Single cell analysis of cribriform prostate cancer reveals cell intrinsic and tumor microenvironmental pathways of aggressive disease

Urologic Imaging of the Prostate: Cancer and Mimics

This article provides a comprehensive overview of prostate cancer imaging, including detection of clinically significant cancer and initial staging. The role of multiparametric MRI in detection and local staging is discussed, along with the use of conventional imaging and advanced techniques such as Prostate-Specific Membrane Antigen-Positron Emission Tomography (PSMA-PET) for staging of nodal and distant metastases. The article also highlights the importance of differentiating benign prostatic conditions from prostate cancer on imaging to improve diagnostic accuracy and reduce false-positive interpretations.

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

Molecular Hallmarks of Prostate-specific Membrane Antigen in Treatment-naïve Prostate Cancer

BACKGROUND AND OBJECTIVE

We characterized tumor prostate-specific membrane antigen (PSMA) levels as a reflection of cancer biology and treatment sensitivities for treatment-naïve prostate cancer.

METHODS

We first correlated PSMA positron emission tomography (PET) maximum standardized uptake values (SUVmax) in primary prostate cancer with tumor FOLH1 (PSMA RNA abundance) to establish RNA as a proxy (n = 55). We then discovered and validated molecular pathways associated with PSMA RNA levels in two large primary tumor cohorts. We validated those associations in independent cohorts (18 total; 5684 tumor samples) to characterize the pathways and treatment responses associated with PSMA.

KEY FINDINGS AND LIMITATIONS

PSMA RNA abundance correlates moderately with SUVmax (ρ = 0.41). In independent cohorts, androgen receptor signaling is more active in tumors with high PSMA. Accordingly, patients with high PSMA tumors experienced longer cancer-specific survival when managed with androgen deprivation therapy for biochemical recurrence (adjusted hazard ratio [AHR] 0.54 [0.34-0.87]; n = 174). PSMA low tumors possess molecular markers of resistance to radiotherapy. Consistent with this, patients with high PSMA tumors experience longer time to recurrence following primary radiotherapy (AHR 0.50 [0.28-0.90]; n = 248). In the SAKK09/10 trial (n = 224), patients with high PSMA tumors who were managed with salvage radiotherapy experienced longer time to progression in the 64-Gy arm (restricted mean survival time [RMST] +7.60 [0.05-15.16]), but this effect was mitigated in the 70-Gy arm (RMST 3.52 [-3.30 to 10.33]). Limitations include using PSMA RNA as a surrogate for PET SUVmax.

CONCLUSIONS AND CLINICAL IMPLICATIONS

PSMA levels in treatment-naïve prostate cancer differentiate tumor biology and treatment susceptibilities. These results warrant validation using PET metrics to substantiate management decisions based on imaging.

Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 120 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells are associated with myeloid inflammation previously linked to androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

Metabolic adaptations in prostate cancer

Prostate cancer is one of the most commonly diagnosed cancers in men and is a major cause of cancer-related deaths worldwide. Among the molecular processes that contribute to this disease, the weight of metabolism has been placed under the limelight in recent years. Tumours exhibit metabolic adaptations to comply with their biosynthetic needs. However, metabolites also play an important role in supporting cell survival in challenging environments or remodelling the tumour microenvironment, thus being recognized as a hallmark in cancer. Prostate cancer is uniquely driven by androgen receptor signalling, and this knowledge has also influenced the paths of cancer metabolism research. This review provides a comprehensive perspective on the metabolic adaptations that support prostate cancer progression beyond androgen signalling, with a particular focus on tumour cell intrinsic and extrinsic pathways.

Single-Cell RNA Profiling of Ocular Adnexal Sebaceous Carcinoma Reveals a Complex Tumor Microenvironment and Identifies New Biomarkers

PURPOSE

Ocular adnexal sebaceous carcinoma (OaSC) is an aggressive malignancy that often necessitates orbital exenteration. Its tumor composition and transcriptional profile remain largely unknown, which poses a significant barrier to medical advances. Here, we report the first in-depth transcriptomic analysis of OaSC at the single-cell resolution and discern mechanisms underlying cancer progression for the discovery of potential globe-sparing immunotherapies, targeted therapies, and biomarkers to guide clinical management.

DESIGN

Laboratory investigation with a retrospective observational case series.

METHODS

Single-cell RNA sequencing was performed on six patient specimens: three primary tumors, two tumors with pagetoid spread, and a normal tarsus sample. Cellular components were identified via gene signatures. Molecular pathways underlying tumorigenesis and pagetoid spread were discerned via gene ontology analysis of the differentially expressed genes between specimens. CALML5 immunohistochemistry was performed on an archival cohort of OaSC, squamous cell carcinoma, ocular surface squamous neoplasia (OSSN), and basal cell carcinoma cases.

RESULTS

Analysis of 29,219 cells from OaSC specimens revealed tumor, immune, and stromal cells. Tumor-infiltrating immune cells include a diversity of cell types, including exhausted T-cell populations. In primary OaSC tumors, mitotic nuclear division and oxidative phosphorylation pathways are upregulated, while lipid biosynthesis and metabolism pathways are downregulated. Epithelial tissue migration pathways are upregulated in tumor cells undergoing pagetoid spread. Single-cell RNA sequencing analyses also revealed that CALML5 is upregulated in OaSC tumor cells. Diffuse nuclear and cytoplasmic CALML5 staining was present in 28 of 28 (100%) OaSC cases. Diffuse nuclear and membranous CALML5 staining was present in 5 of 25 (20%) squamous cell carcinoma and OSSN cases, while diffuse nuclear staining was present in 1 of 12 (8%) basal cell carcinoma cases.

CONCLUSIONS

This study reveals a complex OaSC tumor microenvironment and confirms that the CALML5 immunohistochemical stain is a sensitive diagnostic marker.

The Observed T Cell Receptor Space database enables paired-chain repertoire mining, coherence analysis, and language modeling

T cell activation is governed through T cell receptors (TCRs), heterodimers of two sequence-variable chains (often an α and β chain) that synergistically recognize antigen fragments presented on cell surfaces. Despite this, there only exist repositories dedicated to collecting single-chain, not paired-chain, TCR sequence data. We addressed this gap by creating the Observed TCR Space (OTS) database, a source of consistently processed and annotated, full-length, paired-chain TCR sequences. Currently, OTS contains 5.35 million redundant (1.63 million non-redundant), predominantly human sequences from across 50 studies and at least 75 individuals. Using OTS, we identify pairing biases, public TCRs, and distinct chain coherence patterns relative to antibodies. We also release a paired-chain TCR language model, providing paired embedding representations and a method for residue in-filling conditional on the partner chain. OTS will be updated as a central community resource and is freely downloadable and available as a web application.

The co-location of CD14+APOE+ cells and MMP7+ tumour cells contributed to worse immunotherapy response in non-small cell lung cancer

Intra-tumour immune infiltration is a crucial determinant affecting immunotherapy response in non-small cell lung cancer (NSCLC). However, its phenotype and related spatial structure have remained elusive. To overcome these restrictions, we undertook a comprehensive study comprising spatial transcriptomic (ST) data (28 712 spots from six samples). We identified two distinct intra-tumour infiltration patterns: immune exclusion (characterised by myeloid cells) and immune activation (characterised by plasma cells). The immune exclusion and immune activation signatures showed adverse and favourable roles in NSCLC patients' survival, respectively. Notably, CD14+APOE+ cells were recognised as the main cell type in immune exclusion samples, with increased epithelial‒mesenchymal transition and decreased immune activities. The co-location of CD14+APOE+ cells and MMP7+ tumour cells was observed in both ST and bulk transcriptomics data, validated by multiplex immunofluorescence performed on 20 NSCLC samples. The co-location area exhibited the upregulation of proliferation-related pathways and hypoxia activities. This co-localisation inhibited T-cell infiltration and the formation of tertiary lymphoid structures. Both CD14+APOE+ cells and MMP7+ tumour cells were associated with worse survival. In an immunotherapy cohort from the ORIENT-3 clinical trial, NSCLC patients who responded unfavourably exhibited higher infiltration of CD14+APOE+ cells and MMP7+ tumour cells. Within the co-location area, the MK, SEMA3 and Macrophage migration inhibitory factor (MIF) signalling pathway was most active in cell‒cell communication. This study identified immune exclusion and activation patterns in NSCLC and the co-location of CD14+APOE+ cells and MMP7+ tumour cells as contributors to immune resistance.

Identification of miRNA signature in cancer-associated fibroblast to predict recurrent prostate cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are one of the major components of prostate stromal cells, which play a crucial part in tumor development and treatment resistance. This study aimed to establish a model of CAFs-related microRNAs (miRNAs) to assess prognostic differences, tumor microenvironments, and screening of anticancer drugs by integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (buRNA-seq).

METHODS

scRNA-seq and buRNA-seq data of primary prostate cancer (PCa) were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas databases. Statistical methods including Least absolute shrinkage and selection operator (Lasso), Lasso penalized, Random Forest, Random Forest Combination, and Support Vector Machine (SVM) were performed to select hub miRNAs. Pathway analyses and assessment of infiltrating immune cells were conducted using Gene Set Enrichment Analysis and the CIBERSORT algorithm. The expression of CAFs-related miRNAs in fibroblast cell lines were validated through quantitative real-time PCR. Cell Counting Kit 8 (CCK8), wound-healing, clone formation, and cell migration assays were used to explore cell proliferation, growth, and migration in vitro. A mouse xenograft model was established to investigate the effect of CAFs on tumor growth in vivo.

RESULTS

Through single-cell transcriptomics analysis in 34 PCa patients, 89 CAFs-related mRNAs were identified. A prognostic model based on 9 CAFs-related miRNAs (hsa-miR-1258, hsa-miR-133b, hsa-miR-222-3p, hsa-miR-145-3p, hsa-miR-493-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-106b-5p, and hsa-miR-191-5p) was established to predict biochemical recurrence (BCR). We have determined through two prediction methods that NVP-TAE684 may be the optimal targeted therapy drug for treating CAFs. Downregulation of hsa-miR-106b-5p in CAFs significantly suppressed cell proliferation, migration, and colony formation in vitro. In vivo studies using a xenograft model further confirmed that hsa-miR-106b-5p downregulation significantly reduced tumor growth.

CONCLUSION

Our findings conducted an integrated bioinformatic analysis to develop a CAFs-related miRNAs model that provides prognostic insights into individualized and precise treatment for prostate adenocarcinoma patients. Downregulation of miR-106b-5p in CAFs significantly suppressed tumor growth, suggesting a potential therapeutic target for cancer treatment.

Convergent alterations in the tumor microenvironment of MYC-driven human and murine prostate cancer

How prostate cancer cells and their precursors mediate changes in the tumor microenvironment (TME) to drive prostate cancer progression is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we perform extensive single-cell RNA-sequencing (scRNA-seq) and molecular pathology of the comparative biology between human prostate cancer and key stages in the disease evolution of a genetically engineered mouse model (GEMM) of prostate cancer. Our studies of human tissues reveal that cancer cell-intrinsic activation of MYC signaling is a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Cell communication network and pathway analyses in GEMMs show that MYC oncogene-expressing neoplastic cells, directly and indirectly, reprogram the TME during carcinogenesis, leading to a convergence of cell state alterations in neighboring epithelial, immune, and fibroblast cell types that parallel key findings in human prostate cancer.

Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis

Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into cancer heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising publicly available cohorts and data generated by our research team, and established the Human Prostate Single cell Atlas (HuPSA) and Mouse Prostate Single cell Atlas (MoPSA) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution re-classified human PCa specimens, validating the presence of these novel subtypes. We then developed a user-friendly web application, "HuPSA-MoPSA" ( https://pcatools.shinyapps.io/HuPSA-MoPSA/ ), for visualizing gene expression across all newly established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

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.

Macrophage and fibroblast trajectory inference and crosstalk analysis during myocardial infarction using integrated single-cell transcriptomic datasets

BACKGROUND

Cardiac fibrosis after myocardial infarction (MI) has been considered an important part of cardiac pathological remodeling. Immune cells, especially macrophages, are thought to be involved in the process of fibrosis and constitute a niche with fibroblasts to promote fibrosis. However, the diversity and variability of fibroblasts and macrophages make it difficult to accurately depict interconnections.

METHODS

We collected and reanalyzed scRNA-seq and snRNA-seq datasets from 12 different studies. Differentiation trajectories of these subpopulations after MI injury were analyzed by using scVelo, PAGA and Slingshot. We used CellphoneDB and NicheNet to infer fibroblast-macrophage interactions. Tissue immunofluorescence staining and in vitro experiments were used to validate our findings.

RESULTS

We discovered two subsets of ECM-producing fibroblasts, reparative cardiac fibroblasts (RCFs) and matrifibrocytes, which appeared at different times after MI and exhibited different transcriptional profiles. We also observed that CTHRC1+ fibroblasts represent an activated fibroblast in chronic disease states. We identified a macrophage subset expressing the genes signature of SAMs conserved in both human and mouse hearts. Meanwhile, the SPP1hi macrophages were predominantly found in the early stages after MI, and cell communication analysis indicated that SPP1hi macrophage-RCFs interactions are mainly involved in collagen deposition and scar formation.

CONCLUSIONS

Overall, this study comprehensively analyzed the dynamics of fibroblast and macrophage subsets after MI and identified specific subsets of fibroblasts and macrophages involved in scar formation and collagen deposition.

Unveiling Novel Double-Negative Prostate Cancer Subtypes Through Single-Cell RNA Sequencing Analysis

Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into disease heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising both publicly available cohorts and data generated by our research team, and established the HuPSA (Human Prostate Single cell Atlas) and the MoPSA (Mouse Prostate Single cell Atlas) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression, and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution allowed for the re-classification of human PCa specimens, validating the presence of these novel subtypes. Leveraging these findings, we developed a user-friendly web application, "HuPSA-MoPSA" (https://pcatools.shinyapps.io/HuPSA-MoPSA/), for visualizing gene expression across all newly-established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.

The role of collagen triple helix repeat containing 1 (CTHRC1) in cancer development and progression

INTRODUCTION

Collagen triple helix repeat containing 1 (CTHRC1) is a protein that has been implicated in pro-migratory pathways, arterial tissue-repair processes, and inhibition of collagen deposition via the regulation of multiple signaling cascades. Studies have also demonstrated an upregulation of CTHRC1 in multiple cancers where it has been linked to enhanced proliferation, invasion, and metastasis. However, the understanding of the exact role and mechanisms of CTHRC1 in cancer is far from complete.

AREAS COVERED

This review focuses on analyzing the role of CTHRC1 in cancer as well as its associations with clinicopathologies and cancer-related processes and signaling. We have also summarized the available literature information regarding the role of CTHRC1 in tumor microenvironment and immune signaling. Finally, we have discussed the mechanisms associated with CTHRC1 regulations, and opportunities and challenges regarding the development of CTHRC1 as a potential target for cancer management.

EXPERT OPINION

CTHRC1 is a multifaceted protein with critical roles in cancer progression and other pathological conditions. Its association with lower overall survival in various cancers, and impact on the tumor immune microenvironment make it an intriguing target for further research and potential therapeutic interventions in cancer.

Unveiling the Genomic Landscape of Intraductal Carcinoma of the Prostate Using Spatial Gene Expression Analysis

Intraductal carcinoma of the prostate (IDCP) has recently attracted increasing interest owing to its unfavorable prognoses. To effectively identify the IDCP-specific gene expression profile, we took a novel approach of characterizing a typical IDCP case using spatial gene expression analysis. A formalin-fixed, paraffin-embedded sample was subjected to Visium CytAssist Spatial Gene Expression analysis. IDCP within invasive prostate cancer sites was recognized as a distinct cluster separate from other invasive cancer clusters. Highly expressed genes defining the IDCP cluster, such as MUC6, MYO16, NPY, and KLK12, reflected the aggressive nature of high-grade prostate cancer. IDCP sites also showed increased hypoxia markers HIF1A, BNIP3L, PDK1, and POGLUT1; decreased fibroblast markers COL1A2, DCN, and LUM; and decreased immune cell markers CCR5 and FCGR3A. Overall, these findings indicate that the hypoxic tumor microenvironment and reduced recruitment of fibroblasts and immune cells, which reflect morphological features of IDCP, may influence the aggressiveness of high-grade prostate cancer.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Identification of recurrent BRAF non-V600 mutations in intraductal carcinoma of the prostate in Chinese populations

While BRAF alterations have been established as a driver in various solid malignancies, the characterization of BRAF alterations in prostate cancer (PCa) has not been thoroughly interrogated. By bioinformatics analysis, we first found that BRAF alterations were associated with advanced PCa and exhibited mutually exclusive pattern with ERG alteration across multiple cohorts. Of the most interest, recurrent non-V600 BRAF mutations were found in 3 of 21 (14.3 %) PCa patients demonstrating IDC-P morphology. Furthermore, experimental overexpression of BRAFK601E and BRAFL597R exhibited emergence of oncogenic phenotypes with intensified MAPK signaling in vitro, which could be targeted by MEK inhibitors. Comparison of the incidence of BRAF alterations in IDC-P between western and Chinese ancestry revealed an increased prevalence in the Chinese population. The BRAF mutation may represent important genetic alteration in a subset of IDC-P, highlighting the role of MAPK signaling pathway in this subtype of PCa. To the best of knowledge, this is the first description of non-V600 BRAF mutation in setting of IDC-P, which may in part explain the aggressive phenotype seen in IDC-P and could also bring more treatment options for PCa patients with IDC-P harboring such mutations.

Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy

Patients with high tumor mutational burden (TMB) levels do not consistently respond to immune checkpoint inhibitors (ICIs), possibly because a high TMB level does not necessarily result in adequate infiltration of CD8+ T cells. Using bulk ribonucleic acid sequencing (RNA-seq) data from 9311 tumor samples across 30 cancer types, we developed a novel tool called the modulator of TMB-associated immune infiltration (MOTIF), which comprises genes that can determine the extent of CD8+ T cell infiltration prompted by a certain TMB level. We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle. By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors, we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8+ T cell infiltration. Using pretreatment RNA-seq data from 13 ICI-treated cohorts, we validated the use of MOTIF in predicting CD8+ T cell infiltration and ICI efficacy. Among the components of MOTIF, we identified EMC3 as a negative regulator of CD8+ T cell infiltration, which was validated via in vivo studies. Additionally, MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8+ T cell infiltration and improve ICI efficacy.

Agent-based modeling of the prostate tumor microenvironment uncovers spatial tumor growth constraints and immunomodulatory properties

Inhibiting androgen receptor (AR) signaling through androgen deprivation therapy (ADT) reduces prostate cancer (PCa) growth in virtually all patients, but response may be temporary, in which case resistance develops, ultimately leading to lethal castration-resistant prostate cancer (CRPC). The tumor microenvironment (TME) plays an important role in the development and progression of PCa. In addition to tumor cells, TME-resident macrophages and fibroblasts express AR and are therefore also affected by ADT. However, the interplay of different TME cell types in the development of CRPC remains largely unexplored. To understand the complex stochastic nature of cell-cell interactions, we created a PCa-specific agent-based model (PCABM) based on in vitro cell proliferation data. PCa cells, fibroblasts, "pro-inflammatory" M1-like and "pro-tumor" M2-like polarized macrophages are modeled as agents from a simple set of validated base assumptions. PCABM allows us to simulate the effect of ADT on the interplay between various prostate TME cell types. The resulting in vitro growth patterns mimic human PCa. Our PCABM can effectively model hormonal perturbations by ADT, in which PCABM suggests that CRPC arises in clusters of resistant cells, as is observed in multifocal PCa. In addition, fibroblasts compete for cellular space in the TME while simultaneously creating niches for tumor cells to proliferate in. Finally, PCABM predicts that ADT has immunomodulatory effects on macrophages that may enhance tumor survival. Taken together, these results suggest that AR plays a critical role in the cellular interplay and stochastic interactions in the TME that influence tumor cell behavior and CRPC development.

Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning

BACKGROUND

The tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli.

METHODS

First, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods.

RESULTS

In this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients.

CONCLUSION

This study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.

CTHRC1 promotes colorectal cancer progression by recruiting tumor-associated macrophages via up-regulation of CCL15

Tumor-associated macrophages (TAMs) represent a key factor in the tumor immune microenvironment (TME), exerting significant influence over tumor migration, invasion, immunosuppressive features, and drug resistance. Collagen triple helix repeat containing 1 (CTHRC1), a 30 KDa protein which was secreted during the tissue-repair process, is highly expressed in several malignant tumors, including colorectal cancer (CRC). Previous studies demonstrated that CTHRC1 expression in TAMs was positively correlated to M2 macrophage polarization and liver metastasis, while our discovery suggesting a novel mechanism that CTHRC1 secreted from cancer cell could indirectly interplay with TAMs. In this study, the high expression level of CTHRC1 was evaluated in CRC based on GEO and TCGA databases. Further, CTHRC1 was detected high in all stages of CRC patients by ELISA and was correlated to poor prognosis. Multispectral imaging of IHC demonstrated that M2 macrophage infiltration was increased accompanied with CTHRC1 enrichment, suggesting that CTHRC1 may have chemotactic effect on macrophages. In vitro, CTHRC1 could have chemotactic ability of macrophage in the presence of HT-29 cell line. Cytokine microarray revealed that CTHRC1 could up-regulate the CCL15 level of HT-29, pathway analysis demonstrated that CTHRC1 could regulate CCL15 by controlling the TGFβ activation and Smad phosphorylation level. In vivo, knocking down of CTHRC1 from CT-26 also inhibits tumor formation. In conclusion, CTHRC1 could promote the chemotactic ability of macrophages by up-regulating CCL15 via TGFβ/Smad pathway; additionally, a high level of CTHRC1 could promote macrophage's M2 polarization. This discovery may be related to tumor immune tolerance and tumor immunotherapy resistance in CRC. KEY MESSAGES: CTHRC1 promotes CRC progression by up-regulating CCL15 via TGF-β/Smad pathways to further recruit tumor-associated macrophages. By the means of autocrine or paracrine, CTHRC1 can indeed promote macrophage chemotaxis and enhance the infiltration of macrophages in tumor tissues but in the presence of tumor cells. CAFs were another source of CTHRC1, indicating CTHRC1 can infiltrate tumor islet as well as the stomal and be secreted from both tumor cells and CAFs. This study validated CTHRC1 as a potential immune therapy target CRC.

Characterization of HOXB13 expression patterns in localized and metastatic castration-resistant prostate cancer

HOXB13 is a key lineage homeobox transcription factor that plays a critical role in the differentiation of the prostate gland. Several studies have suggested that HOXB13 alterations may be involved in prostate cancer development and progression. Despite its potential biological relevance, little is known about the expression of HOXB13 across the disease spectrum of prostate cancer. To this end, we validated a HOXB13 antibody using genetic controls and investigated HOXB13 protein expression in murine and human developing prostates, localized prostate cancers, and metastatic castration-resistant prostate cancers. We observed that HOXB13 expression increases during later stages of murine prostate development. All localized prostate cancers showed HOXB13 protein expression. Interestingly, lower HOXB13 expression levels were observed in higher-grade tumors, although no significant association between HOXB13 expression and recurrence or disease-specific survival was found. In advanced metastatic prostate cancers, HOXB13 expression was retained in the majority of tumors. While we observed lower levels of HOXB13 protein and mRNA levels in tumors with evidence of lineage plasticity, 84% of androgen receptor-negative castration-resistant prostate cancers and neuroendocrine prostate cancers (NEPCs) retained detectable levels of HOXB13. Notably, the reduced expression observed in NEPCs was associated with a gain of HOXB13 gene body CpG methylation. In comparison to the commonly used prostate lineage marker NKX3.1, HOXB13 showed greater sensitivity in detecting advanced metastatic prostate cancers. Additionally, in a cohort of 837 patients, 383 with prostatic and 454 with non-prostatic tumors, we found that HOXB13 immunohistochemistry had a 97% sensitivity and 99% specificity for prostatic origin. Taken together, our studies provide valuable insight into the expression pattern of HOXB13 during prostate development and cancer progression. Furthermore, our findings support the utility of HOXB13 as a diagnostic biomarker for prostate cancer, particularly to confirm the prostatic origin of advanced metastatic castration-resistant tumors. © 2023 The Pathological Society of Great Britain and Ireland.

ASPORIN: A root of the matter in tumors and their host environment

Asporin (ASPN) has been identified as one of the members of the class I small leucine-rich proteoglycans (SLRPs) family in the extracellular matrix (ECM). It is involved in classic ensigns of cancers such as self-dependent growth, resistance to growth inhibitors, restricting apoptosis, cancer metastasis, and bone-related disorders. ASPN is different from other members of SLRPs, such as decorin (DCN) and biglycan (BGN), in a way that it contains a distinctive length of aspartate (D) residues in the amino (N) -terminal region. These D-repeats residues possess germline polymorphisms and are identified to be linked with cancer progression and osteoarthritis (OA). The polyaspartate stretch in the N-terminal region of the protein and its resemblance to DCN are the reasons it is called asporin. In this review, we comprehensively summarized and updated the dual role of ASPN in various malignancies, its structure in mice and humans, variants, mutations, cancer-associated signalings and functions, the relationship between ASPN and cancer-epithelial, stromal fibroblast crosstalk, immune cells and immunosuppression in cancer and other diseases. In cancer and other bone-related diseases, ASPN is identified to be regulating various signaling pathways such as TGFβ, Wnt/β-catenin, notch, hedgehog, EGFR, HER2, and CD44-mediated Rac1. These pathways promote cancer cell invasion, proliferation, and migration by mediating the epithelial-to-mesenchymal transition (EMT) process. Finally, we discussed mouse models mimicking ASPN in vivo function in cancers and the probability of therapeutic targeting of ASPN in cancer cells, fibrosis, and other bone-related diseases.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BACKGROUND

Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.

METHODS

An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.

RESULTS

We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.

CONCLUSIONS

The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Lymphotropic Pattern of Prostate-specific Membrane Antigen-detected Metastases Among Biochemically Recurrent Radical Prostatectomy Patients with Cribriform Disease

BACKGROUND

Cribriform morphology portends worse oncologic outcomes, and has unique cellular intrinsic pathway alterations and tumor microenvironments that may impact metastatic spread patterns.

OBJECTIVE

To determine whether the presence of cribriform morphology in prostatectomy specimens of patients with biochemical recurrence after radical prostatectomy (RP) is associated with the presence of metastasis on prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) and a distinct pattern of spread.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional analysis was conducted of all prostate cancer patients with biochemical recurrence after RP undergoing 18F-DCFPyL-PET/CT between December 2018 and February 2021 at the Princess Margaret Cancer Centre.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Outcomes were presence of any metastasis in the overall cohort and lymphatic versus bone/visceral metastases among patients with metastatic disease. The associations between the presence of intraductal (IDC) and/or invasive cribriform (ICC) carcinoma on the RP specimen and study outcomes were evaluated using logistic regression analyses.

RESULTS AND LIMITATIONS

The cohort included 176 patients. IDC and ICC were observed in 77 (43.8%) and 80 (45.5%) RP specimens, respectively. The median time from RP to PSMA-PET/CT was 5.0 yr. The median serum prostate-specific antigen level at PSMA-PET/CT was 1.12 ng/ml. Overall, metastasis was observed in 77 patients, of whom 58 were had lymphatic-only metastasis. On a multivariable analysis, presence of IDC on RP was associated with increased odds of overall metastasis (odds ratio [OR]: 2.17; 95% confidence interval [CI]: 1.07-4.45; p = 0.033). Presence of ICC on RP was associated with significantly increased odds of lymphatic versus bone/visceral metastases (OR: 3.13; 95% CI: 1.09-21.7; p = 0.004).

CONCLUSIONS

Presence of cribriform morphology on RP specimens of patients with biochemical failure after RP is associated with increased odds of PSMA-PET/CT-detected metastases with a lymphatic predominant pattern of spread. These findings have implications for the design and evaluation of post-RP salvage therapies.

PATIENT SUMMARY

We found that microscopic cribriform appearance correlates with disease spread on imaging in prostate cancer patients with recurrence and has a predilection for spread to lymph nodes, as opposed to bone or visceral organs.

Convergent alterations in the tumor microenvironment of MYC-driven human and murine prostate cancer

The tissue microenvironment in prostate cancer is profoundly altered. While such alterations have been implicated in driving prostate cancer initiation and progression to aggressive disease, how prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) and rigorous molecular pathology of the comparative biology between human prostate cancer and key time points in the disease evolution of a genetically engineered mouse model (GEMM) of prostate cancer. Our studies of human tissues, with validation in a large external data set, revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Likewise, numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, raising the possibility that these cell types may be a sequelae of the convergent MYC activation in the cancer cells. To test this hypothesis, we employed a GEMM of prostate epithelial cell-specific MYC activation in two mouse strains. Cell communication network and pathway analyses suggested that MYC oncogene-expressing neoplastic cells, directly and indirectly, reprogrammed the TME during carcinogenesis, leading to the emergence of cascading cell state alterations in neighboring epithelial, immune, and fibroblast cell types that paralleled key findings in human prostate cancer. Importantly, among these changes, the progression from a precursor-enriched to invasive-cancer-enriched state was accompanied by a cell-intrinsic switch from pro-immunogenic to immunosuppressive transcriptional programs with coinciding enrichment of immunosuppressive myeloid and Treg cells in the immune microenvironment. These findings implicate activation of MYC signaling in reshaping convergent aspects of the TME of prostate cancer as a common denominator across the otherwise well-documented molecular heterogeneity of human prostate cancer.

Identification and validation of cancer-associated fibroblast-related subtypes and the prognosis model of biochemical recurrence in prostate cancer based on single-cell and bulk RNA sequencing

BACKGROUND

Cancer-associated fibroblasts (CAFs) are an essential component of the tumor immune microenvironment that are involved in extracellular matrix (ECM) remodeling. We aim to investigate the characteristics of CAFs in prostate cancer and develop a biochemical recurrence (BCR)-related CAF signature for predicting the prognosis of PCa patients.

METHODS

The bulk RNA-seq and relevant clinical information were obtained from the TCGA and GEO databases, respectively. The infiltration scores of CAFs in prostate cancer patients were calculated using the MCP counter and EPIC algorithms. The single-cell RNA sequencing (scRNA-seq) was downloaded from the GEO database. Subsequently, univariate Cox regression analysis was employed to identify prognostic genes associated with CAFs. We identified two subtypes (C1 and C2) of prostate cancer that were associated with CAFs via non-negative matrix factorization (NMF) clustering. In addition, the BCR-related CAF signatures were constructed using Lasso regression analysis. Finally, a nomogram model was established based on the risk score and clinical characteristics of the patients.

RESULTS

Initially, we found that patients with high CAF infiltration scores had shorter biochemical recurrence-free survival (BCRFS) times. Subsequently, CAFs in four pairs of tumors and paracancerous tissues were identified. We discovered 253 significantly differentially expressed genes, of which 13 had prognostic significance. Using NMF clustering, we divided PCa patients into C1 and C2 subgroups, with the C1 subgroup having a worse prognosis and substantially enriched cell cycle, homologous recombination, and mismatch repair pathways. Furthermore, a BCR-related CAFs signature was established. Multivariate COX regression analysis confirmed that the BCR-related CAFs signature was an independent prognostic factor for BCR in PCa. In addition, the nomogram was based on the clinical characteristics and risk scores of the patient and demonstrated high accuracy and reliability for predicting BCR. Lastly, our findings indicate that the risk score may be a useful tool for predicting PCa patients' sensitivity to immunotherapy and drug treatment.

CONCLUSION

NMF clustering based on CAF-related genes revealed distinct TME immune characteristics between groups. The BCR-related CAF signature accurately predicted prognosis and immunotherapy response in prostate cancer patients, offering a promising new approach to cancer treatment.

Unveiling novel insights in prostate cancer through single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) is a cutting-edge technology that provides insights at the individual cell level. In contrast to traditional bulk RNA-seq, which captures gene expression at an average level and may overlook important details, scRNA-seq examines each individual cell as a fundamental unit and is particularly well-suited for identifying rare cell populations. Analogous to a microscope that distinguishes various cell types within a tissue sample, scRNA-seq unravels the heterogeneity and diversity within a single cell species, offering great potential as a leading sequencing method in the future. In the context of prostate cancer (PCa), a disease characterized by significant heterogeneity and multiple stages of progression, scRNA-seq emerges as a powerful tool for uncovering its intricate secrets.

Club-like cells in proliferative inflammatory atrophy of the prostate

Club cells are a type of bronchiolar epithelial cell that serve a protective role in the lung and regenerate damaged lung epithelium. Single-cell RNA sequencing (scRNA-seq) of young adult human prostate and urethra identified cell populations in the prostatic urethra and collecting ducts similar in morphology and transcriptomic profile to lung club cells. We further identified club cell-like epithelial cells by scRNA-seq of prostate peripheral zone tissues. Here, we aimed to identify and spatially localize club cells in situ in the prostate, including in the peripheral zone. We performed chromogenic RNA in situ hybridization for five club cell markers (CP, LTF, MMP7, PIGR, SCGB1A1) in a series of (1) nondiseased organ donor prostate and (2) radical prostatectomy specimens from individuals with prostate cancer. We report that expression of club cell genes in the peripheral zone is associated with inflammation and limited to luminal epithelial cells classified as intermediate cells in proliferative inflammatory atrophy (PIA). Club-like cells were enriched in radical prostatectomy specimens compared to nondiseased prostates and associated with high-grade prostate cancer. We previously reported that luminal epithelial cells in PIA can rarely harbor oncogenic TMPRSS2:ERG (ERG+) gene fusions, and we now demonstrate that club cells are present in association with ERG+ PIA that is transitioning to early adenocarcinoma. Finally, prostate epithelial organoids derived from prostatectomy specimens demonstrate that club-like epithelial cells can be established in organoids and are sensitive to anti-androgen-directed treatment in vitro in terms of decreased androgen signaling gene expression signatures compared to basal or hillock cells. Overall, our study identifies a population of club-like cells in PIA and proposes that these cells play an analogous role to that of club cells in bronchiolar epithelium. Our results further suggest that inflammation drives lineage plasticity in the human prostate and that club cells in PIA may be prone to oncogenic transformation. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Single-cell and bulk RNA sequencing reveal cancer-associated fibroblast heterogeneity and a prognostic signature in prostate cancer

Cancer-associated fibroblasts (CAFs), the central players in the tumor microenvironment (TME), can promote tumor progression and metastasis via various functions. However, the properties of CAFs in prostate cancer (PCa) have not been fully assessed. Therefore, we aimed to examine the CAF characteristics in PCa and construct a CAF-derived signature to predict PCa prognosis. CAFs were identified using single-cell RNA sequencing (scRNA-seq) data from 3 studies. We performed the FindAllMarkers function to extract CAF marker genes and constructed a signature to predict the biochemical relapse-free survival (bRFS) of PCa in the Cancer Genome Atlas (TCGA) cohort. Subsequently, different algorithms were applied to reveal the differences of the TME, immune infiltration, treatment responses in the high- and low-risk groups. Additionally, the CAF heterogeneity was assessed in PCa, which were confirmed by the functional enrichment analysis, gene set enrichment analysis (GSEA), and AUCell method. The scRNA-seq analysis identified a CAF cluster with 783 cells and determined 183 CAF marker genes. Cell-cell communication revealed extensive interactions between fibroblasts and immune cells. A CAF-related prognostic model, containing 7 genes (ASPN, AEBP1, ALDH1A1, BGN, COL1A1, PAGE4 and RASD1), was developed to predict bRFS and validated by 4 independent bulk RNA-seq cohorts. Moreover, the high-risk group of the signature score connected with an immunosuppressive TME, such as a higher level of M2 macrophages and lower levels of plasma cells and CD8+ T cells, and a reduced reaction rate for immunotherapy compared with low-risk group. After re-clustering CAFs via unsupervised clustering, we revealed 3 biologically distinct CAF subsets, namely myofibroblast-like CAFs (myCAFs), immune and inflammatory CAFs (iCAFs) and antigen-presenting CAFs (apCAFs). In conclusion, the CAF-derived signature, the first of its kind, can effectively predict PCa prognosis and serve as an indicator for immunotherapy. Furthermore, our study identified 3 CAF subpopulations with distinct functions in PCa.

Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer

Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.g., biopsy), radiogenomics, combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which in turn can provide non-invasive advice on individualized treatment regimens. In this study, we carried out a parallel analysis on both imaging and transcriptomics data in order to identify features associated with clinically significant PCa (defined as an ISUP grade ≥ 3), subsequently evaluating the correlation between them. Textural imaging features were extracted from multi-parametric MRI sequences (T2W, DWI, and DCE) and combined with DCE-derived parametric pharmacokinetic maps obtained using magnetic resonance dispersion imaging (MRDI). A transcriptomic analysis was performed to derive functional features on transcription factors (TFs), and pathway activity from RNA sequencing data, here referred to as transcriptomic features. For both the imaging and transcriptomic features, different machine learning models were separately trained and optimized to classify tumors in either clinically insignificant or significant PCa. These models were validated in an independent cohort and model performance was used to isolate a subset of relevant imaging and transcriptomic features to be further investigated. A final set of 31 imaging features was correlated to 33 transcriptomic features obtained on the same tumors. Five significant correlations (p < 0.05) were found, of which, three had moderate strength (|r| ≥ 0.5). The strongest significant correlations were seen between a perfusion-based imaging feature-MRDI A median-and the activities of the TFs STAT6 (-0.64) and TFAP2A (-0.50). A higher-order T2W textural feature was also significantly correlated to the activity of the TF STAT6 (-0.58). STAT6 plays an important role in controlling cell proliferation and migration. Loss of the AP2alpha protein expression, quantified by TFAP2A, has been strongly associated with aggressiveness and progression in PCa. According to our findings, a combination of texture features extracted from T2W and DCE, as well as perfusion-based pharmacokinetic features, can be considered for the prediction of clinically significant PCa, with the pharmacokinetic MRDI A feature being the most correlated with the underlying transcriptomic information. These results highlight a link between quantitative imaging features and the underlying transcriptomic landscape of prostate tumors.

Identification of TREM2-positive tumor-associated macrophages in esophageal squamous cell carcinoma: implication for poor prognosis and immunotherapy modulation

Background

It is now understood that the effectiveness of checkpoint immunotherapy can be impaired by immunosuppressive tumor-associated macrophages (TAMs). Nonetheless, the impact of different TAM subpopulations on the antitumor immune response remains unclear, mainly due to their heterogeneity. Herein, we identified a novel TAM subpopulation in esophageal squamous cell carcinoma (ESCC) that might contribute to poor clinical outcomes and immunotherapy modulation.

Methods and results

We analyzed two single-cell RNA sequencing (scRNA-seq) datasets (GSE145370 and GSE160269) of esophageal squamous cell carcinoma to identify a novel TREM2-positive TAM subpopulation characterized by upregulation of TREM2, C1QC, C1QB, C1QA, SPP1, and APOE. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) demonstrated that these genes were significantly overexpressed in ESCC. Multiplex immunofluorescence validated the infiltration of TREM2+ TAMs in ESCC tissues, which correlated with poorer overall survival (OS). The scRNA-seq analysis in dataset GSE120575 indicated significant enrichment of TREM2+ TAMs in melanoma patients (n=48) with poor immunotherapy response, which had an identical gene signature with TREM2+ TAMs from ESCC. Analysis of 29 bulk-RNA melanoma samples from dataset GSE78220 revealed that a gene signature of 40 genes associated with TREM2+ TAMs was upregulated in the transcriptome of melanomas that did not respond to anti-PD1 therapy. Validation in the TCGA ESCC cohort (n=80) showed that a high enrichment score of the TREM2+ TAM was associated with poor prognosis. In addition, 10 ESCC patients treated with anti-PD1 therapy suggested that patients who are not sensitive to immunotherapy have higher density of TREM2+TAMs infiltration.

Conclusion

Overall, TREM2+ TAM infiltration in ESCC is associated with poor prognosis and may serve as a biomarker for predicting outcomes and immunotherapy modulation in this patient population. modulation; single-cell RNA sequencing.

The Molecular Biology of Prostate Cancer Stem Cells: From the Past to the Future

Prostate cancer (PCa) continues to rank as the second leading cause of cancer-related mortality in western countries, despite the golden treatment using androgen deprivation therapy (ADT) or anti-androgen therapy. With decades of research, scientists have gradually realized that the existence of prostate cancer stem cells (PCSCs) successfully explains tumor recurrence, metastasis and therapeutic failure of PCa. Theoretically, eradication of this small population may improve the efficacy of current therapeutic approaches and prolong PCa survival. However, several characteristics of PCSCs make their diminishment extremely challenging: inherent resistance to anti-androgen and chemotherapy treatment, over-activation of the survival pathway, adaptation to tumor micro-environments, escape from immune attack and being easier to metastasize. For this end, a better understanding of PCSC biology at the molecular level will definitely inspire us to develop PCSC targeted approaches. In this review, we comprehensively summarize signaling pathways responsible for homeostatic regulation of PCSCs and discuss how to eliminate these fractional cells in clinical practice. Overall, this study deeply pinpoints PCSC biology at the molecular level and provides us some research perspectives.

Myeloid cells in the era of cancer immunotherapy: Top 3 unanswered questions

Myeloid cells are increasingly being recognized as central players orchestrating or suppressing antitumor immune responses. With the advent of high-resolution analytical methods such as single-cell technologies, we now appreciate the heterogeneity and complexity of the myeloid compartment in the context of cancer. Because of their highly plastic nature, targeting myeloid cells has shown promising results either as a monotherapy or in combination with immunotherapy in preclinical models and cancer patients. However, the complexity of myeloid cell cellular crosstalk and molecular networks contributes to our poor understanding of the different myeloid cell subsets in tumorigenesis, which makes targeting myeloid cells challenging. Here, we summarize varied myeloid cell subsets and their contribution to tumor progression with a main focus on mononuclear phagocytes. The top three unanswered questions challenging the field of myeloid cells and cancer in the era of cancer immunotherapy are addressed. Through these questions, we discuss how myeloid cell origin and identity influence their function and disease outcomes. Different therapeutic strategies used to target myeloid cells in cancer are also addressed. Finally, the durability of myeloid cell targeting is interrogated by examining the complexity of resultant compensatory cellular and molecular mechanisms.

Single-cell RNA sequencing: Inhibited Notch2 signalling underlying the increased lens fibre cells differentiation in high myopia

High myopia is the leading cause of blindness worldwide. It promotes the overgrowth of lens, which is an important component of ocular refractive system, and increases the risks of lens surgery. While postnatal growth of lens is based on the addition of lens fibre cells (LFCs) supplemented by proliferation and differentiation of lens epithelial cells (LECs), it remains unknown how these cellular processes change in highly myopic eyes and what signalling pathways may be involved. Single-cell RNA sequencing was performed and a total of 50,375 single cells isolated from the lens epithelium of mouse highly myopic and control eyes were analysed to uncover their underlying transcriptome atlas. The proportion of LFCs was significantly higher in highly myopic eyes. Meanwhile, Notch2 signalling was inhibited during lineage differentiation trajectory towards LFCs, while Notch2 predominant LEC cluster was significantly reduced in highly myopic eyes. In consistence, Notch2 was the top down-regulated gene identified in highly myopic lens epithelium. Further validation experiments confirmed NOTCH2 downregulation in the lens epithelium of human and mouse highly myopic eyes. In addition, NOTCH2 knockdown in primary human and mouse LECs resulted in enhanced differentiation towards LFCs accompanied by up-regulation of MAF and CDKN1C. These findings indicated an essential role of NOTCH2 inhibition in lens overgrowth of highly myopic eyes, suggesting a therapeutic target for future interventions.