It has been reported that the PI3K/AKT signaling pathway is activated in diffuse large B-cell lymphoma (DLBCL), PI3K constitutive activation plays a crucial role in PI3K/AKT pathway. However, the copy number variations (CNVs) of PI3K subunits on gene level remain unknown in DLBCL. Therefore, the aim of the study is to investigate the CNV of PI3K subunits and their relationship with clinicopathological features exploring the possible mechanism underlying of PI3K activation in DLBCL.

Chondroitin polymerizing factor (CHPF) is an important glycosyltransferase involved in the biosynthesis of chondroitin sulfate. However, the relationship between CHPF and gastric cancer has not been fully investigated. CHPF expression in gastric cancer tissues was detected by immunohistochemistry and correlated with gastric cancer patient prognosis. Cultured gastric cancer cells and human gastric epithelial cell line GES1 were used to investigate the effects of shCHPF and shE2F1 on the development and progression of gastric cancer by MTT, western blotting, flow cytometry analysis of cell apoptosis, colony formation, transwell and gastric cancer xenograft mouse models, in vitro and in vivo. In gastric cancer tissues, CHPF was found to be significantly upregulated, and its expression correlated with tumor infiltration and advanced tumor stage and shorter patient survival in gastric cancer. CHPF may promote gastric cancer development by regulating cell proliferation, colony formation, cell apoptosis and cell migration, while knockdown induced the opposite effects. Moreover, the results from in vivo experiments demonstrated that tumor growth was suppressed by CHPF knockdown. Additionally, E2F1 was identified as a potential downstream target of CHPF in the regulation of gastric cancer, and its knockdown decreased the CHPF-induced promotion of gastric cancer. Mechanistic study revealed that CHPF may regulate E2F1 through affecting UBE2T-mediated E2F1 ubiquitination. This study showed, for the first time, that CHPF is a potential prognostic indicator and tumor promoter in gastric cancer whose function is likely carried out through the regulation of E2F1.

Several clinical and pathological factors have an impact on the prognosis of colorectal cancer (CRC), but they are not yet adequate for risk assessment. We aimed to identify a molecular signature that can reliably identify CRC patients at high risk for recurrence. Two hundred eighty-one CRC samples (stage II/III) were included in this study. A two-step gene expression profiling study was conducted. First, gene expression measurements from 81 fresh frozen CRC samples were obtained using Affymetrix Human Genome U133 Plus 2.0 Arrays. Second, a focused gene expression assay, including prognostic genes and genes of interest from literature reviews, was performed using 200 fresh frozen samples and a Taqman low-density array (TLDA) analysis. An optimal 31-gene expression classifier for the prediction of recurrence among patients with stage II/III CRC was developed using logistic regression analysis. This gene expression signature classified 58.5% of patients as low-risk and 41.5% as high-risk (P < 0.001). The signature was the strongest independent prognostic factor in the multivariate analysis. The five-year relapse-free survival (RFS) rates for the low-risk patients and the high-risk patients were 88.5% and 41.3% (P < 0.001), respectively. We identified a 31-gene expression signature that is closely associated with the clinical outcome of stage II/III CRC patients.

Purpose: Desmoplastic small round cell tumor (DSRCT) is a rare but highly aggressive soft tissue sarcoma that arises in the abdominopelvic cavity of young males. Since the discovery of EWSR1::WT1 fusion as the driver of DSRCT, no actionable genomic alterations have been identified, limiting disease management to a combination of surgery, chemotherapy, and radiation, with very poor outcomes. Herein, we evaluated ERBB2/HER2 expression in DSRCT as a therapeutic target. Experimental Design: ERBB2/HER2 expression was assessed in clinical samples and patient-derived xenografts (PDX) using RNA sequencing, RT-qPCR, and a newly developed HER2 IHC assay (clone 29D8). Responses to HER2 antibody–drug conjugates (ADC)—trastuzumab deruxtecan (T-DXd) and trastuzumab emtansine—were evaluated in DSRCT PDX, cell line, and organoid models. Drug internalization was demonstrated by live microscopy. Apoptosis was evaluated by Western blotting and caspase activity assays. Results: ERBB2/HER2 was detectable in DSRCT samples from patients and PDXs, with higher sensitivity RNA assays and improved IHC detectability using clone 29D8. Treatment of ERBB2/HER2-expressing DSRCT PDX, cell line, and organoid models with T-DXd or trastuzumab emtansine resulted in tumor regression. This therapeutic response was long-lasting in T-DXd–treated xenografts and was mediated by rapid HER2 ADC complex internalization and cytotoxicity, triggering p53-mediated apoptosis and growth arrest. Xenograft regression was associated with bystander payload effects triggering global tumor niche responses proportional to HER2 status. Conclusions: ERBB2/HER2 is a therapeutic target in DSRCT. HER2 ADCs may represent novel options for managing this exceptionally aggressive sarcoma, possibly fulfilling an urgent and historically unmet need for more effective clinical therapy.

Background: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. Results: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune “hot” and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune “cold” phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. Conclusions: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.