Understanding the tumor microenvironment for effective immunotherapy

Prospect of bacteria for tumor diagnosis and treatment

In recent decades, the comprehensive cancer treatments including surgery, chemotherapy, and radiotherapy have improved the overall survival rate and quality of life of many cancer patients. However, we are still facing many difficult problems in the cancer treatment, such as unpredictable side effects, high recurrence rate, and poor curative effect. Therefore, the better intervention strategies are needed in this field. In recent years, the role and importance of microbiota in a variety of diseases were focused on as a hot research topic, and the role of some intracellular bacteria of cancer cells in carcinogenesis has recently been discovered. The impact of bacteria on cancer is not limited to their contribution to tumorigenesis, but the overall susceptibility of bacteria to subsequent tumor progression, the development of concurrent infections, and the response to anti-cancer therapy have also been found to be affected. Concerns about the contribution of bacteria in the anti-cancer response have inspired researchers to develop bacteria-based anti-cancer treatments. In this paper, we reviewed the main roles of bacteria in the occurrence and development of tumors, and summarized the mechanism of bacteria in the occurrence, development, and clinical anti-tumor treatment of tumors, providing new insights for the in-depth study of the role of bacteria in tumor diagnosis and treatment. This review aims to provide a new perspective for the development of new technologies based on bacteria to enhance anti-tumor immunotherapy.

Crosstalk between Tumor-Associated Macrophages and MicroRNAs: A Key Role in Tumor Microenvironment

As an in-depth understanding of immunotherapy continues to grow, current anticancer therapy research is increasingly focused on the tumor microenvironment (TME). MicroRNAs (miRNAs) play crucial roles in the regulation of genetic information and expression and mediate interactions between tumor cells and components in the TME, such as tumor-associated macrophages (macrophages). Macrophages are abundant in the TME, and their different polarization directions can promote or inhibit tumor growth and progression. By regulating biological behaviors, such as macrophage recruitment, infiltration, and polarization, miRNAs can affect various molecular pathways to regulate tumor progression and treatment response. In this review, we discuss in detail the effects of macrophages on tumors and the multifaceted effects of miRNAs on macrophages. We also discuss the potential clinical applications and prospects of targeted therapy based on miRNAs, novel clinical biomarkers, and drug delivery systems.

Development and validation of prognostic models for colon adenocarcinoma based on combined immune-and metabolism-related genes

Background

The heterogeneity of tumor tissue is one of the reasons for the poor effect of tumor treatment, which is mainly affected by the tumor immune microenvironment and metabolic reprogramming. But more research is needed to find out how the tumor microenvironment (TME) and metabolic features of colon adenocarcinoma (COAD) are related.

Methods

We obtained the transcriptomic and clinical data information of COAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering analysis was used to identify different molecular subtypes, identify differentially expressed genes (DEGs) associated with immune-and metabolism-related genes (IMRGs) prognosis. Univariate and multivariable Cox regression analysis and Lasso regression analysis were applied to construct the prognostic models based on the IMRG risk score. The correlations between risk scores and TME, immune cell infiltration, and immune checkpoint genes were investigated. Lastly, potential appropriate drugs related to the risk score were screened by drug sensitivity analysis.

Results

By consensus clustering analysis, we identified two distinct molecular subtypes. It was also found that the multilayered IMRG subtypes were associated with the patient's clinicopathological characteristics, prognosis, and TME cell infiltration characteristics. Meanwhile, a prognostic model based on the risk score of IMRGs was constructed and its predictive power was verified internally and externally. Clinicopathological analysis and nomogram give it better clinical guidance. The IMRG risk score plays a key role in immune microenvironment infiltration. Patients in the high-risk groups of microsatellite instability (MSI) and tumor mutational burden (TMB) were found to, although with poor prognosis, actively respond to immunotherapy. Furthermore, IMRG risk scores were significantly associated with immune checkpoint gene expression. The potential drug sensitivity study helps come up with and choose a chemotherapy treatment plan.

Conclusion

Our comprehensive analysis of IMRG signatures revealed a broad range of regulatory mechanisms affecting the tumor immune microenvironment (TIME), immune landscape, clinicopathological features, and prognosis. And to explore the potential drugs for immunotherapy. It will help to better understand the molecular mechanisms of COAD and provide new directions for disease treatment.

Regulation of autophagy fires up the cold tumor microenvironment to improve cancer immunotherapy

Immunotherapies, such as immune checkpoint inhibitors (ICIs) and chimeric antigen receptor (CAR) T cells, have revolutionized the treatment of patients with advanced and metastatic tumors resistant to traditional therapies. However, the immunosuppressed tumor microenvironment (TME) results in a weak response to immunotherapy. Therefore, to realize the full potential of immunotherapy and obstacle barriers, it is essential to explore how to convert cold TME to hot TME. Autophagy is a crucial cellular process that preserves cellular stability in the cellular components of the TME, contributing to the characterization of the immunosuppressive TME. Targeted autophagy ignites immunosuppressive TME by influencing antigen release, antigen presentation, antigen recognition, and immune cell trafficking, thereby enhancing the effectiveness of cancer immunotherapy and overcoming resistance to immunotherapy. In this review, we summarize the characteristics and components of TME, explore the mechanisms and functions of autophagy in the characterization and regulation of TME, and discuss autophagy-based therapies as adjuvant enhancers of immunotherapy to improve the effectiveness of immunotherapy.

Single Cell RNA-Seq Identifies Immune-Related Prognostic Model and Key Signature-SPP1 in Pancreatic Ductal Adenocarcinoma

There are no reliable biomarkers for early diagnosis or prognosis evaluation in pancreatic ductal adenocarcinoma (PDAC). Multiple scRNA-seq datasets for PDAC were retrieved from online databases and combined with scRNA-seq results from our previous study. The malignant ductal cells were identified through calculating copy number variation (CNV) scores. The robust markers of malignant ductal cells in PDAC were found. Five immune-related signatures, including SPP1, LINC00683, SNHG10, LINC00237, and CASC19, were used to develop a risk score formula to predict the overall survival of PDAC patients. We also constructed an easy-to-use nomogram, combining risk score, N stage, and margin status. The expression level of SPP1 was related to the prognosis and immune regulators. We found that SPP1 was mainly expressed in ductal cells and macrophages in PDAC. In conclusion, we constructed a promising prognostic model based on immune-related signatures for PDAC using scRNA-seq and TCGA_PAAD datasets.

Cuproptosis depicts tumor microenvironment phenotypes and predicts precision immunotherapy and prognosis in bladder carcinoma

Background

Though immune checkpoint inhibitors (ICIs) exhibit durable efficacy in bladder carcinomas (BLCAs), there are still a large portion of patients insensitive to ICIs treatment.

Methods

We systematically evaluated the cuproptosis patterns in BLCA patients based on 46 cuproptosis related genes and correlated these cuproptosis patterns with tumor microenvironment (TME) phenotypes and immunotherapy efficacies. Then, for individual patient's evaluation, we constructed a cuproptosis risk score (CRS) for prognosis and a cuproptosis signature for precise TME phenotypes and immunotherapy efficacies predicting.

Results

Two distinct cuproptosis patterns were generated. These two patterns were consistent with inflamed and noninflamed TME phenotypes and had potential role for predicting immunotherapy efficacies. We constructed a CRS for predicting individual patient's prognosis with high accuracy in TCGA-BLCA. Importantly, this CRS could be well validated in external cohorts including GSE32894 and GSE13507. Then, we developed a cuproptosis signature and found it was significantly negative correlated with tumor-infiltrating lymphocytes (TILs) both in TCGA-BLCA and Xiangya cohorts. Moreover, we revealed that patients in the high cuproptosis signature group represented a noninflamed TME phenotype on the single cell level. As expected, patients in the high cuproptosis signature group showed less sensitive to immunotherapy. Finally, we found that the high and low cuproptosis signature groups were consistent with luminal and basal subtypes of BLCA respectively, which validated the role of signature in TME in terms of molecular subtypes.

Conclusions

Cuproptosis patterns depict different TME phenotypes in BLCA. Our CRS and cuproptosis signature have potential role for predicting prognosis and immunotherapy efficacy, which might guide precise medicine.

The Immune Contexture of Liposarcoma and Its Clinical Implications

Liposarcomas (LPS) are the most frequent malignancies in the soft tissue sarcoma family and consist of five distinctive histological subtypes, termed well-differentiated LPS, dedifferentiated LPS (DDLPS), myxoid LPS (MLPS), pleomorphic LPS, and myxoid pleomorphic LPS. They display variations in genetic alterations, clinical behavior, and prognostic course. While accumulating evidence implicates a crucial role of the tumor immune contexture in shaping the response to anticancer treatments, the immunological landscape of LPS is highly variable across different subtypes. Thus, DDLPS is characterized by a higher abundance of infiltrating T cells, yet the opposite was reported for MLPS. Interestingly, a recent study indicated that the frequency of pre-existing T cells in soft tissue sarcomas has a predictive value for immune checkpoint inhibitor (CPI) therapy. Additionally, B cells and tertiary lymphoid structures were identified as potential biomarkers for the clinical outcome of LPS patients and response to CPI therapy. Furthermore, it was demonstrated that macrophages, predominantly of M2 polarization, are frequently associated with poor prognosis. An improved understanding of the complex LPS immune contexture enables the design and refinement of novel immunotherapeutic approaches. Here, we summarize recent studies focusing on the clinicopathological, genetic, and immunological determinants of LPS.

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with Wilms tumour

Wilms tumour (WT) is the most common kidney malignancy in children. Chemoresistance is the leading cause of tumour recurrence and poses a substantial therapeutic challenge. Increasing evidence has underscored the role of the tumour immune microenvironment (TIM) in cancers and the potential for immunotherapy to improve prognosis. There remain no reliable molecular markers for reflecting the immune landscape and predicting patient survival in WT. Here, we examine differences in gene expression by high-throughput RNA sequencing, focused on differentially expressed immune-related genes (IRGs) based on the ImmPort database. Via univariate Cox regression analysis and Lasso-penalized Cox regression analysis, IRGs were screened out to establish an immune signature. Kaplan-Meier curves, time-related ROC analysis, univariate and multivariate Cox regression studies, and nomograms were used to evaluate the accuracy and prognostic significance of this signature. Furthermore, we found that the immune signature could reflect the immune status and the immune cell infiltration character played in the tumour microenvironment (TME) and showed significant association with immune checkpoint molecules, suggesting that the poor outcome may be partially explained by its immunosuppressive TME. Remarkably, TIDE, a computational method to model tumour immune evasion mechanisms, showed that this signature holds great potential for predicting immunotherapy responses in the TARGET-wt cohort. To decipher the underlying mechanism, GSEA was applied to explore enriched pathways and biological processes associated with immunophenotyping and Connectivity map (CMap) along with DeSigN analysis for drug exploration. Finally, four candidate immune genes were selected, and their expression levels in WT cell lines were monitored via qRT-PCR. Meanwhile, we validated the function of a critical gene, NRP2. Taken together, we established a novel immune signature that may serve as an effective prognostic signature and predictive biomarker for immunotherapy response in WT patients. This study may give light on therapeutic strategies for WT patients from an immunological viewpoint.

Peritumor tertiary lymphoid structures are associated with infiltrating neutrophils and inferior prognosis in hepatocellular carcinoma

BACKGROUND

The positive prediction of prognosis and immunotherapy within tertiary lymphoid structure (TLS) in cancerous tissue has been well demonstrated, including liver cancer. However, the relationship between TLS and prognosis in the peritumoral region of hepatocellular carcinoma (HCC) has received less attention. Few studies on whether TLS, as a typical representative of acquired immune cell groups, is associated with innate immune cells. The aim of this paper was to identify the prognostic role of peritumor TLS in HCC and to simply explore the relationship with neutrophils infiltration.

METHODS

This study included cancerous and paracancerous tissue from 170 patients after surgical resection of HCC. TLS was examined and identified by pathological H&E examination, and the impact on prognosis was further classified by determination of total TLS area. Immunohistochemical staining of CD15+ neutrophils was also performed on half of the cases. The obtained results were validated by external public database, as TLS has been widely shown to be tagged with 12 chemokines.

RESULTS

In peritumoral tissue, the TLS- group had better overall survival (OS) and disease-free survival (DFS) outcomes compared with the TLS+ group. On the contrary, the intratumor TLS+ group showed better DFS outcomes. When further investigating the relationship between TLS area distribution and DFS, progressively worse prognosis was only found in the peritumor region with increasing TLS density (TLS- vs. TLS_L vs. TLS_H ). In addition, neutrophil infiltration increased in parallel with TLS density in the peritumoral region, which was not observed in the intratumoral region.

CONCLUSIONS

TLS might have a dual prognostic role in different regions of HCC. The abundance of peritumoral TLS is an independent influence of DFS. The inconsistent correlation between neutrophils and corresponding TLS in different regions may indicate different pathways of immune aggregation and may serve as an explanation for the different prognosis of TLS, which needs to be specifically explored.

Integrated Analysis of C16orf54 as a Potential Prognostic, Diagnostic, and Immune Marker across Pan-Cancer

Chromosome 16 open reading frame 54 (C16orf54) is a protein coding gene, showing a biased expression in the bone marrow, lymph node, and 11 other tissues. Reports on the function of C16orf54 in the onset and development of tumours remain scarce. Clinical information and tumour expression profile data from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx) were utilized to determine the relationship between C16orf54 expression and prognosis, diagnosis, immune microenvironment, heterogeneity, and stemness across pan-cancer. The findings ascertained that C16orf54 was expressed at a low level in most cancers. Furthermore, C16orf54 could distinguish between cancer and normal tissues with high accuracy in most cancers, and the prognostic significance of low C16orf54 mRNA levels differs across cancers. C16orf54 expression was positively linked to the stromal, immune, and ESTIMATE scores. On the other hand, C16orf54 was reported to be negatively correlated with tumour purity in most cancers. Further, C16orf54 expression was positively correlated with immune cell infiltration and the expression of immune regulatory genes, including chemokines, receptors, major histocompatibility complexes, immune inhibitory, and immune stimulatory genes, in most cancers. Additionally, C16orf54 expression was significantly associated with tumour heterogeneity indicators, such as tumour mutation burden (TMB) and microsatellite instability (MSI), and was significantly correlated with DNAss and RNAss tumour stemness indicators. Moreover, Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis, as well as Gene Set Enrichment analysis (GSEA), revealed that C16orf54 expression was closely linked to the signalling pathways of immune cells and factors. The integrated analysis of C16orf54 indicates it as a potential prognostic, diagnostic, and immune marker, which could be adopted as a novel target for adjuvant immunotherapy across pan-cancer.

Identification of molecular patterns and prognostic models of epithelial–mesenchymal transition- and immune-combined index in the gastric cancer

Background: Epithelial–mesenchymal transition (EMT) and the immune microenvironment play important roles in the progression of gastric cancer (GC), but the joint role of both in GC is not clear.

Methods: We identified EMT- and immune-related genes (EIRGs), and the molecular subtypes of EIRGs were identified by unsupervised cluster analysis. Then, we constructed an accurate EIRG_score model by using differential genes of molecular subtypes. The correlation of EIRG_score with prognosis, immune infiltration, gene mutation, chemotherapeutic drug sensitivity, and immunotherapy response was comprehensively analyzed. In addition, we investigated the biological function of EIRG_score via in vitro experiments.

Results: A total of 808 GC patients were classified into two molecular subtypes, which were enriched in EMT and immune-related biological pathways and significantly correlated with prognosis and immune infiltration. The constructed EIRG_score had an important role in predicting prognosis and immunotherapeutic response. The higher EIRG_score was associated with worse prognosis, higher abundance of immunosuppressive cell infiltration, lower immune checkpoint genes expression, lower tumor mutation burden, microsatellite instability-high, lower chemotherapeutic drug sensitivity, and poorer immunotherapeutic response.

Conclusion: EIRG_score may be used as a biomarker to assess prognosis and guide precise treatment.

Features of patients with advanced EGFR-mutated non-small cell lung cancer benefiting from immune checkpoint inhibitors

Background

Although immune checkpoint inhibitors (ICIs) generally show poor therapeutic efficacy in patients with epidermal growth factor receptor (EGFR) mutations, certain research indicate that a small proportion of these patients do respond to ICIs. The present study sought to identify the features of patients with EGFR mutations who might benefit from ICIs from multiple studies and discussed the optimal treatment paradigm for advanced non-small cell lung cancer (NSCLC) patients with EGFR mutations.

Methods

The profiles of 114 advanced NSCLC patients with EGFR mutations who received ICIs treatment were retrospectively reviewed. EGFR subtypes, programmed cell death ligand 1 (PD-L1) expression, and clinical characteristics regarding their impact on the efficacy of ICIs were investigated.

Results

Patients with major EGFR mutations (L858R or 19Del) had a shorter progression-free survival (PFS) and a lower objective response rate (ORR) as compared to patients with rare (20ins or G719X) and other EGFR mutations. Although not statistically significant, median overall survival (OS) tended to be longer in patients with negative (<1%) PD-L1 expression than with positive (≥1%) PD-L1 expression (15.61 vs. 7.40 months, p = 0.138). Median PFS and OS were significantly shorter in heavily treated patients (prior lines of therapy ≥3 lines vs. <3 lines: mPFS, 1.80 vs. 2.50 months, p = 0.003; mOS, 6.70 vs. 14.00 months, p = 0.031). ORR was also lower in patients who had received ≥3 prior lines of therapy compared to in those <3 prior lines of therapy (0.00% vs. 21.67%, p = 0.002).

Conclusion

Patients with major EGFR mutations showed poorer responses to ICIs than those with rare EGFR mutations. EGFR-mutated patients with lower PD-L1 expression showed a trend towards a longer OS after receiving ICIs. ICIs should be administered as early as possible to previously treated EGFR-mutated NSCLC patients. ICI-based combined therapies may be a direction for treatment of these patient subtypes in the future.

Circulating T Cell Activation and Exhaustion Markers Are Associated With Radiation Pneumonitis and Poor Survival in Non-Small-Cell Lung Cancer

Introduction

Persistent inflammation and immune activation in the lungs are associated with adverse outcomes such as radiation pneumonitis (RP) and poor survival in non-small-cell lung cancer (NSCLC) patients. However, it is unknown how this is reflected by leukocyte activation markers in serum.

Objective

The aim was to evaluate the serum levels of activation of different leukocyte subsets and to examine those in relation to the pathogenesis of RP and survival in NSCLC.

Methods

We analyzed the serum levels of MPO, sCD25, sTIM-3, sPD-L1, sCD14, sCD163, CCL19 and CCL21 in 66 inoperable NSCLC patients with stage IA-IIIA disease. The patients were treated with stereotactic body radiation therapy (SBRT) or concurrent chemoradiation therapy (CCRT), followed by regular blood sampling for 12 months after treatment and for 5 years for survival.

Results

Nineteen (29%) patients developed RP, which occurred more frequently and earlier in patients receiving CCRT than in those receiving SBRT. Increases in sCD25, sTIM-3 and CCL21 levels were observed at the last 6 months of follow-up in patients who had RP after SBRT. Patients who had RP after CCRT had higher sTIM-3 levels during the first 3 months of follow-up. Baseline sCD25 was independently associated with both 2- and 5-year mortality outcomes, while baseline sTIM-3 was independently associated with 2-year mortality.

Conclusion

We showed that T cell activation and exhaustion markers such as sCD25 and sTIM-3 are enhanced in patients developing RP and are associated with poor survival in NSCLC.

Artificial Intelligence-Assisted Score Analysis for Predicting the Expression of the Immunotherapy Biomarker PD-L1 in Lung Cancer

Programmed cell death ligand 1 (PD-L1) is a critical biomarker for predicting the response to immunotherapy. However, traditional quantitative evaluation of PD-L1 expression using immunohistochemistry staining remains challenging for pathologists. Here we developed a deep learning (DL)-based artificial intelligence (AI) model to automatically analyze the immunohistochemical expression of PD-L1 in lung cancer patients. A total of 1,288 patients with lung cancer were included in the study. The diagnostic ability of three different AI models (M1, M2, and M3) was assessed in both PD-L1 (22C3) and PD-L1 (SP263) assays. M2 and M3 showed improved performance in the evaluation of PD-L1 expression in the PD-L1 (22C3) assay, especially at 1% cutoff. Highly accurate performance in the PD-L1 (SP263) was also achieved, with accuracy and specificity of 96.4 and 96.8% in both M2 and M3, respectively. Moreover, the diagnostic results of these three AI-assisted models were highly consistent with those from the pathologist. Similar performances of M1, M2, and M3 in the 22C3 dataset were also obtained in lung adenocarcinoma and lung squamous cell carcinoma in both sampling methods. In conclusion, these results suggest that AI-assisted diagnostic models in PD-L1 expression are a promising tool for improving the efficiency of clinical pathologists.

Recent Progress in Bio-Responsive Drug Delivery Systems for Tumor Therapy

Spatially- and/or temporally-controlled drug release has always been the pursuit of drug delivery systems (DDSs) to achieve the ideal therapeutic effect. The abnormal pathophysiological characteristics of the tumor microenvironment, including acidosis, overexpression of special enzymes, hypoxia, and high levels of ROS, GSH, and ATP, offer the possibility for the design of stimulus-responsive DDSs for controlled drug release to realize more efficient drug delivery and anti-tumor activity. With the help of these stimulus signals, responsive DDSs can realize controlled drug release more precisely within the local tumor site and decrease the injected dose and systemic toxicity. This review first describes the major pathophysiological characteristics of the tumor microenvironment, and highlights the recent cutting-edge advances in DDSs responding to the tumor pathophysiological environment for cancer therapy. Finally, the challenges and future directions of bio-responsive DDSs are discussed.

Extracellular vesicle-based macromolecule delivery systems in cancer immunotherapy

Great attention has been paid to the impressive role the macromolecules played in cancer immunotherapy, however, the applications were largely limited by their poor circulation stability, low cellular uptake efficiency, and off-target effects. As an important messenger of intercellular communication, extracellular vesicles (EVs) exhibit unique advantages in macromolecule delivery compared to traditional synthetic carriers, offering new possibilities for modern drug delivery. These naturally derived carriers can achieve stable, efficient, and selective delivery of macromolecules and improve the efficacy and potentiality of macromolecular drugs in cancer immunotherapy. This review provides a brief overview of the unique features of EVs related to macromolecule delivery, the strategies and recent advances of using EVs as macromolecule delivery carriers in cancer immunotherapy.

Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration

Background

p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported.

Methods

The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER).

Results

p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma.

Conclusions

The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma.

Understanding the tumor microenvironment in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) represents a heterogeneous group of tumors. While significant progress has been made using multimodal treatment, the 5-year survival remains at 50%. Developing effective therapies, such as immunotherapy, will likely lead to better treatment of primary and metastatic disease. However, not all HNSCC tumors respond to immune checkpoint blockade therapy. Understanding the complex cellular composition and interactions of the tumor microenvironment is likely to lead to new knowledge for effective therapies and treatment resistance. In this review, we discuss HNSCC characteristics, predictive biomarkers, factors influencing immunotherapy response, with a focus on the tumor microenvironment.

The Aging-Related Prognostic Signature Reveals the Landscape of the Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background

Numerous studies have shown that the aging microenvironment played a huge impact on tumor progression. However, the clinical prognostic value of aging-related risk signatures and their effects on the tumor immune microenvironment (TIME) in head and neck squamous cell carcinoma (HNSCC) remains largely unclear. This study aimed to identify novel prognostic signatures based on aging-related genes (AGs) and reveal the landscape of the TIME in HNSCC.

Methods

Differentially expressed AGs were identified using the gene set enrichment analysis (GSEA). The prognostic risk model of AGs was established by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The independent prognostic value of the risk model and the correlations of the prognostic signature with immune score, tumor immune cell infiltration, and immune checkpoints were systematically analyzed.

Results

A prognostic risk model of four AGs (BAK1, DKK1, CDKN2A, and MIF) was constructed and validated in the training and testing datasets. Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed that the four-AG risk signature possessed an accurate predictive value for the prognosis of patients with HNSCC. Correlation analysis revealed that the risk score was negatively associated with immune score and immune cell infiltration level while positively correlated with immune checkpoint blockade (ICB) response score. Patients of the high-risk subtype contained higher infiltration levels of resting natural killer (NK) cells, M0 macrophages, M2 macrophages, and resting mast cells while having lower infiltration levels of memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells (Tregs), and activated mast cells than did those of the low-risk subtype. The expressions of CTLA4, PDCD1, and TIGIT were downregulated while the PDCD1LG2 expression was upregulated in the high-risk subtype compared to those in the low-risk subtype. Furthermore, the four selected AGs in the risk model were demonstrated to possess important functions in immune cell infiltration and ICB response of HNSCC.

Conclusions

The aging-related risk signature is a reliable prognostic model for predicting the survival of HNSCC patients and provides potential targets for improving outcomes of immunotherapy.

KIF2C is a Biomarker Correlated With Prognosis and Immunosuppressive Microenvironment in Human Tumors

Kinesin superfamily member 2C (KIF2C) is an essential regulator of the cell cycle and its aberrant expression can promote tumor progression. However, the mechanism of KIF2C in pan-cancer is unclear.Data were obtained from public databases, including The Cancer Genome Atlas (TCGA), UALCAN, TIMER and CellMiner. The data came from public databases such as The Cancer Genome Atlas (TCGA), UALCAN, TIMER, and CellMiner. We analyzed the correlation of KIF2C with expression, prognosis, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repairs (MMR), immune infiltration and anticancer drug sensitivity by R language.KIF2C was highly expressed in several tumors and correlated with poor prognosis. KIF2C expression was significantly correlated with TMB, MSI, MMRs, and immune checkpoint genes, and with the level of immune cell infiltration such as tumor-associated macrophage (TAM), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs) and Tregs. The GO and KEGG results suggest that KIF2C is involved in immune regulation in addition to cell cycle regulation.In addition, KIF2C is associated with DNA methylation, m6A modifications and m7G modifications. Our data suggest that KIF2C is a prognostic biomarker linked to immunosuppression, targeting KIF2C may improve the outcome of immunotherapy. Our findings indicate that KIF2C is a prognostic biomarker associated with immunosuppression, and that targeting KIF2C may improve the outcome of immunotherapy.

Dissecting Tissue Compartment-Specific Protein Signatures in Primary and Metastatic Oropharyngeal Squamous Cell Carcinomas

Head and neck squamous cell carcinoma (HNSCC) often presents with locoregional or distant disease, despite multimodal therapeutic approaches, which include surgical resection, chemoradiotherapy, and more recently, immunotherapy for metastatic or recurrent HNSCC. Therapies often target the primary and nodal regional HNSCC sites, and their efficacy at controlling occult distant sites remains poor. While our understanding of the tumor microenvironment conducive to effective therapies is increasing, the biology underpinning locoregional sites remains unclear. Here, we applied targeted spatial proteomic approaches to primary and lymph node metastasis from an oropharyngeal SCC (OPSCC) cohort to understand the expression of proteins within tumors, and stromal compartments of the respective sites in samples of both matched and unmatched patients. In unmatched analyses of n = 43 primary and 11 nodal metastases, our data indicated that tumor cells in nodal metastases had higher levels of Ki-67, PARP, BAD, and cleaved caspase 9, suggesting a role for increased proliferation, DNA repair, and apoptosis within these metastatic cells. Conversely, in matched analyses (n = 7), pro-apoptotic markers BIM and BAD were enriched in the stroma of primary tumors. Univariate, overall survival (OS) analysis indicated CD25 in tumor regions of primary tumors to be associated with reduced survival (HR = 3.3, p = 0.003), while progesterone receptor (PR) was associated with an improved OS (HR = 0.33, p = 0.015). This study highlights the utility of spatial proteomics for delineating the tumor and stromal compartment composition, and utility toward understanding these properties in locoregional metastasis. These findings indicate unique biological properties of lymph node metastases that may elucidate further understanding of distant metastatic in OPSCC.

Non-Coding RNAs Implicated in the Tumor Microenvironment of Colorectal Cancer: Roles, Mechanisms and Clinical Study

Colorectal cancer (CRC) is one of the most common malignant tumors. The morbidity and mortality rates have been increasing all over the world. It is critical to elucidate the mechanism of CRC occurrence and development. However, tumor microenvironment (TME) includes immune cells, fibroblasts, endothelial cells, cytokines, chemokines and other components that affect the progression of CRC and patients' prognosis. Non-coding RNAs (ncRNAs) including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) without protein-coding ability have been shown to engage in tumor microenvironment-mediated angiogenesis and metastasis. Therefore, clarifying the mechanism of ncRNAs regulating the microenvironment is very important to develop the therapeutic target of CRC and improve the survival time of patients. This review focuses on the role and mechanism of ncRNAs in the CRC microenvironment and puts forward possible clinical treatment strategies.

AFF3 is a novel prognostic biomarker and a potential target for immunotherapy in gastric cancer

Background

Gastric cancer (GC) is one of the most common cancers worldwide with a poor prognosis. The tumor microenvironment (TME) serves a pivotal role in affecting the prognosis and efficacy of immunotherapy. Given the poor prognosis of GC patients and the limitation of immunotherapy, we urged to identify new prognostic and immunotherapeutic biomarkers.

Methods

The transcriptome data were downloaded from the TCGA, GEO, and GEPIA databases, and performed differential analysis of AFF3 in tumor samples and normal samples. The UALCAN, Kaplan–Meier plotter and GEPIA databases were employed to assess the correlation of AFF3 with clinicopathological characteristics and prognosis. The potential mechanism of AFF3 was explored by the GO and KEGG enrichment. The potential role of AFF3 on tumor‐infiltrating immune cells (TIICs) was explored by TIMER2.0 and TISIDB. TIMER2.0 and SangerBox3.0 databases were, respectively, used to determine the correlation of AFF3 with immune checkpoint (ICs), tumor mutational burden (TMB), and microsatellite instability (MSI) in GC.

Results

We found significant downregulation of AFF3 in GC tissues as compared with normal tissues. However, GC patients having a higher expression of AFF3 were found to have worse clinicopathological characteristics and prognosis. Moreover, the GO enrichment analysis illustrated that AFF3 might regulate the immune cells in the TME. In addition, the AFF3 was positively correlated with TIICs, ICs, TMB, and MSI.

Conclusion

Here, we conclude that AFF3 may be a promising potential marker for the diagnosis and prognosis of GC patients, and may influence response to ICIs by affecting TIICs and ICs expression in the TME.

Immune Checkpoint Inhibitors in Cancer Therapy

The discovery of immune checkpoint proteins such as PD-1/PDL-1 and CTLA-4 represents a significant breakthrough in the field of cancer immunotherapy. Therefore, humanized monoclonal antibodies, targeting these immune checkpoint proteins have been utilized successfully in patients with metastatic melanoma, renal cell carcinoma, head and neck cancers and non-small lung cancer. The US FDA has successfully approved three different categories of immune checkpoint inhibitors (ICIs) such as PD-1 inhibitors (Nivolumab, Pembrolizumab, and Cemiplimab), PDL-1 inhibitors (Atezolimumab, Durvalumab and Avelumab), and CTLA-4 inhibitor (Ipilimumab). Unfortunately, not all patients respond favourably to these drugs, highlighting the role of biomarkers such as Tumour mutation burden (TMB), PDL-1 expression, microbiome, hypoxia, interferon-γ, and ECM in predicting responses to ICIs-based immunotherapy. The current study aims to review the literature and updates on ICIs in cancer therapy.

Essential m6A Methylation Regulator HNRNPC Serves as a Targetable Biomarker for Papillary Renal Cell Carcinoma

m6A RNA modification is a common abundant posttranscriptional modification of mRNAs occurring in cancer growth and progression. Accumulated evidence has proved that HNRNPC, which acts as a m6A reader, plays an essential role in the promotion of cancer occurrence and development; nevertheless, the role of HNRNPC in papillary renal cell carcinoma remained to be discovered. In this study, we comprehensively identified HNRNPC as a hub gene involved in m6A modification in pRCC. Then, the expression level, survival outcomes, PPI network, function enrichment, immune cell infiltration, and single-cell analysis were performed. Finally, we found that HNRNPC significantly promoted renal cell carcinoma proliferation and migration in vitro. In conclusion, our work proved that HNRNPC may act as a momentous m6A regulator, as well as a potential targetable biomarker for pRCC.

Carrier-Free Nanomedicine for Cancer Immunotherapy

With the rapid development of nanotechnology, carrier-based nano-drug delivery systems (DDSs) have been widely studied due to their advantages in optimizing pharmacokinetic and distribution profiles. However, despite those merits, some carrier-related limitations, such as low drug-loading capacity, systematic toxicity and unclear metabolism, usually prevent their further clinical transformation. Carrier-free nanomedicines with non-therapeutic excipients, are considered as an excellent paradigm to overcome these obstacles, owing to their superiority in improving both drug delivery efficacy and safety concern. In recent years, carrier-free nanomedicines have opened new horizons for cancer immunotherapy, and have already made outstanding progress. Herein, in this review, we are focusing on making an integrated and exhaustive overview of lately reports about them. Firstly, the major synthetic strategies of carrier-free nanomedicines are introduced, such as nanocrystals, prodrug-, amphiphilic drug-drug conjugates (ADDCs)-, polymer-drug conjugates-, and peptide-drug conjugates (PepDCs)-assembled nanomedicines. Afterwards, the typical applications of carrier-free nanomedicines in cancer immunotherapy are well-discussed, including cancer vaccines, cytokine therapy, enhancing T-cell checkpoint inhibition, as well as modulating tumor microenvironment (TME). After that, both the advantages and the potential challenges, as well as the future prospects of carrier-free nanomedicines in cancer immunotherapy, were discussed. And we believe that it would be of great potential practiced and reference value to the relative fields.

Navigate Towards the Immunotherapy Era: Value of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer Patients With Brain Metastases

Brain metastases (BMs) in non-small-cell lung cancer (NSCLC) patients are associated with significant morbidity and poor prognosis. Immune checkpoint inhibitors (ICIs) have resulted in a paradigm shift in the management of advanced NSCLC. However, the value of ICIs in NSCLC patients with BMs remains unclear because patients with BMs are routinely excluded in numerous prospective trials on ICIs. Here, starting from the mechanisms of ICIs for BMs, we will reveal the value of ICIs by reviewing the efficacy and adverse effects of ICIs monotherapy as well as promising combination strategies, such as combinations with chemotherapy, radiotherapy, and anti-angiogenic drugs, etc. In addition, the methods of patient selection and response assessment will be summarized to assist clinical practice and further studies.

Single-Cell Profiling Reveals Heterogeneity of Primary and Lymph Node Metastatic Tumors and Immune Cell Populations and Discovers Important Prognostic Significance of CCDC43 in Oral Squamous Cell Carcinoma

Although substantial progress has been made in biological research and clinical treatment in recent years, the clinical prognosis of oral squamous cell carcinoma (OSCC) is still not satisfactory. Tumor immune microenvironment (TIME) is a potential target, which plays an essential role in the response of anti-tumor immunity and immunotherapy. In this study, we used scRNA-seq data, revealing the heterogeneity of TIME between metastatic and primary site. We found that in the metastatic site, the content of cytotoxic T cells and classical activated macrophages (M1 macrophages) increases significantly, while alternately activated macrophages (M2 macrophages) and inflammatory cancer-associated fibroblasts (iCAFs) decrease, which may be due to the increased immunogenicity of OSCC cells in the metastatic site and the changes in some signal pathways. We also found that iCAFs may recruit alternately activated macrophages (M2 macrophages) by secreting CXCL12. Then, we described a regulatory network for communication between various TIME cells centered on OSCC cells, which can help to clarify the possible mechanism of lymph node metastasis in OSCC cells. By performing pseudotime trajectory analysis, we found that the expression CCDC43 is upregulated in more advanced OSCC cells and is an independent prognostic factor for poor living conditions. Other than this, the high expression of CCDC43 may impair the antitumor immunity of the human body and promote the metastasis of OSCC cells. Our research provides a profound insight into the immunological study of OSCC and an essential resource for future drug discovery.

Nano-immunotherapeutics: targeting approach as strategic regulation at tumor microenvironment for cancer treatment

Cancer is the leading cause of mortality worldwide, which necessitates our consideration related to novel treatment approach. Tumor cells at the tumor microenvironment (TME), regulate a plethora of key mechanistic signaling pathways that obstruct antitumor immune responses by immune suppression, immune resistance or acquired immune tolerance. The present therapeutic regimes are provided independently or in combination, or as immunotherapies for cancer immune targeting. Immunotherapy has altered the arena of oncology and patient care. By using the host immune system, the immunostimulatory molecules can exert a robust, personalized response against the patient’s own tumors. Alternatively, tumors may exploit these strategies to escape immune recognition, and accordingly, such mechanisms represent chances for immunotherapy intervention. Nonetheless, despite promising outcomes from immunotherapies in recurrent and metastatic cancers, immune-therapeutics in clinics has been limited owing to unpredictability in the produced immune response and reported instances of immune-related adverse effects. The unrealized potential of immunotherapies in cancer management maybe due to the obstacles such as heterogeneous nature, multiple targets, patients’ immune response, specificity for cancer or variability in response generation in toxicity levels, delivery and cost related to therapeutics etc. Further revolutionary trends related to immunotherapies are noticeable with slower progress for cancer management. Recent advances in nanomedicine strategize to ameliorate the lacuna of immunotherapy as it relies on the inherent biophysical characteristics of nanocarriers: size, shape, surface charge and multifunctionality and exploiting them as first line therapy for delivery of biomolecules, single checkpoint inhibitors and for imaging of TME. Therefore, nano-assisted immunotherapies can boost the immunotherapeutic approach, overcoming factors that are with imminent potential risks related to it, thereby significantly improving the survival rate associated with it in cancer patients. Nanotechnology is anticipated to overcome the confines of existing cancer immunotherapy and to successfully combine various cancer treatment modes.

Nanomedicine Strategies for Management of Drug Resistance in Lung Cancer

Lung cancer (LC) is one of the leading causes of cancer occurrence and mortality worldwide. Treatment of patients with advanced and metastatic LC presents a significant challenge, as malignant cells use different mechanisms to resist chemotherapy. Drug resistance (DR) is a complex process that occurs due to a variety of genetic and acquired factors. Identifying the mechanisms underlying DR in LC patients and possible therapeutic alternatives for more efficient therapy is a central goal of LC research. Advances in nanotechnology resulted in the development of targeted and multifunctional nanoscale drug constructs. The possible modulation of the components of nanomedicine, their surface functionalization, and the encapsulation of various active therapeutics provide promising tools to bypass crucial biological barriers. These attributes enhance the delivery of multiple therapeutic agents directly to the tumor microenvironment (TME), resulting in reversal of LC resistance to anticancer treatment. This review provides a broad framework for understanding the different molecular mechanisms of DR in lung cancer, presents novel nanomedicine therapeutics aimed at improving the efficacy of treatment of various forms of resistant LC; outlines current challenges in using nanotechnology for reversing DR; and discusses the future directions for the clinical application of nanomedicine in the management of LC resistance.

The Role of Circulating Biomarkers in Lung Cancer

Lung cancer is the leading cause of cancer morbidity and mortality worldwide and early diagnosis is crucial for the management and treatment of this disease. Non-invasive means of determining tumour information is an appealing diagnostic approach for lung cancers as often accessing and removing tumour tissue can be a limiting factor. In recent years, liquid biopsies have been developed to explore potential circulating tumour biomarkers which are considered reliable surrogates for understanding tumour biology in a non-invasive manner. Most common components assessed in liquid biopsy include circulating tumour cells (CTCs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), microRNA and exosomes. This review explores the clinical use of circulating tumour biomarkers found in liquid biopsy for screening, early diagnosis and prognostication of lung cancer patients.

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

Background

Clear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.

Methods

The gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan–Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs.

Results

Four immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9, and IL6. Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs.

Conclusion

A total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.

Identification of hepatocellular carcinoma-related genes associated with macrophage differentiation based on bioinformatics analyses

Macrophage differentiation is associated with tumorigenesis, including the tumorigenesis of hepatocellular carcinoma (HCC). Herein, we explored the value of macrophage differentiation-associated genes (MDGs) in the prognosis of HCC using data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We performed multivariate Cox regression analyses to identify the hub genes affecting HCC patient prognoses. The correlations between hub genes and macrophage differentiation and immune checkpoint inhibitors (PD-1, PD-L1, and CTLA4) were investigated. Finally, the potential mechanism was examined with gene set enrichment analysis (GSEA). In total, seventeen differentially expressed MDGs were obtained after intersecting data from the two databases. Multivariate analysis indicated that CDC42 expression was an independent prognostic indicator in both databases. Furthermore, CDC42 showed a strong correlation with the tumor infiltration levels of immune cells in HCC tissue. Correlation analysis revealed that CDC42 expression was positively associated with M2 macrophage markers and immune checkpoint inhibitors, which indicated that CDC42 expression might be related to M2 macrophage differentiation and HCC cell immune tolerance. Finally, GSEA showed that CDC42 expression was most significantly related to the Wnt signaling pathway. In conclusion, this study showed that CDC42 expression might be an important MDG in HCC and may prove to be a new gene for studying macrophage differentiation in HCC. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; ICGC: International Cancer Genome Consortium; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; TNM: Tumor size/lymph nodes/distance metastasis.

Targeting of the tumor microenvironment by curcumin

The tumor microenvironment (TME) is made up of several cells and molecules that affect the survival of cancer cells. Indeed, certain (immunosuppressive) cells which promote tumors can promote the growth of tumors by stimulating the proliferation of cancer cells and promoting angiogenesis. During tumor growth, antitumoral immunity includes natural killer cells and CD8+ T cells cannot overcome immunosuppressive responses and cancer cell proliferation. In order to achieve the appropriate therapeutic response, we must kill cancer cells and suppress the release of immunosuppressive molecules. The balance between anti-tumor immunity and immunosuppressive cells, such as regulatory T cells (Tregs), cancer-associated fibroblasts, tumor-associated macrophages, and myeloid-derived suppressor cells plays a key role in the suppression or promotion of cancer cells. Curcumin is a plant-derived agent that has shown interesting properties for cancer therapy. It has shown that not only directly inhibit the growth of cancer cells, but can also modulate the growth and activity of immunosuppressant and tumor-promoting cells. In this review, we explain how curcumin modulates interactions within TME in favor of tumor treatment. The potential modulating effects of curcumin on the responses of cancer cells to treatment modalities such as immunotherapy will also be discussed.

Identifying immune subtypes of uterine corpus endometrial carcinoma and a four-paired-lncRNA signature with immune-related lncRNAs

Uterine corpus endometrial carcinoma (UCEC) is the third most frequent gynecological malignancies in the female reproductive system. Long non-coding RNAs (lncRNAs) are closely involved in tumor progression. This study aimed to develop an immune subtyping system and a prognostic model based on lncRNAs for UCEC. Paired lncRNAs and non-negative matrix factorization were applied to identify immune subtypes. Enrichment analysis was conducted to assess functional pathways, immune-related genes, and cells. Univariate and multivariate Cox regression analysis were performed to analyze the relation between lncRNAs and overall survival (OS). A prognostic model was constructed and optimized by least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). Two immune subtypes (C1 and C2) and four paired-prognostic lncRNAs closely associated with overall survival were identified. Some immune features, sensitivity of chemotherapy and immunotherapy, and the relation with immune escape showed variations between two subtypes. A nomogram established based on prognostic model and clinical features was effective in OS prediction. The immune subtyping system based on lncRNAs and the four-paired-lncRNA signature was predictive of UCEC prognosis and can facilitate personalized therapies such as immunotherapy or RNA-based therapy for UCEC patients.

Unexpected Favorable Outcome to PD-1 Antibody Plus Lenvatinib in a Patient With Recurrent Intestinal Follicular Dendritic Cell Sarcoma: A Case Report and Literature Review

Background

Follicular dendritic cell sarcoma (FDCS) is an uncommon malignant cancer, and there is no standard treatment to date. Resection followed by adjuvant chemotherapy or radiation is considered the most commonly used strategy for treatment. However, the treatment for patients who have progressed after systemic treatment is more controversial.

Case summary

In this case report, we describe a 57-year-old man with primary small intestine FDCS where surgery and second-line systemic chemotherapy failed. After disease progression (PD), the patient received sintilimab plus lenvatinib as third-line treatment and achieved a progression-free survival (PFS) with 7 months.

Conclusion

This is the first report of a FDCS patient treated with immune checkpoint inhibitors (ICIs) and antiangiogenic agents, sintilimab and lenvatinib, as third-line therapy. Our case provides a potential therapeutic option for patients with FDCS who progressed after multiline therapy.

A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma

BACKGROUND

Glioblastoma is the most aggressive type of brain cancer with high-levels of intra- and inter-tumour heterogeneity that contribute to its rapid growth and invasion within the brain. However, a spatial characterisation of gene signatures and the cell types expressing these in different tumour locations is still lacking.

METHODS

We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions including leading edge (LE), infiltrating tumour (IT), cellular tumour (CT), cellular tumour microvascular proliferation (CTmvp), cellular tumour pseudopalisading region around necrosis (CTpan), cellular tumour perinecrotic zones (CTpnz) and cellular tumour necrosis (CTne) in digitised glioblastoma histopathological slides from The Cancer Genome Atlas (TCGA). Correlation analysis between segmentation results from tumour images together with matched RNA expression data was performed to identify genetic signatures that are specific to different tumour regions.

RESULTS

We found that spatially resolved gene signatures were strongly correlated with survival in patients with defined genetic mutations. Further in silico cell ontology analysis along with single-cell RNA sequencing data from resected glioblastoma tissue samples showed that these tumour regions had different gene signatures, whose expression was driven by different cell types in the regional tumour microenvironment. Our results further pointed to a key role for interactions between microglia/pericytes/monocytes and tumour cells that occur in the IT and CTmvp regions, which may contribute to poor patient survival.

CONCLUSIONS

This work identified key histopathological features that correlate with patient survival and detected spatially associated genetic signatures that contribute to tumour-stroma interactions and which should be investigated as new targets in glioblastoma. The source codes and datasets used are available in GitHub: https://github.com/amin20/GBM_WSSM .

Emerging role of circulating tumor cells in immunotherapy

Over the last few years, immunotherapy, in particular, immune checkpoint inhibitor therapy, has revolutionized the treatment of several types of cancer. At the same time, the uptake in clinical oncology has been slow owing to the high cost of treatment, associated toxicity profiles and variability of the response to treatment between patients. In response, personalized approaches based on predictive biomarkers have emerged as new tools for patient stratification to achieve effective immunotherapy. Recently, the enumeration and molecular analysis of circulating tumor cells (CTCs) have been highlighted as prognostic biomarkers for the management of cancer patients during chemotherapy and for targeted therapy in a personalized manner. The expression of immune checkpoints on CTCs has been reported in a number of solid tumor types and has provided new insight into cancer immunotherapy management. In this review, we discuss recent advances in the identification of immune checkpoints using CTCs and shed light on the potential applications of CTCs towards the identification of predictive biomarkers for immunotherapy.

Research advances on the immune research and prospect of immunotherapy in pituitary adenomas

Background

Pituitary adenomas are one type of intracranial tumor, which can be divided into microadenoma (≤ 1 cm), macroadenoma (> 1 cm), and giant adenoma (≥ 4 cm) according to their diametral sizes. They are benign, typically slow-progressing, whereas the biological behavior of some of them is invasive, which presents a major clinical challenge. Treatment of some pituitary adenomas is still difficult due to drug resistance or multiple relapses, usually after surgery, medication, and radiation. At present, no clear prediction and treatment biomarkers have been found in pituitary adenomas and some of them do not cause clinical symptoms, so patients are often found to be ill through physical examination, and some are even found through autopsy. With the development of research on pituitary adenomas, the immune response has become a hot spot and may serve as a novel disease marker and therapeutic target.

The distribution and function of immune cells and their secreted molecules in pituitary adenomas are extremely complex. Researchers found that infiltration of immune cells may have a positive effect on the treatment and prognosis of pituitary adenomas. In this review, we summarized the advance of tumor immunity in pituitary adenomas, revealing the immunity molecules as potential biomarkers as well as therapeutic agents for pituitary adenomas.

Conclusion

The immune studies related to pituitary adenomas may help us find relevant immune markers. At the same time, the exploration of immunotherapy also provides new options for the treatment of pituitary adenomas.

Understanding the tumor microenvironment for effective immunotherapy

Advances in immunotherapy have led to durable and long-term benefits in a subset of patients across a number of solid tumor types. Understanding of the subsets of patients that respond to immune checkpoint inhibitors at the cellular level, and in the context of their tumor microenvironment (TME) is becoming increasingly important. The TME is composed of a heterogeneous milieu of tumor and immune cells. The immune landscape of the TME can inhibit or promote tumor initiation and progression; thus, a deeper understanding of tumor immunity is necessary to develop immunotherapeutic strategies. Recent developments have focused on characterizing the TME immune contexture (type, density, and function) to discover mechanisms and biomarkers that may predict treatment outcomes. This has, in part, been powered by advancements in spatial characterization technologies. In this review article, we address the role of specific immune cells within the TME at various stages of tumor progression and how the immune contexture determinants affecting tumor growth are used therapeutically.

Spatial profiling technologies and applications for brain cancers

INTRODUCTION

Malignant primary and secondary brain tumors pose a major health challenge, and the incidence of these tumors is rising. The brain tumor microenvironment (TME) is highly complex and thought to impact treatment resistance and failure. To enable a greater understanding of the milieu of cells in the brain TME, advances in imaging and sequential profiling of proteins/mRNA have given rise to the field of spatial transcriptomics. These technologies provide a greater depth of understanding of the tissue architecture, cellular and spatial profiles, including cellular activation status, which may provide insights into effective therapies for brain cancers.

AREAS COVERED

In this review, we provide an overview of spatial profiling technologies at the forefront in the field and describe the applications for brain cancer.

EXPERT OPINION

Brain tumors are often resistant to treatment, and display both an immunosuppressive and heterogeneous tumor microenvironment. Next-generation imaging and multi-omics technologies are providing a tool for intricately characterizing their tissue biology. This information will aid in the design of effective therapies and begin to provide an understanding of therapy resistance.