The binding profile of SARS-CoV-2 with human leukocyte antigen polymorphisms reveals critical alleles involved in immune evasion.

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), astonished the world and led to millions of deaths. Due to viral new mutations and immune evasion, SARS-CoV-2 ranked first in transmission and influence. The binding affinity of human leukocyte antigen (HLA) polymorphisms to SARS-CoV-2 might be related to immune escape, but the mechanisms remained unclear. In this study, we obtained the binding affinity of SARS-CoV-2 strains with different HLA proteins and identified 31 risk alleles. Subsequent structural predictions identified 10 active binding sites in these HLA proteins that may promote immune evasion. Particularly, we also found that the weak binding ability with HLA class I polymorphisms could contribute to the immune evasion of Omicron. These findings suggest important implications for preventing the immune evasion of SARS-CoV-2 and providing new insights for the vaccine design.

Pharmacoepitranscriptomic landscape revealing m6A modification could be a drug-effect biomarker for cancer treatment.

RNA chemical modifications are a new but rapidly developing field. They can directly affect RNA splicing, transport, stability, and translation. Consequently, they are involved in the occurrence and development of diseases that have been studied extensively in recent years. However, few studies have focused on the correlation between chemical modifications and drug effects. Here, we provide a landscape of six RNA modifications in pharmacogene RNA (pharmacoepitranscriptomics) to fully clarify the correlation between chemical modifications and drugs. We performed systematic and comprehensive analyses on pharmacoepitranscriptomics, including basic characteristics of RNA modification and modification-associated mutations and drugs affected by them. Our results show that chemical modifications are common in pharmacogenes, especially N6-methyladenosine (m6A) modification. In addition, we found a very close relationship between chemical modifications and anti-tumor drugs. More interestingly, the results demonstrate the importance of m6A modification for anti-tumor drugs, especially for drugs in triple-negative breast cancer (TNBC), ovarian cancer, and acute myelocytic leukemia (AML). These results indicate that pharmacoepitranscriptomics could be a new source of drug-effect biomarkers, especially for m6A and anti-tumor drugs.

Reprogramming the tumor microenvironment by genome editing for precision cancer therapy.

The tumor microenvironment (TME) is essential for immune escape by tumor cells. It plays essential roles in tumor development and metastasis. The clinical outcomes of tumors are often closely related to individual differences in the patient TME. Therefore, reprogramming TME cells and their intercellular communication is an attractive and promising strategy for cancer therapy. TME cells consist of immune and nonimmune cells. These cells need to be manipulated precisely and safely to improve cancer therapy. Furthermore, it is encouraging that this field has rapidly developed in recent years with the advent and development of gene editing technologies. In this review, we briefly introduce gene editing technologies and systematically summarize their applications in the TME for precision cancer therapy, including the reprogramming of TME cells and their intercellular communication. TME cell reprogramming can regulate cell differentiation, proliferation, and function. Moreover, reprogramming the intercellular communication of TME cells can optimize immune infiltration and the specific recognition of tumor cells by immune cells. Thus, gene editing will pave the way for further breakthroughs in precision cancer therapy.

Research progress of omics technology in the field of tumor resistance: From single-omics to multi-omics combination application. / ç»„å­¦æŠ€æœ¯åœ¨è‚¿ç˜¤è€è¯é¢†åŸŸçš„ç ”ç©¶è¿›å±•ï¼šä»Žå•ç»„å­¦åˆ°å¤šç»„å­¦è”åˆåº”ç”¨.

Drug resistance is the main obstacle in the treatment of many cancers. It is of great clinical significance to study the mechanism of drug resistance and find new targets. Multi-omics mainly includes genomics, epigenomics, transcriptomics, proteomics, metabolomics, and radiomics. In recent years, the research of tumor resistance has made rapid development, which has significantly accelerated the discovery of new targets.

Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude.

AIMS: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. METHODS: Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. "Gene Score" and "Drug Score" were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. RESULTS: Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. CONCLUSION: We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-021-00247-0.

Rs3802278 in 3'-UTR of SULF1 associated with platinum resistance and survival in Chinese epithelial ovarian cancer patients.

Ovarian cancer is the leading cause of death from gynecologic cancers, but platinum resistance remains a major obstacle in the chemotherapy of ovarian cancer. This study aims to examine the role of polymorphisms in sulfatase 1 (SULF1) in platinum resistance and survival in advanced epithelial ovarian cancer (EOC) patients. We genotyped 12 SNPs of SULF1 in 195 EOC patients treated with platinum using MassARRAY method and evaluated the association between the SNPs and platinum response. SULF1 rs3802278 was marginal significantly associated with platinum resistance in recessive model with p value of 0.055. The patients with SULF1 rs3802278 AA were more resistant to platinum-based chemotherapy comparing to those with AG/GG genotype (OR: 2.317, 95%CI: 0.982 ∼ 5.465). In survival analysis, rs3802278 was significantly associated with both of PFS and OS after adjusted by FIGO stage and age. Patients with AA genotypes showed a shorter PFS and OS than with AG/GG genotypes (median PFS: 15 months vs. 21 months, p = 0.010, HR = 1.876, 95%CI: 1.165-3.022; median OS: 42 months vs. 73 months, p = 0.031, HR = 1.928, 95%CI: 1.061-3.504). SULF1 rs3802278 may serve as a potential candidate biomarker for the prediction of platinum resistance and prognosis in Chinese EOC patients.

Incorporating SULF1 polymorphisms in a pretreatment CT-based radiomic model for predicting platinum resistance in ovarian cancer treatment.

OBJECTIVE: Early detection of platinum resistance for ovarian cancer treatment remains challenging. This study aims to develop a machine learning model incorporating genomic data such as Single-Nucleotide Polymorphisms (SNPs) of Human Sulfatase 1 (SULF1) with a CT radiomic model based on pre-treatment CT images, to predict platinum resistance for ovarian cancer (OC) treatment. METHODS: A cohort of 102 patients with pathologically confirmed OC was retrospectively enrolled into this study from January 2006 to February 2018. All patients had platinum-based chemotherapy after maximal cyto-reductive surgery. This cohort was separated into two groups according to treatment response, i.e., the group with platinum-resistant disease (PR group) and the group with platinum-sensitive disease (PS group). We genotyped 12 SNPs of SULF1 for all OC patients using Mass Array Method. Radiomic features, SNP data and clinicopathological data of the 102 patients were used to build the differentiation models. The study participants were divided into two cohorts: the training cohort (n = 71) and the validation cohort (n = 31). Feature selection and predictive modeling were performed using least absolute shrinkage and selection operator (LASSO), Random Forest Classifier and Support Vector Machine methods. Model performance for predicting platinum resistance was assessed with respect to its calibration, discrimination, and clinical application. RESULTS: For prediction of platinum resistance, the approach combining the radiomics, clinicopathological data and SNP data demonstrated higher classification efficiency, with an AUC value of 0.993 (95 % CI: 0.83 to 0.98) in the training cohort and 0.967 (95 % CI: 0.83 to 0.98) in validation cohort, than the performance with only the SNPs of SULF1 model (AUC: training, 0.843 [95 %CI: 0.738-0.948]; validation, 0.815 [0.601-1.000]), or with only the radiomic model (AUC: training, 0.874 [95 %CI: 0.789-0.960]; validation, 0.832 [95 %CI: 0.687-0.976]). This integrated approach also showed good calibration and favorable clinical utility. CONCLUSIONS: A predictive model combining pretreatment CT radiomics with genomic data such as SNPs of SULF1 could potentially help to predict platinum resistance in ovarian cancer treatment.

The Novel Zinc Finger Protein 587B Gene, ZNF587B, Regulates Cell Proliferation and Metastasis in Ovarian Cancer Cells in vivo and in vitro.

BACKGROUND: The zinc finger protein 587B (ZNF587B) is a novel cisplatin-sensitive gene that was identified in our previous research by using a genome-scale CRISPR-Cas9 knockout library in ovarian cancer (OC) cell lines. ZNF587B belongs to the C2H2-type zinc finger protein (ZFP) family. Many ZFP protein could inhibit tumor development and malignancy. However, the function of ZNF587B remains unknown. METHODS: Quantitative PCR (qPCR) was utilized to compare ZNF587B mRNA expression levels in OC and normal ovarian cell lines. The small interfering RNA (siRNA) and full-length ZNF587B eukaryotic expression plasmid were constructed and transfected into OC cells later. Colony formation, 5-ethynyl-2'-deoxyuridine (EdU) assay, transwell assay, and xenograft experiment were conducted to evaluate the effect of ZNF587B on OC cells. RESULTS: ZNF587B was downregulated by approximately 43% and 17% in the OC cell lines SKOV3 and A2780, respectively, compared with that in the normal ovarian cell line IOSE80. Overexpression of ZNF587B reduced cell proliferation, colony formation, migration, and invasion, which could be reversed by knockdown of ZNF587B via siRNA. Xenograft experiments also confirmed that ZNF587B could suppress tumor growth. Survival data of OC patients in the SurvExpress database showed that with respect to overall survival, low-risk patients grouped by the prognostic index had a higher expression of ZNF587B and a better prognosis than high-risk group (HR = 1.77, 95% CI: 0.55-0.70, p = 0.023). Moreover, overexpression of ZNF587B promoted OC cells apoptosis when pretreated with cisplatin. CONCLUSION: ZNF587B is a novel potential tumor suppressor of OC and may be a therapeutic target for OC.

Artesunate inhibits the mevalonate pathway and promotes glioma cell senescence.

Glioma is a common brain malignancy for which new drug development is urgently needed because of radiotherapy and drug resistance. Recent studies have demonstrated that artemisinin (ARS) compounds can display antiglioma activity, but the mechanisms are poorly understood. Using cell lines and mouse models, we investigated the effects of the most soluble ARS analogue artesunate (ART) on glioma cell growth, migration, distant seeding and senescence and elucidated the underlying mechanisms. Artemisinin effectively inhibited glioma cell growth, migration and distant seeding. Further investigation of the mechanisms showed that ART can influence glioma cell metabolism by affecting the nuclear localization of SREBP2 (sterol regulatory element-binding protein 2) and the expression of its target gene HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), the rate-limiting enzyme of the mevalonate (MVA) pathway. Moreover, ART affected the interaction between SREBP2 and P53 and restored the expression of P21 in cells expressing wild-type P53, thus playing a key role in cell senescence induction. In conclusion, our study demonstrated the new therapeutic potential of ART in glioma cells and showed the novel anticancer mechanisms of ARS compounds of regulating MVA metabolism and cell senescence.

Loss of ZNF587B and SULF1 contributed to cisplatin resistance in ovarian cancer cell lines based on Genome-scale CRISPR/Cas9 screening.

Ovarian cancer is one of the most lethal malignancies of the female reproductive system. Platinum-resistance is the major obstacle in the successful treatment of ovarian cancer. Previous studies largely failed to identify the key genes associated with platinum-resistance by using candidate genes testing, bioinformatic analysis and GWAS method. The aim of the study was to utilize the whole human Genome-scale CRISPR-Cas9 knockout (GeCKO) library to screen for novel genes involved in cisplatin resistance in ovarian cancer cell lines. The GeCKO library targeted 19052 genes with 122417 unique guide sequences. Six candidate genes had been screened out including one previously validated gene SULF1 and five novel genes ZNF587B, TADA1, SEMA4G, POTEC and USP17L20. After validated by CCK-8 and RT-PCR analysis, two genes (ZNF587B and SULF1) were discovered to be involved in cisplatin resistance. ZNF587B may serve as a new biomarker for predicting cisplatin resistance.

Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach.

Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment.

[Research progress of copper transporter 1 in platinum-based chemotherapy].

Platinum drugs are widely used in the treatment of various solid tumors, but their resistance to platinum is the most significant obstacle to successful treatment. Copper transporter 1 (CTR1) is the specific transporter for copper, and it mainly locates at the plasma membrane and plays a role in pumping copper into the cell. CTR1 is also the major platinum influx transporter and plays a key role in platinum resistance. The expression, polymorphism, and degradation of CTR1 affect platinum resistance in tumors. Therefore, CTR1 may be a potential predictive biomarker of platinum resistance and a therapeutic target for overcoming platinum resistance.

Association between polymorphisms in CTR1, CTR2, ATP7A, and ATP7B and platinum resistance in epithelial ovarian cancer.

The copper transporters CTR1, CTR2, ATP7A, and ATP7B regulate intracellular concentration of platinum by mediating its uptake and efflux in cells. We sought to explore the effect of genetic polymorphisms in CTR1, CTR2, ATP7A, and ATP7B on platinum resistance in patients suffering from epithelial ovarian cancer (EOC). A total of 152 Chinese EOC patients were enrolled in this study, all of whom underwent adjuvant chemotherapy using platinum and taxane after maximal debulking surgery. In total, 11 single-nucleotide polymorphisms (SNPs) in CTR1, CTR2, ATP7A, and ATP7B were genotyped in these patients. The CTR1 rs10981694 polymorphism was observed to be associated with carboplatin resistance, while patients with the rs10981694 G allele showed a significantly higher rate of carboplatin resistance (OR = 4.00, 95% CI 1.309 - 12.23, p < 0.01). In addition, we found that ATP7A rs2227291 was associated with cisplatin resistance and that carriers of the C allele were more sensitive to cisplatin (OR = 0.40, 95% CI: 0.17 - 0.94, p = 0.03). Our findings suggest that the CTR1 and ATP7A genetic polymorphisms could affect platinum resistance. The CTR1 and ATP7A genes might be considered a predictive marker for carboplatin and cisplatin resistance, respectively.
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