ScRNA-seq revealed an immunosuppression state and tumor microenvironment heterogeneity related to lymph node metastasis in prostate cancer

Role of multi‑omics in advancing the understanding and treatment of prostate cancer (Review)

The application of multi‑omics methodologies, encompassing genomics, transcriptomics, proteomics, metabolomics and integrative genomics, has markedly enhanced the understanding of prostate cancer (PCa). These methods have facilitated the identification of molecular pathways and biomarkers crucial for the early detection, prognostic evaluation and personalized treatment of PCa. Studies using multi‑omics technologies have elucidated how alterations in gene expression and protein interactions contribute to PCa progression and treatment resistance. Furthermore, the integration of multi‑omics data has been used in the identification of novel therapeutic targets and the development of innovative treatment modalities, such as precision medicine. The evolving landscape of multi‑omics research holds promise for not only deepening the understanding of PCa biology but also for fostering the development of more effective and tailored therapeutic interventions, ultimately improving patient outcomes. The present review aims to synthesize current findings from multi‑omics studies associated with PCa and to assess their implications for the improvement of patient management and therapeutic outcomes. The insights provided may guide future research directions and clinical practices in the fight against PCa.

SPP1-SRD5A3 signaling axis regulated lymph node metastasis by activating Mucin type O glycan biosynthesis

Lymph node metastasis (LNM) holds substantial implications for the recurrence and survival of cancer patients, but the intricate regulatory mechanisms underlying LNM remain poorly understood. MTOGB was dominantly increased in LNM of pan-cancer, significantly activated in epithelial cells and enriched in LNM. Subsequently, we identified a specific epithelial cell subpopulation, EC4, located at the terminal of the LNM differentiation trajectory Lineage2. By intersecting differentially expressed genes in cluster 2, EC4 and Lineage2, we identified six crucial genes. Notably, the expression of Steroid 5α-reductase 3 (SRD5A3) increased with the progression of LNM stages. Knockdown of SRD5A3 effectively suppressed the MTOGB, blocking metastasis in both cell and animal models. Nilotinib was screened as a candidate inhibitor of SRD5A3 and was confirmed to remarkably decrease cancer cell metastasis. SOX4 was identified as a potential transcription factor of SRD5A3, modulated by a dramatic increase in cell communication of SPP1+ macrophages in the immune microenvironment. The supernatant from SPP1+ macrophage significantly enhanced the expression of SOX4/SRD5A3 and the metastatic ability of cancer cells, and this effect was reversed by the deletion of SPP1. Collectively, our findings illuminate the SPP1-SRD5A3 signaling as the crucial driver in LNM and suggest that its blockade could be a promising option for overcoming LNM.

Novel molecular mechanisms of immune evasion in hepatocellular carcinoma: NSUN2-mediated increase of SOAT2 RNA methylation

BACKGROUND

Hepatocellular carcinoma (HCC) is a deadly malignancy known for its ability to evade immune surveillance. NOP2/Sun RNA methyltransferase family member 2 (NSUN2), an RNA methyltransferase involved in carcinogenesis, has been associated with immune evasion and energy metabolism reprogramming. This study aimed to examine the molecular mechanisms underlying the involvement of NSUN2 in immune evasion and metabolic reprogramming of HCC.

METHODS

Single-cell transcriptomic sequencing was applied to examine cellular composition changes, particularly immune cell dynamics, in HCC and adjacent normal tissues. Bulk RNA-seq and proteomics identified key genes and proteins. Methylation sequencing and methylated RNA immunoprecipitation (MeRIP) were carried out to characterize the role of NSUN2 in 5-methylcytosine (m5C) modification of sterol O-acyltransferase 2 (SOAT2). Clinical samples from 30 HCC patients were analyzed using reverse transcription-quantitative polymerase chain reaction and Western blotting. Gene expression was manipulated using CRISPR/Cas9 and lentiviral vectors. In vitro co-culture models and metabolomics were used to study HCC cell-T cell interactions, energy metabolism, and immune evasion. Tumor growth in an orthotopic mouse model was monitored by bioluminescence imaging, with subsequent measurements of tumor weight, volume, and immunohistochemical staining.

RESULTS

Single-cell transcriptomic analysis identified a marked increase in malignant cells in HCC tissues. Cell communication analysis indicated that tumor cells might promote cancer progression by evading immune clearance. Multi-omics analyses identified NSUN2 as a key regulator in HCC development. MeRIP confirmed that NSUN2 facilitated the m5C modification of SOAT2. Analysis of human HCC tissue samples demonstrated pronounced upregulation of NSUN2 and SOAT2, along with elevated m5C levels in HCC tissues. In vitro experiments uncovered that NSUN2 augmented the reprogramming of energy metabolism and repressed the activity and cytotoxicity of CD8+ T cells, contributing to immune evasion. In vivo studies further substantiated the role of NSUN2 in fostering immune evasion and tumor formation of HCC by modulating the m5C modification of SOAT2.

CONCLUSIONS

The findings highlight the critical role of NSUN2 in driving HCC progression through the regulation of m5C modification on SOAT2. These findings present potential molecular markers for HCC diagnosis and therapeutic targets for its treatment.

Engineered nanovesicles targeting SERPINE1 overcome temozolomide resistance in glioblastoma

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with limited treatment options due to its resistance to temozolomide (TMZ). This study explores a novel therapeutic approach using engineered cell membrane nanovesicles loaded with SERPINE1 inhibitors to combat TMZ resistance. High-throughput sequencing identified pivotal genes associated with resistance, while the nanovesicles demonstrated excellent stability and the ability to cross the blood-brain barrier. Functional assays revealed significant suppression of GBM cell viability, migration, and invasion, accompanied by reduced expression of SERPINE1 and VEGF, suggesting inhibition of angiogenesis and tumor progression. These findings highlight the potential of SERPINE1-targeted nanovesicles as an innovative and effective strategy for overcoming TMZ resistance in GBM.

Molecular biology of the deadliest cancer - glioblastoma: what do we know?

Glioblastomas are the most prevalent primary brain tumors and are associated with a dramatically poor prognosis. Despite an intensive treatment approach, including maximal surgical tumor removal followed by radio- and chemotherapy, the median survival for glioblastoma patients has remained around 18 months for decades. Glioblastoma is distinguished by its highly complex mechanisms of immune evasion and pronounced heterogeneity. This variability is apparent both within the tumor itself, which can exhibit multiple phenotypes simultaneously, and in its surrounding microenvironment. Another key feature of glioblastoma is its "cold" microenvironment, characterized by robust immunosuppression. Recent advances in single-cell RNA sequencing have uncovered new promising insights, revealing previously unrecognized aspects of this tumor. In this review, we consolidate current knowledge on glioblastoma cells and its microenvironment, with an emphasis on their biological properties and unique patterns of molecular communication through signaling pathways. The evidence underscores the critical need for personalized poly-immunotherapy and other approaches to overcome the plasticity of glioblastoma stem cells. Analyzing the tumor microenvironment of individual patients using single-cell transcriptomics and implementing a customized immunotherapeutic strategy could potentially improve survival outcomes for those facing this formidable disease.

Unveiling the key mechanisms of FOLR2+ macrophage-mediated antitumor immunity in breast cancer using integrated single-cell RNA sequencing and bulk RNA sequencing

Breast cancer (BRCA) is a common malignant tumor, and its immune microenvironment plays a crucial role in disease progression. In this research, we utilized single-cell RNA sequencing and bulk RNA sequencing technologies, combined with in vivo and in vitro experiments, to thoroughly investigate the immunological functions and mechanisms of FOLR2+ macrophages in BRCA. Our findings demonstrate a significant enhancement in the interaction between FOLR2+ macrophages and CD8+ T cells within the tumor tissues of BRCA patients. FOLR2 is closely associated with T cell infiltration in the tumor microenvironment of BRCA patients, particularly with CD8+ T cells. By secreting CXCL9 and engaging with CXCR3, FOLR2+ macrophages can activate the functionality of CD8+ T cells, thereby promoting cancer cell apoptosis. Further animal experiments confirm that FOLR2+ macrophages activate CD8+ T cells through the CXCL9-CXCR3 axis, exhibiting an antitumor immunity effect in BRCA. FOLR2+ macrophages play a crucial role in antitumor immunity in BRCA through the CXCL9-CXCR3 axis.

MASP1 modulation as a novel therapeutic target in severe pediatric pertussis: insights from a multi-omics approach

Pertussis, a severe infectious disease in children, has become increasingly prominent in recent years. This study aims to investigate the role of the MASP1 protein in severe pertussis in children through multi-omics analysis, providing a theoretical basis for the development of novel therapeutic strategies. The study retrieved macro-genome and 16S rRNA data of pediatric pertussis from public databases to analyze microbial diversity and specific flora abundance, conducting pathway functional enrichment analysis. Differential expression analysis of transcriptome data and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis, combined with machine learning, identified the key gene MASP1. A Bordetella pertussis infection model was established using human bronchial epithelial cell line HBE135-E6E7 to validate MASP1 expression changes and investigate its relationship with airway epithelial cell damage by constructing cell lines overexpressing and knocking down MASP1. Finally, the impact of inhibiting MASP1 expression on infection symptoms was evaluated using a mouse pertussis infection model. The results revealed significant differences in microbial diversity and specific flora abundance between healthy children and those with pertussis, with MASP1 significantly upregulated in severe pertussis and its inhibition alleviating infection symptoms. The study highlights the critical role of MASP1 in pertussis, providing a crucial foundation for developing therapeutic strategies targeting MASP1.

ITGB4/GNB5 axis promotes M2 macrophage reprogramming in NSCLC metastasis

OBJECTIVE

Metastasis of non-small cell lung cancer (NSCLC) is a leading cause of high mortality. In recent years, the role of M2 macrophages in promoting tumor metastasis within the tumor microenvironment has garnered increasing attention. This study aims to investigate the role and potential mechanisms of the ITGB4/GNB5 axis in regulating M2 macrophage reprogramming and influencing NSCLC metastasis.

METHODS

This study first used single-cell sequencing technology to reveal the diverse subpopulation structure of NSCLC tumor tissues. Data analysis then identified the correlation between M2 macrophages and the malignant phenotype of NSCLC. Flow cytometry and immunohistochemistry were used to detect changes in M2 macrophages in NSCLC tissues. The impact of the ITGB4/GNB5 axis on M2 macrophage function was assessed through RNA sequencing and proteomic analysis. Finally, in vitro cell experiments and in vivo mouse models were used to validate the function and regulatory mechanisms of this axis.

RESULTS

Our study found diverse cellular subpopulations in NSCLC tumor tissues, with M2 macrophages closely associated with the malignant phenotype of NSCLC. We identified ITGB4 as a characteristic gene of NSCLC and predicted GNB5 as an interacting gene through database analysis. Activation of the ITGB4/GNB5 axis was shown to enhance M2 macrophage polarization, promoting their accumulation in the tumor microenvironment. This change further facilitated NSCLC invasion and metastasis by modulating related cytokines and signaling pathways. Animal experiments demonstrated that inhibition of the ITGB4/GNB5 axis significantly reduced tumor growth and metastasis.

CONCLUSION

The ITGB4/GNB5 axis reshapes the TME by promoting M2 macrophage polarization and functional enhancement, thereby facilitating tumor invasion and metastasis in NSCLC. This research provides new insights into the molecular mechanisms of NSCLC and offers potential molecular targets for future targeted therapies.

Metabolic shifts in lipid utilization and reciprocal interactions within the lung metastatic niche of triple-negative breast cancer revealed by spatial multi-omics

The Triple-Negative Breast Cancer (TNBC) subtype constitutes 15-20% of breast cancer cases and is associated with the poorest clinical outcomes. Distant metastasis, particularly to the lungs, is a major contributor to the high mortality rates in breast cancer patients. Despite this, there has been a lack of comprehensive insights into the heterogeneity of metastatic tumors and their surrounding ecosystem in the lungs. In this study, we utilized spatial RNA sequencing technology to investigate the heterogeneity of lung metastatic tumors and their microenvironment in two spontaneous lung metastatic mouse models. Our findings revealed an increase in metabolic-related genes within the cancer cells, with the hub gene Dlat (Dihydrolipoamide S-Acetyltransferase) showing a significant association with the development of lung metastatic tumors. Upregulation of Dlat led to the reprogramming of fatty acid utilization, markedly enhancing the bioenergetic capacity of cancer cells. This finding was corroborated by the increased dependence on fatty acid utilization in lung metastatic cancer cells, and inhibition of Dlat in breast cancer cells exhibited a reduced oxygen consumption rate. Consequently, inhibition of Dlat resulted in decreased survival capacity of breast cancer by reducing cancer stem cell properties and cell adhesion in the lung in vivo. The three cell components within the lung metastatic niche, including CD163+ macrophages, neutrophils, and endothelial cells, expressed elevated levels of ApoE, leading to the secretion of various protumorigenic molecules that promote cancer cell growth in the lung. These molecules include galectin-1, S100A10, S100A4, and S100A6. Collectively, our findings highlight the lipid metabolism reprogramming of cancer and components of the tumor microenvironment that support lung metastasis of TNBC breast cancer.

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.

EVA1B facilitates esophageal squamous carcinoma progression and recruitment of immunosuppressive myeloid-derived suppressor cells in the tumor microenvironment

Eva-1 Homolog B (EVA1B) has been preliminarily found to be associated with prognostic outcomes and immune microenvironment in several human cancer types, but the implications of EVA1B in ESCC remain unclear. Human ESCC and paracancerous tissues were gathered in this study, and EVA1B expression was measured via immunoblotting. EC109 and KYSE-180 ESCC cells were stably infected by sh-EVA1B lentivirus, and functional experiments were subsequently implemented. Syngeneic mouse models were built, and the expansion and recruitment of myeloid-derived suppressor cells (MDSCs) were then evaluated. The results showed that EVA1B presented the notable up-regulation in clinical ESCC tissues versus controls, and was connected to more advanced stages and the abundance of MDSCs. Silencing EVA1B notably attenuated proliferation of ESCC cells and tumor growth in syngeneic mouse models. Moreover, EVA1B suppression resulted in apoptosis and cell cycle arrest, and impaired ESCC cell aggressiveness. Among ESCC patients, EVA1B was strongly correlated to EMT pathway activity. Targeted suppression of EVA1B mitigated the expression of Wnt3a, β-catenin and LRP6 in ESCC cells and tumor xenografts. Additionally, inhibition of EVA1B attenuated the expansion and recruitment of MDSCs within the immune microenvironment based upon the reduction in the percentage of CD11b+Gr-1+ immunosuppressive MDSCs as well as the expression of MDSC expansion stimulators (S100A8, S100A9, Arg-1, and VEGF). Collectively, our findings unveiled the contribution of high expression of EVA1B to ESCC progression and MDSCs expansion and recruitment, indicating that targeted suppression of EVA1B may be a potential treatment choice for ESCC patients.

Immunome profiling in prostate cancer: a guide for clinicians

Tumor immune microenvironment (TIME) plays a key role to understand how tumors respond to prostate cancer (PC) therapies and potential mechanisms of resistance. Previous research has suggested that specific genomic aberrations, such as microsatellite instability (MSI) or CDK12 bi-allelic loss can allow PC patients more likely to respond to immune checkpoint inhibitors (ICI) or other immune therapies. However, responses to these treatments remain highly variable even in selected patients. Thus, it is essential to obtain more information about tumor immune cells that infiltrate these tumors, and on their plasticity and interactions, in order to better understand the underlying biology to allow development of new therapeutic strategies. This review analyzes: 1) How interactions among immune cell populations and other cells infiltrating the tumor stroma can modulate the progression of PC, 2) How the standard therapies to treat PC (such as androgen deprivation therapy, new androgen-directed hormone therapy or chemotherapy) may influence the dynamic changes of the immunome and 3) What are the limitations in characterizing the immune landscape of the host´s response to tumors.

Hepatic stellate cells promote hepatocellular carcinoma development by regulating histone lactylation: Novel insights from single-cell RNA sequencing and spatial transcriptomics analyses

This study evaluated the cellular heterogeneity and molecular mechanisms of hepatocellular carcinoma (HCC). Single cell RNA sequencing (scRNA-seq), transcriptomic data, histone lactylation-related genes were collected from public databases. Cell-cell interaction, trajectory, pathway, and spatial transcriptome analyses were executed. Differential expression and survival analyses were conducted. Western blot, Real-time reverse transcription PCR (qRT-PCR), and Cell Counting Kit 8 (CCK8) assay were used to detect the expression of αSMA, AKR1B10 and its target genes, and verify the roles of AKR1B10 in HCC cells. Hepatic stellate cell (HSC) subgroups strongly interacted with tumor cell subgroups, and their spatial distribution was heterogeneous. Two candidate prognostic genes (AKR1B10 and RMRP) were obtained. LONP1, NPIPB3, and ZSWIM6 were determined as AKR1B10 targets. Besides, the expression levels of AKR1B10 and αSMA were significantly increased in LX-2 + HepG2 and LX-2 + HuH7 groups compared to those in LX-2 group, respectively. sh-AKR1B10 significantly inhibited the HCC cell proliferation and change the expression of AKR1B10 target genes, Bcl-2, Bax, Pan Kla, and H3K18la at protein levels. Our findings unveil the pivotal role of HSCs in HCC pathogenesis through regulating histone lactylation.

Prediction of Lymph Node Metastasis in Endometrial Cancer Based on Color Doppler Ultrasound Radiomics

RATIONALE AND OBJECTIVES

To construct a model using radiomics features based on ultrasound images and evaluate the feasibility of noninvasive assessment of lymph node status in endometrial cancer (EC) patients.

METHODS

In this multicenter retrospective study, a total of 186 EC patients who underwent hysterectomy and lymph node dissection were included, Pathology confirmed the presence or absence of lymph node metastasis (LNM). The study encompassed patients from seven centers, spanning from September 2018 to November 2023, with 93 patients in each group (with or without LNM). Extracted ultrasound radiomics features from transvaginal ultrasound images, used five machine learning (ML) algorithms to establish US radiomics models, screened clinical features through univariate and multivariate logistic regression to establish a clinical model, and combined clinical and radiomics features to establish a nomogram model. The diagnostic ability of the three models for LNM with EC was compared, and the diagnostic performance and accuracy of the three models were evaluated using receiver operating characteristic curve analysis.

RESULTS

Among the five ML models, the XGBoost model performed the best, with AUC values of 0.900 (95% CI, 0.847-0.950) and 0.865 (95% CI, 0.763-0.950) for the training and testing sets, respectively. In the final model, the nomogram based on clinical features and the ultrasound radiomics showed good resolution, with AUC values of 0.919 (95% CI, 0.874-0.964) and 0.884 (0.801-0.967) in the training and testing sets, respectively. The decision curve analysis verified the clinical practicality of the nomogram.

CONCLUSION

The ML model based on ultrasound radiomics has potential value in the noninvasive differential diagnosis of LNM in patients with EC. The nomogram constructed by combining ultrasound radiomics and clinical features can provide clinical doctors with more comprehensive and personalized image information, which is highly important for selecting treatment strategies.

Application and new findings of scRNA-seq and ST-seq in prostate cancer

Prostate cancer is a malignant tumor of the male urological system with the highest incidence rate in the world, which seriously threatens the life and health of middle-aged and elderly men. The progression of prostate cancer involves the interaction between tumor cells and tumor microenvironment. Understanding the mechanisms of prostate cancer pathogenesis and disease progression is important to guide diagnosis and therapy. The emergence of single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (ST-seq) technologies has brought breakthroughs in the study of prostate cancer. It makes up for the defects of traditional techniques such as fluorescence-activated cell sorting that are difficult to elucidate cell-specific gene expression. This review summarized the heterogeneity and functional changes of prostate cancer and tumor microenvironment revealed by scRNA-seq and ST-seq, aims to provide a reference for the optimal diagnosis and treatment of prostate cancer.

Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD.

METHODS

We employed broad-panel next-generation sequencing (NGS) on a cohort of 257 surgically treated LUAD patients to delineate the molecular landscape of primary tumors and identify actionable driver-gene alterations. Additionally, we used multiplex immunohistochemistry (mIHC) on a propensity score-matched cohort, which enabled us to profile the immune microenvironment of primary tumors in detail while preserving cellular metaclusters, interactions, and neighborhood functional units. By integrating data from NGS and mIHC, we successfully identified spatial immunogenomic patterns and developed a predictive model for LN metastasis, which was subsequently validated independently.

RESULTS

Our analysis revealed distinct immunogenomic alteration patterns associated with LN metastasis stages. Specifically, we observed increased mutation frequencies in genes such as PIK3CG and ATM in LN metastatic primary tumors. Moreover, LN positive primary tumors exhibited a higher presence of macrophage and regulatory T cell metaclusters, along with their enriched neighborhood units (p < 0.05), compared to LN negative tumors. Furthermore, we developed a novel predictive model for LN metastasis likelihood, designed to inform non-surgical treatment strategies, optimize personalized therapy plans, and potentially improve outcomes for patients who are ineligible for surgery.

CONCLUSIONS

This study offers a comprehensive analysis of the genetic and immune profiles in LUAD primary tumors with LN metastasis, identifying key immunogenomic patterns linked to metastatic progression. The predictive model derived from these insights marks a substantial advancement in personalized treatment, underscoring its potential to improve patient management.

Correlation of Magnetic Resonance Imaging and Computed Tomography with Biological Factor Expression and Lymph Node Metastasis in Aggressive Prostate Cancer

INTRODUCTION

This article focused on probing the correlation of magnetic resonance imaging (MRI) and computed tomography (CT) manifestations with biological factor expression and lymph node metastasis (LNM) in aggressive prostate cancer (PCa).

METHODS

A total of 136 PCa patients underwent surgical treatment and received CT and MRI examinations before surgery, whereby the apparent diffusion coefficient (ADC) values of quantitative MRI (qMRI) parameters were obtained. Patients were categorized into the non-aggressive PCa group and the aggressive PCa group according to the postoperative pathological results and Gleason scores. The expression of biological factors (prostate-specific antigen [PSA], proliferating cell nuclear antigen [PCNA], p27, and Ki-67) in both groups was tested. CT and MRI manifestations of aggressive PCa patients were analyzed. The qMRI parameters, biological factors levels, and LNM were compared in two groups; the relationships between CT and MRI manifestations, qMRI parameters, and positive expression of biological factors and LNM were probed in two groups.

RESULTS

In the aggressive PCa group, MRI and CT presented different degrees of abnormal prostate changes. In the aggressive PCa group, PSA and p27 expression and ADC values were lower, and PCNA and Ki-67, and LNM rates were higher. Patients' LNM rate was higher than that of ≤2 cm when the tumor diameter was >2 cm. ADC values were positively correlated with PSA and p27 positive expression and negatively correlated with PCNA, Ki-67, and LNM in the aggressive PCa group.

CONCLUSION

MRI and CT manifestations of aggressive PCa had certain characteristics; MRI manifestations and qMRI possessed a correlation with biological factors and LNM; ADC could be employed to assess the aggressiveness of PCa.

Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.

BMSC derived EVs inhibit colorectal Cancer progression by transporting MAGI2-AS3 or something similar

In this study, we investigated the molecular mechanisms underlying the impact of extracellular vesicles (EVs) derived from bone marrow stromal cells (BMSCs) on colorectal cancer (CRC) development. The focus was on the role of MAGI2-AS3, delivered by BMSC-EVs, in regulating USP6NL DNA methylation-mediated MYC protein translation modification to promote CDK2 downregulation. Utilizing bioinformatics analysis, we identified significant enrichment of MAGI2-AS3 related to copper-induced cell death in CRC. In vitro experiments demonstrated the downregulation of MAGI2-AS3 in CRC cells, and BMSC-EVs were found to deliver MAGI2-AS3 to inhibit CRC cell proliferation, migration, and invasion. Further exploration revealed that MAGI2-AS3 suppressed MYC protein translation modification by regulating USP6NL DNA methylation, leading to CDK2 downregulation and prevention of colorectal cancer. Overexpression of MYC reversed the functional effects of BMSC-EVs-MAGI2-AS3. In vivo experiments validated the inhibitory impact of BMSC-EVs-MAGI2-AS3 on CRC tumorigenicity by promoting CDK2 downregulation through USP6NL DNA methylation-mediated MYC protein translation modification. Overall, BMSC-EVs-MAGI2-AS3 may serve as a potential intervention to prevent CRC occurrence by modulating key molecular pathways.

Metastatic hormone-naïve prostate cancer: a distinct biological entity

Metastatic hormone-naïve prostate cancer (mHNPC) is often the initial form of presentation for metastatic prostate cancer and encompasses a heterogeneous patient population with high inter-patient heterogeneity in prognosis and response to therapy. A more precise treatment of mHNPC, guided by evidence-based biomarkers, remains an unmet medical need. In addition, the limited number of representative laboratory models of mHNPC hampers the translation of basic research into clinical applications. We provide a comprehensive overview of the clinical and biological features that characterize mHNPC, highlight molecular data that could explain the unique prognostic characteristics of mHNPC, and identify key open questions.

Identification of cell differentiation trajectory-related gene signature to reveal the prognostic significance and immune landscape in prostate cancer based on multiomics analysis

Background

In the context of prostate cancer (PCa), the occurrence of biochemical recurrence (BCR) stands out as a pivotal factor significantly impacting prognosis, potentially leading to metastasis and mortality. However, the early detection of BCR poses a substantial challenge for PCa patients. There is an urgent need to pinpoint hub genes that can serve as predictive indicators for BCR in PCa patients.

Methods

Our primary goal was to identify cell differentiation trajectory-related gene signature in PCa patients by pseudo-time trajectory analysis. We further explored the functional enrichment of overlapped marker genes and probed clinically relevant modules and BCR-related genes using Weighted Gene Co-expression Network Analysis (WGCNA) in PCa patients. Key genes predicting recurrence-free survival were meticulously identified through univariate and multivariate Cox regression analyses. Subsequently, these genes were utilized to construct a prognostic gene signature, the expression, predictive efficacy, putative functions, and immunological landscape of which were thoroughly validated. Additionally, we employed immunohistochemistry (IHC) and a western blotting assay to quantify the expression of PYCR1 in clinical samples.

Results

Our single-cell RNA (scRNA) sequencing analysis unveiled three subgroups characterized by distinct differentiation trajectories, and the marker genes associated with these groups were extracted from PCa patients. These marker genes successfully classified the PCa sample into two molecular subtypes, demonstrating a robust correlation with clinical characteristics and recurrence-free survival. Through WGCNA and Lasso analysis, we identified four hub genes (KLK3, CD38, FASN, and PYCR1) to construct a risk profile of prognostic genes linked to BCR. Notably, the high-risk patient group exhibited elevated levels of B cell naive, Macrophage M0, and Macrophage M2 infiltration, while the low-risk group displayed higher levels of T cells CD4 memory activated and monocyte infiltration. Furthermore, IHC and western blotting assays confirmed the heightened expression of PYCR1 in PCa tissues.

Conclusion

This study leveraged the differentiation trajectory and genetic variability of the microenvironment to uncover crucial prognostic genes associated with BCR in PCa patients. These findings present novel perspectives for tailoring treatment strategies for PCa patients on an individualized basis.

It's all about the base: stromal cells are central orchestrators of metastasis

The tumor microenvironment (TME) is an integral part of tumors and plays a central role in all stages of carcinogenesis and progression. Each organ has a unique and heterogeneous microenvironment, which affects the ability of disseminated cells to grow in the new and sometimes hostile metastatic niche. Resident stromal cells, such as fibroblasts, osteoblasts, and astrocytes, are essential culprits in the modulation of metastatic progression: they transition from being sentinels of tissue integrity to being dysfunctional perpetrators that support metastatic outgrowth. Therefore, better understanding of the complexity of their reciprocal interactions with cancer cells and with other components of the TME is essential to enable the design of novel therapeutic approaches to prevent metastatic relapse.

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

Background: Although rheumatoid arthritis (RA) is a common autoimmune disease, the precise pathogenesis of the disease remains unclear. Recent research has unraveled the role of autophagy in the development of RA. This research aims to explore autophagy-related diagnostic biomarkers in the peripheral blood of RA patients. Methods: The gene expression profiles of GSE17755 were retrieved from the gene expression ontology (GEO) database. Differentially expressed autophagy-related genes (DE-ARGs) were identified for the subsequent research by inserting autophagy-related genes and differentially expressed genes (DEGs). Three machine learning algorithms, including random forest, support vector machine recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO), were employed to identify diagnostic biomarkers. A nomogram model was constructed to assess the diagnostic value of the biomarkers. The CIBERSORT algorithm was performed to investigate the correlation of the diagnostic biomarkers with immune cells and immune factors. Finally, the diagnostic efficacy and differential expression trend of diagnostic biomarkers were validated in multiple cohorts containing different tissues and diseases. Results: In this study, 25 DE-ARGs were identified between RA and healthy individuals. In addition to "macroautophagy" and "autophagy-animal," DE-ARGs were also associated with several types of programmed cell death and immune-related pathways according to GO and KEGG analysis. Three diagnostic biomarkers, EEF2, HSP90AB1 and TNFSF10, were identified by the random forest, SVM-RFE, and LASSO. The nomogram model demonstrated excellent diagnostic value in GSE17755 (AUC = 0.995, 95% CI: 0.988-0.999). Furthermore, immune infiltration analysis showed a remarkable association between EEF2, HSP90AB1, and TNFSF10 expression with various immune cells and immune factors. The three diagnostic biomarkers also exhibited good diagnostic efficacy and demonstrated the same trend of differential expression in multiple validation cohorts. Conclusion: This study identified autophagy-related diagnostic biomarkers based on three machine learning algorithms, providing promising targets for the diagnosis and treatment of RA.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.