Clinical and genomic features in patients with second primary glioblastoma following first primary renal cell carcinoma.

PURPOSE: To explore the potential pathogenesis and clinical features of second primary glioblastoma (spGBM) following first primary renal cell carcinoma (fpRCC). METHODS: Patients with spGBM after fpRCC were enrolled from our institution and the SEER dataset. Sanger sequencing, whole genome sequencing, and immunehistochemistry were used to detect molecular biomarkers. RESULTS: Four and 122 cases from our institution and the SEER dataset, respectively, were collected with an overall median age of 69 years at spGBM diagnosis following fpRCC. The median interval time between fpRCC and spGBM was 50.7 months and 4 years, for the four and 122 cases respectively. The median overall survival time was 11.2 and 6.0 months for the two datasets. In addition, spGBM patients of younger age (< 75 years) or shorter interval time (< 1 year) had favorable prognosis (p = 0.081 and 0.05, respectively). Moreover, the spGBM cases were molecularly classified as TERT only paired with TP53 mutation, PIK3CA mutation, EGFR alteration, low tumor mutation burden, and stable microsatellite status. CONCLUSIONS: This is the first study to investigate the pathogenesis and clinical features of spGBM following spRCC. We found that spGBMs are old-age related, highly malignant, and have short survival time. Moreover, they might be misdiagnosed and treated as brain metastases from RCC. Thus, the incidence of spGBMs after fpRCC is underestimated. Further studies are needed to investigate the underlying molecular mechanisms and clinical biomarkers for the development of spGBM following fpRCC.

Functional Portrait and Genomic Feature of Carbapenem-Resistant Pseudomonas mendocina Harboring blaNDM-1 and blaIMP-1 in China.

The purpose of this research was to analyze the functional portraits and genomic features of carbapenem-resistant Pseudomonas mendocina carrying NDM-1 and IMP-1. The resistance mechanism of the strain was verified by in vivo experiments. Genomic data were aligned and analyzed in the NCBI database. Growth curve measurements were used to describe the growth characteristics of the bacteria. The virulence of P. mendocina strain was analyzed by serum killing assay and biofilm formation assay. Plasmid conjugation experiments were performed to verify the transferability of plasmids carrying drug-resistance genes. The P. mendocina strain was highly resistant to carbapenems. In addition, ST typing is unknown and has been submitted to Genebank. The strain carried two carbapenemase genes, including NDM-1 and IMP-1. Among them, blaNDM-1 was located on a 5.62832 Mb chromosome, and blaIMP-1 was located on a 172.851 Kb transferable plasmid, which was a very close relative of pIMP-NY7610 in China. The strain also had a variety of virulence genes, which were expressed in the siderophore, capsule, pilus, alginate, flagella, etc. The study suggests that the functional portrait and genomic features of carbapenem-resistant P. mendocina harboring blaNDM-1 and blaIMP-1 are unique to China. This outcome represents antibiotic resistance exhibited in the genus Pseudomonas by acquiring chromosomes and plasmid genes. The monitoring and supervision of antimicrobial usage must be strengthened since the multi-drug-resistant and moderately virulent P. mendocina will attract much attention in the near future.

Patterns of Chromosomal Variation, Homoeologous Exchange, and Their Relationship with Genomic Features in Early Generations of a Synthetic Rice Segmental Allotetraploid.

Polyploidization is a driving force in plant evolution. Chromosomal variation often occurs at early generations following polyploid formation due to meiotic pairing irregularity that may compromise segregation fidelity and cause homoeologous exchange (HE). The trends of chromosomal variation and especially factors affecting HE remain to be fully deciphered. Here, by whole-genome resequencing, we performed nuanced analyses of patterns of chromosomal number variation and explored genomic features that affect HE in two early generations of a synthetic rice segmental allotetraploid. We found a wide occurrence of whole-chromosome aneuploidy and, to a lesser extent, also large segment gains/losses in both generations (S2 and S4) of the tetraploids. However, while the number of chromosome gains was similar between S2 and S4, that of losses in S4 was lower than in S2. HEs were abundant across all chromosomes in both generations and showed variable correlations with different genomic features at chromosomal and/or local scales. Contents of genes and transposable elements (TEs) were positively and negatively correlated with HE frequencies, respectively. By dissecting TEs into different classes, retrotransposons were found to be negatively correlated with HE frequency to a stronger extent than DNA transposons, whereas miniature terminal inverted elements (MITEs) showed a strong positive correlation. Local HE frequencies in the tetraploids and homologous recombination (HR) rates in diploids within 1 Mb sliding windows were significantly correlated with each other and showed similar overall distribution profiles. Nonetheless, non-concordant trends between HE and HR rates were found at distal regions in some chromosomes. At local scale, both shared and polymorphic retrotransposons between parents were negatively correlated with HE frequency; in contrast, both shared and polymorphic MITEs showed positive correlations with HE frequency. Our results shed new light on the patterns of chromosomal number variation and reveal genomic features influencing HE frequency in early generations following plant polyploidization.

Pathogenic and genomic characterisation of a rabbit sourced Pasteurella multocida serogroup F isolate s4.

BACKGROUND: Pasteurella multocida is one of the most significant pathogens for a number of animals. In rabbits, the infection is generally associated with the P. multocida serogroups A and D, and the knowledge about the serogroup F is limited. In the present study, a P. multocida serogroup F isolate designated s4 was recovered from the lungs of rabbits died of respiratory disease in Fujian, in the southeast of China. The pathogenicity and genomic features of the s4 were then determined. RESULTS: The serotype and sequence type of s4 were F:L3 and ST12, respectively. The s4 was pathogenic for rabbits, but it was a low virulent strain comparing to the previously reported highly pathogenic P. multocida serogroup F strains J-4103, C21724H3km7, P-4218 and HN07. The whole genome of the s4 was then sequenced to understand the genomic basis for pathogenicity. Particularly, a large-sized fragment of approximate 275 kb in length was truncated from the chromosome to form a plasmid. Moreover, the in-frame deletion of natC and N-terminal redundance of gatF would resulted in the production of a mutant L3 outer core structure that was distinct from those of the other P. multocida strains belonging to the lipopolysaccharide genotype L3. We deduced that these features detected in the genome of s4 might impair the pathogenicity of the bacterium. CONCLUSIONS: This study evaluated the pathogenicity and determined the genomic features of the rabbit sourced P. multocida serogroup F isolate s4, the observations and findings would helpful for the understanding of the pathogenicity variability and genetic diversity of P. multocida.

Genomic Features and Clinical Implications of Intraductal Carcinoma of the Prostate.

Intraductal carcinoma of the prostate (IDC-P) is a rare and unique form of aggressive prostate carcinoma, which is characterized by an expansile proliferation of malignant prostatic epithelial cells within prostatic ducts or acini and the preservation of basal cell layers around the involved glands. The vast majority of IDC-P tumors result from adjacent high-grade invasive cancer via the retrograde spreading of tumor cells into normal prostatic ducts or acini. A subset of IDC-P tumors is rarely derived from the de novo intraductal proliferation of premalignant cells. The presence of IDC-P in biopsy or surgical specimens is significantly associated with aggressive pathologic features, such as high Gleason grade, large tumor volume, and advanced tumor stage, and with poor clinical courses, including earlier biochemical recurrence, distant metastasis, and worse survival outcomes. These architectural and behavioral features of IDC-P may be driven by specific molecular properties. Notably, IDC-P possesses distinct genomic profiles, including higher rates of TMPRSS2-ERG gene fusions and PTEN loss, increased percentage of genomic instability, and higher prevalence of germline BRCA2 mutations. Considering that IDC-P tumors are usually resistant to conventional therapies for prostate cancer, further studies should be performed to develop optimal therapeutic strategies based on distinct genomic features, such as treatment with immune checkpoint blockades or poly (adenosine diphosphate-ribose) polymerase inhibitors for patients harboring increased genomic instability or BRCA2 mutations, as well as genetic counseling with genetic testing. Patient-derived xenografts and tumor organoid models can be the promising in vitro platforms for investigating the molecular features of IDC-P tumor.

Ranking genomic features using an information-theoretic measure of epigenetic discordance.

BACKGROUND: Establishment and maintenance of DNA methylation throughout the genome is an important epigenetic mechanism that regulates gene expression whose disruption has been implicated in human diseases like cancer. It is therefore crucial to know which genes, or other genomic features of interest, exhibit significant discordance in DNA methylation between two phenotypes. We have previously proposed an approach for ranking genes based on methylation discordance within their promoter regions, determined by centering a window of fixed size at their transcription start sites. However, we cannot use this method to identify statistically significant genomic features and handle features of variable length and with missing data. RESULTS: We present a new approach for computing the statistical significance of methylation discordance within genomic features of interest in single and multiple test/reference studies. We base the proposed method on a well-articulated hypothesis testing problem that produces p- and q-values for each genomic feature, which we then use to identify and rank features based on the statistical significance of their epigenetic dysregulation. We employ the information-theoretic concept of mutual information to derive a novel test statistic, which we can evaluate by computing Jensen-Shannon distances between the probability distributions of methylation in a test and a reference sample. We design the proposed methodology to simultaneously handle biological, statistical, and technical variability in the data, as well as variable feature lengths and missing data, thus enabling its wide-spread use on any list of genomic features. This is accomplished by estimating, from reference data, the null distribution of the test statistic as a function of feature length using generalized additive regression models. Differential assessment, using normal/cancer data from healthy fetal tissue and pediatric high-grade glioma patients, illustrates the potential of our approach to greatly facilitate the exploratory phases of clinically and biologically relevant methylation studies. CONCLUSIONS: The proposed approach provides the first computational tool for statistically testing and ranking genomic features of interest based on observed DNA methylation discordance in comparative studies that accounts, in a rigorous manner, for biological, statistical, and technical variability in methylation data, as well as for variability in feature length and for missing data.

Genome-wide identification of circular RNAs in peanut (Arachis hypogaea L.).

BACKGROUND: Circular RNAs (circRNAs), a class of widely expressed endogenous regulatory RNAs, are involved in diverse physiological and developmental processes in eukaryotic cells. However, there have been no related studies on the number of circRNAs and their overall characteristics including circRNA abundance and expression profiles in peanut, which is one of the most important edible oil seed crops in the world. RESULTS: We performed a genome-wide identification of circular RNAs using ribosomal-depleted RNA-sequencing from the seeds of two peanut eighth-generation recombinant inbred lines (RIL8): 'RIL 8106' (a medium-pod variety) and 'RIL 8107' (a super-pod variety), at 15 and 35 days after flowering (DAF), respectively. A total of 347 circRNA candidates were detected by two computational pipelines: CIRCexplorer and CIRI, with at least two supporting junction reads. All these circRNAs were generated from exons of annotated genes, and widespread on the 20 peanut chromosomes. The expression profiles revealed that circRNAs were differentially expressed between two stages and between two lines. GO enrichment analysis of the host genes produced differentially-expressed circRNAs suggested that circRNAs are involved in seed development and regulation of seed size. Fifteen circRNAs were experimentally analyzed by qRT-PCR with divergent primers, and six circRNAs were resistant to digestion with RNase R exonuclease, and the back-splicing sites were further validated by Sanger DNA sequencing. CONCLUSIONS: We present the first systematical investigation of the genomic characteristics and expression profiles of circRNAs in peanut. The results revealed that circRNAs are abundant and widespread in peanut, and the differentially-expressed circRNAs between two lines suggested that they might play regulatory roles in peanut seeds development.

Molecular profiles for insular low-grade gliomas with putamen involvement.

BACKGROUND: The newly proposed putamen classification system shows good prognostic value in patients with insular LGGs, yet no study towards the molecular profiles of putamen involved LGGs has been proposed. METHODS: Clinical information and imaging data of patients diagnosed with insular low-grade gliomas were collected retrospectively. Genetic information of the 34 tumors was assessed using RNA-sequencing. Gene set enrichment analysis was further performed to identify the genes showing differential expression between putamen-involved tumors and putamen non-involved tumors. The level of Ki-67 expression was also evaluated. RESULTS: There were 843 genes identified to be differentially expressed between putamen-involved and non-involved gliomas. Specifically, Gene set enrichment analysis discovered 13 Kyoto Encyclopedia of Genes and Genomes pathways and 37 Gene Ontology Biological Process term were upregulated in putamen-involved low-grade glioma cells. The enriched GO sets with the highest gene counts included cell cycle (42 genes), mitotic cell cycle (24 genes), and cell division (19 genes). Furthermore, high expression of Ki-67 was associated with putamen involvement in insular gliomas. CONCLUSIONS: There is clear genetic variation between putamen-involved and non-involved insular low-grade gliomas. The differential expression of genes related to the processes of cell proliferation, cell migration, or DNA repair may lead to putamen involvement. The findings suggest that among the two subtypes, putamen-involved insular low-grade gliomas have higher malignancy, and the clinical treatment towards the putamen-involved insular low-grade gliomas should be more active.

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

BACKGROUND: Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. RESULTS: We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. CONCLUSIONS: TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically relevant data analysis, and the uncovering of variations in the time-dependent behavior of chromatin. TDCA automates the analysis of TC ChIP-seq experiments, permitting researchers to easily obtain raw and modeled data for specific loci or groups of loci with similar behavior while also enhancing consistency of data analysis of TC data within the genomics field.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

BACKGROUND: A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. RESULTS: Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). CONCLUSIONS: Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

[Prediction of cancer drug sensitivity based on genomic feature distribution alignment and drug structure information].

In recent years, precision medicine has demonstrated wide applications in cancer therapy, and the focus of precision medicine lies in accurately predicting the responses of different patients to drug treatment. We propose a model for predicting cancer drug sensitivity based on genomic feature distribution alignment and drug structure information. This model initially aligns the genomic features from cell lines with those from patients and removes noise from gene expression data. Subsequently, it integrates drug structure features and employs multi-task learning to predict the drug sensitivity of patients. The experimental results on the genomics of drug sensitivity in cancer (GDSC) dataset indicates that this method achieved a reduced mean square error of 0.905 2, an increased correlation coefficient of 0.875 4, and an enhanced accuracy rate of 0.836 0 which significantly outperformed the recently published methods. On the cancer genome atlas (TCGA) dataset, this method demonstrates an improved average recall rate of 0.571 4 and an increased F1-score of 0.658 0 in predicting drug sensitivity, exhibiting excellent generalization performance. The result demonstrates the potential of this method to assist in the selection of clinical treatment plans in the future.

Biofilm formation, sodium hypochlorite susceptibility and genetic diversity of Vibrio parahaemolyticus.

Vibrio parahaemolyticus is a marine oriented pathogen; and biofilm formation enables its survival and persistence on seafood processing plant, complicating the hygienic practice. The objectives of this study are to assess the ability of V. parahaemolyticus isolated from seafood related environments to form biofilms, to determine the effective sodium hypochlorite concentrations required to inactivate planktonic and biofilm cells, and to evaluate the genetic diversity required for strong biofilm formation. Among nine isolates, PFR30J09 and PFR34B02 isolates were identified as strong biofilm forming strains, with biofilm cell counts of 7.20, 7.08 log10 CFU/cm2, respectively, on stainless steel coupons after incubation at 25 °C. Free available chlorine of 1176 mg/L and 4704 mg/L was required to eliminate biofilm cells of 1.74-2.28 log10 CFU/cm2 and > 7 log10 CFU/cm2, respectively, whereas 63 mg/L for planktonic cells, indicating the ineffectiveness of sodium hypochlorite in eliminating V. parahaemolyticus biofilm cells at recommended concentration in the food industry. These strong biofilm-forming isolates produced more polysaccharides and were less susceptible to sodium hypochlorite, implying a possible correlation between polysaccharide production and sodium hypochlorite susceptibility. Genetic diversity in mshA, mshC and mshD contributed to the observed variation in biofilm formation between isolates. This study identified strong biofilm-forming V. parahaemolyticus strains of new multilocus sequence typing (MLST) types, showed a relationship between polysaccharide production and sodium hypochlorite resistance.

Bt GS57 Interaction With Gut Microbiota Accelerates Spodoptera exigua Mortality.

The Beet armyworm Spodoptera exigua (Lepidoptera: Noctuidae, Spodoptera) is an important global polyphagous pest. Pathogen infection could destroy the intestinal microbial homeostasis of insects, leading to the death of the host. However, the effect of the host intestinal microbial community on the insecticidal effect of Bacillus thuringiensis is rarely studied. In this study, the genome characteristics of Bt GS57 and the diversity and functions of the gut bacteria in S. exigua are investigated using crystal morphology, biological activity, and Illumina HiSeq high-throughput sequencing. The total size of the Bt GS57 genome is 6.17 Mbp with an average G + C content of 35.66%. Furthermore, the Bt GS57 genome contains six cry genes: cry1Ca, cry1Da, cry2Ab, cry9Ea, cry1Ia, and cry1Aa, and a vegetative insecticidal protein gene vip3Aa. The Bt GS57 strain can produce biconical crystals, mainly expressing 70 kDa and 130 kDa crystal proteins. The LC50 value of the Bt GS57 strain against the S. exigua larvae was 0.339 mg mL-1. Physiological and biochemical reactions showed that Bt GS57 belongs to B.t. var. thuringiensis. In addition, we found that B. thuringiensis can cause a dynamic change in the gut microbiota of S. exigua, with a significant reduction in bacterial diversity and a substantial increase in bacterial load. In turn, loss of gut microbiota significantly decreased the B. thuringiensis susceptibility of S. exigua larvae. Our findings reveal the vital contribution of the gut microbiota in B. thuringiensis-killing activity, providing new insights into the mechanisms of B. thuringiensis pathogenesis in insects.

Genomic and clinical features of endoplasmic reticulum stress factor in digestive system pan-cancer studies.

Introduction: Digestive system pan-cancer is one of the lethal malignant tumors, which have the propensity for poor prognosis and difficult treatment. Endoplasmic reticulum (ER) stress has served as a pivotal role in the progression of the tumor, while the implication of ER stress on digestive system pan-cancers still needs elucidation, especially from the perspective of clinical outcome and that of genomic features. Methods: First, Among the ER STRESS factors from the REACTOME_UNFOLDED_PROTEIN_RESPONSE_UPR (113 genes) and HALLMARK_UNFOLDED_PROTEIN_RESPONSE (92 genes) terms, 153 ER STRESS regulators were identified after removing replicates. The somatic mutation data and copy number variation data of gastrointestinal pan-cancer were downloaded from The Cancer Genome Atlas (TCGA) database. Then, we explored the clinical outcome and genetic mutation of ER stress-related differentially expressed genes (DEGs) by multiple bioinformatics analysis. Subsequently, we analyzed the Spearman correlation between the drug sensitivity of 179 gastrointestinal anticancer drugs and the transcriptional expression of 153 ER stress factors in 769 cancer cell lines of the GDSC2 cohort. Next, ssGSEA method was used to quantify the immune cell infiltration scores in the tumor microenvironment, and Spearman correlation was used to calculate the correlation between ER stress scores and immune cell infiltration. Finally, we analyzed the cellular origin of ER stress factor dysregulation. Results: We analyzed the genomic changes and clinical outcomes of ER stress factors in different tumors of gastrointestinal pan-cancer. Endoplasmic reticulum stress factor (ER) in digestive tract tumors showed high SNV mutation frequency, less methylation dysregulation and was associated with multiple oncogenic pathways. Endoplasmic reticulum stress factor (ER) is a risk factor for many cancers, but the effect on overall survival in rectal adenocarcinoma is opposite to that in other gastrointestinal tumors. And ER stress factors are highly correlated with drugs that target important pathways. Discussion: Based on the clinical prognosis and genomic analysis of ER stress-related factors in patients with gastrointestinal pan-cancer, this study provides a new direction for further research on gastrointestinal pan-cancer.

Utilization Strategies of Two Environment Phenotypes in Genomic Prediction.

Multiple environment phenotypes may be utilized to implement genomic prediction in plant breeding, while it is unclear about optimal utilization strategies according to its different availability. It is necessary to assess the utilization strategies of genomic prediction models based on different availability of multiple environment phenotypes. Here, we compared the prediction accuracy of three genomic prediction models (genomic prediction model (genomic best linear unbiased prediction (GBLUP), genomic best linear unbiased prediction (GFBLUP), and multi-trait genomic best linear unbiased prediction (mtGBLUP)) which leveraged diverse information from multiple environment phenotypes using a rice dataset containing 19 agronomic traits in two disparate seasons. We found that the prediction accuracy of genomic prediction models considering multiple environment phenotypes (GFBLUP and mtGBLUP) was better than the classical genomic prediction model (GBLUP model). The deviation of prediction accuracy of between GBLUP and mtGBLUP or GFBLUP was associated with the phenotypic correlation. In summary, the genomic prediction models considering multiple environment phenotypes (GFBLUP and mtGBLUP) demonstrated better prediction accuracy. In addition, we could utilize different genomic prediction strategies according to different availability of multiple environment phenotypes.

Genomic Landscape of Chinese Clear Cell Renal Cell Carcinoma Patients With Venous Tumor Thrombus Identifies Chromosome 9 and 14 Deletions and Related Immunosuppressive Microenvironment.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with a poor clinical outcome. Although several studies have examined the genomic features of ccRCC, the genetic profile of VTT along with its matched primary tumor has not been fully elucidated. MATERIALS AND METHODS: Samples of VTT tissues and matched primary tumor tissues from ccRCC patients (n = 25), as well as primary tumor tissues from patients without VTT (n = 25) were collected and analyzed using whole-exome sequencing. Four additional ccRCC patients who were unfit for surgery were treated with an anti-programmed death receptor-1 (PD-1) monoclonal antibody (Toripalimab, 240 mg, Q3W, IV). RESULTS: By comparing the primary kidney tumors from ccRCC patients with or without VTT, a relatively higher prevalence of BAP1 and KDM5C alterations were found in ccRCC patients with VTT, and these alterations were associated with worse overall survival in the kidney renal clear cell carcinoma (KIRC) database. Based on subclone analysis, VTT was predicted to primarily originate directly from the primary renal mass. A significantly higher prevalence of CELSR2 and TET2 alterations were identified in the VTTs compared with the matched primary tumors. An increased prevalence of DNA damage repair genes, especially those involved in homologous recombination repair and non-homologous end joining, was found in ccRCC patients with VTT. Notably, VTT was characterized by the increase incidence of copy number loss in the whole exome (p < 0.05), particularly in the chromosome 9 and 14 regions. Deletion of chromosome 9 and 14 was associated with worse survival, unfavorable clinical features, and the presence of an immunosuppressive microenvironment, which was characterized by higher infiltration of regulatory T cells, follicular helper T cells, and resting mast cells, but lower counts of resting CD4 memory T cells and CD8 positive T cells. A significantly lower count of CD4+ and CD8+ tumor-infiltrated lymphocytes was identified in the VTT samples comparing with matched primary tumor. Of note, three out of the four ccRCC patients with VTT in our cohort who were treated with the anti-PD-1 therapy exhibited remarkable remission in the renal mass but no notable shrinkage in the VTT mass. CONCLUSION: Our study revealed the genetic profile of Chinese ccRCC patients with VTT, and identified multiple features associated with known poor outcomes, including gene alterations and copy number loss. The deletions in chromosomes 9 and 14, and the associated immunosuppressive microenvironment may indicate limited sensitivity to anti-PD-1/PD-L1 monotherapy in VTT.

Genomic Profiling of Blood-Derived Circulating Tumor DNA from Patients with Advanced Biliary Tract Cancer.

Background: Biliary tract cancer is a highly lethal malignancy with poor clinical outcome. Accumulating evidence indicates targeted therapeutics may provide new hope for improving treatment response in BTC, hence better understanding the genomic profile is particularly important. Since tumor tissue may not be available for some patients, a complementary method is urgently needed. Circulating tumor DNA (ctDNA) provides a noninvasive means for detecting genomic alterations, and has been regarded as a promising tool to guide clinical therapies. Methods: Next-generation sequencing of 150 cancer-related genes was used to detect gene alterations in blood-derived ctDNA from 154 Chinese patients with BTC. Genomic alterations were analyzed and compared with an internal tissue genomic database and TCGA database. Results: 94.8% patients had at least one change detected in their ctDNA. The median maximum somatic allele frequency was 6.47% (ranging 0.1-34.8%). TP53 and KRAS were the most often mutated genes. The frequencies of single nucleotide variation in commonly mutated genes in ctDNA were similar to those detected in tissue samples, TP53 (35.1 vs. 40.4%) and KRAS (20.1 vs. 22.6%). Pathway analysis revealed that mutated genes were mapped to several key pathways including PI3K-Akt, p53, ErbB and Ras signaling pathway. In addition, patients harboring LRP1B, TP53, and ErbB family mutations presented significantly higher tumor mutation burden. Conclusions: These findings demonstrated that ctDNA testing by NGS was feasible in revealing genomic changes and could be a viable alternative to tissue biopsy in patients with metastatic BTC.

Genomic Features and Construction of Streamlined Genome Chassis of Nisin Z Producer Lactococcus lactis N8.

Lactococcus lactis is a commonly used fermenting bacteria in cheese, beverages and meat products. Due to the lack of simplified chassis strains, it has not been widely used in the fields of synthetic biology. Thus, the construction of lactic acid bacteria chassis strains becomes more and more important. In this study, we performed whole genome sequencing, annotation and analysis of L. lactis N8. Based on the genome analysis, we found that L. lactis N8 contains two large plasmids, and the function prediction of the plasmids shows that some regions are related to carbohydrate transport/metabolism, multi-stress resistance and amino acid uptake. L. lactis N8 contains a total of seven prophage-related fragments and twelve genomic islands. A gene cluster encoding a hybrid NRPS-PKS system that was found in L. lactis N8 reveals that the strain has the potential to synthesize novel secondary metabolites. Furthermore, we have constructed a simplified genome chassis of L. lactis N8 and achieved the largest amount of deletion of L. lactis so far. Taken together, the present study offers further insights into the function and potential role of L. lactis N8 as a model strain of lactic acid bacteria and lays the foundation for its application in the field of synthetic biology.

Genomic Feature of a Rare Case of Mix Small-Cell and Large-Cell Neuroendocrine Lung Carcinoma: A Case Report.

BACKGROUND: Cases of both of small- (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC) were rarely reported. Although typical cases are morphologically distinct, the distinction between LCNEC and SCLC is still controversial, with some LCNECs showing close morphologies with SCLC. Here, we reported on a patient who had tumor with a mix of SCLC and LCNEC and uncovered these components' histological and genomic features. CASE PRESENTATION: A 59-year-old man was diagnosed with lung cancer and had resection surgery in our hospital. The H&E and immunohistochemistry staining revealed that the tumor had 30%-35% LCNEC and 65%-70% SCLC cells. The whole-exome sequencing (WES) identified no potentially actionable alteration in the tumor sample but found five alterations all with allele frequency over 90%, including TP53 p.R273H, MYH8 p.Q1814K, SLC17A6 p.W505L, PTPN5 p.M40I, and RB1 p.L267X. The genomic results supported that these two different components shared a similar dominant clonal origin. Furthermore, fluorescence in situ hybridization analysis revealed that the LCNECs have a higher copy number of MET than the SCLC component while without notable difference in the copy number of HER2 and TP53. Chemotherapy with pemetrexed and carboplatin was administrated for two cycles after the surgery. Although the chest CT showed remission in the lung, he was diagnosed with bone metastasis in 1 year later. Then, he received chemotherapy with etoposide and carboplatin but had severe side effect, leading to the discontinuation of the regime. Unfortunately, he returned to the local hospital with supportive care and died shortly after. CONCLUSION: Based on these observations, we proposed that LCNEC and SCLC components in this patient may have a common clonal origin with dual mutations in TP53 and RB1, while the chromosome instability may cause multiple independent conversion that leads to LCNEC or SCLC morphologies.

An assessment of the genomics, comparative genomics and cellulose degradation potential of Mucilaginibacter polytrichastri strain RG4-7.

In this study, whole genome sequencing and comparative genomic analyses were performed for Mucilaginibacter polytrichastri RG4-7 and its carboxymethyl cellulose degradation potential was assessed. The results showed that the genome of strain RG4-7 was 5.84 Mb and contained 5019 predicted genes, in which a high proportion of strain-specific genes were related to carbohydrate metabolism. The carboxymethyl cellulose (CMC) degradation and cellulase activity tests revealed the strong cellulose degradation ability, CMCase and ß-glucosidase activity in strain RG4-7. Real-time RT-PCR testing of most cellulose degradation related glycoside hydrolase (GH) families showed that GH9 (OKS85969), GH1 (OKS85832), GH3 (OKS89331 and OKS85615) were significantly up-regulated when strain RG4-7 was inoculated with CMC-Na, which suggested that GH9, GH1 and GH3 might determine its cellulose degradation ability. Certainly, further research need to be done to elucidate cellulose degradation mechanisms in strain RG4-7 in order to develop its industrial application value in lignocellulosic biomass degradation and waste management.