Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy

Regulatory mechanism and prognostic value of sex hormone pathways connected with metabolism and immune signaling in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) represents a major subtype of kidney cancer with variable prognosis. A comprehensive understanding of sex hormone-related pathways could potentially refine the prediction of patient outcomes in ccRCC. Patients from TCGA-KIRC (n = 528) and GSE22541 (n = 40) cohorts were analyzed. Sex-hormone-associated pathways were manually collected and calculated with the activated score, then subtypes were identified. Differential gene expression, pathway enrichment, and tumor-infiltrating immunocytes were assessed. A prognostic signature was developed using Cox analysis and LASSO regression. Immunohistochemistry (IHC) was performed to validate the protein level of key model gene in ccRCC tissues. Three distinct subtypes (C1, C2, C3) based on sex hormone pathway activation were discovered. C1 showed the most favorable prognosis (P = 0.00029). 1,094 genes were upregulated in C1 and 197 in C3. 20 risk-associated and 172 protective genes for ccRCC prognosis were identified. LASSO regression narrowed down to 33 genes for the sex-hormone-related-gene (SHAG) prognostic model. In the TCGA-KIRC cohort, the high-SHAG score group had a worse prognosis with an HR of 3.26 (95% CI: 2.334-4.555, P < 0.001). Validation in the GSE22541 cohort corroborated these findings. The nomogram incorporating the SHAG model demonstrated robust predictive accuracy higher than 0.75. IHC validation confirmed that ARHGEF17 protein levels were higher in early-stage ccRCC (stage I-II) compared to advanced-stage (stage III) tumors, supporting its prognostic relevance. The SHAG signature serves as a promising prognostic tool for ccRCC, providing insights into the role of sex hormone-related pathways in tumor progression. Further experimental and clinical validation is warranted to explore its potential in personalized therapy.

Tracing the Evolution of Sex Hormones and Receptor-Mediated Immune Microenvironmental Differences in Prostate and Bladder Cancers: From Embryonic Development to Disease

The bladder and prostate originate from the urogenital sinus. However, bladder cancer (BC) is usually classified as an immune "hot" tumor, whereas prostate cancer (PCa) is deemed as an immune "cold" tumor according to the tumor microenvironment (TME) and clinical outcomes. To investigate the immune differences between BC and PCa, studies are compared focusing on immune regulation mediated by sex hormones and receptors to identify key genes and pathways responsible for the immune differences. From a developmental perspective, it is shown that PCa and BC activate genes and pathways similar to those in the developmental stage. During prostate development, the differential expression and function of the androgen receptor (AR) across cell types may contribute to its dual role in promoting and inhibiting immunity in different cells. Androgen deprivation therapy affects AR function in different cells within the TME, influencing immune cell infiltration and antitumor function. Additionally, estrogenα and estrogenβ exert contrasting effects in PCa and BC, which may hold the potential for modifying the "cold" and "hot" tumor phenotypes. Future research should target key genes and pathways involved in bladder development to clarify the immune regulatory similarities and differences between BC and PCa.

Multi-omics clustering analysis carries out the molecular-specific subtypes of thyroid carcinoma: implicating for the precise treatment strategies

Thyroid cancer (TC) is the most prevalent endocrine malignancy worldwide. This study aimed to explore the molecular subtypes and improve the selection of targeted therapies. We used multi-omics data from 539 patients with DNA methylation, gene mutations, mRNA, lncRNA, and miRNA expressions. This study employed consensus clustering algorithms to identify molecular subtypes and used various bioinformatics tools to analyze genetic alterations, signaling pathways, immune infiltration, and responses to chemotherapy and immunotherapy. Two prognostically relevant TC subtypes, CS1 and CS2, were identified. CS2 was associated with a poorer prognosis of shorter progression-free survival times (P < 0.001). CS1 exhibited higher copy number alterations but a lower tumor mutation burden than CS2. CS2 exhibited activation in cell proliferation and immune-related pathways. Drug sensitivity analysis indicated CS2's higher sensitivity to cisplatin, doxorubicin, paclitaxel, and sunitinib, whereas CS1 was more sensitive to bicalutamide and FH535. The different activated pathways and sensitivity to drugs for the subtypes were further validated in an external cohort. Twenty-four paired tumors and adjacent normal tissues by immunohistochemical staining further demonstrated the prognostic value of CXCL17. In conclusion, we identified two distinct molecular subtypes of TC with significant implications for prognosis, genetic alterations, pathway activation, and treatment response.

Nanotechnology-Based Strategies for Safe and Effective Immunotherapy

Cancer immunotherapy using immune checkpoint blockades has emerged as a promising therapeutic approach. However, immunotherapy faces challenges such as low response rates in solid tumors, necessitating strategies to remodel the immune-suppressive tumor microenvironment (TME) into an immune-activated state. One of the primary approaches to achieve this transformation is through the induction of immunogenic cell death (ICD). Herein, we discussed strategies to maximize ICD induction using nanoparticles. In particular, this review highlighted various studies integrating chemotherapy, radiation therapy (RT), photodynamic therapy (PDT), and photothermal therapy (PTT) with nanoparticle-based immunotherapy. The research covered in this review aims to provide valuable insights for future studies on nanoparticle-assisted immunotherapy.

Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

CMTM7 shapes the chronic inflammatory and immunosuppressive tumor microenvironment in hepatocellular carcinoma as an M2 macrophage biomarker

Transmembrane domain-containing 7 (CMTM7) is a protein located at the plasma membrane. It plays a role in regulating the development and immune microenvironment of tumor cells. However, the impact of CMTM7 on hepatocellular carcinoma (HCC) is not well understood. To better understand the role of CMTM7 in HCC, the correlations of CMTM7 with clinical characteristics, patient prognosis, chronic inflammation, and immune cell infiltration were analyzed using tissue microarray slides, sequencing datasets and various analysis tools (Web). The bulk sequencing analysis indicated that elevated expression of CMTM7 appears to promote chronic inflammation, immunosuppression, M2 macrophage infiltration, a diminished response to cancer immunotherapy, and an unfavorable clinical prognosis in patients with hepatocellular carcinoma (HCC). Further investigation through single-cell RNA sequencing and multiple fluorescence staining demonstrated that CMTM7 serves as a molecular marker for M2 macrophages and is associated with T cell exhaustion as well as highly plastic stem-like characteristics. We propose that CMTM7 may represent a novel immune checkpoint for HCC patients experiencing suboptimal therapeutic outcomes. Utilizing the Connectivity Map and AutoDock Vina, we predicted two potential compounds targeting CMTM7-fasudil and arachidonyltrifluoromethane-as promising therapeutic candidates. Collectively, these findings suggest that CMTM7-positive macrophages play significant roles in establishing an immunosuppressive tumor microenvironment while promoting highly plastic and stem-like traits in HCC cells, ultimately contributing to poor prognostic outcomes.

GREM1 may be a biological indicator and potential target of bladder cancer

Gremlin 1 (GREM1) can regulate the development of many cancers. However, a few studies have revealed the role of GREM1 in bladder cancer (BC). To evaluate the expression and potential function of GREM1 in bladder cancer, we used R version 3.6.3 and related packages to analyze the data from common databases. Samples from our institution were assessed by immunohistochemical staining (IHC), which was approved by the Institutional Ethics Committee (K20220830). GREM1 was highly expressed in BC tissues according to the TCGA and IHC data. Data from TCGA, GSE31684, GSE32894, and IHC showed that GREM1 has significant prognostic value for BC patients. GREM1 is involved in immune and metabolism-related pathways. According to the TIDE algorithm, 61.0% of patients with low GREM1 expression responded well to immunotherapy, compared to only 13.3% in the high GREM1 expression group. High GREM1 expression was associated with sensitivity to cisplatin, docetaxel, gemcitabine, and vinblastine. Thus, GREM1 can predict prognosis and responses to immunotherapy and chemotherapy in BC patients, making it a potential biomarker and therapeutic target.

Transcriptome Profiling Associated with CARD11 Overexpression in Colorectal Cancer Implicates a Potential Role for Tumor Immune Microenvironment and Cancer Pathways Modulation via NF-κB

The immune system plays a critical role in inflammation by initiating responses to infections or tissue damage. The nuclear factor-κB (NF-κB) pathway plays a key role in inflammation and innate immunity, as well as other cellular activities. Dysregulation of this well-choreographed pathway has been implicated in various diseases, including cancer. CARD11 is a key molecule in the BCL10-MALT1 complex, which is involved in transducing the signal downstream of the NF-κB pathway. This study aims to elucidate how CARD11 overexpression exacerbates the prognosis of colorectal cancer (CRC). To identify the cellular pathways influenced by CARD11, transcriptomic analysis in both CRC cell lines and patients was carried out on CARD11- overexpressed HCT-116 and HT-29 CRC cell lines alongside empty vector-transfected cell lines. Furthermore, a comparison of transcriptomic data from adenoma and carcinoma CRC patients with low- (CARD11-) and high-(CARD11+) CARD11 expression was carried out. Whole transcriptomics and bioinformatics analysis results indicate that CARD11 appears to play a key role in CRC progression. Absolute GSEA (absGSEA) on HCT-116 transcriptomics data revealed that CARD11 overexpression promotes cell growth and tissue remodeling and enhances immune response. Key genes co-expressed with CARD11, such as EP300, KDM5A, HIF1A, NFKBIZ, and DUSP1, were identified as mediators of these processes. In the HT-29 cell line, CARD11 overexpression activated pathways involved in chemotaxis and extracellular matrix (ECM) organization, marked by IL1RN, MDK, SPP1, and chemokines like CXCL1, CXCL3, and CCL22, which were shown to contribute to the more invasive stage of CRC. In patient samples, adenoma patients exhibited increased expression of genes associated with the tumor immune microenvironment, such as IL6ST, collagen family members, and CRC transition markers, such as GLI3 and PIEZO2, in CARD11+ adenoma patients. Carcinoma patients showed a dramatic increase in the expression of MAPK8IP2 in CARD11+ carcinoma patients alongside other cancer-related genes, including EMB, EPHB6, and CPEB4.

A metabolic reprogramming-related gene signature correlates with prognosis and proliferation of BLCA

Bladder cancer (BLCA) is one of the most frequent urothelium carcinoma, but with poor prognosis due to lack of reliable predictive biomarkers. Metabolic reprogramming involving in various nutrients, and is reported to be closely associated with malignant progression in BLCA. With the use of transcriptome sequencing data profiles of 349 patients from The Cancer Genome Atlas, we established a three-gene glycolysis-related signature to predict the prognosis of BLCA patients. Our signature constructed on the basis of AK3, GALK1 and NUP205 expression, detail features and interactions between these three genes were further explored. We established a nomogram by integrating clinical variables and the risk score. Glycolytic level and proliferation ability were detected to study the role and mechanisms of NUP205 on BLCA. The connections between three genes in our signature were independent. We found our signature gains more value for patients with highly malignant stage. The established nomogram also confirmed that the signature had a eligible clinically predict capacity. After inhibited NUP205 expression, we found the glycolysis level of BLCA cells decreased and proliferation ability suppressed, mainly through AMPK signaling pathway inactivation. Collectively, our study explored a three-gene glycolysis-related signature that predict the prognosis of patients with BLCA, and highlights NUP205 as a potential therapeutic target for inhibiting glycolytic processes and proliferation in BLCA cells.

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

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

Comprehensive Collection of Whole-Slide Images and Genomic Profiles for Patients with Bladder Cancer

Bladder cancer is one of the leading causes of cancer-related mortality in the urinary system. Understanding genomic information is important in the treatment and prognosis of bladder cancer, but the current method used to identify mutations is time-consuming and labor-intensive. There are now many novel and convenient ways to predict cancerous genomics from pathological slides. However, the publicly available datasets are limited, especially for Asian populations. In this study, we developed a dataset consisting of 75 Asian cases of bladder cancers and 112 Whole-Slide Images with one to two images obtained for each patient. This dataset provides information on the most frequently and clinically significant mutated genes derived by whole-exome sequencing in these patients. This dataset will facilitate exploration and development of novel diagnostic and therapeutic technologies for bladder cancer.

JAM3: A prognostic biomarker for bladder cancer via epithelial-mesenchymal transition regulation

Understanding the intricate relationship between prognosis, immune function, and molecular markers in bladder cancer (BC) demands sophisticated analytical methods. To identify novel biomarkers for predicting prognosis and immune function in BC patients, we combined weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression analysis. This was conducted using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Ultimately, we screened the junctional adhesion molecule 3 (JAM3) as an independent risk factor in BC. High levels of JAM3 were linked to adverse clinical parameters, such as higher T and N stages. Additionally, a JAM3-based nomogram model accurately predicted 1-, 3- and 5-year survival rates of BC patients, indicating potential clinical utility. Functional enrichment analysis revealed that high JAM3 expression activated the calcium signaling pathway, the extracellular matrix (ECM)-receptor interaction, and the PI3K-Akt signaling pathway, and was positively correlated with genes associated with epithelial-mesenchymal transition (EMT). Subsequently, we found that overexpression of JAM3 promoted the migration and invasion abilities in BC cells, regulating the expression levels of N-cadherin, matrix metallopeptidase 2 (MMP2), and Claudin-1 thereby promoting EMT levels. Additionally, we showed that JAM3 was negatively correlated with anti-tumor immune cells such as CD8+ T cells, while positively correlated with pro-tumor immune cells such as M2 macrophages, suggesting its involvement in immune cell infiltration. The immune checkpoint CD200 also showed a positive correlation with JAM3. Our findings revealed that elevated JAM3 levels are predictive of poor prognosis and immune cell infiltration in BC patients by regulating the EMT process.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

Identification of an inflammation-related risk signature for prognosis and immunotherapeutic response prediction in bladder cancer

Tumor inflammation is one of the hallmarks of tumors and is closely related to tumor occurrence and development, providing individualized prognostic prediction. However, few studies have evaluated the relationship between inflammation and the prognosis of bladder urothelial carcinoma (BLCA) patients. Therefore, we constructed a novel inflammation-related prognostic model that included six inflammation-related genes (IRGs) that can precisely predict the survival outcomes of BLCA patients. RNA-seq expression and corresponding clinical data from BLCA patients were downloaded from The Cancer Genome Atlas database. Enrichment analysis was subsequently performed to determine the enrichment of GO terms and KEGG pathways. K‒M analysis was used to compare overall survival (OS). Cox regression and LASSO regression were used to identify prognostic factors and construct the model. Finally, this prognostic model was used to evaluate cell infiltration in the BLCA tumor microenvironment and analyze the effect of immunotherapy in high- and low-risk patients. We established an IRG signature-based prognostic model with 6 IRGs (TNFRSF12A, NR1H3, ITIH4, IL1R1, ELN and CYP26B1), among which TNFRSF12A, IL1R1, ELN and CYP26B1 were unfavorable prognostic factors and NR1H3 and ITIH4 were protective indicators. High-risk score patients in the prognostic model had significantly poorer OS. Additionally, high-risk score patients were associated with an inhibitory immune tumor microenvironment and poor immunotherapy response. We also found a correlation between IRS-related genes and bladder cancer chemotherapy drugs in the drug sensitivity data. The IRG signature-based prognostic model we constructed can predict the prognosis of BLCA patients, providing additional information for individualized prognostic judgment and treatment selection.

Current Landscape of Immune Checkpoint Inhibitors for Metastatic Urothelial Carcinoma: Is There a Role for Additional T-Cell Blockade?

Urothelial carcinoma (UC) is the most common form of bladder cancer (BC) and is the variant with the most immunogenic response. This makes urothelial carcinoma an ideal candidate for immunotherapy with immune checkpoint inhibitors. Key immune checkpoint proteins PD-1 and CTLA-4 are frequently expressed on T-cells in urothelial carcinoma. The blockade of this immune checkpoint can lead to the reactivation of lymphocytes and augment the anti-tumor immune response. The only immune checkpoint inhibitors that are FDA-approved for metastatic urothelial carcinoma target the programmed death-1 receptor and its ligand (PD-1/PD-L1) axis. However, the overall response rate and progression-free survival rates of these agents are limited in this patient population. Therefore, there is a need to find further immune-bolstering treatment combinations that may positively impact survival for patients with advanced UC. In this review, the current immune checkpoint inhibition treatment landscape is explored with an emphasis on combination therapy in the form of PD-1/PD-L1 with CTLA-4 blockade. The investigation of the current literature on immune checkpoint inhibition found that preclinical data show a decrease in tumor volumes and size when PD-1/PD-L1 is blocked, and similar results were observed with CTLA-4 blockade. However, there are limited investigations evaluating the combination of CTLA-4 and PD-1/PD-L1 blockade. We anticipate this review to provide a foundation for a deeper experimental investigation into combination immune checkpoint inhibition therapy in metastatic urothelial carcinoma.

Longitudinal Transcription Profiling of Bladder Cancers Dictate the Response to BCG Treatment and Disease Progression

Although the intravesical instillation of Bacillus Calmette-Guerin (BCG) is widely used as adjuvant treatment for nonmuscle-invasive bladder cancers, the clinical benefit is variable across patients, and the molecular mechanisms underlying the sensitivity to BCG administration and disease progression are poorly understood. To establish the molecular signatures that predict the responsiveness and disease progression of bladder cancers treated with BCG, we performed transcriptome sequencing (RNA-seq) for 13 treatment-naïve and 22 post-treatment specimens obtained from 14 bladder cancer patients. To overcome disease heterogeneity, we used non-negative matrix factorization to identify the latent molecular features associated with drug responsiveness and disease progression. At least 12 molecular features were present, among which the immune-related feature was associated with drug responsiveness, indicating that pre-treatment anti-cancer immunity might dictate BCG responsiveness. We also identified disease progression-associated molecular features indicative of elevated cellular proliferation in post-treatment specimens. The progression-associated molecular features were validated in an extended cohort of BCG-treated bladder cancers. Our study advances understanding of the molecular mechanisms of BCG activity in bladder cancers and provides clinically relevant gene markers for evaluating and monitoring patients.

Mathematical model predicts tumor control patterns induced by fast and slow cytotoxic T lymphocyte killing mechanisms

Immunotherapy has dramatically transformed the cancer treatment landscape largely due to the efficacy of immune checkpoint inhibitors (ICIs). Although ICIs have shown promising results for many patients, the low response rates in many cancers highlight the ongoing challenges in cancer treatment. Cytotoxic T lymphocytes (CTLs) execute their cell-killing function via two distinct mechanisms: a fast-acting, perforin-mediated process and a slower, Fas ligand (FasL)-driven pathway. Evidence also suggests that the preferred killing mechanism of CTLs depends on the antigenicity of tumor cells. To determine the critical factors affecting responses to ICIs, we construct an ordinary differential equation model describing in vivo tumor-immune dynamics in the presence of active or blocked PD-1/PD-L1 immune checkpoint. Specifically, we identify important aspects of the tumor-immune landscape that affect tumor size and composition in the short and long term. We also generate a virtual cohort of mice with diverse tumor and immune attributes to simulate the outcomes of immune checkpoint blockade in a heterogeneous population. By identifying key tumor and immune characteristics associated with tumor elimination, dormancy, and escape, we predict which fraction of a population potentially responds well to ICIs and ways to enhance therapeutic outcomes with combination therapy.

Concomitant Immunotherapy and Metastasis-Directed Radiotherapy in Upper Tract Urothelial Carcinoma: A Biomarker-Driven, Original, Case-Based Proof-of-Concept Study

Metastatic upper tract urothelial carcinoma (mUTUC) has a poor prognosis. Immune checkpoint inhibitors (ICIs) have demonstrated efficacy in patients with metastatic urothelial carcinoma. However, data supporting the use of ICIs in patients with mUTUC are limited. A promising synergy between ICI and concomitant radiotherapy (RT) has been reported in patients with mUTUC. Our research involved a case-based investigation and emphasized the successful integration of different specialists' skills. Observed after partial urethrectomy procedures for muscle-invasive upper tract urothelial carcinoma (UTUC), the radiological detection of lung metastases prompted us to implement cisplatin-based first-line chemotherapy and molecular characterization in the treatment process. We uncovered alterations in the ERBB2 and FGFR3 genes and mismatch repair deficiency at a molecular level. First-line chemotherapy treatment led to a stable disease, and the patient was started on maintenance immunotherapy with Avelumab. Subsequently, an increase in the size of the lung nodules was described, and the patient received radiotherapy for three lung lesions in combination with immunotherapy. After 3 months, a restaging CT scan reported a complete response, which is still ongoing. We discuss the mechanisms driving RT/ICI synergy and the molecular profile of mUTUC as factors that should be considered in therapeutic strategy planning. Molecular insight enhances the originality of our study, providing a nuanced understanding of the genetic landscape of mUTUC and paving the way for targeted therapeutic strategies. The therapeutic armamentarium expansion encourages the design of a multimodal and personalized approach for each mUTUC patient, taking into account tumor heterogeneity and molecular profiling.

Identification of tumor immunophenotypes associated with immunotherapy response in bladder cancer

OBJECTIVES

This study aims to reveal immunophenotypes associated with immunotherapy response in bladder cancer, identify the signature genes of immune subtypes, and provide new molecular targets for improving immunotherapy response.

METHODS

Bladder cancer immunophenotypes were characterized in the bulk RNA sequencing dataset GSE32894 and Imvigor210, and gene expression signatures were established to identify the immunophenotypes. Expression of gene signatures were validated in single-cell RNA sequencing dataset GSE145140 and human proteins expression data source. Investigation of Immunotherapy Response was performed in IMvigor210 dataset. Prognosis of tumor immunophenotypes was further analyzed.

RESULTS

Inflamed and immune-excluded immunophenotypes were characterized based on the tumor immune cell scores. Risk score models that were established rely on RNA sequencing profiles and overall survival of bladder cancer cohorts. The inflamed tumors had lower risk scores, and the low-risk tumors were more likely to respond to atezolizumab, receiving complete response/partial response (CR/PR). Patients who responded to atezolizumab had higher SRRM4 and lower NPHS1 and TMEM72 expression than the non-responders. SRRM4 expression was a protective factor for bladder cancer prognosis, while the NPHS1 and TMEM72 showed the opposite pattern.

CONCLUSION

This study provided a novel classification method for tumor immunophenotypes. Bladder cancer immunophenotypes can predict the response to immune checkpoint blockade. The immunophenotypes can be identified by the expression of signature genes.

Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty-five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification. Bioinformatic analyses were performed based on our team's recently developed R package "MOVICS." With 10 state-of-the-art algorithms, we identified the multiomics subtypes (MoSs) for ccRCC patients. MoS1 is an immune exhausted subtype, presented the poorest prognosis, and might be caused by an exhausted immune microenvironment, activated hypoxia features, but can benefit from PI3K/AKT inhibitors. MoS2 is an immune "cold" subtype, which represented more mutation of VHL and PBRM1, favorable prognosis, and is more suitable for sunitinib therapy. MoS3 is the immune "hot" subtype, and can benefit from the anti-PD-1 immunotherapy. We successfully verified the different molecular features of the three MoSs in external cohorts GSE22541, GSE40435, and GSE53573. Patients that received Nivolumab therapy helped us to confirm that MoS3 is suitable for anti-PD-1 therapy. E-MTAB-3267 cohort also supported the fact that MoS2 patients can respond more to sunitinib treatment. We also confirm that SETD2 is a tumor suppressor in ccRCC, along with the decreased SETD2 protein level in advanced tumor stage, and knock-down of SETD2 leads to the promotion of cell proliferation, migration, and invasion. In summary, we provide novel insights into ccRCC molecular subtypes based on robust clustering algorithms via multiomics data, and encourage future precise treatment of ccRCC patients.

Advances in immunotyping of colorectal cancer

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies.

TIMEAS, a promising method for the stratification of testicular germ cell tumor patients with distinct immune microenvironment, clinical outcome and sensitivity to frontline therapies

PURPOSE

With the heterogeneous genetic background, prognosis prediction and therapeutic targets for testicular germ cell tumors (TGCTs) are still unclear. We defined the tumor immune microenvironment activation status (TIMEAS).

METHODS

We collected a total of 314 TGCT patients from four cohorts, including a 48-case microarray. A nonnegative matrix factorization algorithm was applied to identify the "immune factor", derived the top 150 weighted genes to divide patients into immune and non-immune classes, and further separated the immune class into activated and exhausted subgroups by nearest template prediction. Tumor mutant burden, gene mutation, and copy number alteration were compared with our recently developed package "MOVICS". A random forest algorithm was performed to establish a prediction model with fewer genes. Immunohistochemistry staining was performed to identify TIMEAS in the microarray.

RESULTS

We constructed the TIMEAS in the TCGA-TGCT cohort and further validated it in the GSE3218 and GSE99420 cohorts. The immune class contained the activated status of T-lymphocytes, B-lymphocytes, and macrophages, while Treg cells and the WNT/TGFβ signature were more activated in the immune-suppressed subgroup. Patients in the immune-exhausted subgroup had the worst prognosis, and 22.9% of patients in the immune-activated subgroup had KRAS mutations, which might stimulate the response of the immune system and lead to a favorable prognosis. The immune-exhausted group benefited more from chemotherapy, while the immune-activated subgroup responded well to anti-PD-1/PD-L1 therapy. FSCN1 was validated as the target of the immune-exhausted microenvironment by immunohistochemistry.

CONCLUSION

TIMEAS classification can separate TGCT patients; patients in the immune-activated subgroup could benefit more from anti-PD-L1 immunotherapy, and those in the immune-exhausted subgroup are more suitable for chemotherapy.

Identification of molecular subtypes based on liquid-liquid phase separation and cross-talk with immunological phenotype in bladder cancer

Background

Mounting evidence has demonstrated that an imbalance in liquid-liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics.

Methods

A total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient's response to immune checkpoint blockade (ICB) treatment.

Results

Three LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA.

Conclusions

Our study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients' sensitivity to immunotherapy.

Molecular Cluster Mining of Adrenocortical Carcinoma via Multi-Omics Data Analysis Aids Precise Clinical Therapy

Adrenocortical carcinoma (ACC) is a malignancy of the endocrine system. We collected clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA, lncRNA, microRNA, and somatic mutations in ACC patients from the TCGA, GSE19750, GSE33371, and GSE49278 cohorts. Based on the MOVICS algorithm, the patients were divided into ACC1-3 subtypes by comprehensive multi-omics data analysis. We found that immune-related pathways were more activated, and drug metabolism pathways were enriched in ACC1 subtype patients. Furthermore, ACC1 patients were sensitive to PD-1 immunotherapy and had the lowest sensitivity to chemotherapeutic drugs. Patients with the ACC2 subtype had the worst survival prognosis and the highest tumor-mutation rate. Meanwhile, cell-cycle-related pathways, amino-acid-synthesis pathways, and immunosuppressive cells were enriched in ACC2 patients. Steroid and cholesterol biosynthetic pathways were enriched in patients with the ACC3 subtype. DNA-repair-related pathways were enriched in subtypes ACC2 and ACC3. The sensitivity of the ACC2 subtype to cisplatin, doxorubicin, gemcitabine, and etoposide was better than that of the other two subtypes. For 5-fluorouracil, there was no significant difference in sensitivity to paclitaxel between the three groups. A comprehensive analysis of multi-omics data will provide new clues for the prognosis and treatment of patients with ACC.

Phototherapy with Cancer-Specific Nanoporphyrin Potentiates Immunotherapy in Bladder Cancer

PURPOSE

Immune checkpoint inhibitors (ICI) in general have shown poor efficacy in bladder cancer. The purpose of this project was to determine whether photodynamic therapy (PDT) with bladder cancer-specific porphyrin-based PLZ4-nanoparticles (PNP) potentiated ICI.

EXPERIMENTAL DESIGN

SV40 T/Ras double-transgenic mice bearing spontaneous bladder cancer and C57BL/6 mice carrying syngeneic bladder cancer models were used to determine the efficacy and conduct molecular correlative studies.

RESULTS

PDT with PNP generated reactive oxygen species, and induced protein carbonylation and dendritic cell maturation. In SV40 T/Ras double-transgenic mice carrying spontaneous bladder cancer, the median survival was 33.7 days in the control, compared with 44.8 (P = 0.0123), 52.6 (P = 0.0054), and over 75 (P = 0.0001) days in the anti-programmed cell death-1 antibody (anti-PD-1), PNP PDT, and combination groups, respectively. At Day 75 when all mice in other groups died, only 1 in 7 mice in the combination group died. For the direct anti-tumor activity, compared with the control, the anti-PD-1, PNP PDT, and combination groups induced a 40.25% (P = 0.0003), 80.72% (P < 0.0001), and 93.03% (P < 0.0001) tumor reduction, respectively. For the abscopal anticancer immunity, the anti-PD-1, PNP PDT, and combination groups induced tumor reduction of 45.73% (P = 0.0001), 54.92% (P < 0.0001), and 75.96% (P < 0.0001), respectively. The combination treatment also diminished spontaneous and induced lung metastasis. Potential of immunotherapy by PNP PDT is multifactorial.

CONCLUSIONS

In addition to its potential for photodynamic diagnosis and therapy, PNP PDT can synergize immunotherapy in treating locally advanced and metastatic bladder cancer. Clinical trials are warranted to determine the efficacy and toxicity of this combination.

Neoadjuvant Chemotherapy Improves the Immunosuppressive Microenvironment of Bladder Cancer and Increases the Sensitivity to Immune Checkpoint Blockade

Although tumor immune microenvironment plays an important role in antitumor therapy, few studies explored the gene signatures associated with the tumor immune microenvironment of bladder cancer after neoadjuvant chemotherapy. We examined and analyzed differentially expressed genes from 9 patients with stage I-III bladder cancer by RNA immune-oncology profiling platform. After neoadjuvant chemotherapy, the expressions of 43 genes in 19 pathways and 10 genes in 5 pathways were upregulated and downregulated, respectively. Neoadjuvant chemotherapy also promoted the expression of genes related to the activation of antitumor immune responses and decreased the expression of genes related to tumor proliferation pathways. In addition, neoadjuvant chemotherapy improved tumor response to immune checkpoint blockade. Furthermore, this study also identified several genes that can be used to predict the efficacy of neoadjuvant chemotherapy and their possible molecular mechanisms. In conclusion, neoadjuvant chemotherapy may promote the activation of antitumor effects, improve the suppressive tumor immune microenvironment, and increase the sensitivity of bladder cancer to immune checkpoint blockade.

RNA modification "writer"-mediated RNA modification patterns and tumor microenvironment characteristics of cervical cancer

PURPOSE

As an epigenetic regulation mechanism after transcription, RNA modification is installed by endogenous "writer" enzymes and is widely involved in a variety of physiological processes, including cancer progression. This study explored the RNA modification patterns of cervical cancer to clarify overall effect of RNA modification on tumor microenvironment (TME) characteristics and immune/targeted therapy.

METHODS

26 RNA modification "writers" were clustered, and the RNA modification patterns and TME characteristics of cervical cancer patients in TCGA were systematically evaluated. Based on differentially expressed genes (DEGs) between different RNA modification patterns, an RNA modification "writer" score (WM score) system was developed to assess the RNA modification of a single sample.

RESULTS

Two different RNA modification patterns of cervical cancer were identified, and these patterns were significantly related to the prognosis and TME infiltration characteristics of patients. WM score was an independent risk factor for the prognosis of cervical cancer. High WM score was characterized by poor prognosis, low immune infiltration and low tumor mutation burden (TMB), while low-WM score was related to relatively long overall survival (OS), more immune components in TME and increased TMB. In addition, the low-WM score group was expected to be more sensitive to programmed cell death protein 1 (PD-1) therapy and showed lower predicted IC₅₀ of chemotherapy drugs paclitaxel and cisplatin treatment.

CONCLUSIONS

This study identified and characterized RNA modification patterns, and clarified potential relationship between RNA modification patterns and immune infiltration characteristics and immunotherapy of cervical cancer, offering a new evaluation scheme for treatment of cervical cancer patients.

X-Box Binding Protein 1 (XBP1): A Potential Role in Chemotherapy Response, Clinical Pathologic Features, Non-Inflamed Tumour Microenvironment for Breast Cancer

X-box binding protein 1 (XBP1) is mainly expressed in breast cancer (BC) in human cancers. Its tumorigenesis and favourable prognosis are contradictory, and its essential role in chemotherapeutic response and immunosuppression is unknown in BC. The study firstly identified XBP1 who received neoadjuvant chemotherapy (NAC) from GSE25055 and GSE24460. Associations between XBP1 expression and clinicopathological characteristics was investigated using Oncomine, TCGA, UALCAN and bc-GenExMiner. The prognostic value of XBP1 was assessed using the Kaplan–Meier Plotter, bc-GenExMiner, GSE25055, and GSE25056. Furthermore, we systematically correlated XBP1 and immunological characteristics in the BC tumour microenvironment (TME) using TISIDB, TIMER, GSE25055, GSE25056 and TCGA dataset. Finally, an essential role of XBP1 in chemotherapy response was evaluated based on GSE25055, GSE25065, GSE24460, GSE5846, ROC Plotter and CELL databases. Furthermore, XBP1 mRNA expression levels were obviously highest in BC among human cancers and were significantly related to a good prognosis. In addition, XBP1 mRNA and protein levels were higher in the luminal subtype than in normal tissues and basal-like subtype, which might be attributed to membrane transport-related processes. Apart from BC, negative immunological correlations of XBP1 were not observed in other malignancies. XBP1 might shape the non-inflamed TME in BC. Finally, XBP1 expression was higher in chemo-resistive than chemo-sensitive cases, it had a predictive value and could independently predict chemotherapy response in BC patients receiving NAC. Our study suggests that the essential role of XBP1 in clinical pathologic features, non-inflamed TME, chemotherapy response in BC.

Molecular Subtypes Based on Genomic and Transcriptomic Features Correlate with the Responsiveness to Immune Checkpoint Inhibitors in Metastatic Clear Cell Renal Cell Carcinoma

Simple Summary

Immune checkpoint inhibitors (ICIs), such as programmed cell death protein 1 (PD-1) blockade, have proven to be the most effective agents for the management of many cancer types. Although ICIs are the current standard of care for treating metastatic clear cell renal cell carcinoma (ccRCC), 40–60% of patients still have intrinsic resistance to ICIs across multiple clinical trials. Therefore, identifying optimal biomarkers that can predict either responders or non-responders to ICIs has been of tremendous importance. Here, we generated targeted sequencing and whole transcriptomic sequencing of 60 patients with metastatic ccRCC treated with ICIs. Moreover, transcriptomic analysis was integrated to identify molecular subtypes using a total of 177 tumor samples by merging our data and published data derived from the CheckMate 025 trial. Our results show that these molecular subtypes are associated with specific genomic alterations, distinct molecular pathways, and differential clinical outcomes in patients with metastatic ccRCC treated with ICIs.

Abstract

Clear cell renal cell carcinoma (ccRCC) has been reported to be highly immune to and infiltrated by T cells and has angiogenesis features, but the effect of given features on clinical outcomes followed by immune checkpoint inhibitors (ICIs) in ccRCC has not been fully characterized. Currently, loss of function mutation in PBRM1, a PBAF-complex gene frequently mutated in ccRCC, is associated with clinical benefit from ICIs, and is considered as a predictive biomarker for response to anti-PD-1 therapy. However, functional mechanisms of PBRM1 mutation regarding immunotherapy responsiveness are still poorly understood. Here, we performed targeted sequencing (n = 60) and whole transcriptomic sequencing (WTS) (n = 61) of patients with metastatic ccRCC treated by ICIs. By integrating WTS data from the CheckMate 025 trial, we obtained WTS data of 177 tumors and finally identified three molecular subtypes that are characterized by distinct molecular phenotypes and frequency of PBRM1 mutations. Patient clustered subtypes 1 and 3 demonstrated worse responses and survival after ICIs treatment, with a low proportion of PBRM1 mutation and angiogenesis-poor, but were immune-rich and cell-cycle enriched. Notably, patients clustered in the subtype 2 showed a better response and survival after ICIs treatment, with enrichment of PBRM1 mutation and metabolic programs and a low exhausted immune phenotype. Further analysis of the subtype 2 population demonstrated that GATM (glycine amidinotransferase), as a novel gene associated with PBRM1 mutation, plays a pivotal role in ccRCC by using a cell culture model, revealing tumor, suppressive-like features in reducing proliferation and migration. In summary, we identified that metastatic ccRCC treated by ICIs have distinct genomic and transcriptomic features that may account for their responsiveness to ICIs. We also revealed that the novel gene GATM can be a potential tumor suppressor and/or can be associated with therapeutic efficacy in metastatic ccRCC treated by ICIs.

Identification of three immune subtypes characterized by distinct tumor immune microenvironment and therapeutic response in stomach adenocarcinoma

BACKGROUND

In primary stomach adenocarcinoma (STAD), the tumor immune microenvironment (TIME) is important for cancer occurrence and progression; however, its clinical significance remains unclear. This study investigated the association between patient survival, TIME, and therapeutic response to STAD.

METHODS

Gene expression profiles of STAD cases were collected from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus. Molecular subtypes were explored with consistent clustering methods according to 119 immune signatures and the infiltrating scores of 22 immune cells using the Multi-Omics Immuno-Oncology Biological Research algorithm. We determined IFNγ scores and immune cytolytic activity (CYT) scores on the basis of corresponding gene signatures via single-sample Gene Set Enrichment Analysis. Comparisons of survival, TIME, 10 immunity-related oncogenic pathways, immune checkpoint expression, and therapeutic response were conducted among the three subtypes. We further applied linear discriminant analysis to construct a characteristic index to classify the subtypes, and the Pearson correlation coefficient for the relationship between the index and immune checkpoint genes. Weighted Correlation Network Analysis (WGCNA) was used to mine the associated modules and specific genes.

RESULTS

We collected gene expression profiles from 352 STAD cases in the TCGA database, 300 in GSE62254, and 344 in GSE84437. Three STAD subtypes (IS1-IS3) were established according to the TIME signatures. The IS3 subtype had the highest immune score and the best prognosis, as well as markedly increased immune T-cell CYT, Th1/IFNγ scores, and immune checkpoint gene expression, compared to the other two subtypes. It was highly similar to the PD-1 response group in the previous study samples of GSE91061. The established TIME classification index performed well in classifying subtypes and was directly proportional to immune checkpoint-related gene expression levels. WGCNA explored 6 modules and 14 genes, namely DYSF, MAN1C1, HTRA3, EMCN, RFLNB, KANK3, MAGEH1, CD93, PCAT19, FUT11, BMP1, FOSB, DCHS1, and TCF3, which were associated with the established TIME classification index and STAD patient prognosis.

CONCLUSION

TIME phenotypes of STAD patients could be divided into three different molecular subtypes, which displayed different prognoses, immune features, and therapeutic responses. Our results shed new light on predicting patient outcomes and the discovery of new anti-STAD therapeutic strategies according to the TIME.

Construction and Validation of a 15-Top-prognostic-gene-based Signature to Indicate the Dichotomized Clinical Outcome and Response to Targeted Therapy for Bladder Cancer Patients

The clinical outcome of heterogeneous bladder cancer (BCa) is impacted by varying molecular characteristics and clinical features, and new molecular classification is necessary to recognize patients with dichotomized prognosis. We enrolled a total of 568 BCa patients from the TCGA-BLCA and GSE13507 cohorts. A total of 107 candidate genes, which were mostly involved in the extracellular matrix-associated pathway, were first selected through the consensus value of the area under the receiver operating characteristic curve (AUC). Furthermore, absolute shrinkage and selection operation regression analysis was implemented to reveal the 15 genes and establish the prognostic signature. The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76–3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76–3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208–34.731). Multivariate Cox analysis involving the signature and clinical features indicated that the signature is an independent factor for the prediction of BCa prognosis. We also explored potential targeted therapy for BCa patients with high- or low-risk scores and found that patients with high risk were more suitable for chemotherapy with gemcitabine, doxorubicin, cisplatin, paclitaxel, and vinblastine (all p < 0.05), but anti-PD-L1 therapy was useless. We knocked down HEYL with siRNAs in T24 and 5,637 cells, and observed the decreased protein level of HEYL, and inhibited cell viability and cell invasion. In summary, we proposed and validated a 15-top-prognostic gene-based signature to indicate the dichotomized prognosis and response to targeted therapy.

High Stromal SFRP2 Expression in Urothelial Carcinoma Confers an Unfavorable Prognosis

Background

Urothelial carcinoma (UC) patients often bear clinical and genetic heterogeneity, which may differ in management and prognosis. Especially, patients with advanced/metastatic UC generally have a poor prognosis and survive for only few months. The Wnt/β-catenin signaling is found to be highly activated in several cancers, including UC. However, accumulated evidence has shown discordance between the Wnt/β-catenin signaling and UC carcinogenesis. Accordingly, we aim to get a better understanding of the molecular characterization of UC, focusing on the Wnt signaling, which may add value to guiding management more precisely.

Patients and Methods

Clinical data and pathological features were retrospectively surveyed. The correlations of secreted Frizzled-related protein 2 (SFRP2) immunoexpression with clinicopathological features were analyzed by Pearson's chi-square test. The Kaplan-Meier method with a log-rank test was employed to plot survival curves. All significant features from the univariate analysis were incorporated into the Cox regression model for multivariate analysis.

Results

Following data mining on a transcriptome dataset (GSE31684), we identified that 8 transcripts in relation to the Wnt signaling pathway (GO: 0016055) were significantly upregulated in advanced/metastatic bladder tumors. Among these transcripts, the SFRP2 level showed the most significant upregulation. Additionally, as SFRP2 is a putative Wnt inhibitor and may be expressed by stroma, we were interested in examining the immunoexpression and clinical relevance of stromal and tumoral SFRP2 in our urothelial carcinoma cohorts containing 295 urinary bladder UC (UBUC) and 340 upper urinary tract UC (UTUC) patients. We observed that high SFRP2 expression in stroma but not in tumors is significantly linked to aggressive UC features, including high tumor stage and histological grade, positive nodal metastasis, the presence of vascular and perineural invasion, and high mitotic activity in UBUC and UTUC. Moreover, high stromal SFRP2 expression significantly and independently predicted worse clinical outcomes in UBUC and UTUC. Utilizing bioinformatic analysis, we further noticed that stromal SFRP2 may link epithelial-mesenchymal transition (EMT) to UC progression.

Conclusion

Collectively, these results imply that stromal SFRP2 may exert oncogenic function beyond its Wnt antagonistic ability, and stromal SFRP2 expression can provide prognostic and therapeutic implications for UC patients.

Role of Circular RNAs in the Regulation of Immune Cells in Response to Cancer Therapies

Circular RNAs (CircRNAs) are a class of small endogenous noncoding RNA that are formed by means of either the spliceosome or lariat-type splicing. CircRNAs have multiple regulatory functions and have been detected in different cell types, like normal, tumor and immune cells. CircRNAs have been suggested to regulate T cell functions in response to cancer. CircRNAs can enter into T cells and promote the expression of molecules that either trigger antitumoral responses or promote suppression and the consequent evasion to the immune response. Additionally, circRNAs may promote tumor progression and resistance to anticancer treatment in different types of neoplasias. In this minireview we discuss the impact of circRNAs and its function in the regulation of the T-cells in immune response caused by cancer therapies.

The Mechanism and Prognostic Value of DNA Polymerase δ Subunits in Hepatocellular Carcinoma: Implications for Precision Therapy

PURPOSE

Polymerase δ (POLD) proteins is a pivotal B-family DNA polymerase in the process of genome replication and repair and are comprised of POLD1-4. The predictive value of POLDs in hepatocellular carcinoma (HCC) has not been evaluated until now.

PATIENTS AND METHODS

A total of 369 hepatocellular carcinoma samples and 50 adjacent normal samples were enrolled from the TCGA-LIHC database, and the GSE10186 database was also used. Transcription, methylation and genetic alteration status of HCC patients were evaluated by GEPIA, Kaplan-Meier plotter, cBioPortal, MethHC, MethSurv. SurvExpress was employed to generate the overall prognosis prediction signature of POLDs. POLDs coexpressed genes were explored and enriched in potential pathways. K-M curves were generated to compare the different survival results in different groups, while ROC curves were used to validate the efficiency of the POLD signature.

RESULTS

All four POLD subunits were highly expressed in HCC tumor tissues. POLD1-3 and increased mRNA levels were also positively associated with advanced tumor stage and OS prognosis. Methylation in the promoter of POLDs affects mRNA expression and OS, especially for some specific CpG sites. Meanwhile, POLDs could preferably predict the prognosis for patients who suffered from a high gene mutation burden. We evaluated the combined prognostic predictive value of four POLD subunits in both the TCGA-LIHC and GSE10186 databases and recognized the statistically significant HR of the high-risk group, along with the reliable predictive value. The coexpressed gene sets and annotation results showed that the POLD coexpressed genes were mostly associated with DNA repair and cell cycle regulation pathways.

CONCLUSION

POLD is an essential predictive factor for the prognosis of HCC. The united signature could precisely identify unfavorable clinical outcome of HCC.

Characterization of an Autophagy-Immune Related Genes Score Signature and Prognostic Model and its Correlation with Immune Response for Bladder Cancer

Purpose

The study aimed to identify an autophagy-related molecular subtype and characterize a novel defined autophagy-immune related genes score (AI-score) signature and prognosis model in bladder cancer (BLCA) patients using public databases.

Methods

The transcriptome cohorts downloaded from TCGA and GEO database were carried out with genomic analysis and unsupervised methods to obtain autophagy-related molecular subtypes. The single-sample gene-set enrichment analysis (ssGSEA) was utilized to perform immune subtype clustering. We defined a novel autophagy subtype and evaluated the role in TME cell infiltration. Then, the principal-component analysis (PCA) was applied to construct an AI-score signature. Subsequently, two immunotherapeutic cohorts were used to evaluate the predictive value in immunotherapeutic benefits and immune response. Finally, univariate, Lasso and multivariate Cox regression algorithm were used to construct and evaluate an autophagy-immune-related genes prognosis model. Also, qRT-PCR and IHC was applied to validate the expression of the 6 genes in the model.

Results

Three distinct autophagy clusters and immune-related clusters were identified, and a novel autophagy-related molecular subtypes were defined. Furthermore, the roles in TME cell infiltration and clinical traits for the autophagy subtypes were characterized. Meanwhile, we constructed an AI-score signature and demonstrated it could predict genetic mutation, clinicopathological traits, prognosis, and TME stromal activity. We found that it could accurately predict the clinicopathological characteristics and immune response of individual BLCA patients and provide guidance for selecting immunotherapy. Ultimately, we constructed and verified an autophagy-immune-related prognostic model of BLCA patients and established a prognostic nomogram with a good prediction accuracy.

Conclusion

We constructed AI-score signatures and prognosis risk model to characterize their role in clinical features and TME immune cell infiltration. It revealed that the AI-score signature and prognosis model could be a valid predictive tool, which could accurately predict the prognosis of BLCA patients and contribute to choosing effective personalized immunotherapy strategies.

Multi-Omics Analysis of Novel Signature for Immunotherapy Response and Tumor Microenvironment Regulation Patterns in Urothelial Cancer

The tumor microenvironment (TME) is mainly composed of tumor cells, tumor-infiltrating immune cells, and stromal components. It plays an essential role in the prognosis and therapeutic response of patients. Nonetheless, the TME landscape of urothelial cancer (UC) has not been fully elucidated. In this study, we systematically analyzed several UC cohorts, and three types of TME patterns (stromal-activation subtype, immune-enriched subtype and immune-suppressive subtype) were defined. The tumor microenvironment signature (TMSig) was constructed by modified Lasso penalized regression. Patients were stratified into high- and low-TMSig score groups. The low-score group had a better prognosis (p < 0.0001), higher M1 macrophage infiltration (p < 0.01), better response to immunotherapy (p < 0.05), and more similar molecular characteristics to the luminal (differentiated) subtype. The accuracy of the TMSig for predicting the immunotherapy response was also verified in three independent cohorts. We highlighted that the TMSig is an effective predictor of patient prognosis and immunotherapy response. Quantitative evaluation of a single sample is valuable for us to combine histopathological and molecular characteristics to comprehensively evaluate the status of the patient. Targeted macrophage treatment has great potential for the individualized precision therapy of UC patients.

Molecular classification reveals the diverse genetic and prognostic features of gastric cancer: A multi-omics consensus ensemble clustering

BACKGROUND

Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits.

METHODS

Multi-omics data, including transcriptomics RNA-sequencing (mRNA, LncRNA, miRNA), DNA methylation, and gene mutations in the TCGA-STAD cohort were used for the clustering. Ten classical clustering algorithms were executed to recognize patients with different molecular features using the "MOVICS" package in R. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The differential distribution of gene mutations, copy number alterations, and tumor mutation burden was compared, and potential responses to immunotherapy and chemotherapy were also assessed.

RESULTS

Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with consensus ensembles. Patients in the CS1 group had a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) as compared to those in the CS2 group. Extracellular associated biological process activation was higher in the CS1 group, while the CS2 group displayed the enhanced activation of cell cycle-associated pathways. Significantly higher total mutation numbers and neoantigens were observed in the CS2 group, along with specific mutations in TTN, MUC16, and ARID1A. Higher infiltration of immunocytes was also observed in the CS2 group, reflective of the potential immunotherapeutic benefits. Moreover, the CS2 group could also respond to 5-fluorouracil, cisplatin, and paclitaxel. The similar diversity in clinical outcomes between CS1 and CS2 groups was successfully validated in the external cohorts, GSE62254, GSE26253, GSE15459, and GSE84437.

CONCLUSION

The findings provided novel insights into the GC subtypes through integrative analysis of five -omics data by ten clustering algorithms. These could provide potential clinical therapeutic targets based on the specific molecular features.

Establishment of a tumor immune microenvironment-based molecular classification system of breast cancer for immunotherapy

Antitumor immunotherapy can enable promising and durable responses following their clinical application. However, heterogeneity in the tumor immune microenvironment leads to differences in the individual response rates. In this study, we identified novel immune-related molecular subclasses of breast cancer using a non-negative matrix factorization analysis. We enrolled 4184 patients with breast cancer, including 1104 patients from The Cancer Genome Atlas as a training cohort and 3080 patients from another four independent datasets as validation cohorts. In the training cohort, 36.9% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were categorized into an immune class, which was confirmed by probing the expression of immunocyte markers (CD3, CD19, and CD163). Within the immune class, 53.3% of patients belonged to an immune-suppressed subclass, characterized by the activation of stroma-related signatures and immune-suppressive cells. The remaining patients in the immune class were allocated to an immune-activated subclass. The interferon-γ and granzyme B levels were higher in the immune-activated subclass, whereas the transforming growth factor-β1 and programmed cell death-1 (PD-1) levels were higher in the immune-suppressed subclass. The established molecular classification system was recapitulated in validation cohorts. The immune-activated subclass was predicted to have a better response to anti-PD-1 immunotherapy. The immune-related subclasses were associated with differences in copy number alterations, tumor mutation burden, neoantigens, tumor-infiltrating lymphocyte enrichment, PD-1/programmed death-ligand 1 expression, mutation landscape, and various infiltration immunocytes. Overall, we established a novel immune-related molecular classification of breast cancer, which may be used to select candidate patients for immunotherapy.

Identification of immune-related subtypes of colorectal cancer to improve antitumor immunotherapy

Immunotherapy involving immune checkpoint inhibitors (ICIs) for enhancing immune system activation is promising for tumor management. However, the patients' responses to ICIs are different. Here, we applied a non-negative matrix factorization algorithm to establish a robust immune molecular classification system for colorectal cancer (CRC). We obtained data of 1503 CRC patients (training cohort: 488 from The Cancer Genome Atlas; validation cohort: 1015 from the Gene Expression Omnibus). In the training cohort, 42.8% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were subdivided into immune classes. Within the immune class, 53.1% of patients were associated with a worse overall prognosis and belonged to the immune-suppressed subclass, characterized by the activation of stroma-related signatures, genes, immune-suppressive cells, and signaling. The remaining immune class patients belonged to the immune-activated subclass, which was associated with a better prognosis and response to anti-PD-1 therapy. Immune-related subtypes were associated with different copy number alterations, tumor-infiltrating lymphocyte enrichment, PD-1/PD-L1 expression, mutation landscape, and cancer stemness. These results were validated in patients with microsatellite instable CRC. We described a novel immune-related class of CRC, which may be used for selecting candidate patients with CRC for immunotherapy and tailoring optimal immunotherapeutic treatment.

A Novel Tool for the Risk Assessment and Personalized Chemo-/Immunotherapy Response Prediction of Adenocarcinoma and Squamous Cell Carcinoma Lung Cancer

Background

The prevalence and cancer-specific death rate of lung cancer (LC) have risen in recent decades. A universally applicable prognostic signature for both adenocarcinoma LC (LUAD) and squamous cell carcinoma LC (LUSC) is still lacking.

Methods

A total of 453 patients from The Cancer Genome Atlas (TCGA)-LUAD cohort and 452 patients from TCGA-LUSC cohort were enrolled, and a prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis based on the consensus prognostic genes in both cohorts. The newly defined pan-lung cancer risk count (PLCRC) of each patient was calculated via the summation formula.

Results

A total of 23 genes were selected for the calculation of the PLCRC. The PLCRC showed a moderate prognostic value in the entire (p < 0.001, HR: 2.75, AUC: 0.643), LUAD (p < 0.001, HR: 2.51, AUC: 0.636) and LUSC (p < 0.001, HR: 2.89, AUC: 0.656) cohorts. The PLCRC was an independent prognostic factor after adjusting the clinical features. The PLCRC was also effective in nine external validation cohorts and in patients with different clinical features. Activation of extracellular matrix pathways and infiltration of immunocytes promoted the tumorigenesis and development of both LUAD and LUSC. We generated a universally applicable prognostic signature, the PLCRC, which could dichotomize patients with significantly different clinical outcomes and guide the clinical treatment of LC patients. Chemotherapy is more suitable for patients with a low PLCRC, while anti-cytotoxic T-lymphocyte-associated protein 4 immunotherapy is more suitable for patients with a high PLCRC.

Conclusion

We established and validated a newly defined prognostic signature, the PLCRC, for both LUAD and LUSC patients and provided clinical strategies for patients from different risk subgroups.

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Background

Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).

Results

We identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.

Conclusions

In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.