Deciphering the Functional Roles of Individual Cancer Alleles Across Comprehensive Cancer Genomic Studies.

Cancer genome data has been growing in both size and complexity, primarily driven by advances in next-generation sequencing technologies, such as Pan-cancer data from TCGA, ICGC, and single-cell sequencing. Yet, discerning the functional role of individual genomic lesions remains a substantial challenge due to the complexity and scale of the data. Previously, we introduced REVEALER, which identifies groups of genomic alterations that significantly associate with target functional profiles or phenotypes, such as pathway activation, gene dependency, or drug response. In this paper, we present a new mathematical formulation of the algorithm. This version (REVEALER 2.0) is considerably more powerful than the original, allowing for rapid processing and analysis of much larger datasets and facilitating higher-resolution discoveries at the level of individual alleles. REVEALER 2.0 employs the Conditional Information Coefficient (CIC) to pinpoint features that are either complementary or mutually exclusive but still correlate with the target functional profile. The aggregation of these features provides a better explanation for the target functional profile than any single alteration on its own. This is indicative of scenarios where several activating genomic lesions can initiate or stimulate a key pathway or process. We replaced the initial three-dimensional kernel estimation with multiple precomputed one-dimensional kernel estimations, resulting in an approximate 150x increase in speed and efficiency. This improvement, combined with its efficient execution, makes REVEALER 2.0 suitable for much larger datasets and a more extensive range of genomic challenges.

Effects of application of rice husk biochar and limestone on cadmium accumulation in wheat under glasshouse and field conditions.

Cadmium (Cd) has seriously threatened the safe production of food crops. Passivator amendments are commonly used to control the soil Cd availability. Yet, few studies are tested to explore the effect of the combination of various amendments. Here, we investigated the effects of different amendments (2% rice husk biochar, 2% limestone, and 1% rice husk biochar + 1% limestone) on the growth and Cd accumulation of wheat in pot and field experiments. The results showed that under the low soil Cd condition, the maximum increase of soil pH (1.83) was found in the limestone treatment compared to CK in pot experiment. Compared with the CK, the treatment of rice husk biochar decreased soil Cd availability and grain Cd content by about 25% and 31.2%, respectively. In contrast, under high soil Cd condition, the highest soil pH was observed in limestone, while the lowest soil Cd availability and grain Cd concentrations were found in rice husk biochar treatment. In the field experiment, the treatment of 1% rice husk biochar + 1% limestone caused a significant increase of soil pH by about 28.2%, whereas the treatment of 2% rice husk biochar reduced soil Cd availability and grain Cd content by about 38.9% and 38.5% compared to the CK. Therefore, rice husk biochar showed great potential to reduce Cd availability and ensure safe food production.

Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma.

The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8+ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand-receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.

Analysis of the immune landscape in virus-induced cancers using a novel integrative mechanism discovery approach.

BACKGROUND: The mechanisms of carcinogenesis from viral infections are extraordinarily complex and not well understood. Traditional methods of analyzing RNA-sequencing data may not be sufficient for unraveling complicated interactions between viruses and host cells. Using RNA and DNA-sequencing data from The Cancer Genome Atlas (TCGA), we aim to explore whether virus-induced tumors exhibit similar immune-associated (IA) dysregulations using a new algorithm we developed that focuses on the most important biological mechanisms involved in virus-induced cancers. Differential expression, survival correlation, and clinical variable correlations were used to identify the most clinically relevant IA genes dysregulated in 5 virus-induced cancers (HPV-induced head and neck squamous cell carcinoma, HPV-induced cervical cancer, EBV-induced stomach cancer, HBV-induced liver cancer, and HCV-induced liver cancer) after which a mechanistic approach was adopted to identify pathways implicated in IA gene dysregulation. RESULTS: Our results revealed that IA dysregulations vary with the cancer type and the virus type, but cytokine signaling pathways are dysregulated in all virus-induced cancers. Furthermore, we also found that important similarities exist between all 5 virus-induced cancers in dysregulated clinically relevant oncogenic signatures and IA pathways. Finally, we also discovered potential mechanisms for genomic alterations to induce IA gene dysregulations using our algorithm. CONCLUSIONS: Our study offers a new approach to mechanism identification through integrating functional annotations and large-scale sequencing data, which may be invaluable to the discovery of new immunotherapy targets for virus-induced cancers.

Cardiovascular, cerebrovascular, and renal co-morbidities in COVID-19 patients: A systematic-review and meta-analysis.

BACKGROUND: COVID-19 has infected over 35 million people worldwide and led to over 1 million deaths. Several risk factors that increase COVID-19 severity have emerged, including age and a history of cardiovascular disease, hypertension, or kidney disease. However, a number of outstanding questions persist, including whether the above comorbidities correlate with increased mortality from COVID-19 or whether age is a significant confounding variable that accounts for the observed relationship between COVID-19 severity and other comorbidities. METHODS AND FINDINGS: We conducted a systematic review and meta-analysis of studies documenting COVID-19 patients with hypertension, cardiovascular disease, cerebrovascular disease, or chronic kidney disease. We classified COVID-19 cases into severe/non-severe or deceased/surviving and calculated the odds ratio (OR) for each of the four comorbidities in these cohorts. 36 studies, comprising 22,573 patients, are included in our meta-analysis. We found that hypertension is the most prevalent comorbidity in deceased COVID-19 patients (55.4%; CI: 49.4-61.3%), followed by cardiovascular disease (30.7%; CI: 22.6-38.8%), cerebrovascular disease (13.4%; CI: 9.12-19.2%), then chronic kidney disease (9.05%; CI: 5.57-15.0%). The risk of death is also significantly higher for patients with these comorbidities, with the greatest risk factor being chronic kidney disease (OR: 8.86; CI: 5.27-14.89), followed by cardiovascular disease (OR: 6.87; CI: 5.56-8.50), hypertension (OR: 4.87; CI: 4.19-5.66), and cerebrovascular disease (OR: 4.28; CI: 2.86-6.41). These risks are significantly higher than previously reported, while correlations between comorbidities and COVID-19 severity are similar to previously reported figures. Using meta-regression analysis with age as a moderating variable, we observed that age contributes to the observed risks but does not explain them fully. CONCLUSIONS: In this meta-analysis, we observed that cardiovascular, cerebrovascular, and kidney-related comorbidities in COVID-19 significantly contributes to greater risk of mortality and increased disease severity. We also demonstrated that age may not be a confounder to these associations.

Epitranscriptomic editing of the RNA N6-methyladenosine modification by dCasRx conjugated methyltransferase and demethylase.

N6-methyladenosine (m6A) is a common modification on endogenous RNA transcripts in mammalian cells. Technologies to precisely modify the RNA m6A levels at specific transcriptomic loci empower interrogation of biological functions of epitranscriptomic modifications. Here, we developed a bidirectional dCasRx epitranscriptome editing platform composed of a nuclear-localized dCasRx conjugated with either a methyltransferase, METTL3, or a demethylase, ALKBH5, to manipulate methylation events at targeted m6A sites. Leveraging this platform, we specifically and efficiently edited m6A modifications at targeted sites, reflected in gene expression and cell proliferation. We employed the dCasRx epitranscriptomic editor system to elucidate the molecular function of m6A-binding proteins YTHDF paralogs (YTHDF1, YTHDF2 and YTHDF3), revealing that YTHDFs promote m6A-mediated mRNA degradation. Collectively, our dCasRx epitranscriptome perturbation platform permits site-specific m6A editing for delineating of functional roles of individual m6A modifications in the mammalian epitranscriptome.

Effect of bamboo biochar on reducing grain cadmium content in two contrasting wheat genotypes.

Wheat is the second most important food crop worldwide, which is prone to accumulate cadmium (Cd). Accumulation of Cd in wheat grains depends not only on wheat genotype, but also largely on the availability of soil Cd and its internal distribution. In this study, several experiments were used to achieve low-grain Cd content: a field trial for wheat genotype screening, a soil incubation experiment to test passivation effect of bamboo biochar on soil Cd, and a soil pot experiment to examine bamboo biochar effect on wheat grain accumulation. The results showed that of the 243 wheat cultivars tested, the variation range of grain Cd content was 0.365-1.243 mg/kg, in a field with soil Cd of 3 mg/kg. The application of bamboo biochar reduced soil Cd availability, among which 5.0% bamboo biochar treatment had the greatest effect. The content of available Cd in soil treated with 5.0% bamboo biochar decreased by 0.32 mg/kg compared with the control in a 120-day incubation experiment. Effect of bamboo biochar (0, 0.1%, 1.0%, and 5.0%) on reducing grain Cd content in two wheat genotypes (Mianyou-1 and 1279-9) was investigated. The application of bamboo biochar decreased Cd uptake by plants, while distribution of Cd in different wheat plant parts was more controlled by the plant genetic characteristics. Compared with the control, Cd content in roots, straw, and grains was decreased by 34.06% (P < 0.05), 21.57%, and 23.33%, respectively, in low-grain Cd wheat cultivar 1279-9 by 5% bamboo biochar application. Overall, the combination of low-grain Cd accumulation wheat and bamboo biochar may be a feasible strategy to lessen grain Cd accumulation in Cd-contaminated soils.

Biomarker Value of miR-221 and miR-222 as Potential Substrates in the Differential Diagnosis of Papillary Thyroid Cancer Based on Data Synthesis and Bioinformatics Approach.

Background: MicroRNA (miRNA) has been reported to play a critical regulatory role in papillary thyroid carcinomas (PTC). However, the role of miR-221/222 in PTC remains unclear. Here, we performed this study to explore the diagnostic potentials and mechanisms of miR-221/222 in PTC. Methods: First, we systematically analyzed the diagnostic value of miR-221/222 in the diagnosis PTC by pooling the published studies. Afterwards, we performed comprehensive bioinformatics analysis including gene ontology analysis, pathway enrichment analysis and protein-protein interaction analysis to explore the potential mechanisms of miR-221/222 involved in PTC. Results: The overall sensitivity and specificity of miR-221/222 for PTC were 0.75 (95% CI: 0.70-0.80) and 0.80 (95% CI: 0.76-0.84) respectively with the AUC of 0.85 (95% CI: 0.81-0.88). The diagnostic performance varied among different subgroups including geographical locations, sample sources and sample sizes. Meanwhile, we found that a combination of miR-221/222 and other miRNAs when used in a diagnostic panel could improve the diagnostic accuracy than individual miR-221/222. Moreover, through the bioinformatics analysis, we confirmed that miR-221/222 targets were highly related to the molecular pathogenesis of PTC. The results revealed that miR-221/222 may exert important functions in PTC through thyroid hormone signaling pathway and some other key pathways by regulating some key genes. Conclusion: These findings indicated that miR-221/222 have the potential to serve as auxiliary tools for diagnosing PTC. Further prospective clinical trials should be performed to assess the accuracy of these findings in a larger cohort and determine the clinical uses.

Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

BACKGROUND: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. METHODS: In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone. RESULTS: We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. CONCLUSIONS: We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.

Influence of Intratumor Microbiome on Clinical Outcome and Immune Processes in Prostate Cancer.

Although 1 in 9 American men will receive a diagnosis of prostate cancer (PC), most men with this diagnosis will not die from it, as most PCs are indolent. However, there is a subset of patients in which the once-indolent PC becomes metastatic and eventually, fatal. In this study, we analyzed microbial compositions of intratumor bacteria in PC to determine the influence of the microbiome on metastatic growth. Using large-scale RNA-sequencing data and corresponding clinical data, we correlated the abundance of microbes to immune pathways and PC risk factors, identifying specific microbes that either significantly deter or contribute to cancer aggressiveness. Interestingly, most of the microbes we found appeared to play anti-tumor roles in PC. Since these anti-tumor microbes were overrepresented in tumor samples, we believe that microbes thrive in the tumor microenvironment, outcompete cancer cells, and directly mitigate tumor growth by recruiting immune cells. These include Listeria monocytogenes, Methylobacterium radiotolerans JCM 2831, Xanthomonas albilineans GPE PC73, and Bradyrhizobium japonicum, which are negatively correlated with Gleason score, Tumor-Node-Metastasis (TNM) stage, prostate-specific antigen (PSA) level, and Androgen Receptor (AR) expression, respectively. We also identified microbes that contribute to tumor growth and are positively correlated with genomic alterations, dysregulated immune-associated (IA) genes, and prostate cancer stem cells (PCSC) genes.

The role of Atg7-mediated autophagy in ionizing radiation-induced neural stem cell damage.

Impairment of neurogenesis is thought to be one of the important mechanisms underlying radiation-induced cognitive decline. Self-renewal and differentiation of neural stem cells (NSCs) are important components of neurogenesis. It has been well established that autophagy plays an important role in neurodegenerative conditions, however, its role in radiation-induced cognitive decline remains unclear. Our previous studies have found that ionizing radiation (IR) induces autophagy in mouse neurons, and minocycline, an antibiotic that can cross the blood-brain barrier, protects neurons from radiation-induced apoptosis through promoting autophagy, thus may contribute to the improvement of mouse cognitive performance after whole-brain irradiation. In the present study, we investigated whether autophagy is involved in radiation-induced damage in self-renewal and differentiation of NSCs. We found that NSCs were extremely sensitive to IR. Irradiation induced autophagy in NSCs in a dose-dependent manner. Atg7 knockdown significantly decreased autophagy, thus increased the apoptosis levels in irradiated NSCs, suggesting that autophagy protected NSCs from radiation-induced apoptosis. Moreover, compared with the negative control NSCs, the neurosphere size was significantly reduced and the neuronal differentiation was notably inhibited in Atg7-deficient NSCs after irradiation, indicating that autophagy defect could exacerbate radiation-induced reduction in NSC self-renewal and differentiation potential. In conclusion, down-regulating autophagy by selective Atg7 knockdown in NSCs enhanced radiation-induced NSC damage, suggesting an important protective role of autophagy in maintaining neurogenesis. Along with the protective effect of autophagy on irradiated neurons, our results on NSCs not only shed the light on the involvement of autophagy in the development of radiation-induced cognitive decline, but also provided a potential target for preventing cognitive impairment after cranial radiation exposure.

Studies of the Anti-amnesic Effects and Mechanisms of Single and Combined Use of Donepezil and Ginkgo Ketoester Tablet on Scopolamine-Induced Memory Impairment in Mice.

Ginkgo ketoester tablets (GT) and donepezil were a clinically used combination for the treatment of Alzheimer's disease (AD). The aim of the study was undertaken to investigate the antiamnesic effects of the two drugs alone and in combination through in vivo models of the Morris water maze along with in vitro antioxidants, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). The potential mechanisms were speculated by the activities of acetylcholine (ACh), AChE, superoxide dismutase (SOD), and malondialdehyde (MDA) and the protein expression of brain-derived neurotrophic factor (BDNF) and tyrosine protein kinase B (TrkB). The combination group showed a concentration-dependent inhibition of cholinesterase and antioxidation. As far as its mechanism was concerned, the combination of two drugs exerted excellent effects on oxidative stress, cholinergic pathway damage, and inactivation of the BDNF-TrkB signaling pathway. Additionally, to elucidate the binding mechanism of GT active ingredients into the structure of AChE, the results of molecular docking studies indicated that hydrogen and/or hydrophobic bonds might play an important role in their binding process. Thus, the combination of drugs could treat AD perfectly and further verify the scientific rationality of clinical medication.

Time-resolved fluorescent immunoassay-based combined detection of procalcitonin, C-reactive protein, heparin binding protein, and serum amyloid A1 to improve the diagnostic accuracy of early infection.

BACKGROUND: Serological tests are indispensable in the diagnosis of early infection. At present, only procalcitonin (PCT) and C-reactive protein (CRP) are commonly used in clinical practice. Recently, serum amyloid A1 (SAA1) and heparin binding protein (HBP) have been shown to be new biomarkers, because SAA1 is highly sensitive and specific for viral infections, and HBP is predictive for septic shock. In this study, PCT, CRP, HBP, and SAA1 were detected in different combinations to improve the diagnostic accuracy of early infection using the biotin-avidin amplifying system-based time-resolved fluorescent immunoassay (BA-TRFIA). METHODS: A time-resolved fluorescent immunoassay for PCT, CRP, HBP, and SAA1 was developed and then tested in a clinical setting. All experiments were carried out using the DR6608 time-resolved fluorescent immunoassay analyzer. RESULTS: The cutoff values of PCT, CRP, HBP, and SAA1 were 0.05 µg/L, 5.59 mg/L, 3.83 µg/L, and 1.56 mg/L, respectively. The area under the ROC curve (AUC) showed that PCT Ëƒ SAA1 Ëƒ CRP Ëƒ HBP > 0.8. A methodological comparison of the results showed that a combination of the four biomarkers had the highest accuracy for the diagnosis of infectious diseases. CONCLUSION: The time-resolved fluorescent immunoassay-based combined detection of PCT, CRP, HBP, and SAA1 was shown to significantly improve the diagnostic accuracy of early infection. Thus, our results indicate that combined detection based on BA-TRFIA may represent a promising strategy in the clinical diagnosis of infection.

Optimization of Ultrasound-Assisted Extraction Followed by Macroporous Resin Purification for Maximal Recovery of Functional Components and Removal of Toxic Components from Ginkgo biloba Leaves.

In the present study, the process of ultrasound-assisted extraction (UAE) followed by macroporous resin purification was successfully developed to achieve maximal recovery of functional components (flavonoids and ginkgolides) with minimal contents of toxic components (alkylphenols) from Ginkgo biloba leaves. Three effective extracted factors including HAc%, EtOH%, and UAE power were screened by Plackett-Burman design (PBD). The important variables were further optimized by rotatable central composite design (RCCD). By combination of PBD and RCCD, the resulting optimal UAE conditions were as follows: HAc% of 1.8%, EtOH% of 63%, ultrasound power of 303 W, G. biloba leaves powder amount of 1.0 g (solvent-to-solid ratio 40 mL/g), particle size of 60 mesh, extraction time of 40 min, and extraction temperature of 45°C. Under the optimum conditions, the yield of flavonoids was 25.1 ± 0.81 mg/g, ginkgolides was 10.6 ± 0.57 mg/g, and alkylphenols was 3.96 ± 0.31 mg/g. Moreover, the further enriching the functional components and removing toxic components from the obtained extracts of G. biloba leaves using the above optimum UAE condition was successfully achieved by macroporous resin DA-201. After column adsorption and desorption on DA-201, the content of total flavonoids was 36.51 ± 1.53%, ginkgolides was 13.24 ± 0.85%, and alkylphenols was 7.0 ± 1.0 µg/g from the obtained dry extracts (drug to extract ratio of 45-50:1) of G. biloba leaves which were complied with Chinese pharmacopoeias.

Multi-Response Optimization of Ultrasonic Assisted Enzymatic Extraction Followed by Macroporous Resin Purification for Maximal Recovery of Flavonoids and Ginkgolides from Waste Ginkgo biloba Fallen Leaves.

In the present study, the process of ultrasonic assisted enzymatic extraction (UAEE), followed by macroporous resin purification, was successfully developed to achieve maximal recovery of flavonoids and ginkgolides from Ginkgo biloba fallen leaves (GBFL). Three effective extracted factors, including UAE power, EtOH%, and the amount of cellulase were screened by Plackett⁻Burman design (PBD). The important variables were further optimized by rotatable central composite design (RCCD). After the combination of PBD and RCCD, the resulting optimal UAEE conditions were as follows: UAE power of 218 W; EtOH% of 68%; the amount of cellulase of 8.4 mg; UAE temperature of 40 °C; UAE time of 20 min; pH of 5.0; and, sample particle size of 40 mesh. Under the optimum conditions; the yields of flavonoids were 0.74 ± 0.05% (n = 3) and ginkgolides was 0.42 ± 0.06% (n = 3), which were close to the predicted values. Moreover, the further enriching flavonoids and ginkgolides from the obtained GBFL extracts using the above optimum UAEE condition was successfully achieved by macroporous resin DA-201. After column adsorption and desorption on DA-201; the percentage of total flavonoids was (25.36 ± 1.03)%; ginkgolides was (12.43 ± 0.85)% and alkylphenols was (0.003 ± 0.0005)% from the obtained dry extracts of GBFL which were complied with Chinese pharmacopoeias. Therefore, the present study provided a convenient and efficient method for extraction and purification of flavonoids and ginkgolides from waste GBFL.