The past decade has witnessed an exponential increase in research on exosomes. For many years considered to be extracellular debris, exosomes are now considered important mediators in intercellular communication. The capability of exosomes to transfer proteins, DNA, mRNA, as well as non-coding RNAs has made them an attractive focus of research into the pathogenesis of different diseases, including cancer. Increasing evidence suggests that tumor cells release a large sum of exosomes, which may not only influence proximal tumor cells and stromal cells in local microenvironment, but also can exert systemic effects when participating in blood circulation. In this study, we review the current understanding on this topic. The literature outlines two broad facets of exosomes in cancer: 1) promotion of tumor growth, tumorigenesis, tumor angiogenesis, tumor immune escape, drug resistance, and metastasis and 2) their role as promising biomarkers for cancer diagnosis and even as potential treatment targets for cancer patients.

Background Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune‐related signature of LUAD. Methods A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co‐expression network analysis (WGCNA) was applied to identify immune‐related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune‐related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA). Results In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses ( P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune‐related genes, and after univariate Cox regression analysis ( P < .005), a total of 133 genes were screened out for subsequent model constructions. A four‐gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan‐Meier survival analysis that eight out of nine patients in high‐risk groups had significantly worse prognoses in validation data sets ( P < .05). IPSLUAD outperformed other signatures in two independent cohorts. Conclusions A robust immune‐related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of lung cancer with poor prognosis. Here, we perform multi-omics analysis of 56 PSC samples, 14 of which are microdissected to analyze intratumoral heterogeneity. We report the mutational landscape of PSC. The epithelial and sarcomatoid components share numerous genomic alterations, indicating a common progenitor. We find that epithelial-mesenchymal transition (EMT) plays important roles in the carcinogenesis of PSC. The pan-cancer analysis reveals high tumor mutation burden and leukocyte fraction of PSC. Integrated molecular classification shows three subgroups with distinct biology, prognosis and potential therapeutic strategies. Actionable mutations are enriched in C1 and C2, patients in C3 have a significantly longer overall survival, and C1 and C2 exhibit T-cell inflamed microenvironments. The three subgroups show molecular similarities to specific subtypes of conventional lung cancer. In conclusion, our study reveals the molecular characteristics and provides entry points for the treatment of PSC.

Accumulated evidence has shown that the programmed cell death receptor 1/programmed cell death receptor 1 ligand 1 (PD-1/PD-L1) pathway is a promising therapeutic target for cancer immunotherapy. However, the association between PD-L1 and esophageal squamous cell carcinoma (ESCC) patient survival remains unclear. We performed a meta-analysis to investigate the prognostic value of PD-L1 in ESCC. We searched PubMed, Embase, Web of Knowledge, and Cochrane Central Register of Controlled Trials databases for relevant studies that evaluated PD-L1 expression and ESCC patient survival. Fixed- and random-effects meta-analyses were conducted according to the heterogeneity of the included studies. Sensitivity analysis was performed according to Metan-based influence analysis. Publication bias was evaluated using Egger’s and Begg’s tests. Overall, 13 studies with 2,877 patients were included. Twelve studies demonstrated the association between overall survival (OS), and 6 studies described the relation between disease-free survival (DFS). PD-L1 overexpression was found in 43.7% (1,258 of 2,877) of the patients with ESCC. High PD-L1 expression was associated with distant metastasis in patients with ESCC (P = 0.04). Moreover, high PD-L1 expression was significantly associated with poor OS (hazard ratio [HR] 1.38, 95% confidence interval [CI] = 1.02–1.86, P = 0.04) and especially in Asian populations (HR 1.49, 95% CI = 1.11–1.99, P = 0.008). But it did not have an impact on disease-free survival (HR 1.15, 95% CI = 0.76–1.74, P = 0.52). Further well-designed clinical studies with uniform assessment approaches for PD-L1 expression are warranted to verify its prognostic value.

BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most common cancer types and represents a threat to global public health. N6-Methyladenosine (m6A) methylation plays a key role in the occurrence and development of many tumors, but there are still few studies investigating ESCC. This study attempts to construct a prognostic signature of ESCC based on m6A RNA methylation regulators and to explore the potential association of these regulators with the tumor immune microenvironment (TIME).MethodsThe transcriptome sequencing data and clinical information of 20 m6A RNA methylation regulators in 453 patients with ESCC (The Cancer Genome Atlas [TCGA] cohort, n = 95; Gene Expression Omnibus [GEO] cohort, n = 358) were obtained. The differing expression levels of m6A regulators between ESCC and normal tissue were evaluated. Based on the expression of these regulators, consensus clustering was performed to investigate different ESCC clusters. PD-L1 expression, immune score, immune cell infiltration and potential mechanisms among different clusters were examined. LASSO Cox regression analysis was utilized to obtain a prognostic signature based on m6A RNA methylation modulators. The relationship between the risk score based on the prognostic signature and the TIME of ESCC patients was studied in detail.ResultsSix m6A regulators (METTL3, WTAP, IGF2BP3, YTHDF1, HNRNPA2B1 and HNRNPC) were observed to be significantly highly expressed in ESCC tissues. Two molecular subtypes (clusters 1/2) were determined by consensus clustering of 20 m6A modulators. The expression level of PD-L1 in ESCC tissues increased significantly and was significantly negatively correlated with the expression levels of YTHDF2, METL14 and KIAA1429. The immune score, CD8 T cells, resting mast cells, and regulatory T cells (Tregs) in cluster 2 were significantly increased. Gene set enrichment analysis (GSEA) shows that this cluster involves multiple hallmark pathways. We constructed a five-gene prognostic signature based on m6A RNA methylation, and the risk score based on the prognostic signature was determined to be an independent prognostic indicator of ESCC. More importantly, the prognostic value of the prognostic signature was verified using another independent cohort. m6A regulators are related to TIME, and their copy-number alterations will dynamically affect the number of tumor-infiltrating immune cells.ConclusionOur study established a strong prognostic signature based on m6A RNA methylation regulators; this signature was able to accurately predict the prognosis of ESCC patients. The m6A methylation regulator may be a key mediator of PD-L1 expression and immune cell infiltration and may strongly affect the TIME of ESCC.