A combination of ssGSEA and mass cytometry identifies immune microenvironment in muscle-invasive bladder cancer

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

A ferroptosis-related LncRNAs signature for predicting prognoses and screening potential therapeutic drugs in patients with lung adenocarcinoma: A retrospective study

BACKGROUND

Lung adenocarcinoma (LUAD) has a high mortality rate. Ferroptosis is linked to tumor initiation and progression.

AIMS

This study aims to develop prognostic models of ferroptosis-related lncRNAs, evaluate the correlation between differentially expressed genes and tumor microenvironment, and identify prospective drugs for managing LUAD.

METHODS AND RESULTS

In this study, transcriptomic and clinical data were downloaded from the TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the LASSO algorithm for constructing a prognostic model, we found that ferroptosis-related lncRNA-based gene signatures (FLncSig) had a strong prognostic predicting ability in the LUAD patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments reconfirmed that ferroptosis is related to receptor-ligand activity, enzyme inhibitor activity, and the IL-17 signaling pathway. Next, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) algorithms, and pRRophetic were used to predict immunotherapy response and chemotherapy sensitivity. The IMvigor210 cohort was also used to validate the prognostic model. In the tumor microenvironment, Type_II_IFN_Response and HLA were found to be a group of low-risk pathways, while MHC_class_I was a group of high-risk pathways. Patients in the high-risk subgroup had lower TIDE scores. Exclusion, MDSC, CAF, and TAMM2 were significantly and positively correlated with risk scores. In addition, we found 15 potential therapeutic drugs for LUAD. Finally, differential analysis of stemness index based on mRNA expression (mRNAsi) indicated that mRNAsi was correlated with gender, primary tumor (T), distant metastasis (M), and the tumor, node, and metastasis (TNM) stage in LUAD patients.

CONCLUSIONS

In conclusion, the prognostic model based on FLncSig can alleviate the difficulty in predicting the prognosis and immunotherapy of LUAD patients. The identified FLncSig and the screened drugs exhibit potential for clinical application and provide references for the treatment of LUAD.

Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes

Discordant abundances of different immune cell subtypes is regarded to be an essential feature of tumour tissue. Direct studies in Prostate cancer (PC) of intratumoral immune heterogeneity characterized by immune cell subtype, are still lacking. Using the single sample gene set enrichment analysis (ssGSEA) algorithm, the abundance of 28 immune cells infiltration (ICI) were determined for PC. A NMF was performed to determine tumour-sample clustering based on the abundance of ICI and PFS information. Hub genes of clusters were identified via weighted gene co-expression network analysis (WGCNA). The multivariate dimensionality reduction analysis of hub genes expression matrix was carried out via principal component analysis (PCA) to obtain immune score (IS). We analysed the correlation between clustering, IS and clinical phenotype. We divided the 495 patients into clusterA (n = 193) and clusterB (n = 302) on the basis of ICI and PFS via NMF. The progression-free survival (PFS) were better for clusterA than for clusterB (p < 0.001). Each immune cell subtypes was more abundant in clusterA than in clusterB (p < 0.001). The expression levels of CTAL-4 and PD-L1 were lower in clusterB than in clusterA (p < 0.001 and p = 0.006). We obtained 103 hub genes via WGCNA. In the training and validation cohorts, the prognosis of high IS group was worse than that of the low IS group (p < 0.05). IS had good predictive effect on 5-year PFS. The expression of immune checkpoint genes was higher in the low IS group than in the high IS group (p < 0.01). Patients with low IS and receiving hormone therapy had better prognosis than other groups. The combination of IS and clinical characteristics including lymph node metastasis and gleason score can better differentiate patient outcomes than using it alone. IS was a practical algorithm to predict the prognosis of patients. Advanced PC patients with low IS may be more sensitive to hormone therapy. CXCL10, CXCL5, MMP1, CXCL12, CXCL11, CXCL2, STAT1, IL-6 and TLR2 were hub genes, which may drive the homing of immune cells in tumours and promote immune cell differentiation.

TP53-related signature for predicting prognosis and tumor microenvironment characteristics in bladder cancer: A multi-omics study

Background: The tumor suppressor gene TP53 is frequently mutated or inactivated in bladder cancer (BLCA), which is implicated in the pathogenesis of tumor. However, the cellular mechanisms of TP53 mutations are complicated, yet well-defined, but their clinical prognostic value in the management of BLCA remains controversial. This study aimed to explore the role of TP53 mutation in regulating the tumor microenvironment (TME), elucidate the effects of TP53 activity on BLCA prognosis and immunotherapy response. Methods: A TP53-related signature based on TP53-induced and TP53-repressed genes was used to construct a TP53 activity-related score and classifier. The abundance of different immune cell types was determined using CIBERSORT to estimate immune cell infiltration. Moreover, the heterogeneity of the tumor immune microenvironment between the high and low TP53 score groups was further evaluated using single-cell mass cytometry (CyTOF) and imaging mass cytometry (IMC). Moreover, pathway enrichment analysis was performed to explore the differential biological functions between tumor epithelial cells with high and low TP53 activity scores. Finally, the receptor-ligand interactions between immune cells and tumor epithelial cells harboring distinct TP53 activity were analyzed by single-cell RNA-sequencing. Results: The TP53 activity-related gene signature differentiated well between TP53 functional retention and inactivation in BLCA. BLCA patients with low TP53 scores had worse survival prognosis, more TP53 mutations, higher grade, and stronger lymph node metastasis than those with high TP53 scores. Additionally, CyTOF and IMC analyses revealed that BLCA patients with low TP53 scores exhibited a potent immunosuppressive TME. Consistently, single-cell sequencing results showed that tumor epithelial cells with low TP53 scores were significantly associated with high cell proliferation and stemness abilities and strongly interacted with immunosuppressive receptor-ligand pairs. Conclusion: BLCA patients with low TP53 scores have a worse prognosis and a more immunosuppressive TME. This TP53 activity-related signature can serve as a potential prognostic signature for predicting the immune response, which may facilitate the development of new strategies for immunotherapy in BLCA.

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

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

Identification of m6A- and ferroptosis-related lncRNA signature for predicting immune efficacy in hepatocellular carcinoma

Background

N6-methyladenosine (m6A) methylation and ferroptosis assist long noncoding RNAs (lncRNAs) in promoting immune escape in hepatocellular carcinoma (HCC). However, the predictive value of m6A- and ferroptosis-related lncRNAs (mfrlncRNAs) in terms of immune efficacy remains unknown.

Method

A total of 365 HCC patients with complete data from The Cancer Genome Atlas (TCGA) database were used as the training cohort, and half of them were randomly selected as the validation cohort. A total of 161 HCC patients from the International Cancer Genome Consortium (ICGC) database were used as external validation (ICGC cohort).

Results

We first identified a group of specific lncRNAs associated with both m6A regulators and ferroptosis-related genes and then constructed prognosis-related mfrlncRNA pairs. Based on this, the mfrlncRNA signature was constructed using the least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Notably, the risk score of patients was proven to be an independent prognostic factor and was better than the TNM stage and tumor grade. Moreover, patients with high-risk scores had lower survival rates, higher infiltration of immunosuppressive cells (macrophages and Tregs), lower infiltration of cytotoxic immune cells (natural killer cells), poorer immune efficacy (both immunophenoscore and score of tumor immune dysfunction and exclusion), higher IC₅₀, and enrichment of the induced Treg pathway, which confirmed that the mfrlncRNA signature contributed to survival prediction and risk stratification of patients with HCC.

Conclusions

The mfrlncRNA signature, which has great prognostic value, provides new clues for identifying “cold” and “hot” tumors and might have crucial implications for individualized therapy to improve the survival rate of patients with HCC.

m7G-Associated subtypes, tumor microenvironment, and validation of prognostic signature in lung adenocarcinoma

Background: 7-Methylguanosine (m7G) is an important posttranscriptional modification that regulates gene expression and is involved in tumorigenesis and development. Tumor microenvironment has been proven to be highly involved in tumor progression and prognosis. However, how m7G-associated genes affect the tumor microenvironment of patients with lung adenocarcinoma (LUAD) remains to be further clarified.

Methods: The genetic alterations of m7G-associated genes and their associations with the prognosis and tumor microenvironment in LUAD patients were systemically analyzed. An m7G-Riskscore was established and analyzed for its performance in disease prognosis and association with patient response to immunotherapy. Expression of the model genes at the protein level was investigated through ex vivo experiments. A nomogram was finally obtained based on the m7G-Riskscore and several significant clinical pathological features.

Results: m7G-Associated genes were obtained from five LUAD datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and their expression pattern was determined. Based on the m7G-associated genes, three LUAD clusters were defined. The differentially expressed genes from the three clusters were screened and used to further divide the LUAD patients into two gene clusters. It was demonstrated that the alterations of m7G-associated genes were associated with the clinical pathological features, prognosis, and tumor immune infiltration in LUAD patients. An m7G-Riskscore including CAND1, RRM2, and SLC2A1 was obtained with robust and accurate prognostic performance. WB and cell immunofluorescence also showed significant dysregulation of CAND1, RRM2, and SLC2A1 in LUAD. In addition, a nomogram was established to improve the clinical feasibility of the m7G-Riskscore. Correlation analysis revealed that patients with a lower m7G-Riskscore had higher immune and stromal scores, responded well to chemotherapeutics and multiple targeted drugs, and survived longer. Patients with a higher m7G-Riskscore tended to suffer from a higher tumor mutation burden. Furthermore, the m7G-Riskscore exhibited significant associations with immune cell infiltration and cancer stemness.

Conclusion: This study systemically analyzed m7G-associated genes and identified their potential role in tumor microenvironment and prognosis in patients with LUAD. The findings of the present study may help better understand LUAD from the m7G perspective and also provide a new thought toward the prognosis and treatment of LUAD.

Identification of an immune gene-associated prognostic signature in patients with bladder cancer

A deeper understanding of the interaction between tumor cell and the immune microenvironment in bladder cancer may help select predictive and prognostic biomarkers. The current study aims to construct a prognostic signature for bladder cancer by analysis of molecular characteristics, as well as tumor-immune interactions. RNA-sequencing and clinical information from bladder cancer patients were downloaded from the TCGA database. The single sample Gene Sets Enrichment Analysis (ssGSEA) and Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) were employed to separate the samples into two clusters. Lasso Cox regression was performed to construct an immune gene signature for bladder cancer. The correlation between key target genes of immune checkpoint blockade and the prognostic signature was also analyzed. Dataset from Gene Expression Omnibus (GEO) was retrieved for validation. Two immunophenotypes and immunological characteristics were identified, and a 17-immune gene signature was constructed to provide an independent prognostic signature for bladder cancer. The signature was verified through external validation and correlated with genomic characteristics and clinicopathologic features. Finally, a nomogram was generated from the clinical characteristics and immune signature. Our study reveals a tumor-immune microenvironment signature useful for prognosis in bladder cancer. The results provide information on the potential development of treatment strategies for bladder cancer patients. Prospective studies are warranted to validate the prognostic capability of this model, but these data highlight the role of the microenvironment in the clinical outcome of patients.

Proteomics as a Complementary Technique to Characterize Bladder Cancer

Simple Summary

Although immunohistochemistry is a routine technique in clinics, and genomics has been rapidly incorporated, proteomics is a step behind. This general situation is also the norm in bladder cancer research. This review shows the contributions of proteomics to the molecular classification of bladder cancer, and to the study of histopathology due to tissue insults caused by tumors. Furthermore, the importance of proteomics for understanding the cellular and molecular changes as a consequence of the therapy of bladder cancer cannot be neglected.

Abstract

Bladder cancer (BC) is the most common tumor of the urinary tract and is conventionally classified as either non-muscle invasive or muscle invasive. In addition, histological variants exist, as organized by the WHO-2016 classification. However, innovations in next-generation sequencing have led to molecular classifications of BC. These innovations have also allowed for the tracing of major tumorigenic pathways and, therefore, are positioned as strong supporters of precision medicine. In parallel, immunohistochemistry is still the clinical reference to discriminate histological layers and to stage BC. Key contributions have been made to enlarge the panel of protein immunomarkers. Moreover, the analysis of proteins in liquid biopsy has also provided potential markers. Notwithstanding, their clinical adoption is still low, with very few approved tests. In this context, mass spectrometry-based proteomics has remained a step behind; hence, we aimed to develop them in the community. Herein, the authors introduce the epidemiology and the conventional classifications to review the molecular classification of BC, highlighting the contributions of proteomics. Then, the advances in mass spectrometry techniques focusing on maintaining the integrity of the biological structures are presented, a milestone for the emergence of histoproteomics. Within this field, the review then discusses selected proteins for the comprehension of the pathophysiological mechanisms of BC. Finally, because there is still insufficient knowledge, this review considers proteomics as an important source for the development of BC therapies.