High CD3D/CD4 ratio predicts better survival in muscle-invasive bladder cancer

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.

Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis

Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma (BLCA) has a poor prognosis. This study focused on identifying and validating prognostic biomarkers utilizing methylation, transcriptomics, and clinical data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA BLCA) cohort. The impact of altered differentially methylated hallmark pathway genes was subjected to clustering analysis to observe changes in the transcriptional landscape on BLCA patients and identify two subtypes of patients from the TCGA BLCA population where Subtype 2 was associated with the worst prognosis with a p-value of 0.00032. Differential expression and enrichment analysis showed that subtype 2 was enriched in immune-responsive and cancer-progressive pathways, whereas subtype 1 was enriched in biosynthetic pathways. Following, regression and network analyses revealed Epidermal Growth Factor Receptor (EGFR), Fos-related antigen 1 (FOSL1), Nuclear Factor Erythroid 2 (NFE2), ADP-ribosylation factor-like protein 4D (ARL4D), SH3 domain containing ring finger 2 (SH3RF2), and Cadherin 3 (CDH3) genes to be the most significant prognostic gene markers. These genes were used to construct a risk model that separated the BLCA patients into high and low-risk groups. The risk model was also validated in an external dataset by performing survival analysis between high and low-risk groups with a p-value < 0.001 and the result showed the high group was significantly associated with poor prognosis compared to the low group. Single-cell analyses revealed the elevated level of these genes in the tumor microenvironment and associated with immune response. High-grade patients also tend to have a high expression of these genes compared to low-grade patients. In conclusion, this research developed a six-gene signature that is pertinent to the prediction of overall survival (OS) and might contribute to the advancement of precision medicine in the management of bladder cancer.

A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer

p53 pathway is important in tumorigenesis. However, no study has been performed to specifically investigate the role of p53 pathway genes in bladder cancer (BLCA). In this study, transcriptomics data of muscle invasive bladder cancer patients (n = 411) from The Cancer Genome Atlas (TCGA) were investigated. Using the hallmark p53 pathway gene set, the Non-Negative Matrix factorization (NMF) analysis identified two subtypes (C1 and C2). Clinical, survival, and immunological analysis were done to validate distinct characteristics of the subtypes. Pathway enrichment analysis showed the subtype C1 with poor prognosis having enrichment in genes of the immunity related pathways, where C2 subtype with better prognosis being enriched in genes of the steroid synthesis and drug metabolism pathways. A signature gene set consisting of MDGA2, GNLY, GGT2, UGT2B4, DLX1, and DSC1 was created followed by a risk model. Their expressions were analyzed in RNA extracted from the blood and matched tumor tissues of BLCA patients (n = 10). DSC1 had significant difference of expression (p = 0.005) between the blood and tumor tissues in our BLCA samples. Contrary to the usual normal bladder tissue to blood ratio, DLX1 expression was lower (p = 0.02734) in tumor tissues than in blood. Being the first research of p53 pathway related signature gene set in bladder cancer, this study potentially has a substantial impact on the development of biomarkers for BLCA.

Construction of the novel immune risk scoring system related to CD8+ T cells in uterine corpus endometrial carcinoma

BACKGROUND

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with high incidence and poor prognosis. Although immunotherapy has brought significant survival benefits to advanced UCEC patients, traditional evaluation indicators cannot accurately identify all potential beneficiaries of immunotherapy. Consequently, it is necessary to construct a new scoring system to predict patient prognosis and responsiveness of immunotherapy.

METHODS

CIBERSORT combined with weighted gene co-expression network analysis (WGCNA), non-negative matrix factorization (NMF), and random forest algorithms to screen the module associated with CD8⁺ T cells, and key genes related to prognosis were selected out by univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to develop the novel immune risk score (NIRS). Kaplan-Meier (K-M) analysis was used to compare the difference of survival between high- and low- NIRS groups. We  also explored the correlations between NIRS, immune infiltration and immunotherapy, and three external validation sets were used to verify the predictive performance of NIRS. Furthermore, clinical subgroup analysis, mutation analysis, differential expression of immune checkpoints, and drug sensitivity analysis were performed to generate individualized treatments for patients with different risk scores. Finally, gene set variation analysis (GSVA) was conducted to explore the biological functions of NIRS, and qRT-PCR was applied to verify the differential expressions of three trait genes at cellular and tissue levels.

RESULTS

Among the modules clustered by WGCNA, the magenta module was most positively associated with CD8⁺ T cells. Three genes (CTSW, CD3D and CD48) were selected to construct NIRS after multiple screening procedures. NIRS was confirmed as an independent prognostic factor of UCEC, and patients with high NIRS had significantly worse prognosis compared to those with low NIRS. The high NIRS group showed lower levels of infiltrated immune cells, gene mutations, and expression of multiple immune checkpoints, indicating reduced sensitivity to immunotherapy. Three module genes were identified as protective factors positively correlated with the level of CD8⁺ T cells.

CONCLUSIONS

In this study, we constructed NIRS as a novel predictive signature of UCEC. NIRS not only differentiates patients with distinct prognoses and immune responsiveness, but also guides their therapeutic regimens.

Identification of molecular subtypes of ischaemic stroke based on immune-related genes and weighted co-expression network analysis

Immune system has been reported to play a key role in the development of ischaemic stroke (IS). Nevertheless, its exact immune-related mechanism has not yet been fully revealed. Gene expression data of IS and healthy control samples was downloaded from Gene Expression Omnibus database and differentially expressed genes (DEGs) was obtained. Immune-related genes (IRGs) data was downloaded from the ImmPort database. The molecular subtypes of IS were identified based on IRGs and weighted co-expression network analysis (WGCNA). 827 DEGs and 1142 IRGs were obtained in IS. Based on 1142 IRGs, 128 IS samples were clustered into two molecular subtypes: clusterA and clusterB. Based on the WGCNA, the authors found that the blue module had the highest correlation with IS. In the blue module, 90 genes were screened as candidate genes. The top 55 genes were selected as the central nodes according to gene degree in protein-protein interactions network of all genes in blue module. Through taking overlap, nine real hub genes were obtained that might distinguish between clusterA subtype and clusterB subtype of IS. The real hub genes (IL7R, ITK, SOD1, CD3D, LEF1, FBL, MAF, DNMT1, and SLAMF1) may be associated with molecular subtypes and immune regulation of IS.

Significance of tumor-associated neutrophils, lymphocytes, and neutrophil-to-lymphocyte ratio in non-invasive and invasive bladder urothelial carcinoma

Background

Tumor-infiltrating neutrophils and lymphocytes play essential roles in promoting or combating various neoplasms. This study aimed to investigate the association between tumor-infiltrating neutrophils and lymphocytes and the neutrophil-to-lymphocyte ratio in the progression of urothelial carcinoma.

Methods

A total of 106 patients diagnosed with urothelial carcinoma were was. Pathological examination for tumor grade and stage and for tumor-infiltrating neutrophils, both CD4 and CD8+ T lymphocytes, as well as the neutrophil- to-lymphocyte ratio were evaluated.

Results

The presence of neutrophils and the neutrophil-to-lymphocyte ratio correlated with high-grade urothelial neoplasms. In both low- and high-grade tumors, the lymphocytes increased during progression from a non-invasive neoplasm to an early-invasive neoplasm. CD8+ T lymphocytes increased in low-grade non-muscle-invasive tumors compared to non-invasive tumors. Additionally, there was a significant decrease in CD8+ T lymphocytes during progression to muscle-invasive tumors.

Conclusions

Our results suggest that tumor-infiltrating neutrophils and CD8+ T lymphocytes have a significant effect on tumor grade and progression.

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evaluate the prognostic value of quantitative TILs score based on a machine learning (ML) algorithm to identify MIBC patients who might benefit from immunotherapy or the de-escalation of therapy. (2) Methods: We constructed an artificial neural network classifier for tumor cells, lymphocytes, stromal cells, and “ignore” cells from hematoxylin-and-eosin-stained slide images using the QuPath open source software. We defined four unique TILs variables based on ML to analyze TILs measurements. Pathological slide images from 133 MIBC patients were retrospectively collected as the discovery set to determine the optimal association of ML-read TILs variables with patient survival outcomes. For validation, we evaluated an independent external validation set consisting of 247 MIBC patients. (3) Results: We found that all four TILs variables had significant prognostic associations with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TILs score being associated with better prognosis. Univariate and multivariate Cox regression analyses demonstrated that electronic TILs (eTILs) variables were independently associated with overall survival after adjustment for clinicopathological factors including age, sex, and pathological stage (p < 0.001 for all analyses). Results analyzed in different subgroups showed that the eTILs variable was a strong prognostic factor that was not redundant with pre-existing clinicopathological features (p < 0.05 for all analyses). (4) Conclusion: ML-driven cell classifier-defined TILs variables were robust and independent prognostic factors in two independent cohorts of MIBC patients. eTILs have the potential to identify a subset of high-risk stage II or stage III-IV MIBC patients who might benefit from adjuvant immunotherapy.

Detailed bladder cancer immunoprofiling reveals new clues for immunotherapeutic strategies

Objectives

Bladder cancer (BlCa) is the tenth most frequent malignancy worldwide and the costliest to treat and monitor. Muscle-invasive BlCa (MIBC) has a dismal prognosis, entailing the need for alternative therapies for the standard radical cystectomy. Checkpoint blockade immunotherapy has been approved for high-grade non-muscle-invasive BlCa (HG NMIBC) and metastatic disease, but its effectiveness in localised MIBC remains under scrutiny. Herein, we sought to characterise and compare the immune infiltrate of HG NMIBC and MIBC samples, including ICOS expression, a targetable immune checkpoint associated with regulatory T cell(T_regs)-mediated immunosuppression.

Methods

Immunohistochemistry for CD83, CD20, CD68, CD163, CD3, CD8, CD4, FoxP3/ICOS and PD-L1 was performed in HG NMIBC and MIBC samples (n = 206), and positive staining was quantified in the peritumoral and/or intratumoral tissue compartments with QuPath imaging software.

Results

CD20⁺ B cells, CD68⁺ and CD163⁺ tumor-associated macrophages were significantly increased in MIBCs and associated with poor prognosis. In turn, higher infiltration of T cells was associated with prolonged survival, with exception of the CD4⁺ helper subset. Intratumoral expression of CD3 and CD8 was independent prognostic factors for increased disease-free survival (DFS) in multivariable analysis. Remarkably, T_regs (FoxP3⁺/FoxP3⁺ICOS⁺) were found differentially distributed between tissue compartments. PD-L1 immunoexpression independently predicted a shorter DFS and associated with higher infiltration of FoxP3⁺ICOS⁺ T_regs.

Conclusions

Immune infiltrates of HG NMIBC and MIBC display significant differences that may help selecting patients for immunotherapies. Considering ICOS immunoexpression results, it might constitute a relevant therapeutic target, eventually in combination with anti-PD-1/PD-L1 therapies, for certain BlCa patient subsets.

Identification of leucine-rich repeat-containing protein 59 (LRRC59) located in the endoplasmic reticulum as a novel prognostic factor for urothelial carcinoma

BACKGROUND

Urothelial carcinoma (UC) is one of the most common cancers worldwide. The biological heterogeneity of UCs causes considerable difficulties in predicting treatment outcomes and usually leads to clinical mismanagement. The identification of more sensitive and efficient predictive biomarkers is important in the diagnosis and classification of UCs. Herein, we report leucine-rich repeat-containing protein 59 (LRRC59) located in the endoplasmic reticulum as a novel predictive factor and potential therapeutic target for UCs.

METHODS

Using whole-slide image analysis in our cohort of 107 UC samples, we performed immunohistochemistry to evaluate the prognostic value of LRRC59 expression in UCs. In vitro experiments using RNAi were conducted to explore the role of LRRC59 in promoting UC cell proliferation and migration.

RESULTS

A significant correlation between LRRC59 and unfavorable prognosis of UCs in our cohort was demonstrated. Subsequent clinical analysis also revealed that elevated expression levels of LRRC59 were significantly associated with higher pathological grades and advanced stages of UC. Subsequently, knockdown of LRRC59 in UM-UC-3 and T24 cells using small interfering RNA significantly inhibited cell proliferation and migration, resulting in cell cycle arrest at the G1 phase. Conversely, the overexpression of LRRC59 in UC cells enhanced cell proliferation and migration. An integrated bioinformatics analysis revealed a significant functional network of LRRC59 involving protein misfolding, ER stress, and ubiquitination. Finally, in vitro experiments demonstrated that LRRC59 modulates ER stress signaling.

CONCLUSIONS

LRRC59 expression was significantly correlated with UC prognosis. LRRC59 might not only serve as a novel prognostic biomarker for risk stratification of patients with UC but also exhibit as a potential therapeutic target in UC that warrants further investigation.

Construction of the prognostic enhancer RNA regulatory network in osteosarcoma

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Our enhancer RNAs-based prognostic model showed good predictive ability in osteosarcoma.

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CCAAT enhancer binding protein alpha (CEBPA) may regulate CD8A molecule (CD8A).

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CD8A activation may promote CD3E molecule (CD3E) expression and activate allograft rejection in CD8+ T cells.

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Above signal axis provided new insights in the mechanism of osteosarcoma tumorigenesis.

Background

Osteosarcoma (OS) is a common malignant tumor in osteoarticular system, the 5-year overall survival of which is poor. Enhancer RNAs (eRNAs) have been implicated in the tumorigenesis of various cancer types, whereas their roles in OS tumorigenesis remains largely unclear.

Methods

Differentially expressed eRNAs (DEEs), transcription factors (DETFs), target genes (DETGs) were identified using limma (Linear Models for Microarray Analysis) package. Prognosis-related DEEs were accessed by univariate Cox regression analysis. A multivariate model was constructed to evaluate the prognosis of OS samples. Prognosis-related DEEs, DETFs, DETGs, immune cells, and hallmark gene sets were co-analyzed to construct an regulatory network. Specific inhibitors were also filtered by connectivity Map analysis. External validation and scRNA-seq analysis were performed to verify our key findings.

Results

3,981 DETGs, 468 DEEs, 51 DETFs, and 27 differentially expressed hallmark gene sets were identified. A total of Multivariate risk predicting model based on 18 prognosis-related DEEs showed a high accuracy (area under curve (AUC) = 0.896). GW-8510 was the candidate inhibitor targeting prognosis-related DEEs (mean = 0.670, p < 0.001). Based on the OS tumorigenesis-related regulation network, we identified that CCAAT enhancer binding protein alpha (CEBPA, DETF) may regulate CD8A molecule (CD8A, DEE), thereby promoting the transcription of CD3E molecule (CD3E, DETG), which may affect allograft rejection based on CD8+ T cells.

Conclusion

We constructed an eRNA-based prognostic model for predicting the OS patients’ prognosis and explored the potential regulation network for OS tumorigenesis by an integrated bioinformatics analysis, providing promising therapeutic targets for OS patients.

Identification of the Tumor Infiltrating Lymphocytes (TILs) Landscape in Pure Squamous Cell Carcinoma of the Bladder

Background: Tumor infiltrating lymphocytes (TILs) are known as important prognostic biomarkers and build the fundament for immunotherapy. However, the presence of TILs and its impact on outcome in pure squamous cell carcinoma (SCC) of the bladder remains uncertain. Methods: Out of 1600 patients undergoing radical cystectomy, 61 patients revealed pure bladder SCC in the final histopathological specimen. Retrospectively, immunohistochemical staining was performed on a subset of TILs (CD3+, CD4+, CD8+, CD20+). Endpoints were overall survival (OS), cancer-specific survival (CSS) and progression-free survival (PFS). The Kaplan−Meier method was used to evaluate survival outcomes. Results: Strong infiltration of CD3+ was found in 27 (44%); of CD4+ in 28 (46%); of CD8+ in 26 (43%); and of CD20+ in 27 tumors (44%). Improved OS was observed for strong CD3+ (p < 0.001); CD4+ (p = 0.045); CD8+ (p = 0.001); and CD20+ infiltration (p < 0.001). Increased rates of PFS were observed for CD3+ (p = 0.025) and CD20+ TILs (p = 0.002). In multivariate analyses, strong CD3+ (HR: 0.163, CI: 0.044−0.614) and strong CD8+ TILs (HR: 0.265, CI: 0.081−0.864) were revealed as predictors for OS and the strong infiltration of CD20+ cells (HR: 0.095, CI: 0.019−0.464) for PFS. Conclusions: These first results of TILs in bladder SCC revealed predictive values of CD3+, CD8+ and CD20+.

Tumor-infiltrating lymphocytes predict survival in ≥ pT2 urothelial bladder cancer

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in several types of cancers, including genitourinary cancers. However, multiple different scoring methods used to assess TILs complicate the comparison of different studies and are not always suitable for daily practice. In 2014, the International TILs Working Group (ITWG) proposed a simple and robust assessment method for a more standardized evaluation of TILs. Here, we validated this system in muscle-invasive urinary bladder cancer (MIBC). Patient history and histologic specimens from 203 patients with MIBC were retrospectively analyzed. The stromal TIL (sTIL) score was determined using the ITWG system and 3 groups were defined according to the degree of stromal lymphocytic infiltration: low (0-10%), intermediate (10-55%) and high (55-100%). Associations between sTIL score, clinicopathological variables, tumor-specific survival (TSS), overall survival (OS), and disease-free survival (DFS) were analyzed. High stromal lymphocytic infiltration was associated with significantly higher OS, TSS and DFS when compared to low grade sTILs. The survival benefit remained statistically significant in multivariate analyses, confirming that sTILs are a strong independent positive prognostic factor in patients with MIBC. In summary, the degree of sTILs as defined by the ITWG robustly predicts survival in MIBC patients. Prospective studies with larger case numbers are needed to determine whether sTILs should be included in staging guidelines and how they could aid in therapeutic decision making.

CD3D Is an Independent Prognostic Factor and Correlates With Immune Infiltration in Gastric Cancer

The protein encoded by CD3D is part of the T-cell receptor/CD3 complex (TCR/CD3 complex) and is involved in T-cell development and signal transduction. Previous studies have shown that CD3D is associated with prognosis and treatment response in breast, colorectal, and liver cancer. However, the expression and clinical significance of CD3D in gastric cancer are not clear. In this study, we collected 488 gastric cancer tissues and 430 paired adjacent tissues to perform tissue microarrays (TMAs). Then, immunohistochemical staining of CD3D, CD3, CD4, CD8 and PD-L1 was conducted to investigate the expression of CD3D in gastric cancer and the correlation between the expression of CD3D and tumor infiltrating lymphocytes (TILs) and PD-L1. The results showed that CD3D was highly expressed in gastric cancer tissues compared with paracancerous tissues (P<0.000). Univariate and multivariate analyses showed that CD3D was an independent good prognostic factor for gastric cancer (P=0.004, HR=0.677, 95%CI: 0.510-0.898 for univariate analyses; P=0.046, HR=0.687, 95%CI: 0.474-0.994 for multivariate analyses). In addition, CD3D was negatively correlated with the tumor location, Borrmann type and distant metastasis (P=0.012 for tumor location; P=0.007 for Borrmann type; P=0.027 for distant metastasis). In addition, the expression of CD3D was highly positively correlated with the expression of CD3, CD4, CD8, and PD-L1, and the combination of CD3D with CD3, CD4, CD8 and PD-L1 predicted the best prognosis (P=0.043). In summary, CD3D may play an important regulatory role in the tumor immune microenvironment of gastric cancer and may serve as a potential indicator of prognosis and immunotherapy response.

Therapeutic Targeting of Cancer Stem Cells in Lung, Head and Neck, and Bladder Cancers

Simple Summary

Effective cancer treatment hinges upon overcoming therapeutic resistance mechanisms that allow for the continued proliferation of cancer cell subpopulations. Exposure to pharmacotherapy invariably leads to resistance as tumor cells with selected advantageous features evade destruction and alter the tumor composition. Cancer stem cells (CSCs) with features of plasticity that allow for regeneration and differentiation are particularly responsible for this phenomenon. Advances in tumor biology and molecular signaling have highlighted their role in neoplastic initiation, invasion, and maintenance. Novel strategies to direct therapy against these tumor cell subpopulations have the potential to dramatically alter tumor response and change the course of cancer care.

Abstract

Resistance to cancer therapy remains a significant obstacle in treating patients with various solid malignancies. Exposure to current chemotherapeutics and targeted agents invariably leads to therapy resistance, heralding the need for novel agents. Cancer stem cells (CSCs)—a subpopulation of tumor cells with capacities for self-renewal and multi-lineage differentiation—represent a pool of therapeutically resistant cells. CSCs often share physical and molecular characteristics with the stem cell population of the human body. It remains challenging to selectively target CSCs in therapeutically resistant tumors. The generation of CSCs and induction of therapeutic resistance can be attributed to several deregulated critical growth regulatory signaling pathways such as WNT/β-catenin, Notch, Hippo, and Hedgehog. Beyond growth regulatory pathways, CSCs also change the tumor microenvironment and resist endogenous immune attack. Thus, CSCs can interfere with each stage of carcinogenesis from malignant transformation to the onset of metastasis to tumor recurrence. A thorough review of novel targeted agents to act against CSCs is fundamental for advancing cancer treatment in the setting of both intrinsic and acquired resistance.

Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma

Background: Cervical squamous cell carcinoma (CESC) is one of the most frequent malignancies in women worldwide. The level of immune cell infiltration and immune-related genes (IRGs) can significantly affect the prognosis and immunotherapy of CESC patients. Thus, this study aimed to identify an immune-related prognostic signature for CESC.

Methods: TCGA-CESC cohorts, obtained from TCGA database, were divided into the training group and testing group; while GSE44001 dataset from GEO database was viewed as external validation group. ESTIMATE algorithm was applied to evaluate the infiltration levels of immune cells of CESC patients. IRGs were screened out through weighted gene co-expression network analysis (WGCNA). A multi-gene prognostic signature based on IRGs was constructed using LASSO penalized Cox proportional hazards regression, which was validated through Kaplan–Meier, Cox, and receiver operating characteristic curve (ROC) analyses. The abundance of immune cells was calculated using ssGSEA algorithm in the ImmuCellAI database, and the response to immunotherapy was evaluated using immunophenoscore (IPS) analysis and the TIDE algorithm.

Results: In TCGA-CESC cohorts, higher levels of immune cell infiltration were closely associated with better prognoses. Moreover, a prognostic signature was constructed using three IRGs. Based on this given signature, Kaplan–Meier analysis suggested the significant differences in overall survival (OS) and the ROC analysis demonstrated its robust predictive potential for CESC prognosis, further confirmed by internal and external validation. Additionally, multivariate Cox analysis revealed that the three IRGs signature served as an independent prognostic factor for CESC. In the three-IRGs signature low-risk group, the infiltrating immune cells (B cells, CD4/8 + T cells, cytotoxic T cells, macrophages and so on) were much more abundant than that in high-risk group. Ultimately, IPS and TIDE analyses showed that low-risk CESC patients appeared to present with a better response to immunotherapy and a better prognosis than high-risk patients.

Conclusion: The present prognostic signature based on three IRGs (CD3E, CD3D, LCK) was not only reliable for survival prediction but efficient to predict the clinical response to immunotherapy for CESC patients, which might assist in guiding more precise individual treatment in the future.

Prodigiosin Sensitizes Sensitive and Resistant Urothelial Carcinoma Cells to Cisplatin Treatment

Cisplatin-based treatment is the standard of care therapy for urothelial carcinomas. However, complex cisplatin resistance mechanisms limit the success of this approach. Both apoptosis and autophagy have been shown to contribute to this resistance. Prodigiosin, a secondary metabolite from various bacteria, exerts different biological activities including the modulation of these two cellular stress response pathways. We analyzed the effect of prodigiosin on protein levels of different autophagy- and apoptosis-related proteins in cisplatin-sensitive and -resistant urothelial carcinoma cells (UCCs). Furthermore, we investigated the effect on cell viability of prodigiosin alone or in combination with cisplatin. We made use of four different pairs of cisplatin-sensitive and -resistant UCCs. We found that prodigiosin blocked autophagy in UCCs and re-sensitized cisplatin-resistant cells to apoptotic cell death. Furthermore, we found that prodigiosin is a potent anticancer agent with nanomolar IC50 values in all tested UCCs. In combination studies, we observed that prodigiosin sensitized both cisplatin-sensitive and -resistant urothelial carcinoma cell lines to cisplatin treatment with synergistic effects in most tested cell lines. These effects of prodigiosin are at least partially mediated by altering lysosomal function, since we detected reduced activities of cathepsin B and L. We propose that prodigiosin is a promising candidate for the therapy of cisplatin-resistant urothelial carcinomas, either as a single agent or in combinatory therapeutic approaches.

Multi-Omics Analysis of Acute Lymphoblastic Leukemia Identified the Methylation and Expression Differences Between BCP-ALL and T-ALL

Acute lymphoblastic leukemia (ALL) as a common cancer is a heterogeneous disease which is mainly divided into BCP-ALL and T-ALL, accounting for 80–85% and 15–20%, respectively. There are many differences between BCP-ALL and T-ALL, including prognosis, treatment, drug screening, gene research and so on. In this study, starting with methylation and gene expression data, we analyzed the molecular differences between BCP-ALL and T-ALL and identified the multi-omics signatures using Boruta and Monte Carlo feature selection methods. There were 7 expression signature genes (CD3D, VPREB3, HLA-DRA, PAX5, BLNK, GALNT6, SLC4A8) and 168 methylation sites corresponding to 175 methylation signature genes. The overall accuracy, accuracy of BCP-ALL, accuracy of T-ALL of the RIPPER (Repeated Incremental Pruning to Produce Error Reduction) classifier using these signatures evaluated with 10-fold cross validation repeated 3 times were 0.973, 0.990, and 0.933, respectively. Two overlapped genes between 175 methylation signature genes and 7 expression signature genes were CD3D and VPREB3. The network analysis of the methylation and expression signature genes suggested that their common gene, CD3D, was not only different on both methylation and expression levels, but also played a key regulatory role as hub on the network. Our results provided insights of understanding the underlying molecular mechanisms of ALL and facilitated more precision diagnosis and treatment of ALL.

Identification of prognosis-related genes in the cervical cancer immune microenvironment

BACKGROUND

Cervical cancer is the fourth most commonly diagnosed cancer in women worldwide. The metastasis and invasion of this type of cancer are closely related to the tumor microenvironment. Immune cells and stromal cells dominate the tumor microenvironment in cervical cancer. Therefore, we should further investigate the complex interplay between the tumor progression with immune cells or stromal cells.

METHODS

We downloaded the gene expression profiles and clinical data of 307 patients with cervical cancers based on the TCGA database. Subsequently, the Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm was used to calculate the scores of stromal cells and immune cells in order to uncover differential expressed genes, and we analyzed the correlation between their scores and patient survival. Then the Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) deconvolution algorithm was applied to quantify the fraction and infiltration of 22 types of immune cells in cervical cancer. Moreover, we also used R language packs and network tools to analyze GO term, gene enrichment pathway, and protein-protein relationship to trace down genes related to inflammation and immune regulation.

RESULTS

The gene expression profiles and corresponding clinical data of 307 patients were obtained from TCGA database. The results showed that the scores were statistically significant between the high immunescore group and the low immunescore group. And the low immunescore group had shorter survival period than the high scores group (P = 0.035). Among the 22 types of immune cells, only T cells and mast cells were significantly related to the survival rate of cervical cancer patients. Moreover, PPI network analysis revealed that CCR5 and CXCL9, -10, -11/CXCR3 axis might be a new target for cervical cancer treatment. Finally, Kaplan-Meier survival curves found outnine representative genes significantly related to survival rate including BTNL8, CCR7, CD1E, CD6, CD27, CD79A, GRAP2, SP1B, LY9.

CONCLUSIONS

These genes can be used as markers for the prognosis and diagnosis of cervical cancer and also might be used as treatment targets.

Comprehensive analysis reveals a prognostic and therapeutic biomarker CD3D in the breast carcinoma microenvironment

Breast carcinoma (BRCA) is the most common carcinoma among women worldwide. Despite the great progress achieved in early detection and treatment, morbidity and mortality rates remain high. In the present study, we make a systematic analysis of BRCA using TCGA database by applying CIBERSORT and ESTIMATE computational methods, uncovered CD3D as a prognostic biomarker by intersection analysis of univariate COX and protein–protein interaction (PPI). It revealed that high CD3D expression was strongly associated with poor survival of BRCA, based on The Cancer Genome Atlas (TCGA) database and online websites. Gene Set Enrichment Analysis (GSEA) revealed that the high CD3D expression group was mainly enriched for the immune-related pathways and the low CD3D expression group was mainly enriched for metabolic-related activities. Based on CIBERSORT analysis, the difference test and correlation test suggested that CD3D had a strong correlation with T cells, particularly CD8 + T cells, which indicated that CD3D up-regulation may increase T cell immune infiltration in the TME and induce antitumor immunity by activating T lymphocytes. Furthermore, the correlation analysis showed that CD3D expression had a strongly positive correlation with immune checkpoints, which indicating that the underlying mechanism involves CD3D mediated regulation of T cell functions in BRCA, and single cell RNA-seq analysis revealed that CD3D correlate with CD8 + T cells and it is itself highly expressed in CD8 + T cells. In summary, we identified a prognostic biomarker CD3D in BRCA, which was associated with lymphocyte infiltration, immune checkpoints and could be developed for innovative therapeutics of BRCA.

Poor Lymphocyte Infiltration to Primary Tumors in Acral Lentiginous Melanoma and Mucosal Melanoma Compared to Cutaneous Melanoma

Recent clinical trials have demonstrated the efficacy of immune checkpoint inhibitors (ICIs) for treating melanoma. However, these previous studies comprised mainly Caucasian populations, in which cutaneous melanoma (CM) is the major clinical type. In contrast, Asian populations have a distinct profile of melanoma and show much higher frequencies of acral lentiginous melanoma (ALM) and mucosal melanoma (MCM). Compared with CM, ALM and MCM show poorer response to ICIs, but the mechanisms have not been fully understood. To evaluate the immune status in each melanoma subtype, we examined the number of total tumor-infiltrating lymphocytes (TILs), CD4⁺ TILs, CD8⁺ TILs, and tumor-infiltrating FoxP3⁺ regulatory T cells (Tregs) to evaluate the immune status in each melanoma subtype using data from 137 patients with melanoma. Total TIL numbers in ALM and MCM were significantly lower than that in CM. CD4⁺ TIL number in MCM was also lower than CM although CD4⁺ TIL number in ALM was comparable with CM. In contrast, CD8⁺ TIL numbers in both ALM and MCM were significantly lower than that in CM. Although number of tumor-infiltrating Tregs was comparable among the 3 subtypes, the proportion of tumor-infiltrating Tregs in CD4⁺ T cells in MCM was significantly higher than in CM and ALM. Multivariate regression analysis revealed that ALM and MCM were significantly associated with a lower total TIL number, but only MCM was significantly associated with a lower CD4⁺ TIL number. Multivariate regression analysis also revealed that both ALM and MCM were significantly associated with a lower CD8⁺ TIL number. Our results suggest that both ALM and MCM are independent factors of lower total TIL number, which may be associated with poorer responses to ICIs in ALM and MCM.

High Stroma T-Cell Infiltration is Associated with Better Survival in Stage pT1 Bladder Cancer

Stage pT1 bladder cancer (BC) shows highly diverse outcomes. Predictive markers are required to stratify patients for personalized treatment. The present study aimed to validate immune response quantification as a prognostic marker. Patients with pT1 BC (n = 167) treated by transurethral resection of the bladder (TURB) were enrolled. Formaldehyde-fixed paraffin-embedded material was stained for CD3 and CD8. Corresponding T cells were counted in three regions with the highest immune response. Numbers of tertiary lymphoid structures (TLS) and lymphocyte aggregates (LA) were quantified. High CD3⁺ stroma T-cell infiltration was associated with improved survival (p = 0.045), especially in the G3 subgroup (p = 0.01). Cluster with higher immune response showed less recurrence (p = 0.034) and favorable overall survival (OS) (p = 0.019). In contrast, higher CD3⁺ and CD8⁺ tumor T-cell infiltration seemed to have a negative impact on prognosis. TLS and LA were more frequently observed in G3 tumors, indicating an increased anti-tumoral immune response. We proved the role of immune cell infiltration and showed that higher infiltration numbers of CD3⁺ (not CD8⁺) lymphocytes in the stroma are associated with favorable outcome. Immune cell quantification could be used as a marker to help stratify patients’ risk and therefore, to optimize patients’ management and follow-up examination as well as possible therapies.

Identification of Prognosis-Related Genes in Bladder Cancer Microenvironment across TCGA Database

Background

Bladder cancer (BCa) is a common urothelial malignancy. The Cancer Genome Atlas (TCGA) database allows for an opportunity to analyze the relationship between gene expression and clinical outcomes in bladder cancer patients. This study is aimed at identifying prognosis-related genes in the bladder cancer microenvironment.

Methods

Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We divided bladder cancer patients into high and low groups based on their immune/stromal scores. Then, differentially expressed genes (DEGs) were identified in bladder cancer patients based on the TCGA database. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. Finally, we validated identified genes associated with bladder cancer prognosis through a cohort study in the Gene Expression Omnibus (GEO) database.

Results

A higher stromal score was associated with female (vs. malep = 0.037), age > 65 (vs.age ≤ 65 p = 0.015), T3/4 (vs. T1/2,p < 0.001), N status(p = 0.016), and pathological high grade (vs. low gradeP < 0.001). By analyzing DEGs, there were 1125 genes commonly upregulated, and 209 genes were commonly downregulated. Protein-protein interaction networks further showed the important protein that may be involved in the biological behavior and prognosis of BCa, such as FN1, CXCL12, CD3E, LCK, and ZAP70. A total of 14 DEGs were found to be associated with overall survival of bladder cancer. After validation by a cohort of 165 BCa cases with detailed follow-up information from GSE13507, 10 immune-associated DEGs were demonstrated to be predictive of prognosis in BCa. Among them, 5 genes have not been reported previously associated with the prognosis of BCa, including BTBD16, OLFML2B, PRRX1, SPINK4, and SPON2.

Conclusions

Our study elucidated tight associations between stromal score and clinical characteristics as well as prognosis in BCa. Moreover, we obtained a group of genes closely related to the prognosis of BCa in the tumor microenvironment.

Clinical Impact of Tumor-Infiltrating Lymphocytes and PD-L1-Positive Cells as Prognostic and Predictive Biomarkers in Urological Malignancies and Retroperitoneal Sarcoma

Simple Summary

Two host-dependent biological characteristics, “avoiding immune destruction” and “tumor-promoting inflammation” have been added to cancer hallmarks in 2011. The interaction and cross-talk among tumor cells and several immune cells in a tumor microenvironment are dynamic and complex processes. The purpose of this review is to discuss the prognostic impact of tumor-infiltrating lymphocytes and predictive biomarkers for immune checkpoint inhibitors in four urological solid tumors, the urothelial carcinoma, renal cell carcinoma, prostate cancer, and retroperitoneal sarcoma, through summarizing the findings of observation studies and clinical trials.

Abstract

Over the past decade, an “immunotherapy tsunami”, more specifically that involving immune checkpoint inhibitors (ICIs), has overtaken the oncological field. The interaction and cross-talk among tumor cells and several immune cells in the tumor microenvironment are dynamic and complex processes. As immune contexture can vary widely across different types of primary tumors and tumor microenvironments, there is still a significant lack of clinically available definitive biomarkers to predict patient response to ICIs, especially in urogenital malignancies. An increasing body of evidence evaluating urological malignancies has proven that tumor-infiltrating lymphocytes (TILs) are a double-edged sword in cancer. There is an urgent need to shed light on the functional heterogeneity in the tumor-infiltrating immune system and to explore its prognostic impact following surgery and other treatments. Notably, we emphasized the difference in the immunological profile among urothelial carcinomas arising from different primary origins, the bladder, renal pelvis, and ureter. Significant differences in the density of FOXP3-positive TILs, CD204-positive tumor-infiltrating macrophages, PD-L1-positive cells, and colony-stimulating factors were observed. This review discusses two topics: (i) the prognostic impact of TILs and (ii) predictive biomarkers for ICIs, to shed light on lymphocyte migration in four solid tumors, the urothelial carcinoma, renal cell carcinoma, prostate cancer, and retroperitoneal sarcoma.

Prognostic and Predictive Value of Tumor-Infiltrating Immune Cells in Urothelial Cancer of the Bladder

The prognosis and responsiveness to chemotherapy and checkpoint inhibitors differs substantially among patients with bladder cancer (BC). There is an unmet need for biomarkers that can accurately predict prognosis and treatment outcome. Here, we describe the available literature on the prognostic and predictive value of tumor-infiltrating immune cells in BC. Current evidence indicates that a high density of tumor-infiltrating CD8+ T cells is a favorable prognostic factor, whereas PD-L1 expression and tumor-associated macrophages are unfavorable prognostic features. While PD-L1 expression appears unsuccessful as a biomarker for the response to checkpoint inhibitors, there are some indications that high CD8+ T cell infiltration, low transforming growth factor-beta signaling and low densities of myeloid-derived suppressor cells are associated with response. Future studies should focus on combinations of biomarkers to accurately predict survival and response to treatment.

Identification of gene modules associated with survival of diffuse large B-cell lymphoma treated with CHOP-based chemotherapy

Diffuse Large B-cell Lymphoma (DLBCL), a heterogeneous disease, is influenced by complex network of gene interactions. Most previous studies focused on individual genes, but ignored the importance of intergenic correlations. In current study, we aimed to explore the association between gene networks and overall survival (OS) of DLBCL patients treated with CHOP-based chemotherapy (cyclophosphamide combination with doxorubicin, vincristine and prednisone). Weighted gene co-expression network analysis was conducted to obtain insights into the molecular characteristics of DLBCL. Ten co-expression gene networks (modules) were identified in training dataset (n = 470), and their associations with patients' OS after chemotherapy were tested. The results were validated in four independent datasets (n = 802). Gene ontology (GO) biological function enrichment analysis was conducted with Metascape. Three modules (purple, brown and red), which were enriched in T-cell immune, cell-cell adhesion and extracellular matrix (ECM), respectively, were found to be related to longer OS. Higher expression of several hub genes within these three co-expression modules, for example, LCP2 (HR = 0.77, p = 5.40 × 10^-2), CD2 (HR = 0.87, p = 6.31 × 10^-2), CD3D (HR = 0.83, p = 6.94 × 10^-3), FYB (HR = 0.82, p = 1.40 × 10^-2), GZMK (HR = 0.92, p = 1.19 × 10^-1), FN1 (HR = 0.88, p = 7.06 × 10^-2), SPARC (HR = 0.82, p = 2.06 × 10^-2), were found to be associated with favourable survival. Moreover, the associations of the modules and hub genes with OS in different molecular subtypes and different chemotherapy groups were also revealed. In general, our research revealed the key gene modules and several hub genes were upregulated correlated with good survival of DLBCL patients, which might provide potential therapeutic targets for future clinical research.

Immune Responses in Bladder Cancer-Role of Immune Cell Populations, Prognostic Factors and Therapeutic Implications

Immunosurveillance, which describes the immunologically mediated elimination of transformed cells, has been widely accepted in the context of bladder cancer for many decades with the successful use of Bacillus-Calmette Guerin for superficial bladder cancer since the 1970s. With the emergence of checkpoint inhibitor blockade in the treatment of urothelial cancers, there has been a resurgent interest in the immunology of bladder cancer. The theory of cancer immunoediting proposes that the immune system has both pro-tumorigenic and anti-tumor effects, the balance between the two determining the progression of an individual tumor. However, whilst there is evidence for the action of various immune cell populations in bladder cancer, a cohesive picture of the immune response to bladder cancer and its driving forces are still lacking. Additionally, little is still known about the normal immune landscape of the bladder. Future progress in bladder cancer therapeutic approaches will require a strong foundation in understanding the immunology of this disease. This review considers the evidence for the role of the main immune cell populations, both innate and adaptive, in the immune response to bladder cancer. Recent research and overarching themes in the immune response to bladder cancer are explored. The minimal evidence regarding the normal immune landscape of the human bladder is also summarized to contextualize downstream immune responses. Of specific interest are the innate and myeloid populations, some of which are resident in the human bladder and which have significant effects on downstream adaptive tumor immunity. We discuss factors which restrain the efficacy of populations known to have anti-tumor activity such as cytotoxic T cells, including the constraints on checkpoint blockade. Additionally, the effects on the immune response of tumor intrinsic factors such as the genomic subtype of bladder cancer and the effect of common therapies such as chemotherapy and intravesical Bacillus Calmette-Guerin are considered. A significant theme is the polarization of immune responses within the tumor by a heavily immunosuppressive tumor microenvironment which affects the phenotype of multiple innate and adaptive populations. Throughout, clinical implications are discussed with suggestions for future research directions and therapeutic targeting.