metastases in RCC: a prospective clinical study

OBJECTIVES

In this prospective cross-sectional clinical study, we aimed to determine the efficiency of preoperative hematological markers namely SIRI (systemic inflammatory response index) and SII (systemic inflammatory index) for renal cell cancer to predict the possibility of postoperative metastases.

METHODS

Istanbul Education and Research Hospital, Clinic of Urology and Medical Oncology in the clinic between the dates of June 2022 to 2023 February, a diagnosis of renal cell cancer by surgical or medical oncology units imported into the treatment planning of 72 patients were included in the study. All cases with diagnoses of renal cell carcinoma were searched from hospital records. Patients with secondary malignancy, hematological or rheumatological disorders or ones with recent blood product transfusion or diagnoses of infection within the 1-month-time of diagnoses were excluded for data analyses. The data within complete blood counts (CBC) analyzed just before the time of renal biopsy or surgery were studied for SIRI and SII calculations. Twenty-two metastatic and 50 non-metastatic RCC patients were included. SIRI and SII values were compared among groups to seek change of values in case of metastasis and in non-metastatic patients a cut-off value were sought to indicate malignancy before pathological diagnosis.

RESULTS

Mean age of non-metastatic RCC patients were 60.12+/-11.55 years and metastatic RCC patients were 60.25+/-11.72. Histological sub-types of the RCC specimens were clear cell (72%), chromophobe cell (17%), papillary cell (7%) and others (4%). Median SIRI values for non-metastatic and metastatic groups were 1.26 and 2.1 (mean+/-S.D. 1.76 +/-1.9 and 3.12+/-4.22 respectively (p < 0.05). Median SII values for non-metastatic and metastatic groups were 566 and 1434 (mean+/-S.D. 870 +/-1019 and 1537+/-917) respectively (p < 0.001). AUC for detection of metastasis were 0.809 for SII and 0.737 for SIRI.

CONCLUSIONS

SIRI and SII indexes seem to show a moderate efficiency to show metastases in RCC.

Single-cell profiling of the microenvironment in human bone metastatic renal cell carcinoma

Bone metastasis is of common occurrence in renal cell carcinoma with poor prognosis, but no optimal treatment approach has been established for bone metastatic renal cell carcinoma. To explore the potential therapeutic targets for bone metastatic renal cell carcinoma, we profile single cell transcriptomes of 6 primary renal cell carcinoma and 9 bone metastatic renal cell carcinoma. We also include scRNA-seq data of early-stage renal cell carcinoma, late-stage renal cell carcinoma, normal kidneys and healthy bone marrow samples in the study to better understand the bone metastasis niche. The molecular properties and dynamic changes of major cell lineages in bone metastatic environment of renal cell carcinoma are characterized. Bone metastatic renal cell carcinoma is associated with multifaceted immune deficiency together with cancer-associated fibroblasts, specifically appearance of macrophages exhibiting malignant and pro-angiogenic features. We also reveal the dominance of immune inhibitory T cells in the bone metastatic renal cell carcinoma which can be partially restored by the treatment. Trajectory analysis showes that myeloid-derived suppressor cells are progenitors of macrophages in the bone metastatic renal cell carcinoma while monocytes are their progenitors in primary tumors and healthy bone marrows. Additionally, the infiltration of immune inhibitory CD47+ T cells is observed in bone metastatic tumors, which may be a result of reduced phagocytosis by SIRPA-expressing macrophages in the bone microenvironment. Together, our results provide a systematic view of various cell types in bone metastatic renal cell carcinoma and suggest avenues for therapeutic solutions.

Single-cell transcriptome sequencing reveals aberrantly activated inter-tumor cell signaling pathways in the development of clear cell renal cell carcinoma

BACKGROUND

Aberrant intracellular or intercellular signaling pathways are important mechanisms that contribute to the development and progression of cancer. However, the intercellular communication associated with the development of ccRCC is currently unknown. The purpose of this study was to examine the aberrant tumor cell-to-cell communication signals during the development of ccRCC.

METHODS

We conducted an analysis on the scRNA-seq data of 6 ccRCC and 6 normal kidney tissues. This analysis included sub clustering, CNV analysis, single-cell trajectory analysis, cell-cell communication analysis, and transcription factor analysis. Moreover, we performed validation tests on clinical samples using multiplex immunofluorescence.

RESULTS

This study identified eleven aberrantly activated intercellular signaling pathways in tumor clusters from ccRCC samples. Among these, two of the majors signaling molecules, MIF and SPP1, were mainly secreted by a subpopulation of cancer stem cells. This subpopulation demonstrated high expression levels of the cancer stem cell markers POU5F1 and CD44 (POU5F1hiCD44hiE.T), with the transcription factor POU5F1 regulating the expression of SPP1. Further research demonstrated that SPP1 binds to integrin receptors on the surface of target cells and promotes ccRCC development and progression by activating potential signaling mechanisms such as ILK and JAK/STAT.

CONCLUSION

Aberrantly activated tumor intercellular signaling pathways promote the development and progression of ccRCC. The cancer stem cell subpopulation (POU5F1hiCD44hiE.T) promotes malignant transformation and the development of a malignant phenotype by releasing aberrant signaling molecules and interacting with other tumor cells.

Single-cell transcriptomic analyses of tumor microenvironment and molecular reprograming landscape of metastatic laryngeal squamous cell carcinoma

Laryngeal squamous cell carcinoma (LSCC) is a malignant tumor with a high probability of metastasis. The tumor microenvironment (TME) plays a critical role in cancer metastasis. To gain insights into the TME of LSCC, we conducted single-cell RNA-seq (scRNA-seq) on samples collected from LSCC patients with or without lymphatic metastasis. The stem and immune cell signatures in LSCC suggest their roles in tumor invasion and metastasis. Infiltration of a large number of regulatory T cells, dysplastic plasma cells, and macrophages that are at the early development stage in the cancerous tissue indicates an immunosuppressive state. Abundant neutrophils detected at the cancer margins reflect the inflammatory microenvironment. In addition to dynamic ligand-receptor interactions between the stromal and myeloid cells, the enhanced autophagy in endothelial cells and fibroblasts implies a role in nutrient supply. Taken together, the comprehensive atlas of LSCC obtained allowed us to identify a complex yet unique TME of LSCC, which may help identify potential diagnostic biomarkers and therapeutic targets for LSCC.

SETD2 loss in renal epithelial cells drives epithelial-to-mesenchymal transition in a TGF-β-independent manner

Histone-lysine N-methyltransferase SETD2 (SETD2), the sole histone methyltransferase that catalyzes trimethylation of lysine 36 on histone H3 (H3K36me3), is often mutated in clear cell renal cell carcinoma (ccRCC). SETD2 mutation and/or loss of H3K36me3 is linked to metastasis and poor outcome in ccRCC patients. Epithelial-to-mesenchymal transition (EMT) is a major pathway that drives invasion and metastasis in various cancer types. Here, using novel kidney epithelial cell lines isogenic for SETD2, we discovered that SETD2 inactivation drives EMT and promotes migration, invasion, and stemness in a transforming growth factor-beta-independent manner. This newly identified EMT program is triggered in part through secreted factors, including cytokines and growth factors, and through transcriptional reprogramming. RNA-seq and assay for transposase-accessible chromatin sequencing uncovered key transcription factors upregulated upon SETD2 loss, including SOX2, POU2F2 (OCT2), and PRRX1, that could individually drive EMT and stemness phenotypes in SETD2 wild-type (WT) cells. Public expression data from SETD2 WT/mutant ccRCC support the EMT transcriptional signatures derived from cell line models. In summary, our studies reveal that SETD2 is a key regulator of EMT phenotypes through cell-intrinsic and cell-extrinsic mechanisms that help explain the association between SETD2 loss and ccRCC metastasis.

USP31 serves as a potential biomarker for predicting prognosis and immune responses for clear cell renal cell carcinoma via single-cell and bulk RNA-sequencing

BACKGROUND

Currently, there is no research available on the prognosis, potential effect and therapeutic value of USP31 in clear cell renal cell carcinoma (ccRCC). To address this gap, the present study aimed to shed light on its potential roles and possible mechanisms in ccRCC.

METHODS

R software was utilized to conduct bioinformatics analyses with the data derived from The Cancer Genome Atlas (i.e. KIRC) and Gene Expression Omnibus datasets. The expression of USP31 in ccRCC was validated by a PCR. The independent prognostic ability of USP31 was evaluated by Cox regression analysis. We conducted gene set enrichment analysis (GSEA) to explore the potential USP31-related pathways. We also discussed the relationships between USP31 and immunity, by predicting its possible upstream transcription factors (TFs) by ChEA3.

RESULTS

In ccRCC, USP31 demonstrated a high level of expression and this increased expression was correlated with a poor prognosis (p < 0.05). Through univariate and multivariate Cox regression analysis, USP31 was identified as an independent prognostic factor for ccRCC (p < 0.05). Furthermore, eight USP31-related pathways were identified by GSEA (p < 0.05). Moreover, USP31 was found to be associated with microsatellite instability, tumor microenvironment, a variety of immune cells and immune checkpoints and immune infiltration (p < 0.05). Additionally, Patients with high USP31 expression in ccRCC were shown to have better curative effects after immunotherapy (p < 0.05). Finally, we found that AR, USF1, MXI1 and CLOCK could be the potential upstream TFs of USP31.

CONCLUSIONS

USP31 could serve as a potential biomarker for predicting both prognosis and immune responses, revealing its potential mechanisms of TF-USP31 mRNA networks in ccRCC.

Large-scale analysis of cell-cell communication reveals angiogenin-dependent tumor progression in clear cell renal cell carcinoma

Cellular crosstalk in the tumor microenvironment (TME) is still largely uncharacterized, while it plays an essential role in shaping immunosuppression or anti-tumor response. Large-scale analyses are needed to better decipher cell-cell communication in cancer. In this work, we used original and publicly available single-cell RNA sequencing (scRNAseq) data to characterize in-depth the communication networks in human clear cell renal cell carcinoma (ccRCC). We identified 50 putative communication channels specifically used by cancer cells to interact with other cells, including two novel angiogenin-mediated interactions. Expression of angiogenin and its receptors was validated at the protein level in primary ccRCC. Mechanistically, angiogenin enhanced ccRCC cell line proliferation and down-regulated secretion of IL-6, IL-8, and MCP-1 proinflammatory molecules. This study provides novel biological insights into molecular mechanisms of ccRCC, and suggests angiogenin and its receptors as potential therapeutic targets in clear cell renal cancer.

Molecular subtyping and characterization of clear cell renal cell carcinoma by tumor differentiation trajectories

Previous bulk RNA sequencing or whole genome sequencing on clear cell renal cell carcinoma (ccRCC) subtyping mainly focused on ccRCC cell origin or the complex tumor microenvironment (TME). Based on the single-cell RNA sequencing (scRNA-seq) data of 11 primary ccRCC specimens, cancer stem-cell-like subsets could be differentiated into five trajectories, whereby we further classified ccRCC cells into three groups with diverse molecular features. These three ccRCC subgroups showed significantly different outcomes and potential targets to tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitors (ICIs). Tumor cells in three differentiation directions exhibited distinct interactions with other subsets in the ccRCC niches. The subtyping model was examined through immunohistochemistry staining in our ccRCC cohort and validated the same classification effect as the public patients. All these findings help gain a deeper understanding about the pathogenesis of ccRCC and provide useful clues for optimizing therapeutic schemes based on the molecular subtype analysis.

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.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment

Background

Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates.

Results

21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1-ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. In CPTAC, collagen IV protein was more abundant in advanced stages of disease.

Conclusions

On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Epigenetic regulation during cancer transitions across 11 tumour types

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.

Ewing Sarcoma Single-cell Transcriptome Analysis Reveals Functionally Impaired Antigen-presenting Cells

Novel therapeutic strategies are urgently needed for patients with high-risk Ewing sarcoma and for the reduction of severe side effects for all patients. Immunotherapy may fill this need, but its successful application has been hampered by a lack of knowledge on the composition and function of the Ewing sarcoma immune microenvironment. Here, we explore the immune microenvironment of Ewing sarcoma, by single-cell RNA sequencing of 18 Ewing sarcoma primary tissue samples. Ewing sarcoma is infiltrated by natural killer, T, and B cells, dendritic cells, and immunosuppressive macrophages. Ewing sarcoma-associated T cells show various degrees of dysfunction. The antigen-presenting cells found in Ewing sarcoma lack costimulatory gene expression, implying functional impairment. Interaction analysis reveals a clear role for Ewing sarcoma tumor cells in turning the Ewing sarcoma immune microenvironment into an immunosuppressive niche. These results provide novel insights into the functional state of immune cells in the Ewing sarcoma tumor microenvironment and suggest mechanisms by which Ewing sarcoma tumor cells interact with, and shape, the immune microenvironment.

SIGNIFICANCE

This study is the first presenting a detailed analysis of the Ewing sarcoma microenvironment using single-cell RNA sequencing. We provide novel insight into the functional state of immune cells and suggests mechanisms by which Ewing tumor cells interact with, and shape, their immune microenvironment. These insights provide help in understanding the failures and successes of immunotherapy in Ewing sarcoma and may guide novel targeted (immuno) therapeutic approaches.

Unraveling the prognostic significance and molecular characteristics of tumor-infiltrating B lymphocytes in clear cell renal cell carcinoma through a comprehensive bioinformatics analysis

Introduction

Clear cell renal cell carcinoma (ccRCC) is a prevalent subtype of kidney cancer that exhibits a complex tumor microenvironment, which significantly influences tumor progression and immunotherapy response. In recent years, emerging evidence has underscored the involvement of tumor-infiltrating B lymphocytes (TIL-Bs), a crucial component of adaptive immunity, and their roles in ccRCC as compared to other tumors. Therefore, the present study endeavors to systematically explore the prognostic and molecular features of TIL-Bs in ccRCC.

Methods

Initially, xCell algorithm was used to predict TIL-Bs in TCGA-KIRC and other ccRCC transcriptomic datasets. The Log-Rank test and Cox regression were applied to explore the relationship of B-cells with ccRCC survival. Then, we used WGCNA method to identify important modules related to TIL-Bs combining Consensus subcluster and scRNA-seq data analysis. To narrow down the prospective biomarkers, a prognostic signature was proposed. Next, we explored the feature of the signature individual genes and the risk-score. Finally, the potential associations of signature with clinical phenotypes and drugs were investigated.

Results

Preliminary, we found ccRCC survival was negatively associated with TIL-Bs, which was confirmed by other datasets. Afterwards, ten co-expression modules were identified and a distinct ccRCC cluster was subsequently detected. Moreover, we assessed the transcriptomic alteration of B-cell in ccRCC and a relevant B-cell subtype was also pinpointed. Based on two core modules (brown, red), a 10-gene signature (TNFSF13B, SHARPIN, B3GAT3, IL2RG, TBC1D10C, STAC3, MICB, LAG3, SMIM29, CTLA4) was developed in train set and validated in test sets. These biomarkers were further investigated with regards to their differential expression and correlation with immune characteristics, along with risk-score related mutations and pathways. Lastly, we established a nomogram combined tumor grade and discovered underlying drugs according to their sensitivity response.

Discussion

In our research, we elucidated the remarkable association between ccRCC and B-cells. Then, we detected several key gene modules, together with close patient subcluster and B-cell subtype,which could be responsible for the TIL-Bs in ccRCC. Moreover, we proposed a 10-gene signature and investigated its molecular features from multiple perspectives. Overall, understanding the roles of TIL-Bs could aid in the immunotherapeutic approaches for ccRCC, which deserve further research to clarify the implications for patient prognosis and treatment.

Rapid Diagnosis of Urinary Tract Cancers on a LEGO-Inspired Detection Platform via Chemiresistive Profiling of Volatile Metabolites

Rapid and in situ profiling of volatile metabolites from body fluids represents a new trend in cancer diagnosis and classification in the early stages. We report herein an on-chip strategy that combines an array of conductive nanosensors with a chaotic gas micromixer for real-time monitoring of volatiles from urine and for accurate diagnosis and classification of urinary tract cancers. By integrating a class of LEGO-inspired microchambers immobilized with MXene-based sensing nanofilms and zigzag microfluidic gas channels, it enables the intensive intermingling of volatile organic chemicals with sensor elements that tremendously facilitate their ion-dipole interactions for molecular recognition. Aided with an all-in-one, point-of-care platform and an effective machine-learning algorithm, healthy or diseased samples from subpopulations (i.e., tumor subtypes, staging, lymph node metastasis, and distant metastasis) of urinary tract cancers can be reliably fingerprinted in a few minutes with high sensitivity and specificity. The developed detection platform has proven to be a noninvasive supplement to the liquid biopsies available for facile screening of urinary tract cancers, which holds great potential for large-scale personalized healthcare in low-resource areas.

Harnessing neutrophil plasticity for HCC immunotherapy

Neutrophils, until recently, have typically been considered a homogeneous population of terminally differentiated cells with highly conserved functions in homeostasis and disease. In hepatocellular carcinoma (HCC), tumour-associated neutrophils (TANs) are predominantly thought to play a pro-tumour role, promoting all aspects of HCC development and progression. Recent developments in single-cell technologies are now providing a greater insight and appreciation for the level of cellular heterogeneity displayed by TANs in the HCC tumour microenvironment, which we have been able to correlate with other TAN signatures in datasets for gastric cancer, pancreatic ductal adenocarcinoma (PDAC) and non-small cell lung cancer (NSCLC). TANs with classical pro-tumour signatures have been identified as well as neutrophils primed for anti-tumour functions that, if activated and expanded, could become a potential therapeutic approach. In recent years, therapeutic targeting of neutrophils in HCC has been typically focused on impairing the recruitment of pro-tumour neutrophils. This has now been coupled with immune checkpoint blockade with the aim to stimulate lymphocyte-mediated anti-tumour immunity whilst impairing neutrophil-mediated immunosuppression. As a result, neutrophil-directed therapies are now entering clinical trials for HCC. Pharmacological targeting along with ex vivo reprogramming of neutrophils in HCC patients is, however, in its infancy and a greater understanding of neutrophil heterogeneity, with a view to exploit it, may pave the way for improved immunotherapy outcomes. This review will cover the recent developments in our understanding of neutrophil heterogeneity in HCC and how neutrophils can be harnessed to improve HCC immunotherapy.

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.