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.

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.

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.

[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.

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.