Tumor-infiltrating tertiary lymphoid structures (TLS) are thought to have anti-tumor activity and are believed to indicate a favorable prognosis in cancer patients. However, the prognostic value of TLS in gastrointestinal stromal tumors (GIST) is unknown. We evaluated the prognostic value of TLS using two independent GIST cohorts. Pathological examinations identified TLS in 44.9% of patients in our discovery cohort (DC). TLS was significantly associated with smaller tumor size (P = .011), relatively well morphological classification (P < .001), lower NIH classification (P < .001), lower recurrence (P = .005), longer survival time (P < .001) and lower imatinib resistance (P = .006). Kaplan-Meier curves showed that TLS was remarkably associated with favorable survival (P = .0002) and recurrence (P = .0015) time. In addition, the presence of KIT mutations and the absence of TLS suggested worst prognosis both in terms of overall survival (OS) (P = .0029) and time to recurrence (TTR) (P = .0150), while the presence of PDGFRA mutations and TLS suggested optimal prognosis for OS and TTR. Multivariate analyzes demonstrated that TLS was an independent prognostic factor for OS (HR:0.180, P = .002) and TTR (HR:0.412, P = .023). These results were confirmed using our validation cohort. Multiplexed immunohistochemistry staining was used to determine the composition of TLS. Therapies designed to target TLS may be a novel therapeutic strategy for GIST patients with imatinib resistance.

Background Treating patients with advanced sarcomas is challenging due to great histologic diversity among its subtypes. Leiomyosarcoma (LMS) and de-differentiated liposarcoma (DDLPS) are two common and aggressive subtypes of soft tissue sarcoma (STS). They differ significantly in histology and clinical behaviors. However, the molecular driving force behind the difference is unclear. Methods We collected 20 LMS and 12 DDLPS samples and performed whole exome sequencing (WES) to obtain their somatic mutation profiles. We also performed RNA-Seq to analyze the transcriptomes of 8 each of the LMS and DDLPS samples and obtained information about differential gene expression, pathway enrichment, immune cell infiltration in tumor microenvironment, and chromosomal rearrangement including gene fusions. Selected gene fusion events from the RNA-seq prediction were checked by RT-PCR in tandem with Sanger sequencing. Results We detected loss of function mutation and deletion of tumor suppressors mostly in LMS, and oncogene amplification mostly in DDLPS. A focal amplification affecting chromosome 12q13–15 region which encodes MDM2, CDK4 and HMGA2 is notable in DDLPS. Mutations in TP53, ATRX, PTEN, and RB1 are identified in LMS but not DDLPS, while mutation of HERC2 is only identified in DDLPS but not LMS. RNA-seq revealed overexpression of MDM2, CDK4 and HMGA2 in DDLPS and down-regulation of TP53 and RB1 in LMS. It also detected more fusion events in DDLPS than LMS (4.5 vs. 1, p = 0.0195), and the ones involving chromosome 12 in DDLPS stand out. RT-PCR and Sanger sequencing verified the majority of the fusion events in DDLPS but only one event in LMS selected to be tested. The tumor microenvironmental signatures are highly correlated with histologic types. DDLPS has more endothelial cells and fibroblasts content than LMS. Conclusions Our analysis revealed different recurrent genetic variations in LMS and DDLPS including simultaneous upregulation of gene expression and gene copy number amplification of MDM2 and CDK4. Up-regulation of tumor related genes is favored in DDLPS, while loss of suppressor function is favored in LMS. DDLPS harbors more frequent fusion events which can generate neoepitopes and potentially targeted by personalized immune treatment.

Circular RNAs (circRNAs) is a novel class of non-coding RNAs resulting from the non-canonical splicing of linear pre-mRNAs. However, the role of circRNAs in gastric cancer (GC) remains indistinct. This study aims to explore their potential modulation in GC and its prognostic value. We first screen for circRNA expression patterns in GC through GC and adjacent noncancerous tissues by microarray. Based on the bioinformatics analysis of the microarray data, we screened out a novel circRNA, circ-PTPDC1. Then we demonstrated that circ-PTPDC1 was up-regulated in GC cells, tissues, and serum. Its overexpression was positively correlated with age, invasion depth, advanced clinical stages, and worse survival in patients with GC. We further revealed that circ-PTPDC1 promotes the proliferation, migration, and invasion of GC cell lines via sponging miR-139-3p by regulating ELK1. Importantly, we identified that circ-PTPDC1 promotes tumor upgrowth and metabasis in vivo. Additionally, we established its prognostic prediction model based on the follow-up data of the patients. Our study revealed a novel regulatory mechanism and a comprehensive landscape of circ-PTPDC1 in GC, suggesting that circ-PTPDC1 has the potential to be a biomarker for early detection and prognostic prediction of GC.