Search

Epigenetic alterations critically affect tumor development. Polycomb‐group complexes constitute an evolutionarily conserved epigenetic machinery that regulates stem cell fate and development. They are implicated in tumorigenesis, primarily via histone modification. Polycomb repressive complex 1 (PRC1) complexes 1–6 (PRC1.1–6) mediate the ubiquitination of histone H2A on lysine 119 (H2AK119ub). Here, we studied the functional roles of a PRC1.6 molecule, L3MBTL2, in neuroblastoma (NB) cells. L3MBTL2‐knockout and knockdown revealed that L3MBTL2 depletion suppressed NB cell proliferation via cell‐cycle arrest and gamma‐H2A.X upregulation. L3MBTL2‐knockout profoundly suppressed xenograft tumor formation. Transcriptome analysis revealed suppressed cell‐cycle‐related and activated differentiation‐related pathways. Break repair meiotic recombinase recruitment factor 1 (BRME1) and nuclear receptor interacting protein 3 (NRIP3) were notably de‐repressed by L3MBTL2‐knockout. The deletion of L3MBTL2 reduced enrichment of H2AK119ub and PCGF6 at transcriptional start site proximal regions of the targets. Add‐back studies unveiled the importance of L3MBTL2‐BRME1 and ‐NRIP3 axes for NB cell proliferation. We further manifested the association of MYCN with de‐repression of NRIP3 in an L3MBTL2‐deficient context. Therefore, this study first revealed the significance of L3MBTL2‐mediated gene silencing in MYCN‐amplified NB cells. [ABSTRACT FROM AUTHOR]

Simple Summary: This was a multicenter, single-arm, phase II study comprising two protocol treatments. Patients were enrolled after craniotomy or biopsy and initiated the concurrent phase; oral daily temozolomide concomitant with radiation therapy during the first 6 weeks of treatment. Bevacizumab was intravenously administered every other week. The protocol-defined secondary therapy (i.e., BBP regimen) was given as bevacizumab monotherapy or in combination with other chemotherapeutic agents upon first progression or recurrence until further progression or unacceptable toxicity developed. The primary endpoint, the 2-year survival rate of the BBP group, was 27.0% and was unmet. Expression profiling using RNA sequencing identified that Cluster 2, enriched with the genes involved in macrophage or microglia activation, was associated with longer OS and PFS independent of the MGMT methylation status. 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. [ABSTRACT FROM AUTHOR]

We undertook genomic analyses of Japanese patients with stage I esophageal squamous cell carcinoma (ESCC) to investigate the frequency of genomic alterations and the association with survival outcomes. Biomarker analysis was carried out for patients with clinical stage T1bN0M0 ESCC enrolled in JCOG0502 (UMIN000000551). Whole‐exome sequencing (WES) was performed using DNA extracted from formalin‐fixed, paraffin‐embedded tissue of ESCC and normal tissue or blood sample. Single nucleotide variants (SNVs), insertions/deletions (indels), and copy number alterations (CNAs) were identified. We then evaluated the associations between each gene alteration with a frequency of 10% or more and progression‐free survival (PFS) using a Cox regression model. We controlled for family‐wise errors at 0.05 using the Bonferroni method. Among the 379 patients who were enrolled in JCOG0502, 127 patients were successfully analyzed using WES. The median patient age was 63 years (interquartile range, 57‐67 years), and 78.0% of the patients ultimately underwent surgery. The 3‐year PFS probability was 76.3%. We detected 20 genes with SNVs, indels, or amplifications with a frequency of 10% or more. Genomic alterations in FGF19 showed the strongest association with PFS with a borderline level of statistical significance of P =.00252 (Bonferroni‐adjusted significance level is.0025). Genomic alterations in FGF4, MYEOV, CTTN, and ORAOV1 showed a marginal association with PFS (P <.05). These genomic alterations were all CNAs at chromosome 11q13.3. We have identified new genomic alterations associated with the poor efficacy of ESCC (T1bN0M0). These findings open avenues for the development of new potential treatments for patients with ESCC. [ABSTRACT FROM AUTHOR]

Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future. [ABSTRACT FROM AUTHOR]

Common wheat (Triticum aestivum L.) is one of the most important cereals in the world. To improve wheat quality and productivity, the genomic sequence of wheat must be determined. The large genome size (∼17 Gb/1 C) and the hexaploid status of wheat have hampered the genome sequencing of wheat. However, flow sorting of individual chromosomes has allowed us to purify and separately shotgun-sequence a pair of telocentric chromosomes. Here, we describe a result from the survey sequencing of wheat chromosome 6B (914 Mb/1 C) using massively parallel 454 pyrosequencing. From the 4.94 and 5.51 Gb shotgun sequence data from the two chromosome arms of 6BS and 6BL, 235 and 273 Mb sequences were assembled to cover ∼55.6 and 54.9% of the total genomic regions, respectively. Repetitive sequences composed 77 and 86% of the assembled sequences on 6BS and 6BL, respectively. Within the assembled sequences, we predicted a total of 4798 non-repetitive gene loci with the evidence of expression from the wheat transcriptome data. The numbers and chromosomal distribution patterns of the genes for tRNAs and microRNAs in wheat 6B were investigated, and the results suggested a significant involvement of DNA transposon diffusion in the evolution of these non-protein-coding RNA genes. A comparative analysis of the genomic sequences of wheat 6B and monocot plants clearly indicated the evolutionary conservation of gene contents. [ABSTRACT FROM PUBLISHER]

Classification of the individuals' genotype data is important in various kinds of biomedical research. There are many sophisticated clustering algorithms, but most of them require some appropriate similarity measure between objects to be clustered. Hence, accurate inter-diplotype similarity measures are always required for classification of diplotypes. In this article, we propose a new accurate inter-diplotype similarity measure that we call the population model-based distance (PMD), so that we can cluster individuals with diplotype SNPs data (i.e., unphased-diplotypes) with higher accuracies. For unphased-diplotypes, the allele sharing distance (ASD) has been the standard to measure the genetic distance between the diplotypes of individuals. To achieve higher clustering accuracies, our new measure PMD makes good use of a given appropriate population model which has never been utilized in the ASD. As the population model, we propose to use an hidden Markov model (HMM)-based model. We call the PMD based on the model the HHD (HIT HMM-based Distance). We demonstrate the impact of the HHD on the diplotype classification through comprehensive large-scale experiments over the genome-wide 8930 data sets derived from the HapMap SNPs database. The experiments revealed that the HHD enables significantly more accurate clustering than the ASD. [ABSTRACT FROM AUTHOR]

Background/aim: Pembrolizumab, a second-line therapy for platinum-refractory advanced urothelial carcinoma (UC), is needed to improve objective response rate. Hence, it is crucial to identify optimal predictive biomarkers of responses. This study aimed to clarify the predictive value and role of signal transducer and activator of transcription 3 (STAT3) in selecting patients with advanced UC who might benefit clinically from pembrolizumab therapy., Patients and Methods: We retrospectively analyzed 31 patients who received pembrolizumab therapy for UC. STAT3, phosphorylated STAT3 (p-STAT3), and PD-L1 expression were determined using tissue microarrays constructed from patient-derived specimens, and the association of these expression levels with overall survival was analyzed. We assessed the functional role of STAT3 in bladder cancer cell lines in response to interferon-gamma (IFN-γ)., Results: Patients with high STAT3 or p-STAT3 expression, and high platelet-to-lymphocyte ratio (PLR) (n=6) had a significantly shorter OS; in the other patients (n=25), high STAT3 or p-STAT3 expression was significantly associated with improved prognosis. IFN-γ-induced apoptosis was partially dependent on STAT3 in T24 cells but not in JMSU1 cells., Conclusion: In patients with advanced UC, STAT3 plays a key role in mediating the efficacy of pembrolizumab through apoptosis in response to IFN-γ., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Background/aim: Several prognostic risk factors have been recognized when using cisplatin-based conventional chemotherapy for the treatment of advanced urothelial carcinoma (UC); these include performance status (PS), liver metastasis, hemoglobin (Hb) levels, time from prior chemotherapy (TFPC), and other systemic inflammation scores including neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). However, the benefit of these indicators for predicting outcome of immune checkpoint inhibitors is not fully understood. Here, we investigated the predictive value of the indicators in patients who received pembrolizumab for the treatment of advanced UC., Patients and Methods: Seventy-five patients who received pembrolizumab treatment for advanced UC were included. The Karnofsky PS, liver metastasis, hemoglobin levels, TFPC, NLR, and PLR were analyzed, and their relationship with overall survival (OS) was determined., Results: All factors were highlighted as significant prognostic indicators for OS in the univariate proportional regression analysis (p<0.05 for each). Multivariate analysis revealed that Karnofsky PS and liver metastasis were independent prognostic indicators for OS (p<0.01) but were applicable only for a small number of patients. Notably, the combined analysis with low Hb levels and high PLR was significantly associated with OS in patients who could gain less benefit from pembrolizumab at a median of 6.6 [95% confidence interval (CI)=4.2-9.0] versus 15.1 (95% CI=12.4-17.8) months (p=0.002)., Conclusion: The combination of Hb levels and PLR may be a broadly applicable indicator for the outcome of pembrolizumab as second-line chemotherapy in patients with advanced UC., Competing Interests: None of the Authors declare any conflicts of interest., (Copyright 2023, International Institute of Anticancer Research.)

Phenotype prediction from genotype data is one of the most important issues in computational genetics. In this work, we propose a new kernel (i.e., an SVM: Support Vector Machine) method for phenotype prediction from genotype data. In our method, we first infer multiple suboptimal haplotype candidates from each genotype by using the HMM (Hidden Markov Model), and the kernel matrix is computed based on the predicted haplotype candidates and their emission probabilities from the HMM. We validated the performance of our method through experiments on several datasets: One is an artificially constructed dataset via a program GeneArtisan, others are a real dataset of the NAT2 gene from the international HapMap project, and a real dataset of genotypes of diseased individuals. The experiments show that our method is superior to ordinary naive kernel methods (i.e., not based on haplotype prediction), especially in cases of strong LD (linkage disequilibrium).