Unresectable glioblastoma (GBM) cells in the invading tumor edge can act as seeds for recurrence. The molecular and phenotypic properties of these cells remain elusive. Here, we report that the invading edge and tumor core have two distinct types of glioma stem-like cells (GSCs) that resemble proneural (PN) and mesenchymal (MES) subtypes, respectively. Upon exposure to ionizing radiation (IR), GSCs, initially enriched for a CD133+ PN signature, transition to a CD109+ MES subtype in a C/EBP-β-dependent manner. Our gene expression analysis of paired cohorts of patients with primary and recurrent GBMs identified a CD133-to-CD109 shift in tumors with an MES recurrence. Patient-derived CD133-/CD109+ cells are highly enriched with clonogenic, tumor-initiating, and radiation-resistant properties, and silencing CD109 significantly inhibits these phenotypes. We also report a conserved regulation of YAP/TAZ pathways by CD109 that could be a therapeutic target in GBM.

We aimed to evaluate the potential of radiomics as an imaging biomarker for glioblastoma (GBM) patients and explore the molecular rationale behind radiomics using a radio-genomics approach. A total of 144 primary GBM patients were included in this study (training cohort). Using multi-parametric MR images, radiomics features were extracted from multi-habitats of the tumor. We applied Cox-LASSO algorithm to build a survival prediction model, which we validated using an independent validation cohort. GBM patients were consensus clustered to reveal inherent phenotypic subtypes. GBM patients were successfully stratified by the radiomics risk score, a weighted sum of radiomics features, corroborating the potential of radiomics as a prognostic biomarker. Using consensus clustering, we identified three distinct subtypes which significantly differed in the prognosis (“heterogenous enhancing”, “rim-enhancing necrotic”, and “cystic” subtypes). Transcriptomic traits enriched in individual subtypes were in accordance with imaging phenotypes summarized by radiomics. For example, rim-enhancing necrotic subtype was well described by radiomics profiling (T2 autocorrelation and flat shape) and highlighted by the inflammatory genomic signatures, which well correlated to its phenotypic peculiarity (necrosis). This study showed that imaging subtypes derived from radiomics successfully recapitulated the genomic underpinnings of GBMs and thereby confirmed the feasibility of radiomics as an imaging biomarker for GBM patients with comprehensible biologic annotation.

Background: Gastric cancer is among the most lethal human malignancies. Previous studies have identified molecular aberrations that constitute dynamic biological networks and genomic complexities of gastric tumors. However, the clinical translation of molecular-guided targeted therapy is hampered by challenges. Notably, solid tumors often harbor multiple genetic alterations, complicating the development of effective treatments.Methods: To address such challenges, we established a comprehensive dataset of molecularly annotated patient derivatives coupled with pharmacological profiles for 60 targeted agents to explore dynamic pharmacogenomic interactions in gastric cancers.Results: We identified lineage-specific drug sensitivities based on histopathological and molecular subclassification, including substantial sensitivities toward VEGFR and EGFR inhibition therapies in diffuse- and signet ring-type gastric tumors, respectively. We identified potential therapeutic opportunities for WNT pathway inhibitors inALK-mutant tumors, a significant association betweenPIK3CA-E542K mutation and AZD5363 response, and transcriptome expression ofRNF11as a potential predictor of response to gefitinib.Conclusions: Collectively, our results demonstrate the feasibility of drug screening combined with tumor molecular characterization to facilitate personalized therapeutic regimens for gastric tumors.

As the clinical failure of glioblastoma treatment is attributed by multiple components, including myelin-associated infiltration, assessment of the molecular mechanisms underlying such process and identification of the infiltrating cells have been the primary objectives in glioblastoma research. Here, we adopted radiogenomic analysis to screen for functionally relevant genes that orchestrate the process of glioma cell infiltration through myelin and promote glioblastoma aggressiveness. The receptor of the Nogo ligand (NgR1) was selected as the top candidate through Differentially Expressed Genes (DEG) and Gene Ontology (GO) enrichment analysis. Gain and loss of function studies on NgR1 elucidated its underlying molecular importance in suppressing myelin-associated infiltration in vitro and in vivo. The migratory ability of glioblastoma cells on myelin is reversibly modulated by NgR1 during differentiation and dedifferentiation process through deubiquitinating activity of USP1, which inhibits the degradation of ID1 to downregulate NgR1 expression. Furthermore, pimozide, a well-known antipsychotic drug, upregulates NgR1 by post-translational targeting of USP1, which sensitizes glioma stem cells to myelin inhibition and suppresses myelin-associated infiltration in vivo. In primary human glioblastoma, downregulation of NgR1 expression is associated with highly infiltrative characteristics and poor survival. Together, our findings reveal that loss of NgR1 drives myelin-associated infiltration of glioblastoma and suggest that novel therapeutic strategies aimed at reactivating expression of NgR1 will improve the clinical outcome of glioblastoma patients.

Background: Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and simultaneous activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step toward clinical application of patient-tailored treatment regimens. Results: Toward this goal, we establish a library of 139 gynecologic tumors including epithelial ovarian cancers (EOCs), cervical, endometrial tumors, and uterine sarcomas that are genomically and/or pharmacologically annotated and explore dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discover lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identify TP53 mutation as a molecular determinant that elicits therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identify transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Conclusions: Together, our results demonstrate the potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.

Cancer is a complex disease with profound genomic alterations and extensive heterogeneity. Recent studies on large-scale genomics have shed light on the impact of core oncogenic pathways, which are frequently dysregulated in a wide spectrum of cancer types. Aberrant activation of the hepatocyte growth factor (HGF) signaling axis has been associated with promoting various oncogenic programs during tumor initiation, progression, and treatment resistance. As a result, HGF-targeted therapy has emerged as an attractive therapeutic approach. However, recent clinical trials involving HGF-targeted therapies have demonstrated rather disappointing results. Thus, an alternative, in-depth assessment of new patient stratification is necessary to shift the current clinical course. To address such challenges, we have evaluated the therapeutic efficacy of YYB-101, an HGF-neutralizing antibody, in a series of primary glioblastoma stem cells (GSCs) both in vitro and in vivo. Furthermore, we performed genome and transcriptome analysis to determine genetic and molecular traits that exhibit therapeutic susceptibility to HGF-mediated therapy. We have identified several differentially expressed genes, including MET, KDR, and SOX3, which are associated with tumor invasiveness, malignancy, and unfavorable prognosis in glioblastoma patients. We also demonstrated the HGF-MET signaling axis as a key molecular determinant in GSC invasion, and we discovered that a significant association in HGF expression existed between mesenchymal phenotype and immune cell recruitment. Upregulation of MET and mesenchymal cellular state are essential in generating HGF-mediated therapeutic responses. Our results provide an important framework for evaluating HGF-targeted therapy in future clinical settings.