Genome-wide identification of ATG genes and their expression profiles under biotic and abiotic stresses in Fenneropenaeus chinensis.

BACKGROUND: Autophagy is a conserved catabolic process in eukaryotes that contributes to cell survival in response to multiple stresses and is important for organism fitness. Extensive research has shown that autophagy plays a pivotal role in both viral infection and replication processes. Despite the increasing research dedicated to autophagy, investigations into shrimp autophagy are relatively scarce. RESULTS: Based on three different methods, a total of 20 members of the ATGs were identified from F. chinensis, all of which contained an autophagy domain. These genes were divided into 18 subfamilies based on their different C-terminal domains, and were found to be located on 16 chromosomes. Quantitative real-time PCR (qRT-PCR) results showed that ATG genes were extensively distributed in all the tested tissues, with the highest expression levels were detected in muscle and eyestalk. To clarify the comprehensive roles of ATG genes upon biotic and abiotic stresses, we examined their expression patterns. The expression levels of multiple ATGs showed an initial increase followed by a decrease, with the highest expression levels observed at 6 h and/or 24 h after WSSV injection. The expression levels of three genes (ATG1, ATG3, and ATG4B) gradually increased until 60 h after injection. Under low-salt conditions, 12 ATG genes were significantly induced, and their transcription abundance peaked at 96 h after treatment. CONCLUSIONS: These results suggested that ATG genes may have significant roles in responding to various environmental stressors. Overall, this study provides a thorough characterization and expression analysis of ATG genes in F. chinensis, laying a strong foundation for further functional studies and promising potential in innate immunity.

Molecular mechanisms and differences in lynch syndrome developing into colorectal cancer and endometrial cancer based on gene expression, methylation, and mutation analysis.

PURPOSE: The aim of this study was to screen biomarkers specific to Lynch syndrome (LS) with colorectal cancer (CRC) or endometrial cancer (EC) to explore the mechanisms by which LS develops into CRC and EC and their differences. METHODS: Differentially expressed or differentially methylated genes and differential mutations were identified in 10 LS, 50 CRC, and 50 EC patients from TCGA, and genes overlapping between LS and CRC or EC (named SGs-LCs and SGs-LEs, respectively) were identified. Afterward, we annotated the enriched GO terms and pathways and constructed a protein-protein interaction (PPI) network. Finally, samples from 10 clinical cases with MSI-H/MSS CRC and EC were collected to verify the mutations and their correlations with five LS pathogenic genes in the SGs-LCs and SGs-LEs. RESULTS: A total of 494 SGs-LCs and 104 SGs-LEs were identified and enriched in 106 and 14 GO terms, respectively. There were great differences in the gene count and enriched terms between SGs-LCs and SGs-LEs. In the PPI network, SST, GCG, SNAP25, and NPY had the highest degree of connection among the SGs-LCs, and KIF20A and NUF2 had the highest degree of connection among the SGs-LE. In the SGs-LCs and SGs-LEs, the genes whose expression levels affected the survival of LS, CRC or EC patients were quite different. CONCLUSIONS: COL11A1 was found to be mutated in MSS CRC patients, similar to the mutations of MSH6. SST, GCG, SNAP25, and NPY may be biomarkers for the development of LS into CRC, and KIF20A and NUF2 may be markers of LS developing into EC.

Novel mutation signatures in the prognosis of EGFR-TKIs targeted therapy for non-small cell lung cancer patients based on the 1000-gene panel sequencing.

The application of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (EGFR-TKIs) in non-small cell lung cancer (NSCLC) may be affected by somatic mutations. The purpose of this study was to explore the effect of mutations on the prognosis and tumor markers of NSCLC patients treated with EGFR-TKIs. 21 NSCLC patients treated with EGFR-TKIs were selected, and the targeted sequencing of the tumor tissues or whole blood samples with the 1000-gene panel was conducted to screen mutations. Afterward, functional enrichment analysis was performed based on mutant genes. Subsequently, the correlation between mutations and clinical indicators, prognosis, and tumor markers were analyzed. Finally, the prognosis after taking osimertinib was compared between NSCLC patients with EGFR p.T790M positive and negative mutations, and the EGFR p.T790M concomitant and uncommon mutations were screened. A total of 485 mutations in 251 genes were identified, in which MTOR, AXIN2, AR, EGFR, NOTCH1, and HRAS mutations were significantly correlated with PFS and/or tumor markers. There was no significant difference in PFS, therapeutic effect, and prognosis between EGFR p.T790M positive and negative patients who received osimertinib treatment. Besides, we also found 80 concomitant mutations and 54 uncommon mutations of EGFR p.T790M. AR, HRAS, EGFR, AXIN2, NOTCH1, and MTOR might be key genes to the prognosis of NSCLC treated with EGFR-TKIs. Osimertinib has certain efficacy in EGFR p.T790M negative NSCLC patients.

Prognostic prediction of systemic immune-inflammation status for patients with colorectal cancer: a novel pyroptosis-related model.

Pyroptosis and related gasdermin family proteins play an important role in the tumorigenesis of colorectal cancer (CRC). However, the prognostic roles of pyroptosis-related genes (PRGs) and their relation to infiltrates of immune cells in the pathogenesis of CRC remain unclear. Using this study, we set up a prognostic gene pattern on the basis of 13 PRGs (AIM2, CASP1, CASP5, CASP6, CASP8, CASP9, ELANE, GPX4, GSDMD, NLRP7, NOD2, PJVK, and PRKACA) for CRC patients. A comprehensive bioinformatics analysis based on these genes was then performed. With the good AUC prediction value of the ROC curves, the group with high hazard first had a poorer survival prognosis than the group with low hazard. Second, we found that PRGs were significantly related to inflammation-associated genes and immune-associated genes in CRC. Then, we identified a correlation of PRGs with immune infiltrations in CRC. For instance, the abundances of resting NK cells resting and neutrophils were higher in the low hazard group than in the high hazard group. Overall, this work indicated that PRGs contributed to generate heterogeneity of the tumor microenvironment (TME) in CRC. This prognostic PRG model may provide a starting point for the early diagnosis and medication use of CRC.

Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis.

BACKGROUND: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. METHODS: Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). RESULTS: Mutations of TP53, APC, KRAS, BRAF and ATM covered 97.55% of TCGA population and 83.02% validation patients. Moreover, 57.14% validation samples and 22.06% TCGA samples indicated that patients with mucinous adenocarcinoma tended to have BRAF mutation, but no TP53 mutation. Mutations of TP53, PIK3CA, FAT4, FMN2 and TRRAP had a remarkable difference between I-II and III-IV stage patients (P < 0.0001). Besides, the combination of PIK3CA, LRP1B, FAT4 and ROS1 formed signatures for the prognosis and survival of CRC patients. The mutations of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4, FMN2, TRRAP, LRP1B, and ROS1 formed the signatures for predicting diagnosis and prognosis of CRC. Among them, mutation of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4 and TRRAP significantly reduced their RNA expression level. Stromal score, immune score and ESTIMATE score were lower in patients with TP53, APC, KRAS, PIK3CA mutation compared non-mutation patients. All the 11 gene mutations affected the distributions of immune cells. CONCLUSION: This study constructed gene mutation signatures for the diagnosis, treatment and prognosis in CRC, and proved that their mutations affected RNA expression levels, TME and immunocyte infiltration. Our results put forward further insights into the genotype of CRC.

Establishment of a typing model for diffuse large B-cell lymphoma based on B-cell receptor repertoire sequencing.

BACKGROUND: The purpose of this study was to construct a new typing model for diffuse large B-cell lymphoma (DLBCL) patients based on the B-cell receptor (BCR) and explore its potential molecular mechanism. METHODS: BCR repertoire sequencing and whole-exome sequencing were performed on formalin-fixed paraffin-embedded samples from 12 DLBCL patients. Subsequently, a typing model was built with cluster analysis, and prognostic indicators between the two groups were compared to verify the typing model. Then, mutation and bioinformatics analyses were conducted to investigate the potential biomarkers of prognostic differences between the two groups. RESULTS: Based on BCR sequencing data, we divided patients into two clusters (cluster 1 and cluster 2); this classification differed from the traditional typing method (GCB and non-GCB), in which cluster 1 included some non-GCB patients. The progression-free survival (PFS), overall survival (OS), metastasis and Shannon diversity index of IGH V-J and survival after chemotherapy were significantly different (P < 0.05) between the two clusters, but no statistical significance was found between the GCB and non-GCB groups. The mutation status of 248 genes was significantly different between cluster 1 and cluster 2. Among them, FTSJ3, MAGED2, and ODF3L2 were the specific mutated genes in all patients in cluster 2, and these genes could be considered critical to the different prognoses of the two clusters of DLBCL patients. CONCLUSION: We constructed a new typing model of DLBCL based on BCR repertoire sequencing that can better predict the survival time after chemotherapy. FTSJ3, MAGED2, and ODF3L2 may represent key genes for the difference in prognosis between the two clusters.

Postinvasive Bacterial Resistance Conferred by Open Stomata in Rice.

Stomata are leaf pores that regulate gas exchange and water transpiration in response to environmental cues. They also function in innate immunity by limiting pathogen entry through actively closing in so-called stomatal defense. However, roles of stomata in plant disease resistance are not fully elucidated, especially in monocots. Here, we report that non-race specific resistance of the rice abscisic acid-deficient mutant Osaba1 to Xanthomonas oryzae pv. oryzae is due to increased stomatal conductance. Reducing stomatal conductance in the Osaba1 mutant increases its susceptibility to X. oryzae pv. oryzae. Artificial opening of stomata in wild-type plants leads to enhanced resistance to X. oryzae pv. oryzae. The rice mutant es1-1 with constitutively higher stomatal conductance exhibits strong resistance to X. oryzae pv. oryzae. Additionally, Osaba1 and es1-1 are resistant to X. oryzae pv. oryzicola. The data support that open stomata confer postinvasive resistance against bacterial pathogens in rice, and such resistance probably results from decreased leaf water potential. Our findings reveal a novel role of stomata in plant immunity through modulation of leaf water status, which provides physiological insight into the interactions between plant, pathogen, and environment.

Effects of Low-Salinity Stress on Histology and Metabolomics in the Intestine of Fenneropenaeus chinensis.

Metabolomics has been used extensively to identify crucial molecules and biochemical effects induced by environmental factors. To understand the effects of acute low-salinity stress on Fenneropenaeus chinensis, intestinal histological examination and untargeted metabonomic analysis of F. chinensis were performed after exposure to a salinity of 15 ppt for 3, 7, and 14 d. The histological examination revealed that acute stress resulted in most epithelial cells rupturing, leading to the dispersion of nuclei in the intestinal lumen after 14 days. Metabolomics analysis identified numerous differentially expressed metabolites (DEMs) at different time points after exposure to low-salinity stress, in which some DEMs were steadily downregulated at the early stage of stress and then gradually upregulated. We further screened 14 overlapping DEMs, in which other DEMs decreased significantly during low-salinity stress, apart from L-palmitoylcarnitine and vitamin A, with enrichments in phenylalanine, tyrosine and tryptophan biosynthesis, fatty acid and retinol metabolism, and ABC transporters. ABC transporters exhibit significant abnormalities and play a vital role in low-salinity stress. This study provides valuable insights into the molecular mechanisms underlying the responses of F. chinensis to acute salinity stress.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.

BACKGROUND: The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer. AIM: To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes. METHODS: In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases. RESULTS: Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival. CONCLUSION: We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.

Integrated Analysis of the Intestinal Microbiota and Transcriptome of Fenneropenaeus chinensis Response to Low-Salinity Stress.

Salinity is an important environmental stress factor in mariculture. Shrimp intestines harbor dense and diverse microbial communities that maintain host health and anti-pathogen capabilities under salinity stress. In this study, 16s amplicon and transcriptome sequencing were used to analyze the intestine of Fenneropenaeus chinensis under low-salinity stress (15 ppt). This study aimed to investigate the response mechanisms of the intestinal microbiota and gene expression to acute low-salinity stress. The intestinal tissues of F. chinensis were analyzed using 16S microbiota and transcriptome sequencing. The microbiota analysis demonstrated that the relative abundances of Photobacterium and Vibrio decreased significantly, whereas Shewanella, Pseudomonas, Lactobacillus, Ralstonia, Colwellia, Cohaesibacter, Fusibacter, and Lachnospiraceae_NK4A136_group became the predominant communities. Transcriptome sequencing identified numerous differentially expressed genes (DEGs). The DEGs were clustered into many Gene Ontology terms and further enriched in some immunity- or metabolism-related Kyoto Encyclopedia of Genes and Genomes pathways, including various types of N-glycan biosynthesis, amino acid sugar and nucleotide sugar metabolism, and lysosome and fatty acid metabolism. Correlation analysis between microbiota and DEGs showed that changes in Pseudomonas, Ralstonia, Colwellia, and Cohaesibacter were positively correlated with immune-related genes such as peritrophin-1-like and mucin-2-like, and negatively correlated with caspase-1-like genes. Low-salinity stress caused changes in intestinal microorganisms and their gene expression, with a close correlation between them.

The mechanism investigation of mutation genes in liver and lung metastasis of colorectal cancer by using NGS technique.

BACKGROUND: We analyzed the somatic mutation distributions as well as pathways associated with liver/lung metastasis of CRC using next-generation sequencing panel. METHODS: We detected the somatic SNV/indel mutations of 1126 tumor-related genes in CRC, liver/lung metastasis of CRC and liver /lung cancer. We combined the MSK and GEO datasets to identified the genes and pathways related to the metastasis of CRC. RESULTS: We identified 174 genes related to liver metastasis of CRC, 78 genes related to lung metastasis of CRC, and 57 genes related to both liver and lung metastasis in two datasets. The genes related to liver and lung metastasis were collectively enriched in various pathways. Finally we found that IRS1, BRCA2, EphA5, PTPRD, BRAF, and PTEN could be prognosis-related genes in CRC metastasis. CONCLUSION: Our finding may help clarify the pathogenesis of CRC metastasis more clearly and provide new perspectives for the diagnosis and treatment of CRC metastasis.

Leaf rolling controlled by the homeodomain leucine zipper class IV gene Roc5 in rice.

Leaf rolling is considered an important agronomic trait in rice (Oryza sativa) breeding. To understand the molecular mechanism controlling leaf rolling, we screened a rice T-DNA insertion population and isolated the outcurved leaf1 (oul1) mutant showing abaxial leaf rolling. The phenotypes were caused by knockout of Rice outermost cell-specific gene5 (Roc5), an ortholog of the Arabidopsis (Arabidopsis thaliana) homeodomain leucine zipper class IV gene GLABRA2. Interestingly, overexpression of Roc5 led to adaxially rolled leaves, whereas cosuppression of Roc5 resulted in abaxial leaf rolling. Bulliform cell number and size increased in oul1 and Roc5 cosuppression plants but were reduced in Roc5-overexpressing lines. The data indicate that Roc5 negatively regulates bulliform cell fate and development. Gene expression profiling, quantitative polymerase chain reaction, and RNA interference (RNAi) analyses revealed that Protodermal Factor Like (PFL) was probably down-regulated in oul1. The mRNA level of PFL was increased in Roc5-overexpressing lines, and PFL-RNAi transgenic plants exhibit reversely rolling leaves by reason of increases of bulliform cell number and size, indicating that Roc5 may have a conserved function. These are, to our knowledge, the first functional data for a gene encoding a homeodomain leucine zipper class IV transcriptional factor in rice that modulates leaf rolling.

[Advances on molecular mechanisms of plant-pathogen interactions].

Plants have established a complicated immune defense system during co-evolution with pathogens. The innate immune system of plants can be generally divided into two levels. One, named PAMP-triggered immunity (PTI), is based on the recognition of pathogen-associated molecular patterns by pattern-recognition receptors, which confers resistance to most pathogenic microbes. The other begins in cytoplasm and mainly relies on recognition of microbial effectors by plant resistance proteins in direct or indirect ways, which then initiates potent defense responses. This process, termed effector-triggered immunity (ETI), is necessary for defense against pathogens that can secret effectors to suppress the first level of immunity. Activation of these two layers of immunity in plant is based on distinguishing and recognition of "self" and "non-self" signals. Recognition of "non-self" signals can activate signal cascades, such as MAPK cascades, which will then induce defense gene expression and corresponding defense responses. In this review, we focused on underlying molecular mechanisms of plant-pathogen interactions and the latest advances of the PTI and ETI signaling network.

Detection of Potential Mutated Genes Associated with Common Immunotherapy Biomarkers in Non-Small-Cell Lung Cancer Patients.

Microsatellite instability (MSI), high tumor mutation burden (TMB-H) and programmed cell death 1 ligand 1 (PD-L1) expression are hot biomarkers related to the improvement of immunotherapy response. Two cohorts of non-small-cell lung cancer (NSCLC) were collected and sequenced via targeted next-generation sequencing. Drug analysis was then performed on the shared genes using three different databases: Drugbank, DEPO and DRUGSURV. A total of 27 common genes were mutated in at least two groups of TMB-H-, MSI- and PD-L1-positive groups. AKT1, SMAD4, SCRIB and AXIN2 were severally involved in PI3K-activated, transforming growth factor beta (TGF-ß)-activated, Hippo-repressed and Wnt-repressed pathways. This study provides an understanding of the mutated genes related to the immunotherapy biomarkers of NSCLC.

DeteX: A highly accurate software for detecting SNV and InDel in single and paired NGS data in cancer research.

Background: Genetic testing is becoming more and more accepted in the auxiliary diagnosis and treatment of tumors. Due to the different performance of the existing bioinformatics software and the different analysis results, the needs of clinical diagnosis and treatment cannot be met. To this end, we combined Bayesian classification model (BC) and fisher exact test (FET), and develop an efficient software DeteX to detect SNV and InDel mutations. It can detect the somatic mutations in tumor-normal paired samples as well as mutations in a single sample. Methods: Combination of Bayesian classification model (BC) and fisher exact test (FET). Results: We detected SNVs and InDels in 11 TCGA glioma samples, 28 clinically targeted capture samples and 2 NCCL-EQA standard samples with DeteX, VarDict, Mutect, VarScan and GatkSNV. The results show that, among the three groups of samples, DeteX has higher sensitivity and precision whether it detects SNVs or InDels than other callers and the F1 value of DeteX is the highest. Especially in the detection of substitution and complex mutations, only DeteX can accurately detect these two kinds of mutations. In terms of single-sample mutation detection, DeteX is much more sensitive than the HaplotypeCaller program in Gatk. In addition, although DeteX has higher mutation detection capabilities, its running time is only .609 of VarDict, which is .704 and .343 longer than VarScan and MuTect, respectively. Conclusion: In this study, we developed DeteX to detect SNV and InDel mutations in single and paired samples. DeteX has high sensitivity and precision especially in the detection of substitution and complex mutations. In summary, DeteX from NGS data is a good SNV and InDel caller.

Identification of Potential Biomarkers for Liver Cancer Through Gene Mutation and Clinical Characteristics.

Liver cancer is a common malignant tumor worldwide, which is a serious threat to the health of people. We try to investigate some mutations and clinical indicators as candidate markers for the development of liver cancer through targeted region capture technology combined with next-generation sequencing. We collected peripheral blood and liver cancer tissue samples from 32 liver patients concurrently. The SeqCap EZ Prime Choice Probe was used to perform the targeted enrichment; this probe captures 1,000 known cancer-associated genes. We calculated the tumor mutation burden (TMB) for each patient. The high-frequency mutations and these relative genes were identified. Eventually, survival analysis was performed based on the mutations and clinical indicators. In 32 liver patients, a total of 29 high-frequency mutations were investigated. They were located in 25 genes, which were enriched in 9 cellular components (CCs), 6 molecular functions (MFs), and 21 biological processes (BPs). Among them, EZH2 c.1544A>G and CCND1 c.839A>T had the highest mutation frequency (5/32). In the protein-protein interaction (PPI) network, EZH2-DNMT3A, NOTCH1-CCND1, and ABL1-CCND1 were the top three pairs. The survival analysis showed that there were significant differences in progression-free survival (PFS) and overall survival (OS) between the Karnofsky performance score (KPS) groups. The PFS and OS in the TMB high group were higher than those in the TMB low group. OS and tumor stage had a remarkable relationship. In conclusion, EZH2 c.1544A>G and CCND1 c.839A>T might be potential biomarkers of liver cancer. TMB might be used as a prognosis and survival indicator of liver cancer.

PD-L1 is a direct target of cancer-FOXP3 in pancreatic ductal adenocarcinoma (PDAC), and combined immunotherapy with antibodies against PD-L1 and CCL5 is effective in the treatment of PDAC.

High expression of PD-L1 marks the poor prognosis of pancreatic ductal adenocarcinomas (PDAC). However, the regulatory mechanism of PD-L1 remains elusive. We recently reported that cancer Forkhead box protein 3 (Cancer-FOXP3 or C-FOXP3) promoted immune evasion of PDAC by recruiting Treg cells into PDAC via upregulation of CCL5. In this study, we confirmed that PD-L1 was overexpressed in PDAC samples from two independent cohorts of patients with radical resection. Moreover, C-FOXP3 was colocalized and correlated with the expression of PD-L1 in tumor cells at the mRNA and protein levels, and this finding was confirmed by the The Cancer Genome Atlas (TCGA) database. Chromatin immunoprecipitation (ChIP) revealed that C-FOXP3 directly bound to the promoter region of PD-L1 in pancreatic cancer cells. Furthermore, overexpression of C-FOXP3 activated the luciferase reporter gene under the control of the PD-L1 promoter. However, mutation of the binding motif-a completely reversed the luciferase activity. In addition, C-FOXP3-induced upregulation of PD-L1 effectively inhibited the activity of CD8+ T cells. Based on our recent finding that the CCL-5 antibody achieved a better response to PDAC models with high C-FOXP3 levels, we further demonstrated that the PD-L1 antibody strengthened the antitumor effect of CCL-5 blockade in xenograft and orthotopic mouse models with high C-FOXP3 levels. In conclusion, C-FOXP3 directly activates PD-L1 and represents a core transcription factor that mediates the immune escape of PDAC. Combined blockade of PD-L1 and CCL-5 may provide an effective therapy for patients with PDAC that have high C-FOXP3 levels.

Somatic gene mutation signatures predict cancer type and prognosis in multiple cancers with pan-cancer 1000 gene panel.

Most cancers are caused by somatic mutations. Some common mutations in the same cancer type can form a "signature" to specifically predict the prognosis or to distinguish it from other cancers. In this study, 710 somatic cell mutations were identified in 142 cases, including digestive, lung and urogenital cancers, and the digestive cancers were further divided into liver, stomach, intestinal, esophageal and cardia cancer. The above mutations were located in 166 genes. In addition, a group of high-frequency mutation genes with specific characteristics were screened to form predictive signatures for each cancer. Verification using TCGA suggested that the signatures could predict the stages, progression-free survival, and overall survival of digestive, intestinal, and liver cancers (P < 0.05). The validation cases further confirmed the predictive role of digestive and liver cancers signatures in diagnosis and prognosis. Overall, this study established predictive signatures for different cancer systems and their subtypes. These findings enable a better understanding in cancer genome, and contribute to the personalized diagnosis and treatment.

Identification and Characterization of ABA-Responsive MicroRNAs in Rice.

MicroRNAs (miRNAs) are endogenous non-coding small RNAs that silence genes through mRNA degradation or translational inhibition. The phytohormone abscisic acid (ABA) is essential for plant development and adaptation to abiotic and biotic stresses. In Arabidopsis, miRNAs are implicated in ABA functions. However, ABA-responsive miRNAs have not been systematically studied in rice. Here high throughput sequencing of small RNAs revealed that 107 miRNAs were differentially expressed in the rice ABA deficient mutant, Osaba1. Of these, 13 were confirmed by stem-loop RT-PCR. Among them, miR1425-5P, miR169a, miR169n, miR390-5P, miR397a and miR397b were up-regulated, but miR162b reduced in expression in Osaba1. The targets of these 13 miRNAs were predicted and validated by gene expression profiling. Interestingly, the expression levels of these miRNAs and their targets were regulated by ABA. Cleavage sites were detected on 7 of the miRNA targets by 5'-Rapid Amplification of cDNA Ends (5'-RACE). Finally, miR162b and its target OsTRE1 were shown to affect rice resistance to drought stress, suggesting that miR162b increases resistance to drought by targeting OsTRE1. Our work provides important information for further characterization and functional analysis of ABA-responsive miRNAs in rice.