Serum miR-224 Reflects Stage of Hepatocellular Carcinoma and Predicts Survival

Background. In our previous study, we conducted a systematic screening of miRNA to identify potential serum biomarkers for predicting venous metastasis and survival in patients with hepatocellular carcinoma (HCC). miR-224 was one of the differentially expressed miRNAs. This study aimed to confirm whether serum miR-224 level is associated with the presence of venous metastasis and survival. Methods. TaqMan miRNA probe was used to perform qRT-PCR assays to evaluate the expression of serum miR-224 in a cohort of 182 HCC patients. Results. Patients with high miR-224 serum level showed poor survival compared to that with low miR-224 serum level (HR 1.985; 95% CI, 1.08, 3.65, = 0.027). The serum miR-224 levels were significantly higher in the BCLC stage C patients compared with the stage B patients ( = 0.005). In further analysis, significant difference of serum miR-224 expression level was observed when patients grouped by the status of PVTT but not the status of extra-liver metastasis ( = 0.013 and = 0.091). Serum levels of miR-224 showed significant relation with parameters of liver damage and serum AFP. Conclusion. Serum miR-224 might be BCLC stage dependent. It can reflect the status of tumor and liver damage. It was an independent predictor for the survival of HCC patients

The rubber tree genome reveals new insights into rubber production and species adaptation

The Para rubber tree (Hevea brasiliensis) is an economically important tropical tree species that produces natural rubber, an essential industrial raw material. Here we present a high-quality genome assembly of this species (1.37 Gb, scaffold N50 = 1.28 Mb) that covers 93.8% of the genome (1.47 Gb) and harbours 43,792 predicted protein-coding genes. A striking expansion of the REF/SRPP (rubber elongation factor/small rubber particle protein) gene family and its divergence into several laticifer-specific isoforms seem crucial for rubber biosynthesis. The REF/SRPP family has isoforms with sizes similar to or larger than SRPP1 (204 amino acids) in 17 other plants examined, but no isoforms with similar sizes to REF1 (138 amino acids), the predominant molecular variant. A pivotal point in Hevea evolution was the emergence of REF1, which is located on the surface of large rubber particles that account for 93% of rubber in the latex (despite constituting only 6% of total rubber particles, large and small). The stringent control of ethylene synthesis under active ethylene signalling and response in laticifers resolves a longstanding mystery of ethylene stimulation in rubber production. Our study, which includes the re-sequencing of five other Hevea cultivars and extensive RNA-seq data, provides a valuable resource for functional genomics and tools for breeding elite Hevea cultivars. The rubber tree (Hevea brasiliensis, hereafter referred to as Hevea) is a member of the spurge family (Euphorbiaceae), along with several other economically important species such as cassava (Manihot esculenta) and the castor oil plant (Ricinus communis). Natural rubber (cis-1, 4-polyisoprene) makes up about one-third of the volume of latex that is essentially cytoplasm of the articulated laticifers in Hevea. The latex is extracted by tapping the bark, a non-destructive method of harvesting that facilitates continual production. As an industrial commodity, natural rubber is an elastomer with physical and chemical properties that cannot be fully matched by synthetic rubber1. In contrast to synthetics, the production of natural rubber is sustainable and environment friendly2. The commercial cultivation of Hevea, a native to the Amazon Basin, began in 1896 on a plantation scale in Malaya (now Malaysia) and expanded to other Southeast Asian countries that lead in world natural rubber production today3. Decades of selective breeding have resulted in a gradual improvement in rubber productivity, from 650 kg ha–1 derived from unselected seedlings during the 1920s to 2,500 kg ha–1 yielded by elite cultivars by the 1990s4. Nevertheless, the field production achieved so far is still well below the theoretical yield of 7,000–12,000 kg ha–1, as has been suggested for the rubber tree5. Meanwhile, conventional rubber breeding has been stagnating in the introduction of high-yield cultivars. The reasons include a narrow genetic basis for exploiting breeding potential and difficulty in introducing wild germplasms because of the genetic burden in removing unfavourable alleles6. The incorporation of marker-assisted selection and transgenic techniques offers promise to improve breeding efficiency for latex yield, and sequencing of the Hevea genome would uncover even more avenues leading to this end. The first draft Hevea genome was released by a Malaysian team7 that was participant to the recent boom in transcriptomic and proteomic studies of the species8,9,10,11. However, its low sequence coverage (∼13×) and a lack of large insert libraries (such as fosmid- or BAC-based clone libraries) have limited the success of genome assembly (a scaffold N50 size of 2,972 bp), precluding its application for furthering quality research in the field. Here, we report a high-quality genome assembly of Hevea Reyan7-33-97, an elite cultivar widely planted in China12,13 based on sequence data from both whole-genome shotgun (WGS) and pooled BAC clones. This assembly contains 7,453 scaffolds (N50 = 1.28 Mb), has a length of 1.37 Gb and covers ∼94% of the predicted genome size (1.46 Gb). Together with analysis of data from re-sequencing five other cultivars and comprehensive transcriptomic surveys, we aim to obtain new insights into the physiology of laticifers and molecular details of rubber biosynthesis, especially in relation to ethylene-stimulated rubber production. (Résumé d'auteur

Development and validation of a 14-CpG DNA methylation signature and drug targets for prognostic prediction in breast cancer

BackgroundBreast cancer (BC) is the most prevalent cancer among women and a leading cause of cancer-related deaths worldwide. Emerging evidence suggests that DNA methylation, a well-studied epigenetic modification, regulates various cellular processes critical for cancer development and progression and holds promise as a biomarker for cancer diagnosis and prognosis, potentially enhancing the efficacy of precision therapies.MethodsWe developed a robust prognostic model for BC based on DNA methylation and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). We analyzed the association of the model with clinicopathological features, survival outcomes, and chemotherapy drug sensitivity.ResultsA set of 216 differentially methylated CpGs was identified by intersecting three datasets (TCGA, GSE22249, and GSE66695). Using univariate Cox proportional hazard and LASSO Cox regression analyses, we constructed a 14-CpG model significantly associated with progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) in BC patients. Kaplan–Meier (KM) survival analysis, receiver operating characteristic (ROC) analysis, and nomogram validation confirmed the clinical value of the signature. The Cox analysis showed a significant association between the signature and PFI and DSS in BC patients. KM analysis effectively distinguished high-risk from low-risk patients, while ROC analysis demonstrated high sensitivity and specificity in predicting BC prognosis. A nomogram based on the signature effectively predicted 5- and 10-year PFI and DSS. Additionally, combining our model with clinical risk factors suggested that patients in the I–II & M+ subgroup could benefit from adjuvant chemotherapy regarding PFI, DSS, and OS. Gene Ontology (GO) functional enrichment and KEGG pathway analyses indicated that the top 3,000 differentially expressed genes (DEGs) were enriched in pathways related to DNA replication and repair and cell cycle regulation. Patients in the high-risk group might benefit from drugs targeting DNA replication and repair processes in tumor cells.ConclusionThe 14-CpG model serves as a useful biomarker for predicting prognosis in BC patients. When combined with TNM staging, it offers a potential strategy for individualized clinical decision-making, guiding personalized therapeutic regimen selection for clinicians

Enabling Large-Scale and High-Precision Fluid Simulations on Near-Term Quantum Computers

Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation. The Poiseuille flow simulation achieved a relative error of less than $0.2\%$, and the unsteady acoustic wave simulation solved a 5043-dimensional matrix. We emphasize the utilization of the quantum-classical hybrid approach in applications of near-term quantum computers. By adapting to quantum hardware constraints and offering scalable solutions for large-scale CFD problems, our method paves the way for practical applications of near-term quantum computers in computational science.Comment: 31 pages, 10 figure

Genomic and oncogenic preference of HBV integration in hepatocellular carcinoma

Hepatitis B virus (HBV) can integrate into the human genome, contributing to genomic instability and hepatocarcinogenesis. Here by conducting high-throughput viral integration detection and RNA sequencing, we identify 4,225 HBV integration events in tumour and adjacent non-tumour samples from 426 patients with HCC. We show that HBV is prone to integrate into rare fragile sites and functional genomic regions including CpG islands. We observe a distinct pattern in the preferential sites of HBV integration between tumour and non-tumour tissues. HBV insertional sites are significantly enriched in the proximity of telomeres in tumours. Recurrent HBV target genes are identified with few that overlap. The overall HBV integration frequency is much higher in tumour genomes of males than in females, with a significant enrichment of integration into chromosome 17. Furthermore, a cirrhosis-dependent HBV integration pattern is observed, affecting distinct targeted genes. Our data suggest that HBV integration has a high potential to drive oncogenic transformation

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443