Inflammatory markers S100A8/A9 and metabolic alteration for evaluating signs of early phase toxicity of anticancer agent treatment.

Anticancer agents can cause various side effects, including tissue damages/inflammatory reactions. Drug-responsive biomarkers are essential for evaluating drug toxicity in disease processes. S100 calcium-binding proteins A8/A9 (S100A8/A9) are highly expressed in neutrophils and monocytes/macrophages accumulated at inflammatory sites and are known to be related to tissue damage/inflammation; however, their response to drug toxicity has not been reported. Herein, we investigated the effects of anticancer agents (doxorubicin, cisplatin, and docetaxel) on S100A8/A9 gene expression profiles in four representative tissues (heart, kidney, liver, and lung) in normal C57BL/6J mice. Both S100A8/A9 expression was transiently or time-dependently elevated in four tissues within 48 h after dosing of the three anticancer agents under toxicity-inducing conditions. S100A8/A9 patterns differed among agents and tissues. This result suggests that S100A8/A9 is useful for evaluating anticancer agent-induced tissue damage. Metabolomic analysis revealed that some metabolites showed temporal patterns similar to that of S100A8/A9 expression. The amounts of fumarate (doxorubicin-treated heart), tyrosine (cisplatin-treated kidney), acetylcarnosine (doxorubicin-treated liver), and 2-phosphoglycerate (docetaxel-treated lung) showed similar patterns to that of S100A8/A9 expression. Although these metabolites showed different behaviors between tissues and serum, they may be useful marker candidates for evaluating anticancer agent-induced tissue damage at an earlier stage after dosing.

High-dimensional immune profiling identifies a biomarker to monitor dimethyl fumarate response in multiple sclerosis.

Dimethyl fumarate (DMF) is an immunomodulatory treatment for multiple sclerosis (MS). Despite its wide clinical use, the mechanisms underlying clinical response are not understood. This study aimed to reveal immune markers of therapeutic response to DMF treatment in MS. For this purpose, we prospectively collected peripheral blood mononuclear cells (PBMCs) from a highly characterized cohort of 44 individuals with MS before and at 12 and 48 wk of DMF treatment. Single cells were profiled using high-dimensional mass cytometry. To capture the heterogeneity of different immune subsets, we adopted a bioinformatic multipanel approach that allowed cell population-cluster assignment of more than 50 different parameters, including lineage and activation markers as well as chemokine receptors and cytokines. Data were further analyzed in a semiunbiased fashion implementing a supervised representation learning approach to capture subtle longitudinal immune changes characteristic for therapy response. With this approach, we identified a population of memory T helper cells expressing high levels of neuroinflammatory cytokines (granulocyte-macrophage colony-stimulating factor [GM-CSF], interferon γ [IFNγ]) as well as CXCR3, whose abundance correlated with treatment response. Using spectral flow cytometry, we confirmed these findings in a second cohort of patients. Serum neurofilament light-chain levels confirmed the correlation of this immune cell signature with axonal damage. The identified cell population is expanded in peripheral blood under natalizumab treatment, substantiating a specific role in treatment response. We propose that depletion of GM-CSF-, IFNγ-, and CXCR3-expressing T helper cells is the main mechanism of action of DMF and allows monitoring of treatment response.

Efficacy and Safety of Lenvatinib for Patients With Advanced Hepatocellular Carcinoma: A Retrospective, Real-world Study Conducted in Japan.

AIM: We evaluated real-world efficacy and toxicity of lenvatinib in 142 patients with advanced hepatocellular carcinoma (HCC) at six tertiary referral centres. PATIENTS AND METHODS: The patients with advanced HCC treated with lenvatinib were grouped into two categories based on REFLECT criteria for analysis of efficacy and safety. The primary endpoint was progression-free survival (PFS). RESULTS: The objective response rate (ORR) at week 12 of therapy was 41.5%, with a median PFS of 176 days. Child-Pugh score of 5 points, the presence of extrahepatic metastasis and adverse effects grade 2 or higher were considered independent factors associated with both better PFS and ORR. The ORR for patients who fulfilled the REFLECT inclusion criteria was significantly higher than that for those who did not. However, no significant differences in PFS were observed between the two groups. The incidence rate of adverse effects grade 3 or higher was 40.1%, which was similar for the two groups. CONCLUSION: Lenvatinib is safe and effective for patients, whether or not they satisfy REFLECT criteria. The result warrants replication in a larger study.

Expression and Content of Protein LC3B in Gastric Cancer Tissue, Relationship with Expression of mTOR, AMPK in Gastric Cancer Tissue and HER2 and PD-L1 Status of the Tumor.

Analysis of HER2 status of the tumor and expression of mTOR, AMPK showed a decrease in mTOR mRNA level in HER2+ tumors in comparison with HER- status. The appearance of PD-L1+ transformed cells in the tumor was associated with increased expression of the LC3B gene and elevated content of the corresponding protein measured after treatment.

Predicting patient response with models trained on cell lines and patient-derived xenografts by nonlinear transfer learning.

Preclinical models have been the workhorse of cancer research, producing massive amounts of drug response data. Unfortunately, translating response biomarkers derived from these datasets to human tumors has proven to be particularly challenging. To address this challenge, we developed TRANSACT, a computational framework that builds a consensus space to capture biological processes common to preclinical models and human tumors and exploits this space to construct drug response predictors that robustly transfer from preclinical models to human tumors. TRANSACT performs favorably compared to four competing approaches, including two deep learning approaches, on a set of 23 drug prediction challenges on The Cancer Genome Atlas and 226 metastatic tumors from the Hartwig Medical Foundation. We demonstrate that response predictions deliver a robust performance for a number of therapies of high clinical importance: platinum-based chemotherapies, gemcitabine, and paclitaxel. In contrast to other approaches, we demonstrate the interpretability of the TRANSACT predictors by correctly identifying known biomarkers of targeted therapies, and we propose potential mechanisms that mediate the resistance to two chemotherapeutic agents.

MicroRNA Expression Profiling in Porcine Liver, Jejunum and Serum upon Dietary DON Exposure Reveals Candidate Toxicity Biomarkers.

Deoxynivalenol (DON), a frequent mycotoxin worldwide, impairs human and animal health. The response of microRNAs, small non-coding RNAs, to DON has been scarcely investigated, but holds remarkable potential for biomarker applications. Hence, we aimed to investigate DON-induced changes in the microRNA expression in porcine liver, jejunum and serum by combining targeted and untargeted analyses. Piglets received uncontaminated feed or feed containing 900 µg/kg and 2500 µg/kg DON for four weeks, followed by a wash-out period. In tissue, only slight changes in microRNA expression were detected, with ssc-miR-10b being downregulated in liver of DON-exposed piglets. In serum, several microRNAs were differentially expressed upon DON exposure, four of which were validated by qPCR (ssc-miR-16, ssc-miR-128, ssc-miR-451, ssc-miR-205). The serum microRNA response to DON increased over time and declined after removal of contaminated diets. Receiver operating curve analyses for individual microRNAs were significant, and a combination of the four microRNAs increased the predictive capacity for DON exposure. Predicted microRNA target genes showed enrichment of several pathways including PIK3-AKT, Wnt/ß-catenin, and adherens junctions. This study gives, for the first time, a comprehensive view of the porcine microRNA response to DON, providing a basis for future research on microRNAs as biomarkers for mycotoxins.

Glutamine Antagonist GA-607 Causes a Dramatic Accumulation of FGAR which can be used to Monitor Target Engagement.

BACKGROUND: Metabolomic analyses from our group and others have shown that tumors treated with glutamine antagonists (GA) exhibit robust accumulation of formylglycinamide ribonucleotide (FGAR), an intermediate in the de novo purine synthesis pathway. The increase in FGAR is attributed to the inhibition of the enzyme FGAR amidotransferase (FGAR-AT) that catalyzes the ATP-dependent amidation of FGAR to formylglycinamidine ribonucleotide (FGAM). While perturbation of this pathway resulting from GA therapy has long been recognized, no study has reported systematic quantitation and analyses of FGAR in plasma and tumors. OBJECTIVE: Herein, we aimed to evaluate the efficacy of our recently discovered tumor-targeted GA prodrug, GA-607 (isopropyl 2-(6-acetamido-2-(adamantane-1-carboxamido)hexanamido)-6-diazo-5-oxohexanoate), and demonstrate its target engagement by quantification of FGAR in plasma and tumors. METHODS: Efficacy and pharmacokinetics of GA-607 were evaluated in a murine EL4 lymphoma model followed by global tumor metabolomic analysis. Liquid chromatography-mass spectrometry (LC-MS) based methods employing the ion-pair chromatography approach were developed and utilized for quantitative FGAR analyses in plasma and tumors. RESULTS: GA-607 showed preferential tumor distribution and robust single-agent efficacy in a murine EL4 lymphoma model. While several metabolic pathways were perturbed by GA-607 treatment, FGAR showed the highest increase qualitatively. Using our newly developed sensitive and selective LC-MS method, we showed a robust >80- and >10- fold increase in tumor and plasma FGAR levels, respectively, with GA-607 treatment. CONCLUSION: These studies describe the importance of FGAR quantification following GA therapy in cancer and underscore its importance as a valuable pharmacodynamic marker in the preclinical and clinical development of GA therapies.

Potential Roles of Extracellular Vesicles as Biomarkers and a Novel Treatment Approach in Multiple Sclerosis.

Extracellular vesicles (EVs) are a heterogeneous group of bilayer membrane-wrapped molecules that play an important role in cell-to-cell communication, participating in many physiological processes and in the pathogenesis of several diseases, including multiple sclerosis (MS). In recent years, many studies have focused on EVs, with promising results indicating their potential role as biomarkers in MS and helping us better understand the pathogenesis of the disease. Recent evidence suggests that there are novel subpopulations of EVs according to cell origin, with those derived from cells belonging to the nervous and immune systems providing information regarding inflammation, demyelination, axonal damage, astrocyte and microglia reaction, blood-brain barrier permeability, leukocyte transendothelial migration, and ultimately synaptic loss and neuronal death in MS. These biomarkers can also provide insight into disease activity and progression and can differentiate patients' disease phenotype. This information can enable new pathways for therapeutic target discovery, and consequently the development of novel treatments. Recent evidence also suggests that current disease modifying treatments (DMTs) for MS modify the levels and content of circulating EVs. EVs might also serve as biomarkers to help monitor the response to DMTs, which could improve medical decisions concerning DMT initiation, choice, escalation, and withdrawal. Furthermore, EVs could act not only as biomarkers but also as treatment for brain repair and immunomodulation in MS. EVs are considered excellent delivery vehicles. Studies in progress show that EVs containing myelin antigens could play a pivotal role in inducing antigen-specific tolerance of autoreactive T cells as a novel strategy for the treatment as "EV-based vaccines" for MS. This review explores the breakthrough role of nervous and immune system cell-derived EVs as markers of pathological disease mechanisms and potential biomarkers of treatment response in MS. In addition, this review explores the novel role of EVs as vehicles for antigen delivery as a therapeutic vaccine to restore immune tolerance in MS autoimmunity.

Clinical Perspectives of Single-Cell RNA Sequencing.

The ability of single-cell genomics to resolve cellular heterogeneity is highly appreciated in cancer and is being exploited for precision medicine. In the recent decade, we have witnessed the incorporation of cancer genomics into the clinical decision-making process for molecular-targeted therapies. Compared with conventional genomics, which primarily focuses on the specific and sensitive detection of the molecular targets, single-cell genomics addresses intratumoral heterogeneity and the microenvironmental components impacting the treatment response and resistance. As an exploratory tool, single-cell genomics provides an unprecedented opportunity to improve the diagnosis, monitoring, and treatment of cancer. The results obtained upon employing bulk cancer genomics indicate that single-cell genomics is at an early stage with respect to exploration of clinical relevance and requires further innovations to become a widely utilized technology in the clinic.

Evidence-Based Second-Line Treatment in RAS Wild-Type/Mutated Metastatic Colorectal Cancer in the Precision Medicine Era.

Target-oriented agents improve metastatic colorectal cancer (mCRC) survival in combination with chemotherapy. However, the majority of patients experience disease progression after first-line treatment and are eligible for second-line approaches. In such a context, antiangiogenic and anti-Epidermal Growth Factor Receptor (EGFR) agents as well as immune checkpoint inhibitors have been approved as second-line options, and RAS and BRAF mutations and microsatellite status represent the molecular drivers that guide therapeutic choices. Patients harboring K- and N-RAS mutations are not eligible for anti-EGFR treatments, and bevacizumab is the only antiangiogenic agent that improves survival in combination with chemotherapy in first-line, regardless of RAS mutational status. Thus, the choice of an appropriate therapy after the progression to a bevacizumab or an EGFR-based first-line treatment should be evaluated according to the patient and disease characteristics and treatment aims. The continuation of bevacizumab beyond progression or its substitution with another anti-angiogenic agents has been shown to increase survival, whereas anti-EGFR monoclonals represent an option in RAS wild-type patients. In addition, specific molecular subgroups, such as BRAF-mutated and Microsatellite Instability-High (MSI-H) mCRCs represent aggressive malignancies that are poorly responsive to standard therapies and deserve targeted approaches. This review provides a critical overview about the state of the art in mCRC second-line treatment and discusses sequential strategies according to key molecular biomarkers.

Modulation of the effects of class Ib antiarrhythmics on cardiac NaV1.5-encoded channels by accessory NaVß subunits.

Native myocardial voltage-gated sodium (NaV) channels function in macromolecular complexes comprising a pore-forming (α) subunit and multiple accessory proteins. Here, we investigated the impact of accessory NaVß1 and NaVß3 subunits on the functional effects of 2 well-known class Ib antiarrhythmics, lidocaine and ranolazine, on the predominant NaV channel α subunit, NaV1.5, expressed in the mammalian heart. We showed that both drugs stabilized the activated conformation of the voltage sensor of domain-III (DIII-VSD) in NaV1.5. In the presence of NaVß1, the effect of lidocaine on the DIII-VSD was enhanced, whereas the effect of ranolazine was abolished. Mutating the main class Ib drug-binding site, F1760, affected but did not abolish the modulation of drug block by NaVß1/ß3. Recordings from adult mouse ventricular myocytes demonstrated that loss of Scn1b (NaVß1) differentially affected the potencies of lidocaine and ranolazine. In vivo experiments revealed distinct ECG responses to i.p. injection of ranolazine or lidocaine in WT and Scn1b-null animals, suggesting that NaVß1 modulated drug responses at the whole-heart level. In the human heart, we found that SCN1B transcript expression was 3 times higher in the atria than ventricles, differences that could, in combination with inherited or acquired cardiovascular disease, dramatically affect patient response to class Ib antiarrhythmic therapies.

Association between body mass index, dosing strategy, and efficacy of immune checkpoint inhibitors.

BACKGROUND: Increased body mass index (BMI) has been associated with improved response to immune checkpoint inhibitors (ICIs) in multiple cancer types. We evaluated associations between BMI, ICI dosing strategy, and clinical outcomes. METHODS: We abstracted clinical data on patients with cancer treated with ICI, including age, sex, cancer type, BMI, ICI type, dosing strategy (weight-based or fixed), radiographic response, overall survival (OS), and progression-free survival (PFS). We compared clinical outcomes between low-BMI and high-BMI populations using Kaplan-Meier curves, Cox regressions, and Pearson product-moment correlation coefficients. RESULTS: A total of 297 patients were enrolled, of whom 40% were women and 59% were overweight (BMI≥25). Of these, 204 (69%) received fixed and 93 (31%) received weight-based ICI dosing. In the overall cohort, overweight BMI was associated with improved PFS (HR 0.69; 95% CI 0.51 to 0.94; p=0.02) and had a trend toward improved OS (HR 0.77; 95% CI 0.57 to 1.04; p=0.08). For both endpoints, improved outcomes in the overweight population were limited to patients who received weight-based ICI dosing (PFS HR 0.53; p=0.04 for weight-based; vs HR 0.79; p=0.2 for fixed dosing) (OS HR 0.56; p=0.03 for weight-based; vs HR 0.89; p=0.54 for fixed dosing). In multivariable analysis, BMI was not associated with PFS or OS. However, the interaction of BMI≥25 and weight-based dosing had a trend toward association with PFS (HR 0.53; 95% CI 0.26 to 1.10; p=0.09) and was associated with OS (HR 0.50; 95% CI 0.25 to 0.99; p=0.05). Patients with BMI<25 tended to have better outcomes with fixed-dose compared with weight-based ICI, while patients with BMI≥25 tended to have better outcomes with weight-based ICI, although these differences did not achieve statistical significance. There was no association between radiographic response and BMI with fixed-dose ICI (p=0.97), but a near-significant trend with weight-based ICI (p=0.1). In subset analyses, the association between BMI, ICI dosing strategy, and clinical outcomes appeared limited to men. CONCLUSIONS: The clinical benefit of ICI in high-BMI populations appears limited to individuals receiving weight-based ICI dosing. Further research into optimal ICI dosing strategies may be warranted.

Molecular Characteristics of Lymphocyte-predominant Triple-negative Breast Cancer.

BACKGROUND/AIM: Tumor-infiltrating lymphocytes (TILs) are considered a prognostic marker for triple-negative breast cancer (TNBC). Immune checkpoint inhibitor (ICI)-based treatments are more effective for tumors with PD-L1-positive TILs, suggesting crucial roles of TILs in the local tumor immunity. However, factors attracting TILs are still largely unknown. Focusing on tumor antigenicity, we examined TNBC samples to identify the characteristics of TIL-high tumors. PATIENTS AND METHODS: Nine treatment-naïve TNBCs (TIL-high: five, TIL-low: four) were subjected to next-generation sequencing (NGS). Loss of heterozygosity (LOH) of PTEN was also analyzed. RESULTS: A variety of copy number variations were observed, and no genes differed significantly between TIL-high and -low groups. However, PTEN loss was more frequently observed in the TIL-high group: 60% compared to 25% in TIL-low tumors. NGS correlated well with LOH analysis in identifying PTEN loss. All three tumors with PTEN loss in the TIL-high group showed high PD-L1. All nine samples were microsatellite-stable. CONCLUSION: Frequent PTEN loss and high expression of PD-L1 in TIL-high TNBC suggest that PTEN mutation may be a biomarker for ICIs.

Association of expression of epigenetic molecular factors with DNA methylation and sensitivity to chemotherapeutic agents in cancer cell lines.

BACKGROUND: Altered DNA methylation patterns play important roles in cancer development and progression. We examined whether expression levels of genes directly or indirectly involved in DNA methylation and demethylation may be associated with response of cancer cell lines to chemotherapy treatment with a variety of antitumor agents. RESULTS: We analyzed 72 genes encoding epigenetic factors directly or indirectly involved in DNA methylation and demethylation processes. We examined association of their pretreatment expression levels with methylation beta-values of individual DNA methylation probes, DNA methylation averaged within gene regions, and average epigenome-wide methylation levels. We analyzed data from 645 cancer cell lines and 23 cancer types from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer datasets. We observed numerous correlations between expression of genes encoding epigenetic factors and response to chemotherapeutic agents. Expression of genes encoding a variety of epigenetic factors, including KDM2B, DNMT1, EHMT2, SETDB1, EZH2, APOBEC3G, and other genes, was correlated with response to multiple agents. DNA methylation of numerous target probes and gene regions was associated with expression of multiple genes encoding epigenetic factors, underscoring complex regulation of epigenome methylation by multiple intersecting molecular pathways. The genes whose expression was associated with methylation of multiple epigenome targets encode DNA methyltransferases, TET DNA methylcytosine dioxygenases, the methylated DNA-binding protein ZBTB38, KDM2B, SETDB1, and other molecular factors which are involved in diverse epigenetic processes affecting DNA methylation. While baseline DNA methylation of numerous epigenome targets was correlated with cell line response to antitumor agents, the complex relationships between the overlapping effects of each epigenetic factor on methylation of specific targets and the importance of such influences in tumor response to individual agents require further investigation. CONCLUSIONS: Expression of multiple genes encoding epigenetic factors is associated with drug response and with DNA methylation of numerous epigenome targets that may affect response to therapeutic agents. Our findings suggest complex and interconnected pathways regulating DNA methylation in the epigenome, which may both directly and indirectly affect response to chemotherapy.

Novel candidate factors predicting the effect of S-1 adjuvant chemotherapy of pancreatic cancer.

The collagen gel droplet-embedded drug sensitivity test (CD-DST) was revealed to be useful for predicting the effect of S-1 adjuvant chemotherapy for pancreatic ductal adenocarcinoma (PDAC). However, collection of an adequate number of PDAC cells is difficult due to the surrounding fibroblasts. Thus, the aim of this study was to discover novel biomarkers to predict chemosensitivity based on the CD-DST results. Proteomics analysis was performed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Candidate proteins were validated in patients with 5-FU CD-DST results via immunohistochemistry (IHC). The relationships between the candidate proteins and the effect of the adjuvant S-1 were investigated via IHC. Among the 2696 proteins extracted by LC-MS/MS, C1TC and SAHH could accurately predict the CD-DST results. Recurrence-free survival (RFS) was significantly improved in the IHC-positive group compared with the IHC-negative group in both factors. The negative group did not show a significant difference from the group that did not receive S-1. The double-positive group was associated with significantly prolonged RFS compared to the no adjuvant chemotherapy group. C1TC and SAHH have been shown to be useful biomarkers for predicting 5-FU sensitivity as a substitute for the CD-DST in adjuvant chemotherapy for PDAC.

Dosage strategies for delaying resistance emergence in heterogeneous tumors.

Drug resistance in cancer treatments is a frequent problem that, when it arises, leads to failure in therapeutic efforts. Tumor heterogeneity is the primary reason for resistance emergence and a precise treatment design that takes heterogeneity into account is required to postpone the rise of resistant subpopulations in the tumor environment. In this paper, we present a mathematical framework involving clonal evolution modeling of drug-sensitive and drug-resistant clones. Using our framework, we examine delaying the rise of resistance in heterogeneous tumors during control phase of therapy in a containment treatment approach. We apply pharmacokinetic/pharmacodynamic (PKPD) modeling and show that dosage strategies can be designed to control the resistant subpopulation. Our results show that the drug dosage and schedule determine the relative dynamics of sensitive and resistant clones. We present an optimal control problem that finds the dosing strategy that maximizes the delay in resistance emergence for a given period of containment treatment.

CD3E as a new predictive biomarker of response to omalizumab treatment in asthma patients: Evidence from bioinformatic analysis.

BACKGROUND AND OBJECTIVE: Omalizumab is a bio-targeted agent approved as add-on therapy for the treatment of severe asthma. Most patients with severe asthma show no response to omalizumab. American Thoracic Society (ATS) and European Respiratory Society (ERS) recommend blood eosinophil count and fractional exhaled nitric oxide (FeNO) as biomarkers with high value for increased response to omalizumab and periostin as a biomarker with a low value. In this study, we aimed to identify the biomarkers for predicting treatment response to omalizumab by performing whole blood transcriptional expression profiling using array and clinical data from GSE134544. METHODS: We analyzed GSE134544 whole blood transcriptional and clinical data of omalizumab treatment using xCell, weighted gene co-expression network analysis (WGCNA), gene ontology enrichment analysis, KEGG pathway analysis, protein-protein interaction (PPI) network, and logistic regression analysis. RESULTS: We calculated the immune enrichment score using xCell and found that CD4+ T cells, CD4+ Tem, CD4+ memory T cells, CD8+ Tcm, and dendritic cells (DC) were relatively higher in responders than in non-responders. Analysis of omalizumab response using WGCNA revealed that the above-mentioned significant immune cells in the red module was relevant to the sample traits; there were 547 genes in the red module. We identified 20 hub genes for the PPI network using cytoHubba, a Cytoscape plugin. Using logistic regression analysis, CD3E was found to be the only significant biomarker, and the area under the curve of ROC curves was 0.763. CONCLUSION: CD3E maybe a new predictive biomarker of response to omalizumab treatment in asthma patients and be used to select more suitable asthma patients for omalizumab treatment.

5-Hydroxymethylcytosine profiles of cfDNA are highly predictive of R-CHOP treatment response in diffuse large B cell lymphoma patients.

BACKGROUND: Although R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard chemotherapy regimen for diffuse large B cell lymphoma (DLBCL) patients, not all patients are responsive to the scheme, and there is no effective method to predict treatment response. METHODS: We utilized 5hmC-Seal to generate genome-wide 5hmC profiles in plasma cell-free DNA (cfDNA) from 86 DLBCL patients before they received R-CHOP chemotherapy. To investigate the correlation between 5hmC modifications and curative effectiveness, we separated patients into training (n = 56) and validation (n = 30) cohorts and developed a 5hmC-based logistic regression model from the training cohort to predict the treatment response in the validation cohort. RESULTS: In this study, we identified thirteen 5hmC markers associated with treatment response. The prediction performance of the logistic regression model, achieving 0.82 sensitivity and 0.75 specificity (AUC = 0.78), was superior to existing clinical indicators, such as LDH and stage. CONCLUSIONS: Our findings suggest that the 5hmC modifications in cfDNA at the time before R-CHOP treatment are associated with treatment response and that 5hmC-Seal may potentially serve as a clinical-applicable, minimally invasive approach to predict R-CHOP treatment response for DLBCL patients.

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response.

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.

Genetic ancestry plays a central role in population pharmacogenomics.

Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD ( http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/ ).