Drought-responsive WRKY transcription factor genes TaWRKY1 and TaWRKY33 from wheat confer drought and/or heat resistance in Arabidopsis.

BACKGROUND: Drought stress is one of the major causes of crop loss. WRKY transcription factors, as one of the largest transcription factor families, play important roles in regulation of many plant processes, including drought stress response. However, far less information is available on drought-responsive WRKY genes in wheat (Triticum aestivum L.), one of the three staple food crops. RESULTS: Forty eight putative drought-induced WRKY genes were identified from a comparison between de novo transcriptome sequencing data of wheat without or with drought treatment. TaWRKY1 and TaWRKY33 from WRKY Groups III and II, respectively, were selected for further investigation. Subcellular localization assays revealed that TaWRKY1 and TaWRKY33 were localized in the nuclei in wheat mesophyll protoplasts. Various abiotic stress-related cis-acting elements were observed in the promoters of TaWRKY1 and TaWRKY33. Quantitative real-time PCR (qRT-PCR) analysis showed that TaWRKY1 was slightly up-regulated by high-temperature and abscisic acid (ABA), and down-regulated by low-temperature. TaWRKY33 was involved in high responses to high-temperature, low-temperature, ABA and jasmonic acid methylester (MeJA). Overexpression of TaWRKY1 and TaWRKY33 activated several stress-related downstream genes, increased germination rates, and promoted root growth in Arabidopsis under various stresses. TaWRKY33 transgenic Arabidopsis lines showed lower rates of water loss than TaWRKY1 transgenic Arabidopsis lines and wild type plants during dehydration. Most importantly, TaWRKY33 transgenic lines exhibited enhanced tolerance to heat stress. CONCLUSIONS: The functional roles highlight the importance of WRKYs in stress response.

Genome-wide analysis of the Hsf family in soybean and functional identification of GmHsf-34 involvement in drought and heat stresses.

BACKGROUND: High temperature affects organism growth and metabolic activity. Heat shock transcription factors (Hsfs) are key regulators in heat shock response in eukaryotes and prokaryotes. Under high temperature conditions, Hsfs activate heat shock proteins (Hsps) by combining with heat stress elements (HSEs) in their promoters, leading to defense of heat stress. Since the first plant Hsf gene was identified in tomato, several plant Hsf family genes have been thoroughly characterized. Although soybean (Glycine max), an important oilseed crops, genome sequences have been available, the Hsf family genes in soybean have not been characterized accurately. RESULT: We analyzed the Hsf genetic structures and protein function domains using the GSDS, Pfam, SMART, PredictNLS, and NetNES online tools. The genome scanning of dicots (soybean and Arabidopsis) and monocots (rice and maize) revealed that the whole-genome replication occurred twice in soybean evolution. The plant Hsfs were classified into 3 classes and 16 subclasses according to protein structure domains. The A8 and B3 subclasses existed only in dicots and the A9 and C2 occurred only in monocots. Thirty eight soybean Hsfs were systematically identified and grouped into 3 classes and 12 subclasses, and located on 15 soybean chromosomes. The promoter regions of the soybean Hsfs contained cis-elements that likely participate in drought, low temperature, and ABA stress responses. There were large differences among Hsfs based on transcriptional levels under the stress conditions. The transcriptional levels of the A1 and A2 subclass genes were extraordinarily high. In addition, differences in the expression levels occurred for each gene in the different organs and at the different developmental stages. Several genes were chosen to determine their subcellular localizations and functions. The subcellular localization results revealed that GmHsf-04, GmHsf-33, and GmHsf-34 were located in the nucleus. Overexpression of the GmHsf-34 gene improved the tolerances to drought and heat stresses in Arabidopsis plants. CONCLUSIONS: This present investigation of the quantity, structural features, expression characteristics, subcellular localizations, and functional roles provides a scientific basis for further research on soybean Hsf functions.

Post-radiation circulating tumor DNA as a prognostic factor in locally advanced esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a highly malignant and deadly tumor. Radiation therapy is one of the primary treatments for locally advanced ESCC. However, the biomarkers for prognosis of definitive radiation remain undefined. Peripheral blood circulating tumor (ct)DNA provides information of tumor genetic alterations and has been confirmed as a potential non-invasive biomarker for several types of cancer. The present study investigated the clinical implications of ctDNA detection in patients with ESCC and receiving definitive radiation therapy. Patients with locally advanced ESCC were retrospectively recruited. Plasma samples were collected before, during and following radiation therapy. Next-generation sequencing was performed to identify somatic mutations in 180 genes. A total of 69 baseline and post-radiation plasma samples were collected from 25 patients. A total of 59 non-silent single nucleotide variants were present in 33 genes. All pre-radiation and 58.3% (14/24) of post-radiation samples had at least one mutation. Patients with lymph node metastases (LNM) exhibited a higher number of pre-radiation mutations compared with those without LNM. The variables, progression-free survival (PFS) and overall survival (OS) of the patients with one baseline mutation were not significantly different compared with that in patients with more than one baseline mutation. Patients with initial ctDNA-positive post-radiation samples exhibited significantly reduced PFS (P=0.047) and OS (P=0.005) compared with that in patients with ctDNA-negative samples. The post-radiation plasma ctDNA status was an independent prognostic factor from univariate and multivariate analyses. Dynamic monitoring of ctDNA during follow-up was examined. The results indicated that ctDNA was a predictive and prognostic marker in patients with ESCC and receiving definitive radiation therapy, which may guide subsequent treatment.

Genomic characteristics and drug screening among organoids derived from non-small cell lung cancer patients.

BACKGROUND: Patient-derived organoid (PDO) models are highly valuable and have potentially widespread clinical applications. However, limited information is available regarding organoid models of non-small cell lung cancer (NSCLC). This study aimed to characterize the consistency between primary tumors in NSCLC and PDOs and to explore the applications of PDOs as preclinical models to understand and predict treatment response during lung cancer. METHODS: Fresh tumor samples were harvested for organoid culture. Primary tumor samples and PDOs were analyzed via whole-exome sequencing. Paired samples were subjected to immunohistochemical analysis. There were 26 antineoplastic drugs tested in the PDOs. Cell viability was assessed using the Cell Titer Glo assay 7-10 days after drug treatment. A heatmap of log-transformed values of the half-maximal inhibitory concentrations was generated on the basis of drug responses of PDOs through nonlinear regression (curve fit). A total of 12 patients (stages I-III) were enrolled, and 7 paired surgical tumors and PDOs were analyzed. RESULTS: PDOs retained the histological and genetic characteristics of the primary tumors. The concordance between tumors and PDOs in mutations in the top 20 NSCLC-related genes was >80% in five patients. Sample purity was significantly and positively associated with variant allele frequency (Pearson r = 0.82, P = 0.0005) and chromosome stability. The in vitro response to drug screening with PDOs revealed high correlation with the mutation profiles in the primary tumors. CONCLUSIONS: PDOs are highly credible models for detecting NSCLC and for prospective prediction of the treatment response for personalized precision medicine. KEY POINTS: Lung cancer organoid models could save precious time of drug testing on patients, and accurately select anticancer drugs according to the drug sensitivity results, so as to provide a powerful supplement and verification for the gene sequencing.