CellTracer: a comprehensive database to dissect the causative multilevel interplay contributing to cell development trajectories.

During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.

Integrating bioinformatic strategies in spatial life science research.

As space exploration programs progress, manned space missions will become more frequent and farther away from Earth, putting a greater emphasis on astronaut health. Through the collaborative efforts of researchers from various countries, the effect of the space environment factors on living systems is gradually being uncovered. Although a large number of interconnected research findings have been produced, their connection seems to be confused, and many unknown effects are left to be discovered. Simultaneously, several valuable data resources have emerged, accumulating data measuring biological effects in space that can be used to further investigate the unknown biological adaptations. In this review, the previous findings and their correlations are sorted out to facilitate the understanding of biological adaptations to space and the design of countermeasures. The biological effect measurement methods/data types are also organized to provide references for experimental design and data analysis. To aid deeper exploration of the data resources, we summarized common characteristics of the data generated from longitudinal experiments, outlined challenges or caveats in data analysis and provided corresponding solutions by recommending bioinformatics strategies and available models/tools.

LncACTdb 3.0: an updated database of experimentally supported ceRNA interactions and personalized networks contributing to precision medicine.

LncACTdb 3.0 is a comprehensive database of experimentally supported interactions among competing endogenous RNA (ceRNA) and the corresponding personalized networks contributing to precision medicine. LncACTdb 3.0 is freely available at http://bio-bigdata.hrbmu.edu.cn/LncACTdb or http://www.bio-bigdata.net/LncACTdb. We have updated the LncACTdb 3.0 database with several new features, including (i) 5669 experimentally validated ceRNA interactions across 25 species and 537 diseases/phenotypes through manual curation of published literature, (ii) personalized ceRNA interactions and networks for 16 228 patients from 62 datasets in TCGA and GEO, (iii) sub-cellular and extracellular vesicle locations of ceRNA manually curated from literature and data sources, (iv) more than 10 000 experimentally supported long noncoding RNA (lncRNA) biomarkers associated with tumor diagnosis and therapy, and (v) lncRNA/mRNA/miRNA expression profiles with clinical and pathological information of thousands of cancer patients. A panel of improved tools has been developed to explore the effects of ceRNA on individuals with specific pathological backgrounds. For example, a network tool provides a comprehensive view of lncRNA-related, patient-specific, and custom-designed ceRNA networks. LncACTdb 3.0 will provide novel insights for further studies of complex diseases at the individual level and will facilitate the development of precision medicine to treat such diseases.

Green preparation of CaO-based CO2 adsorbent by calcium-induced hydrogenation of shell wastes at room/moderate temperature.

Capturing CO2 using clamshell/eggshell-derived CaO adsorbent can not only reduce carbon emissions but also alleviate the impact of trash on the environment. However, organic acid was usually used, high-temperature calcination was often performed, and CO2 was inevitably released during preparing CaO adsorbents from shell wastes. In this work, CaO-based CO2 adsorbent was greenly prepared by calcium-induced hydrogenation of clamshell and eggshell wastes in one pot at room/moderate temperature. CO2 adsorption experiments were performed in a thermogravimetric analyzer (TGA). The adsorption performance of the adsorbents obtained from the mechanochemical reaction (BM-C/E-CaO) was superior to that of the adsorbents obtained from the thermochemical reaction (Cal-C/E-CaO). The CO2 adsorption capacity of BM-C-CaO at 650 °C is up to 36.82 wt%, but the adsorption decay rate of the sample after 20 carbonation/calcination cycles is only 30.17%. This study offers an alternative energy-saving method for greenly preparing CaO-based adsorbent from shell wastes.

LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution.

Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision medicine. Here, we describe a database, LnCeCell (http://www.bio-bigdata.net/LnCeCell/ or http://bio-bigdata.hrbmu.edu.cn/LnCeCell/), which aims to document cellular-specific long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) networks for personalised characterisation of diseases based on the 'One Cell, One World' theory. LnCeCell is curated with cellular-specific ceRNA regulations from >94 000 cells across 25 types of cancers and provides >9000 experimentally supported lncRNA biomarkers, associated with tumour metastasis, recurrence, prognosis, circulation, drug resistance, etc. For each cell, LnCeCell illustrates a global map of ceRNA sub-cellular locations, which have been manually curated from the literature and related data sources, and portrays a functional state atlas for a single cancer cell. LnCeCell also provides several flexible tools to infer ceRNA functions based on a specific cellular background. LnCeCell serves as an important resource for investigating the gene regulatory networks within a single cell and can help researchers understand the regulatory mechanisms underlying complex microbial ecosystems and individual phenotypes.

Characterizing the variation of particles in varied sizes from a container truck in a port area.

The transportation of container trucks in urban areas not only frequently causes traffic jams but also produces severe air pollution. With regard to this consideration, measurements of particle concentrations and traffic volume on different polluted days were carried out to discover the varied characteristics of particles from container truck transportation in the port area. Based on the original data, descriptive statistics were performed firstly to reveal the statistical characteristics of particle number concentrations (PNC). The Kolmogorov-Smirnov test as well as the Anderson-Darling test was adopted to identify the "best-fit" distributions on PNC data while the corresponding maximum likelihood estimation was conducted to estimate the parameters of the identified distribution. Additionally, the Pearson correlation analysis and principal component analysis were performed respectively to reveal the relationships between traffic volume and PNC. The results showed that on a hazy day, PNC levels in the morning were generally higher than those in the afternoon, while on a non-hazy day, the results were opposite. Particles in all sizes on a non-hazy day and larger than 0.5 µm on a hazy day were verified to fit the lognormal distribution. In contrast to the particles below 2 µm, the particles above 2 µm exhibited higher correlations with the traffic flow of a container truck in the morning on a hazy day. These results indicate the importance of reducing air pollution from a container truck and provide policymakers with a foundation for possible measures in a port city.

Dependence receptor UNC5A restricts luminal to basal breast cancer plasticity and metastasis.

BACKGROUND: The majority of estrogen receptor-positive (ERα+) breast cancers respond to endocrine therapies. However, resistance to endocrine therapies is common in 30% of cases, which may be due to altered ERα signaling and/or enhanced plasticity of cancer cells leading to breast cancer subtype conversion. The mechanisms leading to enhanced plasticity of ERα-positive cancer cells are unknown. METHODS: We used short hairpin (sh)RNA and/or the CRISPR/Cas9 system to knockdown the expression of the dependence receptor UNC5A in ERα+ MCF7 and T-47D cell lines. RNA-seq, quantitative reverse transcription polymerase chain reaction, chromatin immunoprecipitation, and Western blotting were used to measure the effect of UNC5A knockdown on basal and estradiol (E2)-regulated gene expression. Mammosphere assay, flow cytometry, and immunofluorescence were used to determine the role of UNC5A in restricting plasticity. Xenograft models were used to measure the effect of UNC5A knockdown on tumor growth and metastasis. Tissue microarray and immunohistochemistry were utilized to determine the prognostic value of UNC5A in breast cancer. Log-rank test, one-way, and two-way analysis of variance (ANOVA) were used for statistical analyses. RESULTS: Knockdown of the E2-inducible UNC5A resulted in altered basal gene expression affecting plasma membrane integrity and ERα signaling, as evident from ligand-independent activity of ERα, altered turnover of phosphorylated ERα, unique E2-dependent expression of genes effecting histone demethylase activity, enhanced upregulation of E2-inducible genes such as BCL2, and E2-independent tumorigenesis accompanied by multiorgan metastases. UNC5A depletion led to the appearance of a luminal/basal hybrid phenotype supported by elevated expression of basal/stem cell-enriched ∆Np63, CD44, CD49f, epidermal growth factor receptor (EGFR), and the lymphatic vessel permeability factor NTN4, but lower expression of luminal/alveolar differentiation-associated ELF5 while maintaining functional ERα. In addition, UNC5A-depleted cells acquired bipotent luminal progenitor characteristics based on KRT14+/KRT19+ and CD49f+/EpCAM+ phenotype. Consistent with in vitro results, UNC5A expression negatively correlated with EGFR expression in breast tumors, and lower expression of UNC5A, particularly in ERα+/PR+/HER2- tumors, was associated with poor outcome. CONCLUSION: These studies reveal an unexpected role of the axon guidance receptor UNC5A in fine-tuning ERα and EGFR signaling and the luminal progenitor status of hormone-sensitive breast cancers. Furthermore, UNC5A knockdown cells provide an ideal model system to investigate metastasis of ERα+ breast cancers.

The effects of pig manure application on the spread of tetracycline resistance in bulk and cucumber rhizosphere soils: a greenhouse experiment.

It is important to understand the dynamics of tetracycline-resistant bacteria (TRB) and tetracycline resistance genes (TRGs) in bulk and rhizosphere soils for evaluating the spread of TRGs from pig manure to human. In this work, a greenhouse experiment was conducted to investigate the difference in abundance of TRB, tetracycline-resistant Escherichia coli (TRE), tetracycline-resistant Pseudomonas spp. (TRP), and TRGs between bulk and cucumber rhizosphere soils. The application of pig manure resulted in the long-term persistence of TRB, TRE, TRP, and TRGs in bulk soil and rhizosphere of cucumber for at least 65 days. Pig manure application dose was the major driving force in altering the abundances of TRB and TRE, whereas TRP was disturbed mainly by compartment (bulk soil or rhizosphere). Both TRE and the percentage of TRE in bulk and rhizosphere soils increased linearly with an increase in dose of pig manure. The exponential relationships between pig manure dose and TRP along with TRP percentage were also noted. There were significant differences in the relative abundances of TRGs between bulk and cucumber rhizosphere soils, suggesting the use of pig manure exerted a more lasting impact on the spread of TRGs in the rhizosphere than in the bulk soil.

Statistical modeling for sensitive detection of low-frequency single nucleotide variants.

BACKGROUND: Sensitive detection of low-frequency single nucleotide variants carries great significance in many applications. In cancer genetics research, tumor biopsies are a mixture of normal and tumor cells from various subpopulations due to tumor heterogeneity. Thus the frequencies of somatic variants from a subpopulation tend to be low. Liquid biopsies, which monitor circulating tumor DNA in blood to detect metastatic potential, also face the challenge of detecting low-frequency variants due to the small percentage of the circulating tumor DNA in blood. Moreover, in population genetics research, although pooled sequencing of a large number of individuals is cost-effective, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 2 % to 5 %; most fail to consider differential sequencing artifacts. RESULTS: We aimed to push down the frequency detection limit close to the position specific sequencing error rates by modeling the observed erroneous read counts with respect to genomic sequence contexts. 4 distributions suitable for count data modeling (using generalized linear models) were extensively characterized in terms of their goodness-of-fit as well as the performances on real sequencing data benchmarks, which were specifically designed for testing detection of low-frequency variants; two sequencing technologies with significantly different chemistry mechanisms were used to explore systematic errors. We found the zero-inflated negative binomial distribution generalized linear mode is superior to the other models tested, and the advantage is most evident at 0.5 % to 1 % range. This method is also generalizable to different sequencing technologies. Under standard sequencing protocols and depth given in the testing benchmarks, 95.3 % recall and 79.9 % precision for Ion Proton data, 95.6 % recall and 97.0 % precision for Illumina MiSeq data were achieved for SNVs with frequency > = 1 %, while the detection limit is around 0.5 %. CONCLUSIONS: Our method enables sensitive detection of low-frequency single nucleotide variants across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.

Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies.

BACKGROUND: Ion Torrent and Ion Proton are semiconductor-based sequencing technologies that feature rapid sequencing speed and low upfront and operating costs, thanks to the avoidance of modified nucleotides and optical measurements. Despite of these advantages, however, Ion semiconductor sequencing technologies suffer much reduced sequencing accuracy at the genomic loci with homopolymer repeats of the same nucleotide. Such limitation significantly reduces its efficiency for the biological applications aiming at accurately identifying various genetic variants. RESULTS: In this study, we propose a Bayesian inference-based method that takes the advantage of the signal distributions of the electrical voltages that are measured for all the homopolymers of a fixed length. By cross-referencing the length of homopolymers in the reference genome and the voltage signal distribution derived from the experiment, the proposed integrated model significantly improves the alignment accuracy around the homopolymer regions. CONCLUSIONS: Besides improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies with the proposed model, similar strategies can also be used on other high-throughput sequencing technologies that share similar limitations.

Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation.

Small insertions/deletions (INDELs) of ≤21 bp comprise 18% of all recorded mutations causing human inherited disease and are evident in 24% of documented Mendelian diseases. INDELs affect gene function in multiple ways: for example, by introducing premature stop codons that either lead to the production of truncated proteins or affect transcriptional efficiency. However, the means by which they impact post-transcriptional regulation, including alternative splicing, have not been fully evaluated. In this study, we collate disease-causing INDELs from the Human Gene Mutation Database (HGMD) and neutral INDELs from the 1000 Genomes Project. The potential of these two types of INDELs to affect binding-site affinity of RNA-binding proteins (RBPs) was then evaluated. We identified several sequence features that can distinguish disease-causing INDELs from neutral INDELs. Moreover, we built a machine-learning predictor called PinPor (predicting pathogenic small insertions and deletions affecting post-transcriptional regulation, http://watson.compbio.iupui.edu/pinpor/) to ascertain which newly observed INDELs are likely to be pathogenic. Our results show that disease-causing INDELs are more likely to ablate RBP-binding sites and tend to affect more RBP-binding sites than neutral INDELs. Additionally, disease-causing INDELs give rise to greater deviations in binding affinity than neutral INDELs. We also demonstrated that disease-causing INDELs may be distinguished from neutral INDELs by several sequence features, such as their proximity to splice sites and their potential effects on RNA secondary structure. This predictor showed satisfactory performance in identifying numerous pathogenic INDELs, with a Matthews correlation coefficient (MCC) value of 0.51 and an accuracy of 0.75.

Impacts of supplementing chemical fertilizers with organic fertilizers manufactured using pig manure as a substrate on the spread of tetracycline resistance genes in soil.

Using pig manure (PM) compost as a partial substitute for the conventional chemical fertilizers (CFs) is considered an effective approach in sustainable agricultural systems. This study aimed to analyze the impacts of supplementing CF with organic fertilizers (OFs) manufactured using pig manure as a substrate on the spread of tetracycline resistance genes (TRGs) as well as the community structures and diversities of tetracycline-resistant bacteria (TRB) in bulk and cucumber rhizosphere soils. In this study, three organic fertilizers manufactured using the PM as a substrate, namely fresh PM, common OF, and bio-organic fertilizer (BF), were supplemented with a CF. Composted manures combined with a CF did not significantly increase TRB compared with the CF alone, but PM treatment resulted in the long-term survival of TRB in soil. The use of CF+PM also increased the risk of spreading TRGs in soil. As beneficial microorganisms in BF may function as reservoirs for the spread of antibiotic resistance genes, care should be taken when adding them to the OF matrix. The PM treatment significantly altered the community structures and increased the species diversity of TRB, especially in the rhizosphere soil. BF treatment caused insignificant changes in the community structure of TRB compared with CF treatment, yet it reduced the species diversities of TRB in soil. Thus, the partial use of fresh PM as a substitute for CF could increase the risk of spread of TRGs. Apart from plant growth promotion, BF was a promising fertilizer owing to its potential ability to control TRGs.

Reward sensitivity predicts ice cream-related attentional bias assessed by inattentional blindness.

The cognitive mechanism underlying the association between individual differences in reward sensitivity and food craving is unknown. The present study explored the mechanism by examining the role of reward sensitivity in attentional bias toward ice cream cues. Forty-nine college students who displayed high level of ice cream craving (HICs) and 46 who displayed low level of ice cream craving (LICs) performed an inattentional blindness (IB) task which was used to assess attentional bias for ice cream. In addition, reward sensitivity and coping style were assessed by the Behavior Inhibition System/Behavior Activation System Scales and Simplified Coping Style Questionnaire. Results showed significant higher identification rate of the critical stimulus in the HICs than LICs, suggesting greater attentional bias for ice cream in the HICs. It was indicated that attentional bias for food cues persisted even under inattentional condition. Furthermore, a significant correlation was found between the attentional bias and reward sensitivity after controlling for coping style, and reward sensitivity predicted attentional bias for food cues. The mediation analyses showed that attentional bias mediated the relationship between reward sensitivity and food craving. Those findings suggest that the association between individual differences in reward sensitivity and food craving may be attributed to attentional bias for food-related cues.

Epidemiology of the non-head and neck sebaceous carcinoma and implications for distant metastasis screening.

Introduction: Extraocular sebaceous carcinoma (SC), particularly those outside the head and neck region, is rare and not well-described. Purpose: This study aimed to explore the epidemiology and identify the prognostic factors of non-head and neck SC, describe the possible relevant factors of distant metastasis, and provide implications for distant metastasis screening. Methods: Data from the 17 registries in the Surveillance, Epidemiology, and End Results database were retrospectively collected for patients with SC outside the head and neck from 2000 through 2020. Overall survival (OS) and disease-specific survival (DSS) were the primary endpoints. Survival analysis was conducted through Kaplan-Meier curves, and multivariate analysis was carried out using Cox proportional hazard models. Results: A total of 1,237 patients with SC outside the head and neck were identified. The mean age at diagnosis of the entire patient cohort was 67.7 years (30 to 90+ years), and the mean tumor size was 2.2 cm (0.1-16 cm). Patients with distant disease experienced the lowest OS (mean, 29.5 months) than those with localized disease and regional disease (p < 0.0001). Multivariate analysis revealed that age, tumor size, and stage were independent determinants of OS; age, stage, and primary site were independent determinants of DSS. Tumor grade and lymph node status had less prognostic value for survival. Undifferentiated tumors have a trend toward distant metastasis, especially those at the primary site of the trunk. Conclusion: The prognosis of the non-head and neck SC is excellent, while the survival of distant disease is very poor. Distant metastasis screening can be considered for undifferentiated tumors, especially those located in the trunk region with large tumor sizes.

Histopathology of telomerase reverse transcriptase promoter (TERT) mutated indeterminate thyroid nodules.

Objective: The objective of this study was to analyze the risk of malignancy and the histopathology of telomerase reverse transcriptase promoter (TERT) mutated cytologically indeterminate thyroid nodules (ITN). Methods: A PUBMED search of molecularly tested ITN was conducted and data on TERT mutated ITN with histopathology correlation were extracted. Results: Twenty-six manuscripts (published between 2014 and 2022) reported on 77 TERT mutated ITN. Sixty-five nodules were malignant (84 %), with 16 (25 %) described with high-risk histopathology, 5 (8 %) described as low-risk, and most without any description. Isolated TERT mutations were malignant in 26/30 ITNs (87 %) with 9 (35 %) described as high risk and none described as low risk. TERT + RAS mutated ITNs were malignant in 29/34 ITNs (85 %) with 3 (10 %) described as high risk and 4 (14 %) described as low risk. Finally, all 5 TERT + BRAFV600E mutated nodules were malignant and 3/5 (60 %) were described as high risk. Conclusion: TERT mutated ITNs have a high risk of malignancy (84 %), and the current data does not show a difference in malignancy rate between isolated TERT mutations and TERT + RAS co-mutated ITNs. When described, TERT + RAS co-mutated ITNs did not have a higher rate of high-risk histopathology as compared to isolated TERT mutated lesions. Most TERT mutated ITNs did not have a description of histopathology risk and the oncologic outcomes, including rate of recurrence, metastases, and disease specific survival, are unknown. Further data is needed to determine if TERT mutated ITNs should be subjected to aggressive initial treatment.

Analytical Validation of a Telomerase Reverse Transcriptase (TERT) Promoter Mutation Assay.

CONTEXT: TERT promoter mutated thyroid cancers are associated with a decreased rate of disease free and disease specific survival. High quality analytical validation of a diagnostic test promotes confidence in the results which inform clinical decision making. OBJECTIVE: To demonstrate the analytical validation of the Afirma TERT promoter mutation assay. METHODS: TERT promoter C228T and C250T variant detection in genomic DNA (gDNA) was analyzed by assessing variable DNA input and the limit of detection (LOD) of variant allele frequency (VAF). The negative and positive percent agreement (NPA and PPA) of the Afirma TERT test was examined against a reference primer pair as was the analytical specificity from potential interfering substances (RNA and blood gDNA). Further, the intra-run, inter-run and inter-laboratory reproducibility of the assay were tested. RESULTS: The Afirma TERT test is tolerant to variation in DNA input amount (7-13 ng) and can detect expected positive TERT promoter variants down to 5% VAF LOD at 7ng DNA input with > 95% sensitivity. Both NPA and PPA were 100% against the reference primer pair. The test remains accurate in presence of 20% RNA or 80% blood gDNA for an average patient sample that typically has 30% VAF. The test also demonstrated a 100% confirmation rate when compared with an external NGS-based reference assay executed in a non-Veracyte laboratory. CONCLUSION: The analytical robustness and reproducibility of the Afirma TERT test support its routine clinical use among thyroid nodules with indeterminate cytology that are Afirma GSC suspicious or among Bethesda V/VI nodules.

Reversible promoter demethylation of PDGFD confers gemcitabine resistance through STAT3 activation and RRM1 upregulation.

Drug resistance is a major problem in cancer treatment with traditional or targeted therapeutics. Gemcitabine is approved for several human cancers and the first line treatment for locally advanced or metastatic pancreatic ductal adenocarcinoma (PDAC). However, gemcitabine resistance frequently occurs and is a major problem in successful treatments of these cancers and the mechanism of gemcitabine resistance remains largely unknown. In this study, we identified 65 genes that had reversible methylation changes in their promoters in gemcitabine resistant PDAC cells using whole genome Reduced Representation Bisulfite Sequencing analyses. One of these genes, PDGFD, was further studied in detail for its reversible epigenetic regulation in expression and shown to contribute to gemcitabine resistance in vitro and in vivo via stimulating STAT3 signaling in both autocrine and paracrine manners to upregulate RRM1 expression. Analyses of TCGA datasets showed that PDGFD positively associates with poor outcome of PDAC patients. Together, we conclude that the reversible epigenetic upregulation plays an important role in gemcitabine resistance development and targeting PDGFD signaling alleviates gemcitabine resistance for PDAC treatment.

Characterization of tumour microenvironment reprogramming reveals invasion in epithelial ovarian carcinoma.

BACKGROUND: Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging. RESULTS: Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival. CONCLUSION: We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Real-World Performance of the Afirma Genomic Sequencing Classifier (GSC)-A Meta-analysis.

CONTEXT: The Afirma® GSC aids in risk stratifying indeterminate thyroid nodule cytology (ITN). The 2018 GSC validation study (VS) reported a sensitivity (SN) of 91%, specificity (SP) of 68%, positive predictive value (PPV) of 47%, and negative predictive value (NPV) of 96%. Since then, 13 independent real-world (RW) postvalidation studies have been published. OBJECTIVE: This study's objective is to compare the RW GSC performance to the VS metrics. METHODS: Rules and assumptions applying to this analysis include: (1) At least 1 patient with molecular benign results must have surgery for that study to be included in SN, SP, and NPV analyses. (2) Molecular benign results without surgical histology are considered true negatives (TN) (as are molecular benign results with benign surgical histology). (3) Unoperated patients with suspicious results are either excluded from analysis (observed PPV [oPPV] and observed SP [oSP]) or assumed histology negatives (false positives; conservative PPV [cPPV] and conservative SP [cSP]) 4. Noninvasive follicular thyroid neoplasm with papillary-like nuclear features is considered malignant. RESULTS: In RW studies, the GSC demonstrates a SN, oSP, oPPV, and NPV of 97%, 88%, 65%, 99% respectively, and conservative RW performance showed cSP of 80% and cPPV of 49%, all significantly higher than the VS except for SN and cPPV. There was also a higher benign call rate (BCR) of 67% in RW studies compared to 54% in the VS (P < 0.05). CONCLUSION: RW data for the Afirma GSC demonstrates significantly better oSP and oPPV performance than the VS, indicating an increased yield of cancers for resected GSC suspicious nodules. The higher BCR likely increases the overall rate of clinical observation in lieu of surgery.

Alt Event Finder: a tool for extracting alternative splicing events from RNA-seq data.

BACKGROUND: Alternative splicing increases proteome diversity by expressing multiple gene isoforms that often differ in function. Identifying alternative splicing events from RNA-seq experiments is important for understanding the diversity of transcripts and for investigating the regulation of splicing. RESULTS: We developed Alt Event Finder, a tool for identifying novel splicing events by using transcript annotation derived from genome-guided construction tools, such as Cufflinks and Scripture. With a proper combination of alignment and transcript reconstruction tools, Alt Event Finder is capable of identifying novel splicing events in the human genome. We further applied Alt Event Finder on a set of RNA-seq data from rat liver tissues, and identified dozens of novel cassette exon events whose splicing patterns changed after extensive alcohol exposure. CONCLUSIONS: Alt Event Finder is capable of identifying de novo splicing events from data-driven transcript annotation, and is a useful tool for studying splicing regulation.