Sleeping Beauty transposon mutagenesis identified genes and pathways involved in inflammation-associated colon tumor development.

Chronic inflammation promotes development and progression of colorectal cancer (CRC). To comprehensively understand the molecular mechanisms underlying the development and progression of inflamed CRC, we perform in vivo screening and identify 142 genes that are frequently mutated in inflammation-associated colon tumors. These genes include senescence and TGFß-activin signaling genes. We find that TNFα can induce stemness and activate senescence signaling by enhancing cell plasticity in colonic epithelial cells, which could act as a selective pressure to mutate senescence-related genes in inflammation-associated colonic tumors. Furthermore, we show the efficacy of the Cdk4/6 inhibitor in vivo for inflammation-associated colonic tumors. Finally, we functionally validate that Arhgap5 and Mecom are tumor suppressor genes, providing possible therapeutic targets for CRC. Thus, we demonstrate the importance of the inactivation of senescence pathways in CRC development and progression in an inflammatory microenvironment, which can help progress toward precision medicine.

Bevacizumab beyond Progression for Newly Diagnosed Glioblastoma (BIOMARK): Phase II Safety, Efficacy and Biomarker Study.

We evaluated the efficacy and safety of bevacizumab beyond progression (BBP) in Japanese patients with newly diagnosed glioblastoma and explored predictors of response to bevacizumab. This phase II study evaluated a protocol-defined primary therapy by radiotherapy with concurrent and adjuvant temozolomide plus bevacizumab, followed by bevacizumab monotherapy, and secondary therapy (BBP: bevacizumab upon progression). Ninety patients received the protocol-defined primary therapy (BBP group, n = 25). Median overall survival (mOS) and median progression-free survival (mPFS) were 25.0 and 14.9 months, respectively. In the BBP group, in which O6-methylguanine-DNA methyltransferase (MGMT)-unmethylated tumors predominated, mOS and mPFS were 5.8 and 1.9 months from BBP initiation and 16.8 and 11.4 months from the initial diagnosis, respectively. The primary endpoint, the 2-year survival rate of the BBP group, was 27.0% and was unmet. No unexpected adverse events occurred. Expression profiling using RNA sequencing identified that Cluster 2, which was enriched with the genes involved in macrophage or microglia activation, was associated with longer OS and PFS independent of the MGMT methylation status. Cluster 2 was identified as a significantly favorable independent predictor for PFS, along with younger age and methylated MGMT. The novel expression classifier may predict the prognosis of glioblastoma patients treated with bevacizumab.

Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model.

BACKGROUND: Intra-tumor heterogeneity (ITH) encompasses cellular differences in tumors and is related to clinical outcomes such as drug resistance. However, little is known about the dynamics of ITH, owing to the lack of time-series analysis at the single-cell level. Mouse models that recapitulate cancer development are useful for controlled serial time sampling. RESULTS: We performed single-cell exome and transcriptome sequencing of 200 cells to investigate how ITH is generated in a mouse colorectal cancer model. In the model, a single normal intestinal cell is grown into organoids that mimic the intestinal crypt structure. Upon RNAi-mediated downregulation of a tumor suppressor gene APC, the transduced organoids were serially transplanted into mice to allow exposure to in vivo microenvironments, which play relevant roles in cancer development. The ITH of the transcriptome increased after the transplantation, while that of the exome decreased. Mutations generated during organoid culture did not greatly change at the bulk-cell level upon the transplantation. The RNA ITH increase was due to the emergence of new transcriptional subpopulations. In contrast to the initial cells expressing mesenchymal-marker genes, new subpopulations repressed these genes after the transplantation. Analyses of colorectal cancer data from The Cancer Genome Atlas revealed a high proportion of metastatic cases in human subjects with expression patterns similar to the new cell subpopulations in mouse. These results suggest that the birth of transcriptional subpopulations may be a key for adaptation to drastic micro-environmental changes when cancer cells have sufficient genetic alterations at later tumor stages. CONCLUSIONS: This study revealed an evolutionary dynamics of single-cell RNA and DNA heterogeneity in tumor progression, giving insights into the mesenchymal-epithelial transformation of tumor cells at metastasis in colorectal cancer.

Slow-Cycling Cancer Stem Cells Regulate Progression and Chemoresistance in Colon Cancer.

Cancer chemoresistance is often attributed to the presence of cancer stem cell (CSC)-like cells, but whether they are homogeneously chemoresistant remains unclear. We previously showed that in colon tumors, a subpopulation of LGR5+ CSC-like cells driven by TCF1 (TCF7), a Wnt-responsive transcription factor, were responsible for tumorigenicity. Here we demonstrate that the tumorigenic subpopulation of mouse LGR5+ cells exists in a slow-cycling state and identify a unique 22-gene signature that characterizes these slow-cycling CSC. Seven of the signature genes are specifically expressed in slow-cycling LGR5+ cells from xenografted human colon tumors and are upregulated in colon cancer clinical specimens. Among these seven, four genes (APCDD1, NOTUM, PROX1, and SP5) are known to be direct Wnt target genes, and PROX1 was expressed in the invasive fronts of colon tumors. PROX1 was activated by TCF1 to induce CDKN1C and maintain a slow-cycling state in colon cancer organoids. Strikingly, PROX1 was required for recurrent growth after chemotherapeutic treatment, suggesting that inhibition of slow-cycling CSC by targeting the TCF1-PROX1-CDKN1C pathway is an effective strategy to combat refractory colon cancer in combination with conventional chemotherapy. SIGNIFICANCE: These findings illustrate the importance of a slow-cycling CSC subpopulation in colon cancer development and chemoresistance, with potential implications for the identified slow-cycling CSC signatures and the TCF1-PROX1-CDKN1C pathway as therapeutic targets.

Feasibility and utility of a panel testing for 114 cancer-associated genes in a clinical setting: A hospital-based study.

Next-generation sequencing (NGS) of tumor tissue (ie, clinical sequencing) can guide clinical management by providing information about actionable gene aberrations that have diagnostic and therapeutic significance. Here, we undertook a hospital-based prospective study (TOP-GEAR project, 2nd stage) to investigate the feasibility and utility of NGS-based analysis of 114 cancer-associated genes (the NCC Oncopanel test). We examined 230 cases (comprising more than 30 tumor types) of advanced solid tumors, all of which were matched with nontumor samples. Gene profiling data were obtained for 187 cases (81.3%), 111 (59.4%) of which harbored actionable gene aberrations according to the Clinical Practice Guidelines for Next Generation Sequencing in Cancer Diagnosis and Treatment (Edition 1.0) issued by 3 major Japanese cancer-related societies. Twenty-five (13.3%) cases have since received molecular-targeted therapy according to their gene aberrations. These results indicate the utility of tumor-profiling multiplex gene panel testing in a clinical setting in Japan. This study is registered with UMIN Clinical Trials Registry (UMIN 000011141).

Significance of molecular classification of ependymomas: C11orf95-RELA fusion-negative supratentorial ependymomas are a heterogeneous group of tumors.

Extensive molecular analyses of ependymal tumors have revealed that supratentorial and posterior fossa ependymomas have distinct molecular profiles and are likely to be different diseases. The presence of C11orf95-RELA fusion genes in a subset of supratentorial ependymomas (ST-EPN) indicated the existence of molecular subgroups. However, the pathogenesis of RELA fusion-negative ependymomas remains elusive. To investigate the molecular pathogenesis of these tumors and validate the molecular classification of ependymal tumors, we conducted thorough molecular analyses of 113 locally diagnosed ependymal tumors from 107 patients in the Japan Pediatric Molecular Neuro-Oncology Group. All tumors were histopathologically reviewed and 12 tumors were re-classified as non-ependymomas. A combination of RT-PCR, FISH, and RNA sequencing identified RELA fusion in 19 of 29 histologically verified ST-EPN cases, whereas another case was diagnosed as ependymoma RELA fusion-positive via the methylation classifier (68.9%). Among the 9 RELA fusion-negative ST-EPN cases, either the YAP1 fusion, BCOR tandem duplication, EP300-BCORL1 fusion, or FOXO1-STK24 fusion was detected in single cases. Methylation classification did not identify a consistent molecular class within this group. Genome-wide methylation profiling successfully sub-classified posterior fossa ependymoma (PF-EPN) into PF-EPN-A (PFA) and PF-EPN-B (PFB). A multivariate analysis using Cox regression confirmed that PFA was the sole molecular marker which was independently associated with patient survival. A clinically applicable pyrosequencing assay was developed to determine the PFB subgroup with 100% specificity using the methylation status of 3 genes, CRIP1, DRD4 and LBX2. Our results emphasized the significance of molecular classification in the diagnosis of ependymomas. RELA fusion-negative ST-EPN appear to be a heterogeneous group of tumors that do not fall into any of the existing molecular subgroups and are unlikely to form a single category.

Sweepstake evolution revealed by population-genetic analysis of copy-number alterations in single genomes of breast cancer.

Single-cell sequencing is a promising technology that can address cancer cell evolution by identifying genetic alterations in individual cells. In a recent study, genome-wide DNA copy numbers of single cells were accurately quantified by single-cell sequencing in breast cancers. Phylogenetic-tree analysis revealed genetically distinct populations, each consisting of homogeneous cells. Bioinformatics methods based on population genetics should be further developed to quantitatively analyse the single-cell sequencing data. We developed a bioinformatics framework that was combined with molecular-evolution theories to analyse copy-number losses. This analysis revealed that most deletions in the breast cancers at the single-cell level were generated by simple stochastic processes. A non-standard type of coalescent theory, the multiple-merger coalescent model, aided by approximate Bayesian computation fit well with the data, allowing us to estimate the population-genetic parameters in addition to false-positive and false-negative rates. The estimated parameters suggest that the cancer cells underwent sweepstake evolution, where only one or very few parental cells produced a descendent cell population. We conclude that breast cancer cells successively substitute in a tumour mass, and the high reproduction of only a portion of cancer cells may confer high adaptability to this cancer.

Adverse events associated with incretin-based drugs in Japanese spontaneous reports: a mixed effects logistic regression model.

BACKGROUND: Spontaneous Reporting Systems (SRSs) are passive systems composed of reports of suspected Adverse Drug Events (ADEs), and are used for Pharmacovigilance (PhV), namely, drug safety surveillance. Exploration of analytical methodologies to enhance SRS-based discovery will contribute to more effective PhV. In this study, we proposed a statistical modeling approach for SRS data to address heterogeneity by a reporting time point. Furthermore, we applied this approach to analyze ADEs of incretin-based drugs such as DPP-4 inhibitors and GLP-1 receptor agonists, which are widely used to treat type 2 diabetes. METHODS: SRS data were obtained from the Japanese Adverse Drug Event Report (JADER) database. Reported adverse events were classified according to the MedDRA High Level Terms (HLTs). A mixed effects logistic regression model was used to analyze the occurrence of each HLT. The model treated DPP-4 inhibitors, GLP-1 receptor agonists, hypoglycemic drugs, concomitant suspected drugs, age, and sex as fixed effects, while the quarterly period of reporting was treated as a random effect. Before application of the model, Fisher's exact tests were performed for all drug-HLT combinations. Mixed effects logistic regressions were performed for the HLTs that were found to be associated with incretin-based drugs. Statistical significance was determined by a two-sided p-value <0.01 or a 99% two-sided confidence interval. Finally, the models with and without the random effect were compared based on Akaike's Information Criteria (AIC), in which a model with a smaller AIC was considered satisfactory. RESULTS: The analysis included 187,181 cases reported from January 2010 to March 2015. It showed that 33 HLTs, including pancreatic, gastrointestinal, and cholecystic events, were significantly associated with DPP-4 inhibitors or GLP-1 receptor agonists. In the AIC comparison, half of the HLTs reported with incretin-based drugs favored the random effect, whereas HLTs reported frequently tended to favor the mixed model. CONCLUSION: The model with the random effect was appropriate for analyzing frequently reported ADEs; however, further exploration is required to improve the model. The core concept of the model is to introduce a random effect of time. Modeling the random effect of time is widely applicable to various SRS data and will improve future SRS data analyses.