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Despite the existence of effective drugs used to treat inflammatory bowel disease (IBD), many patients fail to respond or lose response over time. Further, many drugs can carry serious adverse effects, including increased risk of infections and malignancies. Saffron (Crocus sativus) has been reported to have anti-inflammatory properties. Its protective role in IBD and how the microbiome and metabolome play a role has not been explored extensively. We aimed to establish whether saffron treatment modulates the host microbiome and metabolic profile in experimental colitis. Colitis was induced in C57BL/6 mice with 3% DSS and treated with either saffron in a dose of 20 mg/kg body weight or vehicle through daily gavage. On day 10, stool pellets from mice were collected and analyzed to assess saffron’s effect on fecal microbiota and metabolites through 16S rRNA sequencing and untargeted primary metabolite analysis. Saffron treatment maintained gut microbiota homeostasis by counter-selecting pro-inflammatory bacteria and maintained Firmicutes/Bacteroides ratio, which was otherwise disturbed by DSS treatment. Several metabolites (uric acid, cholesterol, 2 hydroxyglutaric acid, allantoic acid, 2 hydroxyhexanoic acid) were altered significantly with saffron treatment in DSS-treated mice, and this might play a role in mediating saffron’s colitis-mitigating effects. These data demonstrate saffron’s therapeutic potential, and its protective role is modulated by gut microbiota, potentially acting through changes in metabolites.

Major advances have been made in the field of precision medicine for treating cancer. However, many open questions remain that need to be answered to realize the goal of matching every cancer patient to the most efficacious therapy. To facilitate these efforts, we have developed CellMinerCDB:NCATS (https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/), which makes available activity information for 2,675 drugs and compounds, including multiple non-oncology drugs and 1,866 drugs and compounds unique to the National Center for Advancing Translational Sciences (NCATS). CellMinerCDB:NCATS comprises 183 cancer cell lines with 72 unique to NCATS including some from previously understudied tissues of origin. Multiple forms of data from different institutes are integrated, including single and combination drug activity, DNA copy number, methylation and mutation, transcriptome, protein levels, histone acetylation and methylation, metabolites, CRISPR and miscellaneous signatures. Curation of cell lines and drug names enables cross-database (CDB) analyses. Comparison of the datasets is made possible by the overlap between cell lines and drugs across databases. Multiple univariate and multivariate analysis tools are built-in, including linear regression and LASSO. Examples have been presented here for the clinical topoisomerase I (TOP1) inhibitors topotecan and irinotecan/SN-38. This web-application provides both substantial new data and significant pharmacogenomic integration allowing exploration of interrelationships.

Purpose: One of the main challenges in cancer therapy is the identification of molecular mechanisms mediating resistance or sensitivity to treatment. Cytidine deaminase (CDA) was reported to be downregulated in cells derived from patients with Bloom syndrome, a genetic disease associated with a strong predisposition to a wide range of cancers. The purpose of this study was to determine whether CDA deficiency could be associated with tumors from the general population and could constitute a predictive marker of susceptibility to antitumor drugs.Experimental Design: We analyzed CDA expression in silico, in large datasets for cancer cell lines and tumors and in various cancer cell lines and primary tumor tissues using IHC, PDXs, qRT-PCR, and Western blotting. We also studied the mechanism underlying CDA silencing and searched for molecules that might target specifically CDA-deficient tumor cells using in silico analysis coupled to classical cellular experimental approaches.Results: We found that CDA expression is downregulated in about 60% of cancer cells and tissues. We demonstrate that DNA methylation is a prevalent mechanism of CDA silencing in tumors. Finally, we show that CDA-deficient tumor cells can be specifically targeted with epigenetic treatments and with the anticancer drug aminoflavone.Conclusions: CDA expression status identifies new subgroups of cancers, and CDA deficiency appears to be a novel and relevant predictive marker of susceptibility to antitumor drugs, opening up new possibilities for treating cancer. Clin Cancer Res; 23(8); 2116–26. ©2016 AACR.

Depletion of CDA expression by short hairpin RNA in HeLa cells.

Supplementary Fig. S2 from Asparagine synthetase is a predictive biomarker of l-asparaginase activity in ovarian cancer cell lines

Supplementary Table S1 from DNA fingerprinting of the NCI-60 cell line panel

PDF file, 1202KB, Supplementary Figure 1. Kaplan-Meier Survival Curves. Supplementary Figure 2. Kaplan-Meier Survival Curves. Supplementary Table 1. Univariate analysis of clinical covariates.

Legends for Supplemental Figures S1-S2.

A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (∼21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and miRNA transcripts, DNA copy number, and protein levels. Here, we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17% to 84%. A six-gene model, including PARP1, EP300, KDM5C, SMARCB1, and UHRF1 matched this pattern. In addition, promoter methylation of two translationally relevant genes, Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT), served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacologic data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer types. Cancer Res; 77(3); 601–12. ©2016 AACR.

Transcript levels for 46,834 isoforms (fragments per kilobase per million reads, FPKM)

Supplementary Table S2 from DNA fingerprinting of the NCI-60 cell line panel

Gene composite transcript levels for 23,826 genes (fragments per kilobase per million reads, FPKM)

We recently used RNA interference to show that a negative correlation of l-asparaginase (l-ASP) chemotherapeutic activity with asparagine synthetase (ASNS) expression in the ovarian subset of the NCI-60 cell line panel is causal. To determine whether that relationship would be sustained in a larger, more diverse set of ovarian cell lines, we have now measured ASNS mRNA expression using microarrays and a branched-DNA RNA assay, ASNS protein expression using an electrochemiluminescent immunoassay, and l-ASP activity using an MTS assay on 19 human ovarian cancer cell lines. Contrary to our previous findings, l-ASP activity was only weakly correlated with ASNS mRNA expression; Pearson's correlation coefficients were r = -0.21 for microarray data and r = -0.39 for the branched-DNA RNA assay, with just the latter being marginally statistically significant (P = 0.047, one-tailed). ASNS protein expression measured by liquid-phase immunoassay exhibited a much stronger correlation (r = -0.65; P = 0.0014, one-tailed). We conclude that ASNS protein expression measured by immunoassay is a strong univariate predictor of l-ASP activity in ovarian cancer cell lines. These findings provide rationale for evaluation of ASNS protein expression as a predictive biomarker of clinical l-ASP activity in ovarian cancer. [Mol Cancer Ther 2008;7(10):3123–8]

Supplemental Figure 1. Density plot comparisons of RNA-Seq to microarray transcript data and comparison of both to DNA copy, DNA methylation and protein expression data. Supplemental Figure 2. Scatter plots for 9 selected genes for transcript expression as measured by microarray versus RNA-seq in the NCI-60. "r" is Pearson's correlation.

Supplementary Fig. S1 from DNA fingerprinting of the NCI-60 cell line panel

Supplementary figure 1. The protein levels of SLFN11 in 25 EWS-FLI1-expressing cells (black) and 4 EWS-ERG-expressing cells (red) were detected by Western blotting using antibodies against SLFN11 (98 kDa) and actin (42 kDa, loading control). The relative SLFN11 levels of each cell line were normalized to actin levels and the SLFN11/actin ratio of TC-106 was set as 1.

Purpose: This study assesses the ability of multidrug resistance (MDR)–associated gene expression patterns to predict survival in patients with newly diagnosed carcinoma of the ovary. The scope of this research differs substantially from that of previous reports, as a very large set of genes was evaluated whose expression has been shown to affect response to chemotherapy.Experimental Design: We applied a customized TaqMan low density array, a highly sensitive and specific assay, to study the expression profiles of 380 MDR-linked genes in 80 tumor specimens collected at initial surgery to debulk primary serous carcinoma. The RNA expression profiles of these drug resistance genes were correlated with clinical outcomes.Results: Leave-one-out cross-validation was used to estimate the ability of MDR gene expression to predict survival. Although gene expression alone does not predict overall survival (OS; P = 0.06), four covariates (age, stage, CA125 level, and surgical debulking) do (P = 0.03). When gene expression was added to the covariates, we found an 11-gene signature that provides a major improvement in OS prediction (log-rank statistic P < 0.003). The predictive power of this 11-gene signature was confirmed by dividing high- and low-risk patient groups, as defined by their clinical covariates, into four specific risk groups on the basis of expression levels.Conclusion: This study reveals an 11-gene signature that allows a more precise prognosis for patients with serous cancer of the ovary treated with carboplatin- and paclitaxel-based therapy. These 11 new targets offer opportunities for new therapies to improve clinical outcome in ovarian cancer. Clin Cancer Res; 18(11); 3197–206. ©2012 AACR.

Relationship between methylation and lack of SLFN11 and MGMT expression in the NCI-60.

The development of multidrug resistance (MDR) to chemotherapy remains a major challenge in the treatment of cancer. Resistance exists against every effective anticancer drug and can develop by multiple mechanisms. These mechanisms can act individually or synergistically, leading to MDR, in which the cell becomes resistant to a variety of structurally and mechanistically unrelated drugs in addition to the drug initially administered. Although extensive work has been done to characterize MDR mechanisms in vitro, the translation of this knowledge to the clinic has not been successful. Therefore, identifying genes and mechanisms critical to the development of MDR in vivo and establishing a reliable method for analyzing highly homologous genes from small amounts of tissue is fundamental to achieving any significant enhancement in our understanding of MDR mechanisms and could lead to treatments designed to circumvent it. In this study, we use a previously established database that allows the identification of lead compounds in the early stages of drug discovery that are not ATP-binding cassette (ABC) transporter substrates. We believe this can serve as a model for appraising the accuracy and sensitivity of current methods used to analyze the expression profiles of ABC transporters. We found two platforms to be superior methods for the analysis of expression profiles of highly homologous gene superfamilies. This study also led to an improved database by revealing previously unidentified substrates for ABCB1, ABCC1, and ABCG2, transporters that contribute to MDR. [Mol Cancer Ther 2009;8(7):2057–66]

Correlations between expression and DNA methylation for 17,144 transcripts.

Linear regression analysis of 15,798 genes with with transcript expression, DNA methylation, and DNA copy number data available.

Supplementary Table S1 from Asparagine synthetase is a predictive biomarker of l-asparaginase activity in ovarian cancer cell lines

Single-nucleotide polymorphisms identified by direct sequencing of the CDA gene in breast cell lines (S2A) and NCI60 cell lines (S2B).

Supplementary figure 2. Scatterplots showing correlations between FLI1 expression (x axis, Log2 normalized intensity) and ETS1 expression (y axis, Log2 normalized intensity) in breast and prostate cancers. n, number of samples; r, correlation coefficient.

Supplementary Table 1. Cell line data comparison across three institutes

Experiments related to studies on the silencing of CDA gene expression.

CellMiner (http://discover.nci.nih.gov/cellminer) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) are web-based applications for mining publicly available genomic, molecular, and pharmacologic datasets of human cancer cell lines including the NCI-60, Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, NCI/DTP small cell lung cancer, and NCI Almanac cell line sets. Here, we introduce our RNA sequencing (RNA-seq) data for the NCI-60 and their access and integration with the other databases. Correlation to transcript microarray expression levels for identical genes and identical cell lines across CellMinerCDB demonstrates the high quality of these new RNA-seq data. We provide composite and isoform transcript expression data and demonstrate diversity in isoform composition for individual cancer- and pharmacologically relevant genes, including HRAS, PTEN, EGFR, RAD51, ALKBH2, BRCA1, ERBB2, TP53, FGFR2, and CTNND1. We reveal cell-specific differences in the overall levels of isoforms and show their linkage to expression of RNA processing and splicing genes as well as resultant alterations in cancer and pharmacologic gene sets. Gene–drug pairings linked by pathways or functions show specific correlations to isoforms compared with composite gene expression, including ALKBH2-benzaldehyde, AKT3-vandetanib, BCR-imatinib, CDK1 and 20-palbociclib, CASP1-imexon, and FGFR3-pazopanib. Loss of MUC1 20 amino acid variable number tandem repeats, which is used to elicit immune response, and the presence of the androgen receptor AR-V4 and -V7 isoforms in all NCI-60 tissue of origin types demonstrate translational relevance. In summary, we introduce RNA-seq data to our CellMiner and CellMinerCDB web applications, allowing their exploration for both research and translational purposes.Significance:The current study provides RNA sequencing data for the NCI-60 cell lines made accessible through both CellMiner and CellMinerCDB and is an important pharmacogenomics resource for the field.

Methylation gene probe selection and correlation to expression level.

Supplementary Materials from Evaluation of current methods used to analyze the expression profiles of ATP-binding cassette transporters yields an improved drug-discovery database

Supplementary Data from DNA fingerprinting of the NCI-60 cell line panel

Cell lines (Supplementary Material 1), Primer sequences and Antibodies (Supplementary Material 2).

Pearson correlation between the levels of CDA transcripts and the cytotoxicity of a panel of drugs.

The NCI-60 cancer cell line panel provides a premier model for data integration, and systems pharmacology being the largest publicly available database of anticancer drug activity, genomic, molecular, and phenotypic data. It comprises gene expression (25,722 transcripts), microRNAs (360 miRNAs), whole-genome DNA copy number (23,413 genes), whole-exome sequencing (variants for 16,568 genes), protein levels (94 genes), and cytotoxic activity (20,861 compounds). Included are 158 FDA-approved drugs and 79 that are in clinical trials. To improve data accessibility to bioinformaticists and non-bioinformaticists alike, we have developed the CellMiner web–based tools. Here, we describe the newest CellMiner version, including integration of novel databases and tools associated with whole-exome sequencing and protein expression, and review the tools. Included are (i) “Cell line signature” for DNA, RNA, protein, and drugs; (ii) “Cross correlations” for up to 150 input genes, microRNAs, and compounds in a single query; (iii) “Pattern comparison” to identify connections among drugs, gene expression, genomic variants, microRNA, and protein expressions; (iv) “Genetic variation versus drug visualization” to identify potential new drug:gene DNA variant relationships; and (v) “Genetic variant summation” designed to provide a synopsis of mutational burden on any pathway or gene group for up to 150 genes. Together, these tools allow users to flexibly query the NCI-60 data for potential relationships between genomic, molecular, and pharmacologic parameters in a manner specific to the user's area of expertise. Examples for both gain- (RAS) and loss-of-function (PTEN) alterations are provided. Clin Cancer Res; 21(17); 3841–52. ©2015 AACR.

The National Cancer Institute's NCI-60 cell line panel, the most extensively characterized set of cells in existence and a public resource, is frequently used as a screening tool for drug discovery. Because many laboratories around the world rely on data from the NCI-60 cells, confirmation of their genetic identities represents an essential step in validating results from them. Given the consequences of cell line contamination or misidentification, quality control measures should routinely include DNA fingerprinting. We have, therefore, used standard DNA microsatellite short tandem repeats to profile the NCI-60, and the resulting DNA fingerprints are provided here as a reference. Consistent with previous reports, the fingerprints suggest that several NCI-60 lines have common origins: the melanoma lines MDA-MB-435, MDA-N, and M14; the central nervous system lines U251 and SNB-19; the ovarian lines OVCAR-8 and OVCAR-8/ADR (also called NCI/ADR); and the prostate lines DU-145, DU-145 (ATCC), and RC0.1. Those lines also show that the ability to connect two fingerprints to the same origin is not affected by stable transfection or by the development of multidrug resistance. As expected, DNA fingerprints were not able to distinguish different tissues-of-origin. The fingerprints serve principally as a barcodes.[Mol Cancer Ther 2009;8(4):713–24]

Comparison of CDA mRNA expression data between cancerous and non-cancerous tissues.

Supplementary Figure Legend

Supplementary Figure 1. The "Cross-correlations" and "Pattern comparison" tools

Supplementary Fig. S3 from Asparagine synthetase is a predictive biomarker of l-asparaginase activity in ovarian cancer cell lines

128,394 probes used for the determination of gene methylation levels.

Purpose: SLFN11 was identified as a critical determinant of response to DNA-targeted therapies by analyzing gene expression and drug sensitivity of NCI-60 and CCLE datasets. However, how SLFN11 is regulated in cancer cells remained unknown. Ewing sarcoma, which is characterized by the chimeric transcription factor EWS-FLI1, has notably high SLFN11 expression, leading us to investigate whether EWS-FLI1 drives SLFN11 expression and the role of SLFN11 in the drug response of Ewing sarcoma cells.Experimental Design: Binding sites of EWS-FLI1 on the SLFN11 promoter were analyzed by chromatin immunoprecipitation sequencing and promoter-luciferase reporter analyses. The relationship between SLFN11 and EWS-FLI1 were further examined in EWS-FLI1-knockdown or -overexpressing cells and in clinical tumor samples.Results: EWS-FLI1 binds near the transcription start site of SLFN11 promoter and acts as a positive regulator of SLFN11 expression in Ewing sarcoma cells. EWS-FLI1–mediated SLFN11 expression is responsible for high sensitivity of Ewing sarcoma to camptothecin and combinations of PARP inhibitors with temozolomide. Importantly, Ewing sarcoma patients with higher SLFN11 expression showed better tumor-free survival rate. The correlated expression between SLFN11 and FLI1 extends to leukemia, pediatric, colon, breast, and prostate cancers. In addition, expression of other ETS members correlates with SLFN11 in NCI-60 and CCLE datasets, and molecular experiments demonstrate that ETS1 acts as a positive regulator for SLFN11 expression in breast cancer cells.Conclusions: Our results imply the emerging relevance of SLFN11 as an ETS transcription factor response gene and for therapeutic response to topoisomerase I inhibitors and temozolomide–PARP inhibitor combinations in ETS-activated cancers. Clin Cancer Res; 21(18); 4184–93. ©2015 AACR.See related commentary by Kovar, p. 4033

Topoisomerase I (Top1) relaxes DNA supercoiling by forming transient cleavage complexes (Top1cc) up- and downstream of transcription complexes. Top1cc can be trapped by carcinogenic and endogenous DNA lesions and by camptothecin, resulting in transcription blocks. Here, we undertook genome-wide analysis of camptothecin-treated cells at exon resolution. RNA samples from HCT116 and MCF7 cells were analyzed with the Affy Exon Array platform, allowing high-resolution mapping along 18,537 genes. Long genes that are highly expressed were the most susceptible to downregulation, whereas short genes were preferentially upregulated. Along the body of genes, downregulation was most important toward the 3′-end and increased with the number of exon–intron junctions. Ubiquitin and RNA degradation-related pathway genes were selectively downregulated. Parallel analysis of microRNA with the Agilent miRNA microarray platform revealed that miR-142-3p was highly induced by camptothecin. More than 10% of the downregulated genes were targets of this p53-dependent microRNA. Our study shows the profound impact of Top1cc on transcription elongation, especially at intron–exon junctions and on transcript stability by microRNA miR-142-3p upregulation. Cancer Res; 73(15); 4830–9. ©2013 AACR.

To identify genetic alterations underlying rectal carcinogenesis, we used global gene expression profiling of a series of 17 locally advanced rectal adenocarcinomas and 20 normal rectal mucosa biopsies on oligonucleotide arrays. A total of 351 genes were differentially expressed (P < 1.0e−7) between normal rectal mucosa and rectal carcinomas, 77 genes had a >5-fold difference, and 85 genes always had at least a 2-fold change in all of the matched samples. Twelve genes satisfied all three of these criteria. Altered expression of genes such as PTGS2 (COX-2), WNT1, TGFB1, VEGF, and MYC was confirmed, whereas our data for other genes, like PPARD and LEF1, were inconsistent with previous reports. In addition, we found deregulated expression of many genes whose involvement in rectal carcinogenesis has not been reported. By mapping the genomic imbalances in the tumors using comparative genomic hybridization, we could show that DNA copy number gains of recurrently aneuploid chromosome arms 7p, 8q, 13q, 18q, 20p, and 20q correlated significantly with their average chromosome arm expression profile. Taken together, our results show that both the high-level, significant transcriptional deregulation of specific genes and general modification of the average transcriptional activity of genes residing on aneuploid chromosomes coexist in rectal adenocarcinomas. (Cancer Res 2006; 66(1): 267-82)

PDF file - 2059K, Importance of Exon numbers for transcript downregulation by CPT (SF1); CPT up-regulates the p53 signaling pathway genes (SF2); Down-regulation of RNA degradation-related genes after CPT treatment (SF3); Down-regulation of ubiquitin-related genes after CPT treatment (SF4); Top1 down-regulation does not impacts gene expression for CUL5 and UBE2W (SF5); miR-142-3p decreases cell survival, and down-regulation of its target genes BCL2L1 and MAP3K7IP2 sensitize to CPT (SF6). *** List of Primers (ST1); List of the 3808 down-regulated genes in CPT-treated HCT116 cells, by 2-fold or more (ST2); List of the 835 up-regulated genes in CPT-treated HCT116 cells, by 2-fold or more (ST3).

Supplementary Tables 1-5 from Gene Expression Profiling Reveals a Massive, Aneuploidy-Dependent Transcriptional Deregulation and Distinct Differences between Lymph Node–Negative and Lymph Node–Positive Colon Carcinomas

Supplementary Figure 1 from Gene Expression Profiling Reveals a Massive, Aneuploidy-Dependent Transcriptional Deregulation and Distinct Differences between Lymph Node–Negative and Lymph Node–Positive Colon Carcinomas

Supplementary Figures 1-2, Tables 1-4 from Genome-wide Analysis of Novel Splice Variants Induced by Topoisomerase I Poisoning Shows Preferential Occurrence in Genes Encoding Splicing Factors

Supplementary Tables 1-9 from Aneuploidy-Dependent Massive Deregulation of the Cellular Transcriptome and Apparent Divergence of the Wnt/β-catenin Signaling Pathway in Human Rectal Carcinomas

To characterize patterns of global transcriptional deregulation in primary colon carcinomas, we did gene expression profiling of 73 tumors [Unio Internationale Contra Cancrum stage II (n = 33) and stage III (n = 40)] using oligonucleotide microarrays. For 30 of the tumors, expression profiles were compared with those from matched normal mucosa samples. We identified a set of 1,950 genes with highly significant deregulation between tumors and mucosa samples (P < 1e−7). A significant proportion of these genes mapped to chromosome 20 (P = 0.01). Seventeen genes had a >5-fold average expression difference between normal colon mucosa and carcinomas, including up-regulation of MYC and of HMGA1, a putative oncogene. Furthermore, we identified 68 genes that were significantly differentially expressed between lymph node–negative and lymph node–positive tumors (P < 0.001), the functional annotation of which revealed a preponderance of genes that play a role in cellular immune response and surveillance. The microarray-derived gene expression levels of 20 deregulated genes were validated using quantitative real-time reverse transcription-PCR in >40 tumor and normal mucosa samples with good concordance between the techniques. Finally, we established a relationship between specific genomic imbalances, which were mapped for 32 of the analyzed colon tumors by comparative genomic hybridization, and alterations of global transcriptional activity. Previously, we had conducted a similar analysis of primary rectal carcinomas. The systematic comparison of colon and rectal carcinomas revealed a significant overlap of genomic imbalances and transcriptional deregulation, including activation of the Wnt/β-catenin signaling cascade, suggesting similar pathogenic pathways. [Cancer Res 2007;67(1):41–56]

Limiting the spread of virus during the recent pandemic outbreak was a major challenge. Viral loads in saliva, nasopharyngeal and oropharyngeal swabs were the major cause for droplet transmission and aerosols. Saliva being the major contributor for the presence of viral load is the major key factor; various mouthwashes and their combination were analyzed and utilized in health care centers to hamper the spread of virus and decrease viral load. The compositions of these mouthwashes to an extent affected the viral load and thereby transmission, but there is always a scope for other protocols which may provide better results. Here we evaluated the potential of antimicrobial peptide LL-37 in decreasing the viral load of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through an in silico work and evidence from other studies. This narrative review highlighted a brief nonsystematic methodology to include the selected articles for discussion. Accessible electronic databases (Medline, Scopus, Web of Science, SciELO, and PubMed) were used to find studies that reported the salivary viral load of SARS-CoV-2 published between December 2019 and June 2021. The following keywords were utilized for brief searching of the databases: “saliva,” “viral load,” and “SARS-CoV-2.” Articles in English language, in vitro cell-line studies, ex vivo studies, and clinical trials explaining the viral load of SARS-CoV-2 in saliva and strategies to decrease viral load were included in this review. The search was complemented by manual searching of the reference lists of included articles and performing a citation search for any additional reviews. The antiviral potential of cationic host defense peptide LL-37 was evaluated using computational approaches providing in silico evidence. The analysis of docking studies and the display of positive interfacial hydrophobicity of LL-37 resulting in disruption of COVID-19 viral membrane elucidate the fact that LL-37 could be effective against all variants of SARS-CoV-2. Further experimental studies would be needed to confirm the binding of the receptor-binding domain with LL-37. The possibility of using it in many forms further to decrease the viral load by disrupting the viral membrane is seen.

The role of brain cholesterol metabolism in Alzheimer’s disease (AD) remains unclear. Peripheral and brain cholesterol levels are largely independent due to the impermeability of the blood brain barrier (BBB), highlighting the importance of studying the role of brain cholesterol homeostasis in AD. We first tested whether metabolite markers of brain cholesterol biosynthesis and catabolism were altered in AD and associated with AD pathology using linear mixed-effects models in two brain autopsy samples from the Baltimore Longitudinal Study of Aging (BLSA) and the Religious Orders Study (ROS). We next tested whether genetic regulators of brain cholesterol biosynthesis and catabolism were altered in AD using the ANOVA test in publicly available brain tissue transcriptomic datasets. Finally, using regional brain transcriptomic data, we performed genome-scale metabolic network modeling to assess alterations in cholesterol biosynthesis and catabolism reactions in AD. We show that AD is associated with pervasive abnormalities in cholesterol biosynthesis and catabolism. Using transcriptomic data from Parkinson’s disease (PD) brain tissue samples, we found that gene expression alterations identified in AD were not observed in PD, suggesting that these changes may be specific to AD. Our results suggest that reduced de novo cholesterol biosynthesis may occur in response to impaired enzymatic cholesterol catabolism and efflux to maintain brain cholesterol levels in AD. This is accompanied by the accumulation of nonenzymatically generated cytotoxic oxysterols. Our results set the stage for experimental studies to address whether abnormalities in cholesterol metabolism are plausible therapeutic targets in AD.