Immune-Checkpoint Inhibitors in Advanced Bladder Cancer: Seize the Day

Heterogeneity of modulatory immune microenvironment in bladder cancer

Urinary bladder cancer (UBC) is the ninth most common cancer worldwide. The intra-tumor heterogeneity of the UBC microenvironment explains the variances in response to therapy among patients. Tumor immune microenvironment (TIME) is based on the balance between anti-tumor and pro-tumorigenic immunity that eventually determines the tumor fate. This review addresses the recent insights of the cytokines, immune checkpoints, receptors, enzymes, proteins, RNAs, cancer stem cells (CSCs), tissue-resident cells, growth factors, epithelial-mesenchymal transition, microbiological cofactor, and paracrine action of cancer cells that mutually cross-talk within the TIME. In-depth balance and alteration of these factors influence the TIME and the overall tumor progression. This, in turn, highlights the prospects of the new era of manipulating these co-factors for improving the diagnosis, prognosis, and treatment of UBC. CONCLUSION: The heterogenic architecture of the TIME orchestrates the fate of the tumor. Nevertheless, recognizing the mutual cross-talk between these key players seems useful in prognostic and therapeutic approaches.

A patient stratification signature mirrors the immunogenic potential of high grade serous ovarian cancers

BACKGROUND

While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials and case reports. These observations suggest that a molecular basis for effective immunity may exist within a subpopulation of HGSC. Herein, we developed an algorithm, CONSTRU (Computing Prognostic Marker Dependencies by Successive Testing of Gene-Stratified Subgroups), to facilitate the discovery and characterization of molecular backgrounds of HGSC that confer resistance or susceptibility to protective anti-tumor immunity.

METHODS

We used CONSTRU to identify genes from tumor expression profiles that influence the prognostic power of an established immune cytolytic activity signature (CYTscore). From the identified genes, we developed a stratification signature (STRATsig) that partitioned patient populations into tertiles that varied markedly by CYTscore prognostic power. The tertile groups were then analyzed for distinguishing biological, clinical and immunological properties using integrative bioinformatics approaches.

RESULTS

Patient survival and molecular measures of immune suppression, evasion and dysfunction varied significantly across STRATsig tertiles in validation cohorts. Tumors comprising STRATsig tertile 1 (S-T1) showed no immune-survival benefit and displayed a hyper-immune suppressed state marked by activation of TGF-β, Wnt/β-catenin and adenosine-mediated immunosuppressive pathways, with concurrent T cell dysfunction, reduced potential for antigen presentation, and enrichment of cancer-associated fibroblasts. By contrast, S-T3 tumors exhibited diminished immunosuppressive signaling, heightened antigen presentation machinery, lowered T cell dysfunction, and a significant CYTscore-survival benefit that correlated with mutational burden in a manner consistent with anti-tumor immunoediting. These tumors also showed elevated activity of DNA damage/repair, cell cycle/proliferation and oxidative phosphorylation, and displayed greater proportions of Th1 CD4 + T cells. In these patients, but not those of S-T1 or S-T2, validated predictors of immunotherapy response were prognostic of longer patient survival. Further analyses showed that STRATsig tertile properties were not explained by known HGSC molecular or clinical subtypes or singular immune mechanisms.

CONCLUSIONS

STRATsig is a composite of parallel immunoregulatory pathways that mirrors tumor immunogenic potential. Approximately one-third of HGSC cases classify as S-T3 and display a hypo-immunosuppressed and antigenic molecular composition that favors immunologic tumor control. These patients may show heightened responsiveness to current immunotherapies.

Improve clinical feature-based bladder cancer survival prediction models through integration with gene expression profiles and machine learning techniques

Background

Bladder cancer (BCa), one of the most common cancers worldwide, is characterized by high rates of recurrence, progression, and mortality. Machine learning algorithms offer promising advancements in enhancing predictive models. This study aims to develop robust machine learning models for predicting BCa survival using clinical and gene expression data.

Methods

Clinical data from BCa patients were obtained from the Surveillance, Epidemiology, and End Results database. Cox proportional hazards regression models assessed the association between clinical variables and overall survival. Machine learning algorithms, including logistic regression, random forest, XGBoost, decision tree, and LightGBM, were employed to predict survival at 1, 3, and 5 years. The TAGO database, combined with the data from The Cancer Genome Atlas and four databases from the Gene Expression Omnibus, which have available genomic data and clinical data, were selected. Gene expression data were transformed into gene sets data, and the performance of models based on clinical data and gene sets data and their combination were compared. Furthermore, the impact of model-derived scores on overall survival was evaluated.

Results

Among 138,741 BCa patients with available clinical data, key independent predictors of survival included age, race, marital status, surgery, chemotherapy, radiation, and TNM stages. Clinical data machine learning (CML) models used these clinical predictors to achieve AUC values of 0.860, 0.821, and 0.804 in the testing sets for predicting survival at 1, 3, and 5 years, respectively. In the TAGO database, which has 863 patients with clinical and genomic data, the integrated clinical and gene expression machine learning model (IML) outperformed the CML and gene expression machine learning (GML) models in survival prediction. Patients with higher IML and GML model scores exhibited poorer survival outcomes.

Conclusions

This study successfully identifies key clinical and genomic predictors, a significant step forward in BCa research. The development of predictive models for BCa survival underscores the potential of integrated data approaches in improving BCa management and treatment strategies.

LIG1 is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing

Background

Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors.

Methods

We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA.

Results

Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1high and LIG1low groups.Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples.

Conclusions

Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker.

Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.

Prognostic role of circulating cytokines and inflammation indexes for avelumab maintenance in metastatic urothelial carcinoma

Background

Avelumab maintenance after first-line platinum-based chemotherapy represents a cornerstone for the treatment of metastatic urothelial carcinoma (mUC). However, identifying prognostic biomarkers is paramount for optimizing patients' benefits while minimizing toxicity. Cytokines represent circulating mediators of the complex interaction between cancer, the immune system, and inflammation. Inflammation, a hallmark of cancer, can be expressed by circulating factors. In different tumor subtypes, peripheral blood biomarkers, such as circulating cytokines, and systemic inflammatory indexes, have been addressed as potential prognostic factors for immune checkpoint inhibitors. However, their role in mUC still needs to be determined.

Methods

Between February 2021 and April 2023, we prospectively collected plasma cytokines and inflammation indexes in 28 patients with mUC before starting avelumab as first-line maintenance. The primary endpoint was the relationship between baseline cytokines and inflammatory indexes with the clinical benefit (CB), defined as the number of Responders. Secondary endpoints included the correlation of baseline cytokines and inflammatory indexes with progression-free survival (PFS), overall survival (OS), and the number and grade of immune-related adverse events.

Results

High pre-treatment levels of interferon (IFN)-γ and interleukin (IL)-2, and low levels of IL-6, IL-8, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and systemic-inflammation index (SII) were associated with clinical benefit and longer survival. In the multivariate analysis, low IL-8, NLR, and SII levels maintained a positive prognostic value for OS.

Conclusion

Our data suggest that, in mUC patients receiving avelumab, pre-treatment levels of plasma cytokines and inflammatory indexes may serve as potential prognostic biomarkers for response and efficacy. In particular, patients with signs of pre-therapeutic inflammation showed a significantly lower response and survival to avelumab. On the contrary, low systemic inflammation and high levels of cytokines characterized responders and longer survivors.

Clinical implications of single cell sequencing for bladder cancer

Bladder cancer (BC) is the 10th most common cancer worldwide, with about 0.5 million reported new cases and about 0.2 million deaths per year. In this scoping review, we summarize the current evidence regarding the clinical implications of single-cell sequencing for bladder cancer based on PRISMA guidelines. We searched PubMed, CENTRAL, Embase, and supplemented with manual searches through the Scopus, and Web of Science for published studies until February 2023. We included original studies that used at least one single-cell technology to study bladder cancer. Forty-one publications were included in the review. Twenty-nine studies showed that this technology can identify cell subtypes in the tumor microenvironment that may predict prognosis or response to immune checkpoint inhibition therapy. Two studies were able to diagnose BC by identifying neoplastic cells through single-cell sequencing urine samples. The remaining studies were mainly a preclinical exploration of tumor microenvironment at single cell level. Single-cell sequencing technology can discriminate heterogeneity in bladder tumor cells and determine the key molecular properties that can lead to the discovery of novel perspectives on cancer management. This nascent tool can advance the early diagnosis, prognosis judgment, and targeted therapy of bladder cancer.

Significance of PD-L1 in Metastatic Urothelial Carcinoma Treated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis

IMPORTANCE

Immune checkpoint inhibitors (ICIs) have broadened the metastatic urothelial carcinoma (mUC) therapeutic scenario. The association of programmed death ligand 1 (PD-L1) with response and survival in patients treated with ICIs is still controversial.

OBJECTIVES

To evaluate the association of PD-L1 with response rate and overall survival among patients with mUC treated with ICIs.

DATA SOURCES

PubMed, Embase, American Society of Clinical Oncology and European Society for Medical Oncology Meeting Libraries, and Web of Science were searched up to December 10, 2023.

STUDY SELECTION

Two authors independently screened the studies. Included studies were randomized and nonrandomized clinical trials enrolling patients with mUC receiving ICIs with available overall survival (OS), progression-free survival (PFS), or overall response rate (ORR) data, separated between patients with PD-L1-positive and -negative tumors.

DATA EXTRACTION AND SYNTHESIS

The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed. Two reviewers independently extracted data. Fixed- or random-effects models were used depending on the heterogeneity among the studies.

MAIN OUTCOMES AND MEASURES

Primary outcomes were odds ratios (ORs) for ORR and hazard ratios (HRs) for OS, comparing patients with PD-L1-positive tumors and patients with PD-L1-negative tumors. Secondary outcomes were the PFS HR between patients with PD-L1-positive and -negative tumors and OS HR between ICI arms and non-ICI arms of only randomized clinical trials.

RESULTS

A total of 14 studies were selected, comprising 5271 patients treated with ICIs (2625 patients had PD-L1-positive tumors). The ORR was 13.8% to 78.6% in patients with PD-L1-positive tumors and 5.1% to 63.2% in patients with PD-L1-negative tumors, with an association between PD-L1 status and ORR favoring patients with PD-L1-positive tumors (OR, 1.94; 95% CI, 1.47-2.56; P < .001). Median OS ranged from 8.4 to 24.1 months in patients with PD-L1-positive tumors and from 6.0 to 19.1 months in patients with PD-L1-negative tumors. The pooled HR showed a significant reduction for patients with PD-L1-positive tumors compared with those with PD-L1-negative tumors in the risk of death (HR, 0.71; 95% CI, 0.57-0.89; P = .003) and risk of progression (HR, 0.55; 95% CI, 0.44-0.69; P < .001) when ICIs were administered. PD-L1 is not likely to be a predictive biomarker of ICI response.

CONCLUSIONS AND RELEVANCE

This systematic review and meta-analysis suggests that PD-L1 expression is associated with improved ORR, OS, and PFS for patients with mUC who receive ICIs, but it is unlikely to be useful as a predictive biomarker. Developing predictive biomarkers is essential to select patients most likely to benefit from ICIs and avoid toxic effects and financial burden with these agents.

Predictors of Efficacy of Immune Checkpoint Inhibitors in Patients With Advanced Urothelial Carcinoma: A Systematic Review and Meta-Analysis

INTRODUCTION

Several programmed death ligand-1 (PD1/L1) immune checkpoint inhibitors (ICIs) are approved in urothelial carcinoma (UC).

PATIENTS AND METHODS

To address the need for predictors of the efficacy of ICIs in metastatic urothelial carcinoma (mUC), randomized controlled trials of PD1/L1 inhibitors alone or in combination with chemotherapy in this patient population were systematically reviewed, and differences in ICI-associated survival outcomes according to available baseline variables were quantitatively assessed.

RESULTS

The quantitative analysis included 6524 patients with mUC. No visceral metastatic site (HR 0.67; 95% CI, 0.76-0.90) and high PDL-1 expression (HR 0.74; 95% CI, 0.640.87) were significantly associated with a reduced risk of death.

CONCLUSION

Treatment with an ICI-containing regimen was associated with a reduced risk of death in mUC patients, which was associated with PDL-1 expression and metastatic site. Further research is warranted.

Enfortumab vedotin in metastatic urothelial carcinoma: the solution EVentually?

Metastatic urothelial carcinoma (mUC) is an aggressive malignancy with a dismal prognosis. Enfortumab vedotin (EV) is an antibody-drug conjugate consisting of an antibody targeting Nectin-4. This protein is highly expressed in UC cells. After binding, monomethyl auristatin E is released into cells, causing UC cell death. EV has been approved as a single agent for pre-treated mUC, with interesting improvements in response rate and survival in a setting with limited treatment options. More recently, EV approval occurred in cisplatin-ineligible naïve mUC patients in combination with pembrolizumab. Our review aims to summarize the pharmacological properties, clinical studies, and future developments of EV in mUC.

Bladder cancer immunomodulatory effects of intravesical Nitazoxanide, Rapamycin, Thalidomide and Bacillus Calmette-Guérin (BCG)

PURPOSE

To understand the effect of Nitazoxanide (NTZ), Rapamycin, Thalidomide, alone and in combination with BCG on bladder cancer (BC) histopathology and programmed death-ligand 1 (PD-L1) and anti-cytotoxic T lymphocyte antigen 4 (CTLA4) expression.

METHODS

Female Fisher-344 rats underwent intravesical N-methyl-N-nitrosourea (MNU) followed by weekly intravesical treatment with saline (controls, n = 10), BCG (n = 10), NTZ (n = 8), BCG plus NTZ (n = 8), Rapamycin (n = 10) BCG plus Rapamycin (n = 10), Thalidomide (n = 10), and BCG plus Thalidomide (n = 10), and euthanized after 8 weeks and their bladders were investigated for BC and PD-L1 and CTLA4 expression.

RESULTS

Rapamicyn alone and in combination with BCG had the lowest number of bladder neoplasias in the histopathology exam (1/10). Neoplastic lesions were found in 4/10 BCG recipients, 5/10 Thalidomide recipients, 4/10 Thalidomide plus BCG recipients, 5/8 NTZ and 3/8 NTZ plus BCG recipients. Adding NTZ to BCG increased the expression of PD-L1 and adding Rapamycin or Thalidomide decreased PD-L1 and CTLA4 expression compared to BCG alone. Rapamycin alone significantly increased CTLA4 and slightly increased PD-L1 expression but its combination with BCG significantly decreased both markers. Thalidomide had a similar effect; however, it was only slightly different from the control and BCG alone groups.

CONCLUSION

Intravesical BCG combination treatment seems to effectively prevent BC development in an immunecompetent clinically relevant animal model, introducing Thalidomide, Nitazoxanide, and specially Rapamycin as candidates in the intravesical immunotherapy advancement. Our study contributes in understanding the mechanism of cancer immunotherapy.

Artificial intelligence-driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi-center integration analysis

To accurately predict the prognosis and further improve the clinical outcomes of bladder cancer (BLCA), we leveraged large-scale data to develop and validate a robust signature consisting of small gene sets. Ten machine-learning algorithms were enrolled and subsequently transformed into 76 combinations, which were further performed on eight independent cohorts (n = 1218). We ultimately determined a consensus artificial intelligence-derived gene signature (AIGS) with the best performance among 76 model types. In this model, patients with high AIGS showed a higher risk of mortality, recurrence, and disease progression. AIGS is not only independent of traditional clinical traits [(e.g., American Joint Committee on Cancer (AJCC) stage)] and molecular features (e.g., TP53 mutation) but also demonstrated superior performance to these variables. Comparisons with 58 published signatures also indicated that AIGS possessed the best performance. Additionally, the combination of AIGS and AJCC stage could achieve better performance. Patients with low AIGS scores were sensitive to immunotherapy, whereas patients with high AIGS scores might benefit from seven potential therapeutics: BRD-K45681478, 1S,3R-RSL-3, RITA, U-0126, temsirolimus, MRS-1220, and LY2784544. Additionally, some mutations (TP53 and RB1), copy number variations (7p11.2), and a methylation-driven target were characterized by AIGS-related multi-omics alterations. Overall, AIGS provides an attractive platform to optimize decision-making and surveillance protocol for individual BLCA patients.

Prognostic significance and identification of basement membrane-associated lncRNA in bladder cancer

Based on the importance of basement membrane (BM) in cancer invasion and metastasis, we constructed a BM-associated lncRNA risk model to group bladder cancer (BCa) patients. Transcriptional and clinical data of BCa patients were downloaded from The Cancer Genome Atlas (TCGA), and the expressed genes of BM-related proteins were obtained from the BM-BASE database. We download the GSE133624 chip data from the GEO database as an external validation dataset. We screened for statistically different BM genes between tumors and adjacent normal tissues. Co-expression analysis of lncRNAs and differentially expressed BM genes was performed to identify BM-related lncRNAs. Then, differentially expressed BM-related lncRNAs (DEBMlncRNAs) between tumor and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select lncRNAs for risk assessment. LASSO analysis was performed to build a prognostic model. We constructed a model containing 8 DEBMlncRNAs (AC004034.1, AL662797.1, NR2F1-AS1, SETBP1-DT, AC011503.2, AC093010.2, LINC00649 and LINC02321). The prognostic risk model accurately predicted the prognosis of BCa patients and revealed that tumor aggressiveness and distant metastasis were associated with higher risk scores. In this model, we constructed a nomogram to assist clinical decision-making based on clinicopathological characteristics such as age, T, and N. The model also showed good predictive power for the tumor microenvironment and mutational burden. We validated the expression of eight lncRNAs using the dataset GSE133624 and two human bladder cancer cell lines (5637, BIU-87) and examined the expression and cellular localization of LINC00649 and AC011503.2 using a human bladder cancer tissue chip. We found that knockdown of LINC00649 expression in 5637 cells promoted the proliferation of 5637 cells.Our eight DEBMlncRNA risk models provide new insights into predicting prognosis, tumor invasion, and metastasis in BCa patients.

The Interplay between Anti-Angiogenics and Immunotherapy in Colorectal Cancer

Simple Summary

Colorectal cancer is a frequent and lethal neoplasm. The tumor often creates new vessels to grow and spread—a process called ‘angiogenesis’. Therefore, drugs blocking angiogenesis are effective against this malignancy. On the other side, immune checkpoint inhibitors, which unleash the immune system to fight against tumors, have limited efficacy in patients carrying instability of DNA regions called microsatellites. However, there is an interaction between angiogenic factors and the immune system. This gives a chance to combine anti-angiogenic agents and immune checkpoint inhibitors to improve the efficacy of treating this malignancy.

Abstract

Angiogenesis, a hallmark of cancer, plays a fundamental role in colorectal cancer (CRC). Anti-angiogenic drugs and chemotherapy represent a standard of care for treating metastatic disease. Immune checkpoint inhibitors (ICIs) have changed the therapeutic algorithm of many solid tumors. However, the efficacy of ICIs is limited to mCRC patients carrying microsatellite instability (MSI-H), which represent approximately 3–5% of mCRC. Emerging evidence suggests that anti-angiogenic drugs could exhibit immunomodulatory properties. Thus, there is a strong rationale for combining anti-angiogenics and ICIs to improve efficacy in the metastatic setting. Our review summarizes the pre-clinical and clinical evidence regarding the combination of anti-angiogenics and ICIs in mCRC to deepen the possible application in daily clinical practice.

Immunogenic Cell Death Role in Urothelial Cancer Therapy

PURPOSE

Bladder cancer is the 13th most common cause of cancer death with the highest lifetime cost for treatment of all cancers. This scoping review clarifies the available evidence on the role of a novel therapeutic approach called immunogenic cell death (ICD) in urothelial cancer of the bladder.

METHODS

In accordance with the recommendations of the Joanna Briggs Institute, we searched MEDLINE (Ovid), EMBASE, CENTRAL databases, and supplemented with manual searches through the conferences, Google scholar, and clinicaltrials.gov for published studies up to April 2022. We included literature that studied molecular mechanisms of ICD and the role of certain danger-associated molecular patterns (DAMPs) in generating ICD, safety and efficacy of different ICD inducers, and their contributions in combination with other urothelial cancer treatments.

RESULTS

Oncolytic viruses, radiotherapy, certain chemo/chemo radiation therapy combinations, photodynamic therapy, and novel agents were studied as ICD-inducing treatment modalities in the included studies. ICD was observed in vitro (murine or human urothelial carcinoma) in ten studies, eight studies were performed on mouse models (orthotopic or subcutaneous), and five clinical trials assessed patient response to ICD inducing agents. The most common studied DAMPs were Calreticulin, HMGB1, ATP, and Heat Shock Proteins (HSP) 70 and 90, which were either expressed on the cancer cells or released.

CONCLUSION

ICD inducers were able to generate lasting antitumor immune responses with memory formation in animal studies (vaccination effect). In clinical trials these agents generally had low side effects, except for one trial, and could be used alone or in combination with other cancer treatment strategies in urothelial cancer patients.

The expression pattern of Immune checkpoints after chemo/radiotherapy in the tumor microenvironment

As a disease with the highest disease-associated burden worldwide, cancer has been the main subject of a considerable proportion of medical research in recent years, intending to find more effective therapeutic approaches with fewer side effects. Combining conventional methods with newer biologically based treatments such as immunotherapy can be a promising approach to treating different tumors. The concept of "cancer immunoediting" that occurs in the field of the tumor microenvironment (TME) is the aspect of cancer therapy that has not been at the center of attention. One group of the role players of the so-called immunoediting process are the immune checkpoint molecules that exert either co-stimulatory or co-inhibitory effects in the anti-tumor immunity of the host. It involves alterations in a wide variety of immunologic pathways. Recent studies have proven that conventional cancer therapies, such as chemotherapy, radiotherapy, or a combination of them, i.e., chemoradiotherapy, alter the "immune compartment" of the TME. The mentioned changes encompass a wide range of variations, including the changes in the density and immunologic type of the tumor-infiltrating lymphocytes (TILs) and the alterations in the expression patterns of the different immune checkpoints. These rearrangements can have either anti-tumor immunity empowering or immune attenuating sequels. Thus, recognizing the consequences of various chemo(radio)therapeutic regimens in the TME seems to be of great significance in the evolution of therapeutic approaches. Therefore, the present review intends to summarize how chemo(radio)therapy affects the TME and specifically some of the most important, well-known immune checkpoints' expressions according to the recent studies in this field.