Clin Pharmacol Ther. 2021 Jul 3. doi: 10.1002/cpt.2329. Online ahead of print.

NO ABSTRACT

PMID:34217153 | DOI:10.1002/cpt.2329

Clin Pharmacol Ther. 2021 Jul 3. doi: 10.1002/cpt.2350. Online ahead of print.

ABSTRACT

Clinical annotations are one of the most popular resources available on the Pharmacogenomics Knowledgebase (PharmGKB). Each clinical annotation summarizes the association between variant-drug pairs, shows relevant findings from the curated literature and is assigned a level of evidence (LOE) to indicate the strength of support for that association. Evidence from the pharmacogenomic literature is curated into PharmGKB as variant annotations, which can be used to create new clinical annotations or added to existing clinical annotations. This means that the same clinical annotation can be worked on by multiple curators over time. As more evidence is curated into PharmGKB, the task of maintaining consistency when assessing all the available evidence and assigning a level of evidence becomes increasingly difficult. To remedy this, a scoring system has been developed to automate LOE assignment to clinical annotations. Variant annotations are scored according to certain attributes including study size, reported p-value and whether the variant annotation supports or fails to find an association. Clinical guidelines or FDA-approved drug labels which give variant-specific prescribing guidance are also scored. The scores of all annotations attached to a clinical annotation are summed together to give a total score for the clinical annotation, which is used to calculate a LOE. Overall, the system increases transparency, consistency and reproducibility in LOE assignment to clinical annotations. In combination with increased standardization of how clinical annotations are written, use of this scoring system helps to ensure that PharmGKB clinical annotations continue to be a robust source of pharmacogenomic information.

PMID:34216021 | DOI:10.1002/cpt.2350

Pharmacogenomics J. 2021 Jul 2. doi: 10.1038/s41397-021-00249-1. Online ahead of print.

ABSTRACT

Nowadays, many relevant drug-gene associations have been discovered, but pharmacogenomics (PGx)-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health care. To address current challenges, this systematic review provides an update regarding previously published studies, which assessed the cost-effectiveness of PGx testing for the prescription of antidepressants and antipsychotics. From a total of 1159 studies initially identified by literature database querying, and after manual assessment and curation of all of them, a mere 18 studies met our inclusion criteria. Of the 18 studies evaluations, 16 studies (88.89%) drew conclusions in favor of PGx testing, of which 9 (50%) genome-guided interventions were cost-effective and 7 (38.9%) were less costly compared to standard treatment based on cost analysis. More precisely, supportive evidence exists for CYP2D6 and CYP2C19 drug-gene associations and for combinatorial PGx panels, but evidence is limited for many other drug-gene combinations. Amongst the limitations of the field are the unclear explanation of perspective and cost inputs, as well as the underreporting of study design elements, which can influence though the economic evaluation. Overall, the findings of this article demonstrate that although there is growing evidence on the cost-effectiveness of genome-guided interventions in psychiatric diseases, there is still a need for performing additional research on economic evaluations of PGx implementation with an emphasis on psychiatric disorders.

PMID:34215853 | DOI:10.1038/s41397-021-00249-1

Cancer Res. 2021 Jul 2:canres.CAN-21-0716-A.2021. doi: 10.1158/0008-5472.CAN-21-0716. Online ahead of print.

ABSTRACT

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most critical gaps in enabling the effective use of cancer therapies. Here we couple a multiplexed and quantitative experimental platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. The complex map of genotype-specific treatment responses uncovered that over 20% of possible interactions show significant resistance or sensitivity. Known and novel interactions were identified, and one of these interactions, the resistance of KEAP1 mutant lung tumors to platinum therapy, was validated using a large patient response dataset. These results highlight the broad impact of tumor suppressor genotype on treatment responses and define a strategy to identify the determinants of precision therapies.

PMID:34215621 | DOI:10.1158/0008-5472.CAN-21-0716

J Clin Endocrinol Metab. 2021 Jul 2:dgab490. doi: 10.1210/clinem/dgab490. Online ahead of print.

ABSTRACT

CONTEXT: In a cross-sectional study, we found an association between type 2 diabetes mellitus (T2DM) and smaller bone area together with a greater bone mineral density (BMD) at the total hip.

OBJECTIVE: To investigate these associations longitudinally, by studying T2DM status (no T2DM n=1521, incident T2DM n=119 or prevalent T2DM n=106) in relation to changes in total hip bone area and BMD.

METHODS: In three cohorts, the Swedish Mammography Cohort Clinical (SMCC; n=1060, Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS; n=483) and Uppsala Longitudinal Study of Adult Men (ULSAM; n=203), with repeat assessment of T2DM status and dual energy x-ray absorptiometry (DXA) measurements of total hip bone area and BMD on average 8 years apart, a linear regression model was used to assess the effect of T2DM status on change in bone area and BMD at the total hip.

RESULTS: After meta-analysis, the change in bone area at the total hip was 0.5% lower among those with incident T2DM compared to those without T2DM (-0.18 cm 2 [95% CI -0.30, -0.06]). The change in bone area was similar among those with prevalent T2DM compared to those without (0.00 cm 2 [95% CI -0.13, 0.13]). For BMD, the combined estimate was 0.004 g/cm 2 (95% CI -0.006, 0.014) among those with incident T2DM and 0.010 g/cm 2 (95% CI -0.000, 0.020) among those with prevalent T2DM, compared to those without T2DM.

CONCLUSION: Those with incident T2DM have a lower expansion in bone area at the total hip compared to those without T2DM.

PMID:34214157 | DOI:10.1210/clinem/dgab490

J Intern Med. 2021 Jul 2. doi: 10.1111/joim.13330. Online ahead of print.

ABSTRACT

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

PMID:34213793 | DOI:10.1111/joim.13330

Clin Pharmacol Ther. 2021 Jul 2. doi: 10.1002/cpt.2352. Online ahead of print.

ABSTRACT

Real-world prescribing of drugs differs from the experimental systems, physiological-pharmacokinetic (PK) models and clinical trials used in drug development and licensing, with drugs often used in patients with multiple comorbidities with resultant polypharmacy. The increasing availability of large biobanks linked to electronic healthcare records enables the potential to identify novel drug-gene interactions in large populations of patients. In this study we used 3 Scottish cohorts and UK Biobank to identify drug-gene interactions for the 50 most commonly used drugs and 162 variants in genes involved in drug pharmacokinetics. We defined two phenotypes based upon prescribing behaviour - drug-stop or dose-decrease. Using this approach, we replicate 11 known drug-gene interactions including, for example, CYP2C9/CYP2C8 variants and sulphonylurea/thiazolidinedione prescribing and ABCB1/ABCG2 variants and statin prescribing. We identify 8 novel associations after bonferroni correction, 3 of which are replicated or validated in the UK biobank or have other supporting results: The C-allele at rs4918758 in CYP2C9 was associated with a 25% (15-44%) lower odds of dose reduction of quinine, p=1.6×10-5 ; the A-allele at rs9895420 in ABCC3 was associated with a 46% (24-62%) reduction in odds of dose reduction with doxazosin, p=1.2×10-4 , and altered blood pressure response in the UK Biobank; the CYP2D6*2 variant was associated with a 30% (18 %- 40%) reduction in odds of stopping ramipril treatment, p=1.01×10-5 , with similar results seen for enalapril and lisinopril and with other CYP2D6 variants. This study highlights the scope of using large population bioresources linked to medical record data to explore drug-gene interactions at scale.

PMID:34213766 | DOI:10.1002/cpt.2352

Front Genet. 2021 Jun 15;12:662734. doi: 10.3389/fgene.2021.662734. eCollection 2021.

ABSTRACT

BACKGROUND: Aromatase inhibitors (AI) reduce recurrence and death in patients with early-stage hormone receptor-positive (HR +) breast cancer. Treatment-related toxicities, including AI-induced musculoskeletal symptoms (AIMSS), are common and may lead to early AI discontinuation. The objective of this study was to replicate previously reported associations for candidate germline genetic polymorphisms with AIMSS.

METHODS: Women with stage 0-III HR + breast cancer initiating adjuvant AI were enrolled in a prospective clinic-based observational cohort. AIMSS were assessed by patient-reported outcomes (PRO) including the PROMIS pain interference and physical function measures plus the FACT-ES joint pain question at baseline and after 3 and 6 months. For the primary analysis, AIMSS were defined as ≥ 4-point increase in the pain interference T-score from baseline. Secondary AIMSS endpoints were defined as ≥ 4-point decrease in the physical function T-score from baseline and as ≥ 1-point increase on the FACT-ES joint pain question from baseline. The primary hypothesis was that TCL1A rs11849538 would be associated with AIMSS. Twelve other germline variants in CYP19A1, VDR, PIRC66, OPG, ESR1, CYP27B1, CYP17A1, and RANKL were also analyzed assuming a dominant genetic effect and prespecified direction of effect on AIMSS using univariate logistic regression with an unadjusted α = 0.05. Significant univariate associations in the expected direction were adjusted for age, race, body mass index (BMI), prior taxane, and the type of AI using multivariable logistic regression.

RESULTS: A total of 143 participants with PRO and genetic data were included in this analysis, most of whom were treated with anastrozole (78%) or letrozole (20%). On primary analysis, participants carrying TCL1A rs11849538 were not more likely to develop AIMSS (odds ratio = 1.29, 95% confidence interval: 0.55-3.07, p = 0.56). In the statistically uncorrected secondary analysis, OPG rs2073618 was associated with AIMSS defined by worsening on the FACT-ES joint pain question (OR = 3.33, p = 0.004), and this association maintained significance after covariate adjustment (OR = 3.98, p = 0.003).

CONCLUSION: Carriers of OPG rs2073618 may be at increased risk of AIMSS. If confirmed in other cohorts, OPG genotyping can be used to identify individuals with HR + early breast cancer in whom alternate endocrine therapy or interventions to enhance symptom detection and implement strategies to reduce musculoskeletal symptoms may be needed.

PMID:34211496 | PMC:PMC8239354 | DOI:10.3389/fgene.2021.662734

Nutrients. 2021 Jun 29;13(7):2234. doi: 10.3390/nu13072234.

ABSTRACT

Gut microbiota dysbiosis is a common feature in colorectal cancer (CRC) and inflammatory bowel diseases (IBD). Adoption of the Mediterranean diet (MD) has been proposed as a therapeutic approach for the prevention of multiple diseases, and one of its mechanisms of action is the modulation of the microbiota. We aimed to determine whether MD can be used as a preventive measure against cancer and inflammation-related diseases of the gut, based on its capacity to modulate the local microbiota. A joint meta-analysis of publicly available 16S data derived from subjects following MD or other diets and from patients with CRC, IBD, or other gut-related diseases was conducted. We observed that the microbiota associated with MD was enriched in bacteria that promote an anti-inflammatory environment but low in taxa with pro-inflammatory properties capable of altering intestinal barrier functions. We found an opposite trend in patients with intestinal diseases, including cancer. Some of these differences were maintained even when MD was compared to healthy controls without a defined diet. Our findings highlight the unique effects of MD on the gut microbiota and suggest that integrating MD principles into a person's lifestyle may serve as a preventive method against cancer and other gut-related diseases.

PMID:34209683 | DOI:10.3390/nu13072234

Behav Sci (Basel). 2021 Jun 30;11(7):97. doi: 10.3390/bs11070097.

ABSTRACT

There is growing research interest in learning the genetic basis of response and adverse effects with psychotropic medications, including antipsychotic drugs. However, the clinical utility of information from genetic studies is compromised by their controversial results, primarily due to relatively small effect and sample sizes. Clinical, demographic, and environmental differences in patient cohorts further explain the lack of consistent results from these genetic studies. Furthermore, the availability of psychopharmacological expertise in interpreting clinically meaningful results from genetic assays has been a challenge, one that often results in suboptimal use of genetic testing in clinical practice. These limitations explain the difficulties in the translation of psychopharmacological research in pharmacogenetics and pharmacogenomics from bench to bedside to manage increasingly treatment-refractory psychiatric disorders, especially schizophrenia. Although these shortcomings question the utility of genetic testing in the general population, the commercially available genetic assays are being increasingly utilized to optimize the effectiveness of psychotropic medications in the treatment-refractory patient population, including schizophrenia. In this context, patients with treatment-refractory schizophrenia are among of the most vulnerable patients to be exposed to the debilitating adverse effects from often irrational and high-dose antipsychotic polypharmacy without clinically meaningful benefits. The primary objective of this comprehensive review is to analyze and interpret replicated findings from the genetic studies to identify specific genetic biomarkers that could be utilized to enhance antipsychotic efficacy and tolerability in the treatment-refractory schizophrenia population.

PMID:34209185 | DOI:10.3390/bs11070097

J Clin Med. 2021 Jun 30;10(13):2949. doi: 10.3390/jcm10132949.

ABSTRACT

Patients with venous thromboembolism (VTE) require immediate treatment with anticoagulants such as acenocoumarol. This multicentre randomised clinical trial evaluated the effectiveness of a dosing pharmacogenetic algorithm versus a standard-of-care dose adjustment at the beginning of acenocoumarol treatment. We included 144 patients with VTE. On the day of recruitment, a blood sample was obtained for genotyping (CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2, APOE). Dose adjustment was performed on day 3 or 4 after the start of treatment according to the assigned group and the follow-up was at 12 weeks. The principal variable was the percentage of patients with an international normalised ratio (INR) within the therapeutic range on day 7. Thirty-four (47.2%) patients had an INR within the therapeutic range at day 7 after the start of treatment in the genotype-guided group compared with 14 (21.9%) in the control group (p = 0.0023). There were no significant differences in the time to achieve a stable INR, the number of INRs within the range in the first 6 weeks and at the end of study. Our results suggest the use of a pharmacogenetic algorithm for patients with VTE could be useful in achieving target INR control in the first days of treatment.

PMID:34209131 | DOI:10.3390/jcm10132949

Cancers (Basel). 2021 Jun 9;13(12):2878. doi: 10.3390/cancers13122878.

ABSTRACT

High-grade osteosarcoma (HGOS), the most common primary malignant tumor of bone, is a highly aggressive neoplasm with a cure rate of approximately 40-50% in unselected patient populations. The major clinical problems opposing the cure of HGOS are the presence of inherent or acquired drug resistance and the development of metastasis. Since the drugs used in first-line chemotherapy protocols for HGOS and clinical outcome have not significantly evolved in the past three decades, there is an urgent need for new therapeutic biomarkers and targeted treatment strategies, which may increase the currently available spectrum of cure modalities. Unresponsive or chemoresistant (refractory) HGOS patients usually encounter a dismal prognosis, mostly because therapeutic options and drugs effective for rescue treatments are scarce. Tailored treatments for different subgroups of HGOS patients stratified according to drug resistance-related biomarkers thus appear as an option that may improve this situation. This review explores drug resistance-related biomarkers, therapeutic targets and new candidate treatment strategies, which have emerged in HGOS. In addition to consolidated biomarkers, specific attention has been paid to the role of non-coding RNAs, tumor-derived extracellular vesicles, and cancer stem cells as contributors to drug resistance in HGOS, in order to highlight new candidate markers and therapeutic targets. The possible use of new non-conventional drugs to overcome the main mechanisms of drug resistance in HGOS are finally discussed.

PMID:34207685 | DOI:10.3390/cancers13122878

J Pers Med. 2021 Jun 18;11(6):573. doi: 10.3390/jpm11060573.

ABSTRACT

Abatacept (ABA) is an immunosuppressant indicated for treatment of rheumatoid arthritis (RA). Effectiveness might be influenced by clinical RA variants and single-nucleotide polymorphisms (SNPs) in genes encoding protein FCGR2A (His131Arg) and FCGR3A (Phe158Val) involved in pharmacokinetics of ABA. An observational cohort study was conducted in 120 RA Caucasian patients treated with ABA for 6 and 12 months. Patients with the FCGR2A rs1801274-AA genotype (FCGR2A-p.131His) showed a better EULAR response (OR = 2.43; 95% CI = 1.01-5.92) at 12 months and low disease activity (LDA) at 6 months (OR = 3.16; 95% CI = 1.19-8.66) and 12 months (OR = 6.62; 95% CI = 1.25-46.89) of treatment with ABA. A tendency was observed towards an association between the FCGR3A rs396991-A allele (FCGR3A-p.158Phe) and better therapeutic response to ABA after 12 months of treatment (p = 0.078). Moreover, we found a significant association between the low-affinity FCGR2A/FCGR3A haplotypes variable and LDA after 12 months of ABA treatment (OR = 1.59; 95% CI = 1.01-2.58). The clinical variables associated with better response to ABA were lower age at starting ABA (OR = 1.06; 95% CI = 1.02-1.11) and greater duration of ABA treatment (OR = 1.02; 95% CI = 1.01-1.04), lower duration of previous biological therapies (OR = 0.99; 95% CI = 0.98-0.99), non-administration of concomitant disease-modifying antirheumatic drugs (DMARDs) (OR = 24.53; 95% CI = 3.46-523.80), non-use of concomitant glucocorticoids (OR = 0.12; 95% CI = 0.02-0.47), monotherapy (OR = 19.22; 95% CI = 2.05-343.00), lower initial patient's visual analogue scale (PVAS) value (OR = 0.95; 95% CI = 0.92-0.97), and lower baseline ESR (OR = 0.92; 95% CI = 0.87-0.97). This study showed that high-affinity FCGR2A-p.131His variant, low-affinity FCGR3A-p.158Phe variant, and combined use of FCGR2A/FCGR3A genetic variations could affect ABA effectiveness. Further studies will be required to confirm these results.

PMID:34207385 | DOI:10.3390/jpm11060573

Genes (Basel). 2021 Jun 18;12(6):933. doi: 10.3390/genes12060933.

ABSTRACT

The identification of genomic alterations in tumor tissues, including somatic mutations, deletions, and gene amplifications, produces large amounts of data, which can be correlated with a diversity of therapeutic responses. We aimed to provide a methodological framework to discover pharmacogenomic interactions based on Random Forests. We matched two databases from the Cancer Cell Line Encyclopaedia (CCLE) project, and the Genomics of Drug Sensitivity in Cancer (GDSC) project. For a total of 648 shared cell lines, we considered 48,270 gene alterations from CCLE as input features and the area under the dose-response curve (AUC) for 265 drugs from GDSC as the outcomes. A three-step reduction to 501 alterations was performed, selecting known driver genes and excluding very frequent/infrequent alterations and redundant ones. For each model, we used the concordance correlation coefficient (CCC) for assessing the predictive performance, and permutation importance for assessing the contribution of each alteration. In a reasonable computational time (56 min), we identified 12 compounds whose response was at least fairly sensitive (CCC > 20) to the alteration profiles. Some diversities were found in the sets of influential alterations, providing clues to discover significant drug-gene interactions. The proposed methodological framework can be helpful for mining pharmacogenomic interactions.

PMID:34207374 | DOI:10.3390/genes12060933

Diagnostics (Basel). 2021 Jun 26;11(7):1169. doi: 10.3390/diagnostics11071169.

ABSTRACT

For many authorized drugs, accumulating scientific evidence supports testing for predictive biomarkers to apply personalized therapy and support preventive measures regarding adverse drug reactions and treatment failure. Here, we review cytogenetic and biochemical genetic testing methods that are available to guide therapy with drugs centrally approved in the European Union (EU). We identified several methods and combinations of techniques registered in the Genetic Testing Registry (GTR), which can be used to guide therapy with drugs for which pharmacogenomic-related information is provided in the European public assessment reports. Although this registry provides information on genetic tests offered worldwide, we identified limitations regarding standard techniques applied in clinical practice and the information on test validity rarely provided in the according sections.

PMID:34206978 | DOI:10.3390/diagnostics11071169

Cancers (Basel). 2021 Jun 22;13(13):3107. doi: 10.3390/cancers13133107.

ABSTRACT

Gastric cancer (GC) is a worldwide health problem, making it one of the most common types of cancer, in fifth place of all tumor types, and the third highest cause of cancer deaths in the world. There is a subgroup of GC that consists of tumors infected with the Epstein-Barr virus (EBV) and is characterized mainly by the overexpression of programmed cell death protein-ligand-1 (PD-L1). In the present study, we present histopathological and survival data of a thousand GC patients, associated with EBV status and PD-L1 expression. Of the thousand tumors analyzed, 190 were EBV-positive and the vast majority (86.8%) had a high relative expression of mRNA and PD-L1 protein (p < 0.0001) in relation to non-neoplastic control. On the other hand, in EBV-negative samples, the majority had a low PD-L1 expression of RNA and protein (p < 0.0001). In the Kaplan-Meier analysis, the probability of survival and increased overall survival of EBV-positive GC patients was impacted by the PD-L1 overexpression (p < 0.0001 and p = 0.004, respectively). However, the PD-L1 low expression was correlated with low overall survival in those patients. Patients with GC positive for EBV, presenting PD-L1 overexpression can benefit from immunotherapy treatments and performing the quantification of PD-L1 in gastric neoplasms should be adopted as routine.

PMID:34206307 | DOI:10.3390/cancers13133107

Medicina (Kaunas). 2021 Jun 19;57(6):636. doi: 10.3390/medicina57060636.

ABSTRACT

Tumor chemosensitivity assays (TCAs), also known as drug response assays or individualized tumor response tests, have been gaining attention over the past few decades. Although there have been strong positive correlations between the results of these assays and clinical outcomes, they are still not considered routine tests in the care of cancer patients. The correlations between the assays' results (drug sensitivity or resistance) and the clinical evaluations (e.g., response to treatment, progression-free survival) are highly promising. However, there is still a need to design randomized controlled prospective studies to secure the place of these assays in routine use. One of the best ideas to increase the value of these assays could be the combination of the assay results with the omics technologies (e.g., pharmacogenetics that gives an idea of the possible side effects of the drugs). In the near future, the importance of personalized chemotherapy is expected to dictate the use of these omics technologies. The omics relies on the macromolecules (Deoxyribonucleic acid -DNA-, ribonucleic acid -RNA-) and proteins (meaning the structure) while TCAs operate on living cell populations (meaning the function). Therefore, wise combinations of TCAs and omics could be a highly promising novel landscape in the modern care of cancer patients.

PMID:34205407 | DOI:10.3390/medicina57060636

Int J Mol Sci. 2021 Jun 17;22(12):6480. doi: 10.3390/ijms22126480.

ABSTRACT

We report two cases of patients who developed severe adverse drug reactions including persistent movement disorders, nausea, and vertigo during treatment with quetiapine at maximum daily doses ranging between 300 and 400 mg. The extensive hepatic metabolism of quetiapine is mainly attributed to cytochrome P450 3A4 (CYP3A4). However, there is recent evidence supporting the idea of CYP2D6 playing a role in the clearance of the quetiapine active metabolite norquetiapine. Interestingly, both patients we are reporting of are carriers of the CYP2D6*4 variant, predicting an intermediate metabolizer phenotype. Additionally, co-medication with a known CYP2D6 inhibitor and renal impairment might have further affected quetiapine pharmacokinetics. The herein reported cases could spark a discussion on the potential impact of a patient's pharmacogenetic predisposition in the treatment with quetiapine. However, further studies are warranted to promote the adoption of pharmacogenetic testing for the prevention of drug-induced toxicities associated with quetiapine.

PMID:34204223 | DOI:10.3390/ijms22126480

Biomedicines. 2021 Jun 15;9(6):677. doi: 10.3390/biomedicines9060677.

ABSTRACT

Perfluorooctane sulfonic acid (PFOS), a persistent environmental pollutant, has adverse effects on gestation pregnancy. Peroxisome proliferator-activated receptor γ (PPARγ) is involved in angiogenesis, metabolic processes, anti-inflammatory, and reproductive development. However, the function of PPARγ in PFOS evoked disadvantageous effects on the placenta remain uncertain. Here, we explored the role of PPARγ in PFOS-induced placental toxicity. Cell viability, cell migration, angiogenesis, and mRNA expression were monitored by CCK-8 assay, wound healing assay, tube formation assay, and real-time PCR, respectively. Activation and overexpression of PPARγ were conducted by rosiglitazone or pcDNA-PPARγ, and inhibition and knockdown of PPARγ were performed by GW9662 or si-PPARγ. Results revealed that PFOS decreased cell growth, migration, angiogenesis, and increased inflammation in human HTR-8/SVneo and JEG-3 cells. Placenta diameter and fetal weight decreased in mice treated with PFOS (12.5 mg/kg). In addition, rosiglitazone or pcDNA-PPARγ rescued cell proliferation, migration, angiogenesis, and decreased inflammation induced by PFOS in HTR8/SVneo and JEG-3 cells. Furthermore, GW9662 or si-PPARγ exacerbated the inhibition of cell viability, migration, angiogenesis, and aggravated inflammation induced by PFOS in HTR-8/SVneo and JEG-3 cells. Meanwhile, the results of mRNA expression level were consistent with the cell representation. In conclusion, our findings revealed that PFOS induced placenta cell toxicity and functional damage through PPARγ pathway.

PMID:34203907 | DOI:10.3390/biomedicines9060677

Cancers (Basel). 2021 Jun 24;13(13):3161. doi: 10.3390/cancers13133161.

ABSTRACT

Acute Myeloid Leukemia (AML) is a heterogeneous disease with several recurrent cytogenetic abnormalities. Despite genomics and transcriptomics profiling efforts to understand AML's heterogeneity, studies focused on the proteomic profiles associated with pediatric AML cytogenetic features remain limited. Furthermore, the majority of biological functions within cells are operated by proteins (i.e., enzymes) and most drugs target the proteome rather than the genome or transcriptome, thus, highlighting the significance of studying proteomics. Here, we present our results from a pilot study investigating global proteomic profiles of leukemic cells obtained at diagnosis from 16 pediatric AML patients using a robust TMT-LC/LC-MS/MS platform. The proteome profiles were compared among patients with or without core binding factor (CBF) translocation indicated by a t(8;21) or inv(16) cytogenetic abnormality, minimal residual disease status at the end of the first cycle of chemotherapy (MRD1), and in vitro chemosensitivity of leukemic cells to cytarabine (Ara-C LC50). Our results established proteomic differences between CBF and non-CBF AML subtypes, providing insights to AML subtypes physiology, and identified potential druggable proteome targets such as THY1 (CD90), NEBL, CTSF, COL2A1, CAT, MGLL (MAGL), MACROH2A2, CLIP2 (isoform 1 and 2), ANPEP (CD13), MMP14, and AK5.

PMID:34202615 | DOI:10.3390/cancers13133161