The SKS of the KMSKS signature of class I aminoacyl-tRNA synthetases corresponds to the GKT/S sequence characteristic of the ATP-binding site of many proteins

On the basis of protein modification studies and primary structure comparison, we propose that the SKS sequence within the KMSKS signature of the class 1 aminoacyl-tRNA synthetases corresponds to the GKT(or S) sequence considered as a signature of the nucleotide triphosphate-binding site of many proteins.     

A genome-wide perspective on the diversity and selection signatures in indigenous goats using 53 K single nucleotide polymorphism array

Tibetan goats, Taihang goats, Jining grey goats, and Meigu goats are the representative indigenous goats in China, found in Qinghai-Tibet Plateau, Western pastoral area, Northern and Southern agricultural regions. Very few studies have conducted a comprehensive analysis of the genomic diversity and selection of these breeds. We genotyped 96 unrelated individuals, using goat 53 K Illumina BeadChip array, of the following goat breeds: Tibetan (TG), Taihang (THG), Jining grey (JGG), and Meigu (MGG). A total of 45 951 single nucleotide polymorphisms were filtered to estimate the genetic diversity and selection signatures. All breeds had a high proportion (over 95%) of polymorphic loci. The observed and excepted heterozygosity ranged from 0.338 (MGG) to 0.402 (JGG) and 0.339 (MGG) to 0.395 (JGG), respectively. Clustering analysis displayed a genetically distinct lineage for each breed, and their Fst were greater than 0.25, indicating that they had a higher genetic differentiation between groups. Furthermore, effective population size reduced in all four populations, indicating a loss of genetic diversity. In addition, runs of homozygosity were mainly distributed in 5–10 Mb. Lastly, we identified signature genes, which were closely related to high-altitude adaptation (ADIRF) and prolificity (CNTROB, SMC3, and PTEN). This study provides a valuable resource for future studies on genome-wide perspectives on the diversity and selection signatures of Chinese indigenous goats.     

Inhibitory effects of different quantitative compositions of Hymenaea leaf resins on a generalist herbivore Spodoptera exigua

The hypotheses that quantitative variation in leaf resins in the leguminous genus Hymenaea may partially be a response to insect predation was tested in feeding experiments with the generalist herbivore, the beet armyworm, Spodoptera exigua Hübn (Noctuidae). Leaf resins of all Hymenaea species are comprised of essentially the same suite of sesquiterpene hydrocarbons, but discrete quantitative patterns have been classified as Compositional Types based on the amounts of major components. In this work pure extracts of leaf resins of Type I (high - and β-selinene), Type II (intermediate amounts of -and β-selinene and caryophyllene) and Type III (high caryophyllene) were incorporated into an artificial diet for the insects at 1 and 3.2% (dry wt). Resin Type treatments produced differential dose-dependent effects on growth rate (lower larval weights and increased time to pupation) and in mortality. More significant inhibitory effects occurred in Compositional Types with a predominance of a single compared (i.e. Types I and III). Significantly higher mortality occurring in Type III treatments suggests that caryophllene may have higher potential toxicity than - and β-selinene for S. exigua. These experiments indicate that feeding by generalist herbivores could be a factor determining quantitative compositional variation: (a) among populations; (b) during the development of leaves; (c) in the spatial distribution within the leaves; and (d) between parent tree and seedling progeny.     

Characterization of WiDr: A human colon carcinoma cell line

Summary We describe the establishment and characterization of WiDr, a cell line derived from a human colon carcinoma. It produces carcinoembryonic antigen in culture, and has a doubling time of 15 hr with plating efficiency of 51%. The HLA antigenic profile and the allozyme genetic signature (composed of eight gene-enzyme systems) of WiDr cells are different from those of HeLa cells. Furthermore, WiDr cells possess three marker chromosomes, again distinct from the HeLa marker chromosomes. Finally, it is highly tumorigenic in four different xenogeneic animal models. Based on these studies, WiDr represents a useful model cell line for tumor cell biology investigations.     

Cancer: Towards a general theory of the target

General theories (GT) are reductionist explications of apparently independent facts. Here, in reviewing the literature, I develop a GT to simplify the cluttered landscape of cancer therapy targets by revealing they cluster parsimoniously according to only a few underlying principles. The first principle is that targets can be only exploited by either or both of two fundamentally different approaches: causality‐inhibition, and ‘acausal’ recognition of some marker or signature. Nonetheless, each approach must achieve both of two separate goals, efficacy (reduction in cancer burden) and selectivity (sparing of normal cells); if the mechanisms are known, this provides a definition of rational treatment. The second principle is target fragmentation, whereby the target may perform up to three categoric functions (cytoreduction, modulation, cytoprotection), potentially mediated by physically different target molecules, even on different cell types, or circulating freely. This GT remains incomplete until the minimal requirements for cure, or alternatively, proof that cure is impossible, become predictable.     

A novel prognostic signature of immune‐related genes for patients with colorectal cancer

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC‐related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune‐related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune‐related prognostic signature for CRC. To this end, we combined gene expression and clinical data from the CRC data sets of The Cancer Genome Atlas (TCGA) into an integrated immune landscape profile. We identified a total of 476 IRGs that were differentially expressed in CRC vs normal tissues, of which 18 were survival related according to univariate Cox analysis. Stepwise multivariate Cox proportional hazards analysis established an immune‐related prognostic signature consisting of SLC10A2, FGF2, CCL28, NDRG1, ESM1, UCN, UTS2 and TRDC. The predictive ability of this signature for 3‐ and 5‐year overall survival was determined using receiver operating characteristics (ROC), and the respective areas under the curve (AUC) were 79.2% and 76.6%. The signature showed moderate predictive accuracy in the validation and GSE38832 data sets as well. Furthermore, the 8‐IRG signature correlated significantly with tumour stage, invasion, lymph node metastasis and distant metastasis by univariate Cox analysis, and was established an independent prognostic factor by multivariate Cox regression analysis for CRC. Gene set enrichment analysis (GSEA) revealed a relationship between the IRG prognostic signature and various biological pathways. Focal adhesions and ECM‐receptor interactions were positively correlated with the risk scores, while cytosolic DNA sensing and metabolism‐related pathways were negatively correlated. Finally, the bioinformatics results were validated by real‐time RT?qPCR. In conclusion, we identified and validated a novel, immune‐related prognostic signature for patients with CRC, and this signature reflects the dysregulated tumour immune microenvironment and has a potential for better CRC patient management.     

Comprehensive analysis of mRNA‐level and miRNA‐level subpathway activities for identifying robust ovarian cancer prognostic signatures

Ovarian cancer (OvCa) causes the highest mortality among all gynaecologic cancers. A large number of mRNA‐ or miRNA‐based signatures were identified for OvCa patient prognosis. However, the comprehensive analysis of function‐level prognostic signatures is currently not considered in OvCa. In the present study, we respectively inferred subpathway activities from mRNA and miRNA levels based on high‐throughput expression profiles and reconstructed subpathways. Firstly, the activities of two tumour pathways were calculated and the difference between normal and tumour samples were analysed using multiple tumour types. Then, we calculated subpathway activities for OvCa based on the expression profiles from both mRNA and miRNA levels. Furthermore, based on these subpathway activity matrices, we performed bootstrap analysis to obtain sub‐training sets and utilized univariate method to identify robust OvCa prognostic subpathways. A comprehensive comparison of subpathway results between these two levels was performed. As a result, we observed subpathway mutual exclusion trend between the levels of mRNA and miRNA, which indicated the necessary of combining mRNA‐miRNA levels. Finally, by using ICGC data as testing sets, we utilized two strategies to verify survival predictive power of the mRNA‐miRNA combined subpathway signatures and performed comparisons with results from individual levels. It was confirmed that our framework displayed application to identify robust and efficient prognostic signatures for OvCa, and the combined signatures indeed exhibited advantages over individual ones. In the study, we took a step forward in relevant novel integrated functional signatures for OvCa prognosis.     

A stroma-related lncRNA panel for predicting recurrence and adjuvant chemotherapy benefit in patients with early-stage colon cancer

The heterogeneity in prognoses and chemotherapeutic responses of colon cancer patients with similar clinical features emphasized the necessity for new biomarkers that help to improve the survival prediction and tailor therapies more rationally and precisely. In the present study, we established a s troma-related l ncRNA s ignature (SLS) based on 52 lncRNAs to comprehensively predict clinical outcome. The SLS model could not only distinguish patients with different recurrence and mortality risks through univariate analysis, but also served as an independent factor for relapse-free and overall survival. Compared with the conventionally used TNM stage system, the SLS model clearly possessed higher predictive accuracy. Moreover, the SLS model also effectively screened chemotherapy-responsive patients, as only patients in the low-SLS group could benefit from adjuvant chemotherapy. The following cell infiltration and competing endogenous RNA (ceRNA) network functional analyses further confirmed the association between the SLS model and stromal activation-related biological processes. Additionally, this study also identified three phenotypically distinct colon cancer subtypes that varied in clinical outcome and chemotherapy benefits. In conclusion, our SLS model may be a significant determinant of survival and chemotherapeutic decision-making in colon cancer and may have a strong clinical transformation value.