DataSheet_1_Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review.pdf

Aims and backgroundA number of population pharmacokinetic (PPK) models of anti-programmed cell death-1 (PD-1) monoclonal antibodies (mAbs) in multiple tumor types have been published to characterize the influencing factors of their pharmacokinetics. This review described PPK models of anti-PD-1 mAbs that investigate the magnitude and types of covariate effects in PK parameters, provide a reference for building PPK models of other anti-PD-1 mAbs, and identify areas requiring additional research to facilitate the application of PPK models.MethodsA systematic search for analyses of PPK models of eleven anti-PD-1 mAbs on the market that were carried out in humans was conducted using PubMed, Embase, and the Cochrane Library. The search covered the period from the inception of the databases to April 2022.ResultsCurrently, there are fourteen analyses on PPK models of anti-PD-1 mAbs summarized in this review, including seven models that refer to nivolumab, four referring to pembrolizumab, one referring to cemiplimab, one referring to camrelizumab, and one referred to dostarlimab. Most analyses described the pharmacokinetics of anti-PD-1 mAbs with a two-compartment model with time-varying clearance (CL) and a sigmoidal maximum effect. The estimated CL and volume of distribution in the central (VC) ranged from 0.179 to 0.290 L/day and 2.98 to 4.46 L, respectively. The median (range) of interindividual variability (IIV) for CL and VC was 30.9% (8.7%–50.8%) and 29.0% (4.32%–40.7%), respectively. The commonly identified significant covariates were body weight (BW) on CL and VC, and albumin (ALB), tumor type, sex, and performance status (PS) on CL. Other less assessed significant covariates included lactate dehydrogenase (LDH), immunoglobulin G (IgG), ipilimumab coadministration (IPICO) on CL, and body mass index (BMI), malignant pleural mesothelioma (MESO) on VC.ConclusionThis review provides detailed information about the characteristics of PPK models of anti-PD-1 mAbs, the effects of covariates on PK parameters, and the current status of the application of the models. ALB, BW, specific tumor type, sex, and PS should be considered for the future development of the PPK model of anti-PD-1 mAbs. Other potential covariates that were assessed less frequently but still have significance (e.g., LDH, IgG, and IPICO) should not be ignored. Thus, further research and thorough investigation are needed to assess new or potential covariates, which will pave the way for personalized anti-PD-1 mAbs therapy.</p

Additional file 1 of Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis

Additional file 1

Data_Sheet_1_Improvements in High-Density Lipoprotein Quantity and Quality Contribute to the Cardiovascular Benefits by Anti-tumor Necrosis Factor Therapies in Rheumatoid Arthritis: A Systemic Review and Meta-Analysis.docx

Objective: Inflammation plays important role in atherosclerotic cardiovascular diseases (CVDs), but the interaction between the inflammation and lipid profile is largely unrevealed in humans. Patients with rheumatoid arthritis (RA) suffer from a higher risk of CVDs. Decreased total cholesterol (TC) and high-density lipoprotein (HDL) were prevalent in patients with RA. Anti-tumor necrosis factor (TNF) therapies relieve disease activity and decrease CVDs risk in RA, but their comprehensive effects on the lipid profile are unclear. This study aims to investigate the changes in blood lipid profile along time in the patients with RA accepting anti-TNF therapies by meta-analysis.Methods: The MEDLINE, the Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched for eligible literature. Data of lipids were classified into short-, mid-, and long-term according to treatment duration. Meta-analyses were performed to compare the lipid levels before and after treatments.Results: A total of 44 records and 3,935 patients were included in the meta-analyses. Anti-TNF therapies were associated with significant increase in TC [mean difference (MD): +0.14, +0.23, and +0.26 mmol/l, respectively] and HDL (MD): +0.11, +0.12, and +0.11 mmol/l, respectively) in the short-, mid-, and long-term; anti-TNF therapies were associated with increased low-density lipoprotein (LDL) (MD: +0.06 mmol/l) and apolipoprotein A1 (ApoA1) (MD: +0.07 g/l) in the short-term, but not in the mid-term and long-term; triglyceride (TG) and apolipoprotein B (ApoB) do not change significantly in all the periods; proatherosclerotic indexes (TC/HDL, ApoB/ApoA1, and LDL/HDL) tend to decrease in the short- and mid-term, but return to baseline in the long-term after TNF inhibition.Conclusion: Anti-TNF therapies were related to a long-term raised HDL level, which, together with evidence of improved HDL function, may contribute partially to the decreased CVDs risk by TNF inhibition.</p

Image_3_Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas.png

Soft tissue sarcomas (STSs) are heterogeneous malignancies derived from mesenchymal cells. Due to its rarity, heterogeneity, and limited overall response to chemotherapy, STSs represent a therapeutic challenge. Necroptosis is a novel therapeutic strategy for enhancing immunotherapy of cancer. Nevertheless, no research has explored the relationship between necroptosis-related genes (NRGs) and STSs. In this study, differentially expressed NRGs were identified using The Cancer Genome Atlas (TCGA) and The Cancer Genotype-Tissue Expression (GTEx) project. The expression levels of 34 NRGs were significantly different. Several key NRGs were validated using RT-qPCR and our own sequencing data. Patients with STSs were divided into two clusters using consensus cluster analysis, and significant differences were observed in their survival (p=0.002). We found the differentially expressed genes (DEGs) between the two clusters and carried out subsequent analysis. The necroptosis-related gene signatures with 10 key DEGs were identified with a risk score constructed. The prognosis of TCGA-SARC cohort with low necroptosis-related risk score was better (p<0.001). Meanwhile, the low-risk group had a significantly increased immune infiltration. Using the data of GSE17118 and another immunotherapy cohort as external validations, we observed significant survival differences between the two risk groups (p=0.019). The necroptosis-related risk score proved to be an independent prognostic factor, and a nomogram was further established and integrated with other clinical features. Notably, the necroptosis-related gene signature could also act as the prognostic indicator in other malignancies based on pan-cancer analysis. In summary, the study outlines NRGs in STSs and their potential role in prognosis and will be one of the important directions for future research.</p

Table_1_Incidence and Predictors of Synchronous Bone Metastasis in Newly Diagnosed Differentiated Thyroid Cancer: A Real-World Population-Based Study.DOCX

BackgroundClinical and sociodemographic characteristics of differentiated thyroid cancer (DTC) patients with synchronous bone metastasis (SBM) remain unclear. This real-world study aimed to elucidate the incidence and prognosis of DTC patients with SBM using population-based data.MethodsData of patients with newly diagnosed DTC from 2010 to 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariable logistic regression analysis was utilized to identify predictors of developing SBM in patients with DTC and was further evaluated by receiver operator characteristics (ROC) analysis. Multivariable Cox regression was applied to identify prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS).ResultsA total of 67,176 patients with DTC were screened from the database, with 0.36% (244/67,176) developed SBM. The age-adjusted incidence of SBM in patients with DTC was relatively stable during the study period with an average annual percentage change (AAPC) of 2.52. Multivariable logistic regression analysis recognized seven factors (older age, male gender, black race, other races, follicular histology, the American Joint Committee on Cancer (AJCC) T2, T3, T4 staging, and N1 staging) as predictors of developing SBM among the entire cohort, with the value of area under the curve (AUC) of 0.931 (95% CI: 0.915–0.947). The median survival time of DTC patients with SBM was 22 months (interquartile range, 7–47 months). The multivariable Cox regression analysis indicated multiple metastatic sites, surgical procedures, and chemotherapy as predictors for the survival of patients.ConclusionsPredictors and prognostic factors of SBM in patients with DTC were identified in this study. Patients with risk factors should be given more attention in clinical practice.</p

Image_3_Incidence and Predictors of Synchronous Bone Metastasis in Newly Diagnosed Differentiated Thyroid Cancer: A Real-World Population-Based Study.JPEG

BackgroundClinical and sociodemographic characteristics of differentiated thyroid cancer (DTC) patients with synchronous bone metastasis (SBM) remain unclear. This real-world study aimed to elucidate the incidence and prognosis of DTC patients with SBM using population-based data.MethodsData of patients with newly diagnosed DTC from 2010 to 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariable logistic regression analysis was utilized to identify predictors of developing SBM in patients with DTC and was further evaluated by receiver operator characteristics (ROC) analysis. Multivariable Cox regression was applied to identify prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS).ResultsA total of 67,176 patients with DTC were screened from the database, with 0.36% (244/67,176) developed SBM. The age-adjusted incidence of SBM in patients with DTC was relatively stable during the study period with an average annual percentage change (AAPC) of 2.52. Multivariable logistic regression analysis recognized seven factors (older age, male gender, black race, other races, follicular histology, the American Joint Committee on Cancer (AJCC) T2, T3, T4 staging, and N1 staging) as predictors of developing SBM among the entire cohort, with the value of area under the curve (AUC) of 0.931 (95% CI: 0.915–0.947). The median survival time of DTC patients with SBM was 22 months (interquartile range, 7–47 months). The multivariable Cox regression analysis indicated multiple metastatic sites, surgical procedures, and chemotherapy as predictors for the survival of patients.ConclusionsPredictors and prognostic factors of SBM in patients with DTC were identified in this study. Patients with risk factors should be given more attention in clinical practice.</p

Image_2_Incidence and Predictors of Synchronous Bone Metastasis in Newly Diagnosed Differentiated Thyroid Cancer: A Real-World Population-Based Study.JPEG

BackgroundClinical and sociodemographic characteristics of differentiated thyroid cancer (DTC) patients with synchronous bone metastasis (SBM) remain unclear. This real-world study aimed to elucidate the incidence and prognosis of DTC patients with SBM using population-based data.MethodsData of patients with newly diagnosed DTC from 2010 to 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariable logistic regression analysis was utilized to identify predictors of developing SBM in patients with DTC and was further evaluated by receiver operator characteristics (ROC) analysis. Multivariable Cox regression was applied to identify prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS).ResultsA total of 67,176 patients with DTC were screened from the database, with 0.36% (244/67,176) developed SBM. The age-adjusted incidence of SBM in patients with DTC was relatively stable during the study period with an average annual percentage change (AAPC) of 2.52. Multivariable logistic regression analysis recognized seven factors (older age, male gender, black race, other races, follicular histology, the American Joint Committee on Cancer (AJCC) T2, T3, T4 staging, and N1 staging) as predictors of developing SBM among the entire cohort, with the value of area under the curve (AUC) of 0.931 (95% CI: 0.915–0.947). The median survival time of DTC patients with SBM was 22 months (interquartile range, 7–47 months). The multivariable Cox regression analysis indicated multiple metastatic sites, surgical procedures, and chemotherapy as predictors for the survival of patients.ConclusionsPredictors and prognostic factors of SBM in patients with DTC were identified in this study. Patients with risk factors should be given more attention in clinical practice.</p

Image_8_Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas.jpeg

Soft tissue sarcomas (STSs) are heterogeneous malignancies derived from mesenchymal cells. Due to its rarity, heterogeneity, and limited overall response to chemotherapy, STSs represent a therapeutic challenge. Necroptosis is a novel therapeutic strategy for enhancing immunotherapy of cancer. Nevertheless, no research has explored the relationship between necroptosis-related genes (NRGs) and STSs. In this study, differentially expressed NRGs were identified using The Cancer Genome Atlas (TCGA) and The Cancer Genotype-Tissue Expression (GTEx) project. The expression levels of 34 NRGs were significantly different. Several key NRGs were validated using RT-qPCR and our own sequencing data. Patients with STSs were divided into two clusters using consensus cluster analysis, and significant differences were observed in their survival (p=0.002). We found the differentially expressed genes (DEGs) between the two clusters and carried out subsequent analysis. The necroptosis-related gene signatures with 10 key DEGs were identified with a risk score constructed. The prognosis of TCGA-SARC cohort with low necroptosis-related risk score was better (p<0.001). Meanwhile, the low-risk group had a significantly increased immune infiltration. Using the data of GSE17118 and another immunotherapy cohort as external validations, we observed significant survival differences between the two risk groups (p=0.019). The necroptosis-related risk score proved to be an independent prognostic factor, and a nomogram was further established and integrated with other clinical features. Notably, the necroptosis-related gene signature could also act as the prognostic indicator in other malignancies based on pan-cancer analysis. In summary, the study outlines NRGs in STSs and their potential role in prognosis and will be one of the important directions for future research.</p

Table_2_Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas.xlsx

Soft tissue sarcomas (STSs) are heterogeneous malignancies derived from mesenchymal cells. Due to its rarity, heterogeneity, and limited overall response to chemotherapy, STSs represent a therapeutic challenge. Necroptosis is a novel therapeutic strategy for enhancing immunotherapy of cancer. Nevertheless, no research has explored the relationship between necroptosis-related genes (NRGs) and STSs. In this study, differentially expressed NRGs were identified using The Cancer Genome Atlas (TCGA) and The Cancer Genotype-Tissue Expression (GTEx) project. The expression levels of 34 NRGs were significantly different. Several key NRGs were validated using RT-qPCR and our own sequencing data. Patients with STSs were divided into two clusters using consensus cluster analysis, and significant differences were observed in their survival (p=0.002). We found the differentially expressed genes (DEGs) between the two clusters and carried out subsequent analysis. The necroptosis-related gene signatures with 10 key DEGs were identified with a risk score constructed. The prognosis of TCGA-SARC cohort with low necroptosis-related risk score was better (p<0.001). Meanwhile, the low-risk group had a significantly increased immune infiltration. Using the data of GSE17118 and another immunotherapy cohort as external validations, we observed significant survival differences between the two risk groups (p=0.019). The necroptosis-related risk score proved to be an independent prognostic factor, and a nomogram was further established and integrated with other clinical features. Notably, the necroptosis-related gene signature could also act as the prognostic indicator in other malignancies based on pan-cancer analysis. In summary, the study outlines NRGs in STSs and their potential role in prognosis and will be one of the important directions for future research.</p

Image_1_Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas.jpeg

Soft tissue sarcomas (STSs) are heterogeneous malignancies derived from mesenchymal cells. Due to its rarity, heterogeneity, and limited overall response to chemotherapy, STSs represent a therapeutic challenge. Necroptosis is a novel therapeutic strategy for enhancing immunotherapy of cancer. Nevertheless, no research has explored the relationship between necroptosis-related genes (NRGs) and STSs. In this study, differentially expressed NRGs were identified using The Cancer Genome Atlas (TCGA) and The Cancer Genotype-Tissue Expression (GTEx) project. The expression levels of 34 NRGs were significantly different. Several key NRGs were validated using RT-qPCR and our own sequencing data. Patients with STSs were divided into two clusters using consensus cluster analysis, and significant differences were observed in their survival (p=0.002). We found the differentially expressed genes (DEGs) between the two clusters and carried out subsequent analysis. The necroptosis-related gene signatures with 10 key DEGs were identified with a risk score constructed. The prognosis of TCGA-SARC cohort with low necroptosis-related risk score was better (p<0.001). Meanwhile, the low-risk group had a significantly increased immune infiltration. Using the data of GSE17118 and another immunotherapy cohort as external validations, we observed significant survival differences between the two risk groups (p=0.019). The necroptosis-related risk score proved to be an independent prognostic factor, and a nomogram was further established and integrated with other clinical features. Notably, the necroptosis-related gene signature could also act as the prognostic indicator in other malignancies based on pan-cancer analysis. In summary, the study outlines NRGs in STSs and their potential role in prognosis and will be one of the important directions for future research.</p