Single-stranded pre-methylated 5mC adapters uncover the methylation profile of plasma ultrashort Single-stranded cell-free DNA.

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Multiomics approach towards characterization of tumor cell plasticity and its significance in precision and personalized medicine.

Cellular plasticity refers to the ability of cells to change their identity or behavior, which can be advantageous in some cases (e.g., tissue regeneration) but detrimental in others (e.g., cancer metastasis). With a better understanding of cellular plasticity, the complexity of cancer cells, their heterogeneity, and their role in metastasis is being unraveled. The plasticity of the cells could also prove as a nemesis to their characterization. In this review, we have attempted to highlight the possibilities and benefits of using multiomics approach in characterizing the plastic nature of cancer cells. There is a need to integrate fragmented evidence at different levels of cellular organization (DNA, RNA, protein, metabolite, epigenetics, etc.) to facilitate the characterization of different forms of plasticity and cell types. We have discussed the role of cellular plasticity in generating intra-tumor heterogeneity. Different omics level evidence is being provided to highlight the variety of molecular determinants discovered using different techniques. Attempts have been made to integrate some of this information to provide a quantitative assessment and scoring of the plastic nature of the cells. However, there is a huge gap in our understanding of mechanisms that lead to the observed heterogeneity. Understanding of these mechanism(s) is necessary for finding targets for early detection and effective therapeutic interventions in metastasis. Targeting cellular plasticity is akin to neutralizing a moving target. Along with the advancements in precision and personalized medicine, these efforts may translate into better clinical outcomes for cancer patients, especially in metastatic stages.

The role of TAOK3 in cancer progression and development as a prognostic marker: A pan-cancer analysis study.

The protein kinase TAOK3, belongs to the MAP kinase family, is one of three closely related members, namely TAOK1, TAOK2, and TAOK3. We performed a pan-cancer investigation of TAOK3 across different cancer types, including uterine carcinosarcoma, adenocarcinoma of the stomach and pancreas, and endometrial carcinoma of the uterus, to better understand TAOK3's role in cancer. In at least 16 types of cancer, our findings indicate that TAOK3 expression levels differ considerably between normal and tumor tissues. In addition, our study is the first to identify the oncogenic role of TAOK3 locus S331 and S471 in renal clear cell carcinoma, Glioblastoma Multiforme, hepatocellular carcinoma, Lung adenocarcinoma, and Pancreatic adenocarcinoma, indicating their involvement in cancer progression. In addition, our data analysis indicates that copy number variation is the most prevalent form of mutation in the TAOK3 gene, and that there is a negative correlation between TAOK3 mRNA and DNA promoter methylation. Moreover, our analysis suggests that TAOK3 may serve as a prognostic marker for several kinds of cancer, including Colon adenocarcinoma, renal clear cell carcinoma, Lower Grade Glioma, Lung adenocarcinoma, Mesothelioma, and hepatocellular carcinoma. In addition, our research on signature cancer genes has uncovered a positive association between TAOK3 and SMAD2, SMAD4, and RNF168 in most of the malignancies we have examined. TAOK3 is also correlated with the frequency of mutations and microsatellite instability in four types of cancer. Numerous immune-related genes are closely associated with TAOK3 levels in numerous malignancies. TAOK3 expression is positively correlated with immune infiltrates, which include activated CD4 T cells, CD8 T cells, and type 2T helper cells. Our pan-cancer analysis of TAOK3 provides vital insight into its potential role across a variety of cancer types.

Fractal feature selection model for enhancing high-dimensional biological problems.

The integration of biology, computer science, and statistics has given rise to the interdisciplinary field of bioinformatics, which aims to decode biological intricacies. It produces extensive and diverse features, presenting an enormous challenge in classifying bioinformatic problems. Therefore, an intelligent bioinformatics classification system must select the most relevant features to enhance machine learning performance. This paper proposes a feature selection model based on the fractal concept to improve the performance of intelligent systems in classifying high-dimensional biological problems. The proposed fractal feature selection (FFS) model divides features into blocks, measures the similarity between blocks using root mean square error (RMSE), and determines the importance of features based on low RMSE. The proposed FFS is tested and evaluated over ten high-dimensional bioinformatics datasets. The experiment results showed that the model significantly improved machine learning accuracy. The average accuracy rate was 79% with full features in machine learning algorithms, while FFS delivered promising results with an accuracy rate of 94%.

Recent advances in probiotication of fruit and vegetable juices.

Probiotics are live bacteria beneficial to health when consumed adequately. Health professionals now recommend probiotics on regular diets due to their positive effects on human health. The probiotics that are usually consumed from the market through food products are mostly dairy-based. Fruit and vegetables are gaining popularity as preferred matrices for probiotic carriers to the human body, owing to their high cholesterol content and the lactose intolerance of dairy products. On the other hand, fruits and vegetable juices are rich in nutrient content such as vitamins, minerals, and antioxidants and do not contain a starter culture that can compete with the nutrients. The probiotication of fruit and vegetable juices (apple, carrot, citrus fruit, pome-granate, watermelon, tomato, and pineapple) are performing as efficient probiotic bacteria carriers. This review covers the previous works that highlighted the variety of probiotic fruit and vegetable juices as well as the viability of each probiotic in various products after proper fermentation and storage. In addition, physicochemical and sensory changes that occurred during the processing and storage period have been discussed. Furthermore, strategies (microencapsulation, adding prebiotics, antioxidant addition, maintaining optimum pH, temperature, adaptation with resistance, and good packaging) to improve the stability of probiotic bacteria are outlined, as it is difficult to maintain the stability of probiotic bacteria during storage. Finally, the manuscript discusses the effect of probiotic fruit and vegetable juices on human health.

Ethical challenges of conducting and reviewing human genomics research in Malaysia: An exploratory study.

Even though there is a significant amount of scholarly work examining the ethical issues surrounding human genomics research, little is known about its footing in Malaysia. This study aims to explore the experience of local researchers and research ethics committee (REC) members in developing it in Malaysia. In-depth interviews were conducted from April to May 2021, and the data were thematically analysed. In advancing this technology, both genomics researchers and REC members have concerns over how this research is being developed in the country especially the absence of a clear ethical and regulatory framework at the national level as a guidance. However, this study argues that it is not a salient issue as there are international guidelines in existence and both researchers and RECs will benefit from a training on the guidelines to ensure genomics research can be developed in an ethical manner.

Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection.

BACKGROUND: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. METHODS: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. RESULTS: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). CONCLUSION: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

Distinct Features of Plasma Ultrashort Single-Stranded Cell-Free DNA as Biomarkers for Lung Cancer Detection.

BACKGROUND: Using broad range cell-free DNA sequencing (BRcfDNA-Seq), a nontargeted next-generation sequencing (NGS) methodology, we previously identified a novel class of approximately 50 nt ultrashort single-stranded cell-free DNA (uscfDNA) in plasma that is distinctly different from 167 bp mononucleosomal cell-free DNA (mncfDNA). We hypothesize that uscfDNA possesses characteristics that are useful for disease detection. METHODS: Using BRcfDNA-Seq, we examined both cfDNA populations in the plasma of 18 noncancer controls and 14 patients with late-stage nonsmall cell lung carcinoma (NSCLC). In comparison to mncfDNA, we assessed whether functional element (FE) peaks, fragmentomics, end-motifs, and G-Quadruplex (G-Quad) signatures could be useful features of uscfDNA for NSCLC determination. RESULTS: In noncancer participants, compared to mncfDNA, uscfDNA fragments showed a 45.2-fold increased tendency to form FE peaks (enriched in promoter, intronic, and exonic regions), demonstrated a distinct end-motif-frequency profile, and presented with a 4.9-fold increase in G-Quad signatures. Within NSCLC participants, only the uscfDNA population had discoverable FE peak candidates. Additionally, uscfDNA showcased different end-motif-frequency candidates distinct from mncfDNA. Although both cfDNA populations showed increased fragmentation in NSCLC, the G-Quad signatures were more discriminatory in uscfDNA. Compilation of cfDNA features using principal component analysis revealed that the first 5 principal components of both cfDNA subtypes had a cumulative explained variance of >80%. CONCLUSIONS: These observations indicate that the distinct biological processes of uscfDNA and that FE peaks, fragmentomics, end-motifs, and G-Quad signatures are uscfDNA features with promising biomarker potential. These findings further justify its exploration as a distinct class of biomarker to augment pre-existing liquid biopsy approaches.

Electrochemical monitoring of congo red degradation using strontium titanate-doped biochar nanohybrids derived photocatalytic plates.

Present investigation demonstrates the development and characterization of strontium titanate (SrTiO3) doped biochar nanohybrid photocatalysts. Biochar nanohybrid was synthesized using an ultrasonic-assisted dispersion technique, which involved dispersing SrTiO3 nanoparticles into activated biochar at a weight ratio of 1:2 (w/w) under ambient conditions. The development of the biochar nanohybrid was verified through a comprehensive analysis of their spectral, microstructural, thermal, electrical, and electrochemical properties. The scanning electron microscopy analysis reveals a surface-associated multiphase morphology of the biochar nanohybrid, attributed to the uniform distribution of SrTiO3 within the activated biochar matrix. Biochar nanohybrid exhibited a reduced optical band gap of 2.77 eV, accompanied by a crystallite size of 32.45. Thermogravimetric analysis revealed the thermal stability of the biochar nanohybrid, as evidenced by a char residue of 70.83% at 1000 °C. The working electrodes derived from biochar nanohybrid have exhibited ohmic behavior and displayed a significantly enhanced DC conductivity (mS/cm) of 1.13, surpassing that of activated biochar (0.53) and SrTiO3 (0.62) at 100 V. The developed biochar nanohybrid were employed for the degradation of congo red dye by exposing the dye solution to photocatalytic plates. These photocatalytic plates were prepared by coating biochar nanohybrid onto glass plates using epoxy-based reactive binders for secure binding. The photodegradation of congo red was evaluated through cyclic voltammetric analysis in a 0.1 M KCl solution at pH 8.0, resulting in an impressive 99.95% photocatalytic efficiency in degrading a congo red solution (50 mg/L). This study presents a novel approach for the fabrication of biochar nanohybrid-derived photocatalytic plates, offering high photocatalytic efficiency for the degradation of congo red dye.

Multi-Faceted Attributes of Salivary Cell-free DNA as Liquid Biopsy Biomarkers for Gastric Cancer Detection.

Background: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. Methods: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. Results: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). Conclusion: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

Differential Gene Expression Signatures and Cellular Signaling Pathways induced by Lamin A/C Transcript Variants in MCF7 Cell Line.

BACKGROUND: Lamins are the major component of nuclear lamina. Alternative splicing of the 12 exons comprising lamin A/C gene creates five known transcript variants, lamin A, lamin C, lamin AΔ10, lamin AΔ50, and lamin C2. The main objective for this study was to examine the association of critical pathways, networks, molecular and cellular functions regulated by each Lamin A/C transcript variants. METHODS: Ion AmpliSeq Transcriptome Human Gene Expression analysis was performed on MCF7 cells stably transfected with lamin A/C transcript variants. RESULTS: Lamin A or lamin AΔ50 upregulation was associated with activation of cell death and inactivation of carcinogenesis while both lamin C or lamin AΔ10 upregulation activated carcinogenesis and cell death. CONCLUSIONS: Data suggest anti-apoptotic and anti-senescence effects of lamin C and lamin AΔ10 as several functions, including apoptosis and necrosis functions are inactivated following lamin C or lamin AΔ10 upregulation. However, lamin AΔ10 upregulation is associated with a more carcinogenic and aggressive tumor phenotype. Lamin A or lamin AΔ50 upregulation is associated with a predicted activation of increased cell death and inactivation of carcinogenesis. Thus, different signaling pathways, networks, molecular and cellular functions are activated/inactivated by lamin A/C transcript variants resulting in a large number of laminopathies.

Deep Transfer Learning-Based Foot No-Ball Detection in Live Cricket Match.

Automation in every part of life has become a frequent situation because of the rapid advancement of technology, mostly driven by AI technology, and has helped facilitate improved decision-making. Machine learning and the deep learning subset of AI provide machines with the capacity to make judgments on their own through a continuous learning process from vast amounts of data. To decrease human mistakes while making critical choices and to improve knowledge of the game, AI-based technologies are now being implemented in numerous sports, including cricket, football, basketball, and others. Out of the most globally popular games in the world, cricket has a stronghold on the hearts of its fans. A broad range of technologies are being discovered and employed in cricket by the grace of AI to make fair choices as a method of helping on-field umpires because cricket is an unpredictable game, anything may happen in an instant, and a bad judgment can dramatically shift the game. Hence, a smart system can end the controversy caused just because of this error and create a healthy playing environment. Regarding this problem, our proposed framework successfully provides an automatic no-ball detection with 0.98 accuracy which incorporates data collection, processing, augmentation, enhancement, modeling, and evaluation. This study starts with collecting data and later keeps only the main portion of bowlers' end by cropping it. Then, image enhancement technique are implied to make the image data more clear and noise free. After applying the image processing technique, we finally trained and tested the optimized CNN. Furthermore, we have increased the accuracy by using several modified pretrained model. Here, in this study, VGG16 and VGG19 achieved 0.98 accuracy and we considered VGG16 as the proposed model as it outperformed considering recall value.

Increasing Systemic Immune-inflammation Index During Treatment in Patients With Advanced Pancreatic Cancer is Associated With Poor Survival: A Retrospective, Multicenter, Cohort Study.

BACKGROUND AND OBJECTIVES: A high systemic immune-inflammation index (SIII) at diagnosis of various cancers, including pancreatic cancer, is associated with poor prognosis. The impact of FOLFIRINOX (5-fluorouracil, leucovorin, irinotecan, and oxaliplatin) chemotherapy or stereotactic body radiotherapy on this index is unknown. In addition, the prognostic value of changes in the SIII during treatment is unclear. In this retrospective analysis, we aimed to find answers regarding patients with advanced pancreatic cancer. METHODS: Patients with advanced pancreatic cancer treated with FOLFIRINOX chemotherapy alone or with FOLFIRINOX chemotherapy followed by stereotactic body radiotherapy between 2015 and 2021 in 2 tertiary referral centers were included. Baseline characteristics, laboratory values at 3 time points during treatment, and survival outcomes were collected. The patient-specific evolutions of SIII and their association with mortality were assessed with joint models for longitudinal and time-to-event data. RESULTS: Data of 141 patients were analyzed. At a median follow-up time of 23.0 months (95% CI: 14.6-31.3), 97 (69%) patients had died. Median overall survival was 13.2 months (95% CI: 11.0-15.5). During treatment with FOLFIRINOX, the log (SIII) was reduced by -0.588 (95% CI: -0.0978, -0.197; P = 0.003). One unit increase in log (SIII) increased the hazard ratio of dying by 1.604 (95% CI: 1.068-2.409; P = 0.023). CONCLUSIONS: In addition to carbohydrate antigen 19-9, the SIII is a reliable biomarker in patients with advanced pancreatic cancer.

Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis.

There is a pertinent need to develop prognostic biomarkers for practicing predictive, preventive and personalized medicine (PPPM) in colorectal cancer metastasis. The analysis of isoform expression data governed by alternative splicing provides a high-resolution picture of mRNAs in a defined condition. This information would not be available by studying gene expression changes alone. Hence, we utilized our prior data from an exon microarray and found ADAM12 and MUC4 to be strong biomarker candidates based on their alternative splicing scores and pattern. In this study, we characterized their isoform expression in a cell line model of metastatic colorectal cancer (SW480 & SW620). These two genes were found to be good prognostic indicators in two cohorts from The Cancer Genome Atlas database. We studied their exon structure using sequence information in the NCBI and ENSEMBL genome databases to amplify and validate six isoforms each for the ADAM12 and MUC4 genes. The differential expression of these isoforms was observed between normal, primary and metastatic colorectal cancer cell lines. RNA-Seq analysis further proved the differential expression of the gene isoforms. The isoforms of MUC4 and ADAM12 were found to change expression levels in response to 5-Fluorouracil (5-FU) treatment in a dose-, time- and cell line-dependent manner. Furthermore, we successfully detected the protein isoforms of ADAM12 and MUC4 in cell lysates, reflecting the differential expression at the protein level. The change in the mRNA and protein expression of MUC4 and ADAM12 in primary and metastatic cells and in response to 5-FU qualifies them to be studied as potential biomarkers. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their potential use as prognostic and/or predictive biomarkers in the PPPM approach towards cancer.

Direct Detection of 4-Dimensions of SARS-CoV-2: Infection (vRNA), Infectivity (Antigen), Binding Antibody, and Functional Neutralizing Antibody in Saliva.

We developed a 4-parameter clinical assay using Electric Field Induced Release and Measurement (EFIRM) technology to simultaneously assess SARS-CoV-2 RNA (vRNA), nucleocapsid antigen, host binding (BAb) and neutralizing antibody (NAb) levels from a drop of saliva with performance that equals or surpasses current EUA-approved tests. The vRNA and antigen assays achieved lower limit of detection (LOD) of 100 copies/reaction and 3.5 TCID50/mL, respectively. The vRNA assay differentiated between acutely infected (n=10) and infection-naïve patients (n=33) with an AUC of 0.9818, sensitivity of 90%, and specificity of 100%. The antigen assay similarly differentiated these patient populations with an AUC of 1.000. The BAb assay detected BAbs with an LOD of 39 pg/mL and distinguished acutely infected (n=35), vaccinated with prior infection (n=13), and vaccinated infection-naïve patients (n=13) from control (n=81) with AUC of 0.9481, 1.000, and 0.9962, respectively. The NAb assay detected NAbs with an LOD of 31.6 Unit/mL and differentiated between COVID-19 recovered or vaccinated patients (n=31) and pre-pandemic controls (n=60) with an AUC 0.923, sensitivity of 87.10%, and specificity of 86.67%. Our multiparameter assay represents a significant technological advancement to simultaneously address SARS-CoV-2 infection and immunity, and it lays the foundation for tackling potential future pandemics.

Comparing Two Methods for the Isolation of Exosomes.

Exosomes are membrane-bound nanovesicles released by cells into their extracellular environment. They carry different types of RNA including mRNA which may be useful in the diagnosis of various diseases. Exosome isolation has been a challenge because of their small size; therefore, two exosome isolation methods were compared in this study. The Exoquick-TC PLUS™ exosome isolation kit (kit) was compared with the classic ultracentrifugation (UC) method for exosome isolation. In samples obtained using both methods, cryo-electron microscopy showed round or slightly elongated vesicles with diameters ranging from 50 to 150 nm and delimited by a bilayered membrane. Dynamic light scattering resulted in multiple peaks for kit exosomes, whereas a single peak was observed for UC exosomes. Significantly, more total RNA was present in UC exosomes in contrast to kit exosomes (P < 0.0001). This was reflected in subsequent mRNA analysis using qPCR, where UC exosomes had lower Ct values compared to kit exosomes. In conclusion, exosome characterization revealed the presence of exosomes in both UC and the kit samples. The kit samples presented additional peaks from DLS which might be due to impurities. Overall, due to a higher total RNA and mRNA content, UC is a better option for subsequent mRNA analysis; nevertheless, the kit can still be used if an ultracentrifuge is not available as four out of the five genes selected were detected and quantified using the kit.

Pharmacogenes that demonstrate high association evidence according to CPIC, DPWG, and PharmGKB.

Background: Different levels of evidence related to the variable responses of individuals to drug treatment have been reported in various pharmacogenomic (PGx) databases. Identification of gene-drug pairs with strong association evidence can be helpful in prioritizing the implementation of PGx guidelines and focusing on a gene panel. This study aimed to determine the pharmacogenes with the highest evidence-based association and to indicate their involvement in drug-gene interactions. Methodology: The publicly available datasets CPIC, DPWG, and PharmGKB were selected to determine the pharmacogenes with the highest drug outcome associations. The upper two levels of evidence rated by the three scoring methods were specified (levels A-B in CPIC, 3-4 in DPWG, or 1-2 levels in PharmGKB). The identified pharmacogenes were further ranked in this study based on the number of medications they interacted with. Results: Fifty pharmacogenes, with high to moderately high evidence of associations with drug response alterations, with potential influence on the therapeutic and/or toxicity outcomes of 152 drugs were identified. CYP2D6, CYP2C9, CYP2C19, G6PD, HLA-B, SLCO1B1, CACNA1S, RYR1, MT-RNR1, and IFNL4 are the top 10 pharmacogenes, where each is predicted to impact patients' responses to ≥5 drugs. Conclusion: This study identified the most important pharmacogenes based on the highest-ranked association evidence and their frequency of involvement in affecting multiple drugs. The obtained data is useful for customizing a gene panel for PGx testing. Identifying the strength of scientific evidence supporting drug-gene interactions aids drug prescribers in making the best clinical decision.

Presence of Circulatory Autoantibodies Against ROS-Modified Histone H1 Protein in Lymphoma Patients.

Lymphoma is a chronic inflammatory disease in which the immune system is highly affected. Increased oxidative stress is one of the common conditions of cancer and affects macromolecules. Histone modifications affect the chromatin structure and functions. In this study, histone H1 (His-H1) protein was modified by reactive oxygen species (ROS), and structural and chemical changes were studied. Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL) patients were selected, and oxidative stress markers, inflammatory cytokines, and serum autoantibodies were analyzed using biochemical and immunological assays. Furthermore, the formation of antigen-antibody immune complexes was assessed by the Langmuir plot. ROS-modified His-H1 (ROS-His-H1) showed substantial structural perturbation in protein (UV-hyperchromicity and increased intrinsic fluorescence) compared to the native His-H1 protein. A possible explanation for the changes is suggested by the exposure of the aromatic chromophore to the solvent. In-depth structural analysis by circular dichroism (CD) exhibited major changes in α-helix (-21.43%) and turns (+33%), reflecting changes in the secondary structure of histone H1 protein after ROS exposure. ELISA and competitive ELISA findings revealed high recognitions of serum autoantibodies to ROS-His-H1 from NHL, followed by HL subjects. Healthy controls showed negligible binding. Non-modified His-H1 did not show any binding with serum samples from either cohort. High apparent association constants (ACCs) were calculated for ROS-His-H1 using purified IgGs from NHL (1.46 × 10-6 M) compared to HL (1.33 × 10-6 M) patients. Non-modified His-H1 exhibited a hundred times less ACC for NHL (2.38 × 10-8 M) and HL (2.46 × 10-8 M) patients. Thus, ROS modifications of histone H1 cause structural changes and expose cryptic neo-epitopes on the protein against which autoantibodies were generated. These perturbations might affect the histone DNA interaction dynamics and potentially be correlated with gene dysregulation. These subtle molecular changes with an immune imbalance might further aggravate the disease.