Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells.

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

An Exosome-based Transcriptomic Signature for Noninvasive, Early Detection of Patients With Pancreatic Ductal Adenocarcinoma: A Multicenter Cohort Study.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and most patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lacks adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly micro RNAs (miRNAs), offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC. METHODS: Small RNA sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 nondisease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs were prioritized that discriminated patients with PDAC from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n = 191) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. RESULTS: The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (area under the curve [AUC] = 0.98 training cohort; AUC = 0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages I and II; AUC = 0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/mL; AUC = 0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC = 0.99 vs AUC = 0.86 for CA19-9 alone). CONCLUSIONS: In this study, an exosome-based liquid biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.

An integrated workflow for biomarker development using microRNAs in extracellular vesicles for cancer precision medicine.

EV-miRNAs are microRNA (miRNA) molecules encapsulated in extracellular vesicles (EVs), which play crucial roles in tumor pathogenesis, progression, and metastasis. Recent studies about EV-miRNAs have gained novel insights into cancer biology and have demonstrated a great potential to develop novel liquid biopsy assays for various applications. Notably, compared to conventional liquid biomarkers, EV-miRNAs are more advantageous in representing host-cell molecular architecture and exhibiting higher stability and specificity. Despite various available techniques for EV-miRNA separation, concentration, profiling, and data analysis, a standardized approach for EV-miRNA biomarker development is yet lacking. In this review, we performed a substantial literature review and distilled an integrated workflow encompassing important steps for EV-miRNA biomarker development, including sample collection and EV isolation, EV-miRNA extraction and quantification, high-throughput data preprocessing, biomarker prioritization and model construction, functional analysis, as well as validation. With the rapid growth of "big data", we highlight the importance of efficient mining of high-throughput data for the discovery of EV-miRNA biomarkers and integrating multiple independent datasets for in silico and experimental validations to increase the robustness and reproducibility. Furthermore, as an efficient strategy in systems biology, network inference provides insights into the regulatory mechanisms and can be used to select functionally important EV-miRNAs to refine the biomarker candidates. Despite the encouraging development in the field, a number of challenges still hinder the clinical translation. We finally summarize several common challenges in various biomarker studies and discuss potential opportunities emerging in the related fields.

Diagnostic efficacy of circular RNAs as noninvasive, liquid biopsy biomarkers for early detection of gastric cancer.

BACKGROUND: Majority of gastric cancers (GC) are diagnosed at advanced stages which contributes towards their poor prognosis. In view of this clinical challenge, identification of non-invasive biomarker for early diagnosis is imperative. Herein, we aimed to develop a non-invasive, liquid-biopsy based assay by using circular RNAs (circRNAs) as molecular biomarkers for early detection of GC. METHODS: We performed systematic biomarker discovery and validation of the candidate circRNAs in matched tissue specimens of GC and adjacent normal mucosa. Next, we translated the discovered circRNA based biomarker panel into serum samples in a training and validation cohort of GC patients (n = 194) and non-disease controls (n = 94) and evaluated their diagnostic performance. In addition, we measured the expression of circRNAs in serum samples of pre- and post-surgical GC patients and evaluated the specificity of circRNAs biomarker panel with respect to other gastro-intestinal (GI) malignancies. RESULTS: We identified 10-circRNAs in the discovery phase with subsequent validation in a pilot cohort of GC tissue specimens. Using a training cohort of patients, we developed an 8-circRNA based risk-prediction model for the diagnosis of GC. We observed that our biomarker panel robustly discriminated GC patients from non-disease controls with an AUC of 0.87 in the training, and AUC of 0.83 in the validation cohort. Notably, the biomarker panel could robustly identify even early-stage GC patients, regardless of their tumor histology (diffuse vs. intestinal). The decreased expression of circRNAs in post-surgery serum specimens indicated their tumor-specificity and their potential source of origin in the systemic circulation. CONCLUSIONS: We identified a panel of 8-circRNAs as non-invasive, liquid-biopsy biomarkers which might serve as potential diagnostic biomarkers for the early detection of GC.

A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study.

BACKGROUND: Currently, there is no clinically relevant non-invasive biomarker for early detection of esophageal squamous cell carcinoma (ESCC). Herein, we established and evaluated a circulating microRNA (miRNA)-based signature for the early detection of ESCC using a systematic genome-wide miRNA expression profiling analysis. METHODS: We performed miRNA candidate discovery using three ESCC tissue miRNA datasets (n = 108, 238, and 216) and the candidate miRNAs were confirmed in tissue specimens (n = 64) by qRT-PCR. Using a serum training cohort (n = 408), we conducted multivariate logistic regression analysis to develop an ESCC circulating miRNA signature and the signature was subsequently validated in two independent retrospective and two prospective cohorts. RESULTS: We identified eighteen initial miRNA candidates from three miRNA expression datasets (n = 108, 238, and 216) and subsequently validated their expression in ESCC tissues. We thereafter confirmed the overexpression of 8 miRNAs (miR-103, miR-106b, miR-151, miR-17, miR-181a, miR-21, miR-25, and miR-93) in serum specimens. Using a serum training cohort, we developed a circulating miRNA signature (AUC:0.83 [95%CI:0.79-0.87]) and the diagnostic performance of the miRNA signature was confirmed in two independent validation cohorts (n = 126, AUC:0.80 [95%CI:0.69-0.91]; and n = 165, AUC:0.89 [95%CI:0.83-0.94]). Finally, we demonstrated the diagnostic performance of the 8-miRNA signature in two prospective cohorts (n = 185, AUC:0.92, [95%CI:0.87-0.96]); and (n = 188, AUC:0.93, [95%CI:0.88-0.97]). Importantly, the 8-miRNA signature was superior to current clinical serological markers in discriminating early stage ESCC patients from healthy controls (p < 0.001). CONCLUSIONS: We have developed a novel and robust circulating miRNA-based signature for early detection of ESCC, which was successfully validated in multiple retrospective and prospective multinational, multicenter cohorts.

GIPS: A Software Guide to Sequencing-Based Direct Gene Cloning in Forward Genetics Studies.

The Gene Identification via Phenotype Sequencing (GIPS) software considers a range of experimental and analysis choices in sequencing-based forward genetics studies within an integrated probabilistic framework, which enables direct gene cloning from the sequencing of several unrelated mutants of the same phenotype without the need to create segregation populations. GIPS estimates four measurements to help optimize an analysis procedure as follows: (1) the chance of reporting the true phenotype-associated gene; (2) the expected number of random genes that may be reported; (3) the significance of each candidate gene's association with the phenotype; and (4) the significance of violating the Mendelian assumption if no gene is reported or if all candidate genes have failed validation. The usage of GIPS is illustrated with the identification of a rice (Oryza sativa) gene that epistatically suppresses the phenotype of the phosphate2 mutant from sequencing three unrelated ethyl methanesulfonate mutants. GIPS is available at https://github.com/synergy-zju/gips/wiki with the user manual and an analysis example.

GCclassifier: An R package for the prediction of molecular subtypes of gastric cancer.

Gastric cancer (GC) is one of the most commonly diagnosed malignancies, threatening millions of lives worldwide each year. Importantly, GC is a heterogeneous disease, posing a significant challenge to the selection of patients for more optimized therapy. Over the last decades, extensive community effort has been spent on dissecting the heterogeneity of GC, leading to the identification of distinct molecular subtypes that are clinically relevant. However, so far, no tool is publicly available for GC subtype prediction, hindering the research into GC subtype-specific biological mechanisms, the design of novel targeted agents, and potential clinical applications. To address the unmet need, we developed an R package GCclassifier for predicting GC molecular subtypes based on gene expression profiles. To facilitate the use by non-bioinformaticians, we also provide an interactive, user-friendly web server implementing the major functionalities of GCclassifier. The predictive performance of GCclassifier was demonstrated using case studies on multiple independent datasets.

Effects of steam and CO2 on gasification tar composition and evolution of aromatic compounds.

The removal of tar is conducive to improving the energy efficiency of downstream equipment and reducing the damage caused to it. In this study, a two-stage continuous feeding apparatus was developed to explore the yield and characteristics of tar produced from the co-gasification of microcrystalline cellulose (MCC) and polyethylene (PE) under separate and mixed atmospheres of steam and CO2. The tar yield can effectively reduce to 2.27 % when the steam and feedstock mass ratio (S/F) is 0.8. CO2 can partially substitute the steam in the gasification process, which can effectively promote a decrease in benzofuran. Furthermore, Gaussian software was employed to analyze the evolution mechanism of aromatic compounds. When the temperature is more than 800 °C, hydrogen consumption in the benzene cracking process is reduced, which is instrumental in improving the quality of syngas. Naphthalene is prone to form through the recombination of two cyclopentadienyls. Controlling the cyclization of cyclopentadienyls is a critical step in reducing the formation of polycyclic aromatic hydrocarbons. H and OH radicals are critical in phenol and benzofuran cracking, respectively. Although radicals act differently on specific aromatic compounds, the gasification effect of CO2 is less than that of steam because steam can provide both H and OH radicals, whereas CO2 needs to consume H radicals to generate OH radicals. The results provide beneficial guidance for controlling tar formation.

Effects of local domestication warrant attention in honey bee population genetics.

Honey bees, Apis mellifera, have for millennia been managed and exploited by humans and introduced into most suitable regions worldwide. However, given the lack of records for many introduction events, treating A. mellifera populations as native would predictably bias genetic studies regarding origin and evolution. Here, we used the Dongbei bee, a well-documented population, introduced beyond the natural distribution range approximately 100 years ago, to elucidate the effects of local domestication on animal population genetic analyses. Strong domestication pressure was detected in this population, and the genetic divergence between Dongbei bee and its ancestral subspecies was found to have occurred at the lineage level. Results of phylogenetic and time divergence analyses could consequently be misinterpreted. Proposing new subspecies or lineages and performing analyses of origin should thus strive to eliminate anthropogenic effects. We highlight the need for definitions of landrace and breed in honey bee sciences and make preliminary suggestions.

iRGvalid: A Robust in silico Method for Optimal Reference Gene Validation.

BACKGROUND: Appropriate reference genes are critical to accurately quantifying relative gene expression in research and clinical applications. Numerous efforts have been made to select the most stable reference gene(s), but a consensus has yet to be achieved. In this report, we propose an in silico reference gene validation method, iRGvalid, that can be used as a universal tool to validate the reference genes recommended from different resources so as to identify the best ones without a need for any wet lab validation tests. METHODS: iRGvalid takes advantage of high throughput gene expression data and is built on a double-normalization strategy. First, the expression level of each individual gene is normalized against the total gene expression level of each sample, followed by a target gene normalization to the candidate reference gene(s). Linear regression analysis is then performed between the pre- and post- normalized target gene across the whole sample set to evaluate the stability of the reference gene(s), which is positively associated with the Pearson correlation coefficient, Rt. The higher the Rt value, the more stable the reference gene. We applied iRGvalid to 14 candidate reference genes to validate and identify the most stable reference genes in four cancer types: lung adenocarcinoma, breast cancer, colon adenocarcinoma, and nasopharyngeal cancer. The stability of the reference gene is evaluated both individually and in groups of all possible combinations. RESULTS: Highly stable reference genes resulted in high Rt values regardless of the target gene used. The highest stability was achieved with a specific combination of 3 to 6 reference genes. A few genes were among the best reference genes across the cancer types studied here. CONCLUSION: iRGvalid provides an easy and robust method to validate and identify the most stable reference gene or genes from a pool of candidate reference genes. The inclusivity of large expression data sets as well as the direct comparison of candidate reference genes makes it possible to identify reference genes with universal quality. This method can be used in any other gene expression studies when large cohorts of expression data are available.

Effect of steam on the homogeneous conversion of tar contained from the co-pyrolysis of biomass and plastics.

The co-pyrolysis tar formed from microcrystalline cellulose (MCC) and polyethylene (PE) was used to study their further conversion path under the effect of steam. This paper addressed the yield and transformation of tar with different steam/feedstock mass ratios (S/F= 0.8, 1.6) in a two-stage fixed bed when the two stages' furnace temperature was set at 600°C and 800°C, separately. Compared with pyrolysis, steam promoted tar cracking effectively, the tar yield decreased at least 1/3. However, when the S/F ratio increases to 1.6, the cracking effect of tar is not further improved. The tar yield depended more on the PE content in the mixture, which was enhanced with PE increment. Besides, the H/C atom ratio was related to the conversion path of tar. Steam was beneficial to the cracking of compounds, but the generated hydrogen radicals affected the direction of the subsequent reaction. The steam mainly promotes the cracking of long-chain hydrocarbons, accompanied by cyclization and aromatization when the steam was limited. Nevertheless, the chain compounds are hard to crack efficiently when the steam was excessive, and the cyclization and aromatization processes were hindered due to the apparent effect of hydrogenation.

Quantifying contrast of latent fingerprints developed by fluorescent nanomaterials based on spectral analysis.

Fluorescent nanoparticles (NPs) have been used to develop latent fingerprints with enhanced contrast. However, a method for quantifying the contrast is still lacking, making it impossible to achieve quantitative comparison in the contrast enhancement between different fingerprint developing agents. Here we proposed a new method to quantify the developed contrast using two indexes when fluorescent NPs were used to develop the latent fingerprint. One is the intensity index (I) defined as the ratio between the integrated fluorescence intensities of the signal and background in the fluorescence spectra of the developed fingerprint. Another is the chroma index (C) determined from the color difference between developed fingerprints and their substrates in the chromaticity graph. We defined the developed contrast as the product of the chroma index and the common logarithm of the intensity index (C·lg I), and validated this method using both down- and up-conversion fluorescent NPs and on a variety of different substrates (glass, marble, red paper and money). We showed that the developed contrast quantified by our method effectively reflected the true contrast but the intensity or chroma index alone was not always effective. This work opens up a new avenue to quantifying and enhancing the developed contrast.

Circulating miRNA Signature Predicts Response to Preoperative Chemoradiotherapy in Locally Advanced Rectal Cancer.

Patients with locally advanced rectal cancer (LARC) are recommended to receive preoperative chemoradiotherapy (PCRT) followed by surgery. Response to PCRT varies widely: 60%-70% of patients with LARC do not derive therapeutic benefit from PCRT, whereas 15%-20% of patients achieve pathologic complete response (pCR). We sought to develop a liquid biopsy assay for identifying response to PCRT in patients with LARC. MATERIALS AND METHODS: We analyzed two genome-wide microRNA (miRNA) expression profiling data sets from tumor tissue samples for in silico discovery (GSE68204) and validation (GSE29298). We prioritized biomarkers in pretreatment plasma specimens from clinical training (n = 41; 15 responders and 26 nonresponders) and validation (n = 65; 29 responders and 36 nonresponders) cohorts of patients with LARC. We developed an integrated miRNA panel and established a risk assessment model, which was combined with the miRNA panel and carcinoembryonic antigen levels. RESULTS: Our comprehensive discovery effort identified an 8-miRNA panel that robustly predicted response to PCRT, with an excellent accuracy in the discovery (area under the curve [AUC] = 0.95) and validation (AUC = 0.92) cohorts. We successfully established a circulating miRNA panel with remarkable diagnostic accuracy in the clinical training (AUC = 0.82) and validation (AUC = 0.81) cohorts. Moreover, the predictive accuracy of the panel was significantly superior to conventional clinical factors in both cohorts (P < .01) and the risk assessment model was superior (AUC = 0.83). Finally, we applied our model to detect patients with pathologic complete response and showed that it was dramatically superior to currently used pathologic features (AUC = 0.92). CONCLUSION: Our novel risk assessment signature for predicting response to PCRT has a potential for clinical translation as a liquid biopsy assay in patients with LARC.

Assessment of the Diagnostic Efficiency of a Liquid Biopsy Assay for Early Detection of Gastric Cancer.

Importance: Noninvasive detection of early-stage disease is a key strategy for reducing gastric cancer (GC)-associated patient mortality. Objective: To establish a novel, noninvasive, microRNA (miRNA)-based signature for the early detection of GC using a comprehensive biomarker discovery approach with retrospective and prospective validation. Design, Setting, and Participants: This diagnostic study was conducted in 4 phases using publicly available genome sequences and tissue samples from patients at an academic medical center in Japan, and validated with retrospective multicenter cohorts of patients with GC. Three tissue miRNA data sets were used to identify a miRNA signature that discriminated GC vs normal tissues. The robustness of this signature was assessed in serum from 2 retrospective cohorts of patients with GC. A risk-scoring model was derived, then the performance of the miRNA signature was evaluated in a prospective cohort of patients with GC. The robustness of the miRNA signature was compared with current blood-based markers, and a cost-effectiveness analysis of the miRNA signature against the current practice of endoscopy was performed. All clinical samples used for this study were collected and data analyzed between April 1997 and March 2018. Main Outcomes and Measures: Assessment of diagnostic efficiency on the basis of area under the curve (AUC), specificity, and sensitivity. Results: The data sets for the genome-wide expression profiling analysis stage included 598 total patient samples (284 [55.4%] from men; mean [SE] patient age, 65.7 [0.5] years). The resulting 10-miRNA signature was validated in 2 retrospective GC serum cohorts (586 patients; 348 [59.4%] men, mean [SE] age, 66.0 [0.7] years), which led to the establishment of a 5-miRNA signature (AUC, 0.90; 95% CI, 0.85-0.94) that also exhibited high levels of diagnostic performance in patients with stage I disease (AUC, 0.89; 95% CI, 0.83-0.94). A risk-scoring model was derived and the assay was optimized to a minimal number of miRNAs. The performance of the resulting 3-miRNA signature was then validated in a prospective cohort of patients with GC (349 patients; 124 [70.5%] men, median [range] age, 66.0 [0.66] years). The final 3-miRNA signature (miR-18a, miR-181b, and miR-335) exhibited high diagnostic accuracy in all stages of patients (AUC, 0.86; 95% CI 0.83-0.90), including in patients with stage I disease (AUC, 0.85; 95% CI, 0.79-0.91). Furthermore, this miRNA signature was superior to currently used blood markers and outperformed the endoscopic screening in a cost-effectiveness analysis (incremental cost-effectiveness ratio, CNY ¥16162.5 per quality-adjusted life-year [USD $2304.80 per quality-adjusted life-year]). Conclusions and Relevance: These results suggest the potential clinical significance of the 3-miRNA signature as a noninvasive, cost-effective, and facile assay for the early detection of GC.

Cleavage and Polyadenylation Specific Factor 1 Promotes Tumor Progression via Alternative Polyadenylation and Splicing in Hepatocellular Carcinoma.

Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism required for cleavage and polyadenylation (CPA) of the 3' untranslated region (3' UTR) of mRNAs. Several aberrant APA events have been reported in hepatocellular carcinoma (HCC). However, the regulatory mechanisms underlying APA remain unclear. In this study, we found that the expression of cleavage and polyadenylation specific factor 1 (CPSF1), a major component of the CPA complex, was significantly increased in HCC tissues and correlated with unfavorable survival outcomes. Knockdown of CPSF1 inhibited HCC cell proliferation and migration, whereas overexpression of CPSF1 caused the opposite effect. Based on integrative analysis of Iso-Seq and RNA-seq data from HepG2.2.15 cells, we identified a series of transcripts with differential 3' UTR lengths following the knockdown of CPSF1. These transcripts were related to the biological functions of gene transcription, cytoskeleton maintenance, and endomembrane system transportation. Moreover, knockdown of CPSF1 induced an increase in alternative splicing (AS) events in addition to APA. Taken together, this study provides new insights into our understanding of the post-transcriptional regulatory mechanisms in HCC and implies that CPSF1 may be a potential prognostic biomarker and therapeutic target for HCC.