Ageing microenvironment mediates lymphocyte carcinogenesis and lymphoma drug resistance: From mechanisms to clinical therapy (Review).

Cellular senescence has a complex role in lymphocyte carcinogenesis and drug resistance of lymphomas. Senescent lymphoma cells combine with immunocytes to create an ageing environment that can be reprogrammed with a senescence­associated secretory phenotype, which gradually promotes therapeutic resistance. Certain signalling pathways, such as the NF­κB, Wnt and PI3K/AKT/mTOR pathways, regulate the tumour ageing microenvironment and induce the proliferation and progression of lymphoma cells. Therefore, targeting senescence­related enzymes or their signal transduction pathways may overcome radiotherapy or chemotherapy resistance and enhance the efficacy of relapsed/refractory lymphoma treatments. Mechanisms underlying drug resistance in lymphomas are complex. The ageing microenvironment is a novel factor that contributes to drug resistance in lymphomas. In terms of clinical translation, some senolytics have been used in clinical trials on patients with relapsed or refractory lymphoma. Combining immunotherapy with epigenetic drugs may achieve better therapeutic effects; however, senescent cells exhibit considerable heterogeneity and lymphoma has several subtypes. Extensive research is necessary to achieve the practical application of senolytics in relapsed or refractory lymphomas. This review summarises the mechanisms of senescence­associated drug resistance in lymphoma, as well as emerging strategies using senolytics, to overcome therapeutic resistance in lymphoma.

Enhancing missense variant pathogenicity prediction with protein language models using VariPred.

Computational approaches for predicting the pathogenicity of genetic variants have advanced in recent years. These methods enable researchers to determine the possible clinical impact of rare and novel variants. Historically these prediction methods used hand-crafted features based on structural, evolutionary, or physiochemical properties of the variant. In this study we propose a novel framework that leverages the power of pre-trained protein language models to predict variant pathogenicity. We show that our approach VariPred (Variant impact Predictor) outperforms current state-of-the-art methods by using an end-to-end model that only requires the protein sequence as input. Using one of the best-performing protein language models (ESM-1b), we establish a robust classifier that requires no calculation of structural features or multiple sequence alignments. We compare the performance of VariPred with other representative models including 3Cnet, Polyphen-2, REVEL, MetaLR, FATHMM and ESM variant. VariPred performs as well as, or in most cases better than these other predictors using six variant impact prediction benchmarks despite requiring only sequence data and no pre-processing of the data.

Transrectal versus transperineal prostate biopsy for cancer detection in patients with gray-zone prostate-specific antigen: a multicenter, real-world study.

Knowledge about the effect of different prostate biopsy approaches on the prostate cancer detection rate (CDR) in patients with gray-zone prostate-specific antigen (PSA) is limited. We performed this study to compare the CDR among patients who underwent different biopsy approaches and had rising PSA levels in the gray zone. Two hundred and twenty-two patients who underwent transrectal prostate biopsy (TRB) and 216 patients who underwent transperineal prostate biopsy (TPB) between June 2016 and September 2022 were reviewed in this study. In addition, 110 patients who received additional targeted biopsies following the systematic TPB were identified. Clinical parameters, including age, PSA derivative, prostate volume (PV), and needle core count, were recorded. The data were fitted via propensity score matching (PSM), adjusting for potential confounders. TPB outperformed TRB in terms of the CDR (49.6% vs 28.3%, P = 0.001). The clinically significant prostate cancer (csPCa) detection rate was not significantly different between TPB and TRB (78.6% vs 68.8%, P = 0.306). In stratified analysis, TPB outperformed TRB in CDR when the age of patients was 65-75 years (59.0% vs 22.0%, P < 0.001), when PV was 25.00-50.00 ml (63.2% vs 28.3%, P < 0.001), and when needle core count was no more than 12 (58.5% vs 31.5%, P = 0.005). The CDR ( P = 0.712) and detection rate of csPCa ( P = 0.993) did not significantly differ among the systematic, targeted, and combined biopsies. TPB outperformed TRB in CDR for patients with gray-zone PSA. Moreover, performing target biopsy after systematic TPB provided no additional benefits in CDR.

Real-world analysis of apalutamide-associated skin rash in Chinese patients with prostate cancer.

PURPOSE: This study aimed to explore the clinical characteristics of apalutamide-associated skin rash and management of skin rash in real-world Chinese patients with prostate cancer. METHODS: We investigated 138 patients with prostate cancer who received apalutamide in the Second Hospital of Tianjin Medical University from January 2022 to March 2023. The primary end points were the incidence of skin rash and the time to skin rash. The second end points were the grade of skin rash, the time to remission, the rate of recurrence of skin rash, clinical risk factors and management of skin rash. RESULTS: One hundred patients were analyzed. Patients were a median of 73 years old (IQR 68-77.75). Thirty-two patients (32%) developed apalutamide­associated skin rash. The median time to incidence and remission of skin rash were 57.5 and 11.5 days, respectively. Of 32 skin rash, 27 patients had apalutamide therapy maintained after rash remission. There were seven patients having recurrence of skin rash. By multivariable logistic regression analysis, we revealed that hypertension history (OR 3.22, 95% CI 1.09-9.53, p = 0.035), bad life-styles (OR 3.29, 95% CI 1.11-9.8, p = 0.032), ECOG ≥ 1 (OR 3.92, 95% CI 1.33-11.55, p = 0.013), and high tumor burden (OR 3.13, 95% CI 1.07-9.14, p = 0.037) were independently associated with higher incidence of skin rash. CONCLUSION: Nearly one-third of Chinese patients experienced skin rash after taking apalutamide in our study. The poor health patients might have a higher incidence of apalutamide-associated skin rash.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL.

PURPOSE: The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort. METHODS: This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort. RESULTS: In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed. CONCLUSION: PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Collagen Anchoring Protein-Nucleic Acid Chimeric Probe for In Situ In Vivo Mapping of a Tumor-Specific Protease.

In situ analysis of biomarkers in the tumor microenvironment (TME) is important to reveal their potential roles in tumor progression and early diagnosis of tumors but remains a challenge. In this work, a bottom-up modular assembly strategy was proposed for a multifunctional protein-nucleic chimeric probe (PNCP) for in situ mapping of cancer-specific proteases. PNCP, containing a collagen anchoring module and a target proteolysis-responsive isothermal amplification sensor module, can be anchored in the collagen-rich TME and respond to the target protease in situ and generate amplified signals through rolling cycle amplification of tandem fluorescent RNAs. Taking matrix metalloproteinase 2 (MMP-2), a tumor-associated protease, as the model, the feasibility of PNCP was demonstrated for the in situ detection of MMP-2 activity in 3D tumor spheroids. Moreover, in situ in vivo mapping of MMP-2 activity was also achieved in a metastatic solid tumor model with high sensitivity, providing a useful tool for evaluating tumor metastasis and distinguishing highly aggressive forms of tumors.

A collagen-immobilized nanodevice for in situ ratiometric imaging of cancer biomarkers in the tumor microenvironment.

Monitoring the spatiotemporal dynamics of cancer biomarkers within the tumor microenvironment (TME) is critical to understanding their roles in tumorigenesis. Here, we reported a multifunctional fusion protein (collagen-binding domain and duck circovirus tag fused to mCherry, CBD-mCherry-DCV) capable of binding collagen with high affinity and covalently binding specific nucleic acids with exceptional efficiency. We then constructed a chimeric protein-nucleic acid nanodevice (CPNN) using CBD-mCherry-DCV and an aptamer-based sensing module to enable spatially controlled ratiometric imaging of cancer biomarkers in the TME. The collagen-anchoring module CBD-mCherry-DCV allowed specific immobilization of CPNN on 3D multicellular tumor spheroids, enabling the sensing module to achieve "off-on" fluorescence imaging of cancer biomarkers upon specific target recognition by an aptamer. Taking advantage of the constant fluorescence signal of mCherry and the activatable fluorescence response of Cy5 to specific cancer biomarkers, the detection sensitivity and reliability of CPNN were improved by self-calibrating the signal intensity. Specifically, CPNN enabled ratiometric fluorescence imaging of varying concentrations of exogenous PDGF-BB and ATP in tumor spheroids with a high signal-to-background ratio. Furthermore, it allowed the visual monitoring of endogenous PDGF-BB and ATP released from cells. Overall, this study demonstrates the potential of the nanodevice as a versatile approach for the visualization and imaging of cancer biomarkers in the TME.

MYC overexpression but not MYC/BCL2 double expression predicts survival in bulky mass diffuse large B-cell lymphoma patients.

PURPOSE: The prognostic factors for diffuse large B-cell lymphoma (DLBCL) have been fully explored, but prognostic information for bulky mass DLBCL patients is limited. This study aimed to analyze the prognostic value of MYC protein expression and other biological parameters in bulky mass DLBCL patients. METHODS: We defined a bulky mass as a maximum tumor diameter ≥7.5 cm and studied 227 patients with de novo bulky mass DLBCL. RESULTS: In all patients with bulky mass DLBCL, the 1-year and 3-year OS rates were 72.7% and 57.1%, respectively, and the 1-year and 3-year PFS rates were 52.0% and 42.5%, respectively. The MYC overexpression group (n = 140) showed significantly worse overall survival (OS; p = 0.019) and progression-free survival (PFS; p = 0.001) than the non-MYC overexpression group (n = 87). Subgroup analyses demonstrated that the MYC overexpression group was associated with inferior OS and PFS in the subgroups with the International Prognostic Index score of 3-5 (OS: p = 0.011; PFS: p < 0.001), Ann Arbor stage 3-4 (OS: p = 0.014; PFS: p < 0.001) and GCB subtype (OS: p = 0.014; PFS: p = 0.010). Consolidation radiotherapy improved OS and PFS in patients with bulky mass DLBCL (OS: p = 0.008; PFS: p = 0.004) as well as in those with MYC overexpression (OS: p = 0.001; PFS: p = 0.001). The prognostic value of MYC overexpression was maintained in a multivariate model adjusted for the International Prognostic Index. CONCLUSION: MYC overexpression is a poor predictor for bulky mass DLBCL patients. Consolidation radiotherapy for residual disease after induction therapy may improve outcomes for patients with bulky mass DLBCL.

A prediction model for severe hematological toxicity of BTK inhibitors.

Bruton's tyrosine kinase inhibitor (BTKi) has revolutionized the treatment of B-cell lymphomas. However, BTKi-related hematological toxicity hinders treatment continuity and may further affect clinical efficacy. To identify risk factors and predict the likelihood of BTKi-related hematological toxicities, we constructed and validated a prediction model for severe hematological toxicity of BTKi. Approved by the hospital medical science research ethics committee (No. M2022427), we collected real-world data in patients treated with BTKi from a Lymphoma Research Center in China. The outcome of interest was severe hematological toxicity caused by BTKi. 36 candidate variables were categorized into demographics, diagnostic and treatment information, laboratory data, and medical history. The study sample was randomly divided into training (70%) and validation (30%) sets. We developed and compared the performance of various modelling methods, including decision tree (DT), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and logistic regression (LR). Finally, we constructed a Web-calculator of the optimal model to estimate the risk of hematological toxicity. This study was designed, conducted and reported strictly in compliance with the TRIPOD checklist. Data from a total 121 patients were included [median age, 65 years (range, 56-73 years); 74 (61.15%) men; 47 (38.84%) severe hematological toxicity]. The XGBoost model demonstrated better overall properties than other models, achieving high discrimination (AUC: 0.671; accuracy: 0.730; specificity: 0.913) and clinical benefit. The following 10 variables were used to develop the XGBoost model: white blood cell count (WBC), neutrophil count (Neut), red blood cell count (RBC), platelet count (PLT), fibrinogen (Fib), total protein (TP), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gender and type of BTKi. SHAP values demonstrated insightful associations between these variables and hematological toxicity. Finally, to facilitate clinical and research use, we also deploy the XGBoost model on a web-calculator for free access. The XGBoost model with promising accuracy was developed to predict the severe hematological toxicity of BTKi. It helps to strengthen the proactive monitoring and management of patients with hematological toxicity, and thus achieve long-term continuous BTKi treatment.

Dynamic Phosphoproteomics of BRS3 Activation Reveals the Hippo Signaling Pathway for Cell Migration.

Bombesin receptor subtype-3 (BRS3) is an orphan G-protein coupled receptor (GPCR) that is involved in a variety of pathological and physiological processes, while its biological functions and underlying regulatory mechanisms remain largely unknown. In this study, a quantitative phosphoproteomics approach was employed to comprehensively decipher the signal transductions that occurred upon intracellular BRS3 activation. The lung cancer cell line H1299-BRS3 was treated with MK-5046, an agonist of BRS3, for different durations. Harvested cellular proteins were digested and phosphopeptides were enriched by immobilized titanium (IV) ion affinity chromatography (Ti4+-IMAC) for label-free quantification (LFQ) analysis. A total of 11,938 phosphopeptides were identified, corresponding to 3,430 phosphoproteins and 10,820 phosphosites. Data analysis revealed that 27 phosphopeptides corresponding to six proteins were involved in the Hippo signaling pathway, which was significantly regulated by BRS3 activation. Verification experiments demonstrated that downregulation of the Hippo signaling pathway caused by BRS3 activation could induce the dephosphorylation and nucleus localization of the Yes-associated protein (YAP), and its association with cell migration was further confirmed by kinase inhibition. Our data collectively demonstrate that BRS3 activation contributes to cell migration through downregulation of the Hippo signaling pathway.

ALDOB represents a potential prognostic biomarker for patients with clear cell renal cell carcinoma.

Background: Previous studies have shown that aldolase B (ALDOB) might play controversial roles in multiple types of cancer, which could act as a cancer-promoting factor or a cancer-inhibiting factor depending on the subtype of the cancer. However, the role of ALDOB in clear cell renal cell carcinoma (ccRCC) patients has not been clearly elucidated. Therefore, this study aimed to comprehensively explore the expression level, prognostic value, functional enrichment, immune infiltration, and N6-methyladenosine (m6A) modification of ALDOB in ccRCC patients. Methods: A total of 1,070 ccRCC tissues and 409 normal tissues from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database, and the ArrayExpress database were enrolled to evaluate the expression level and prognostic value of ALDOB in ccRCC. The Kaplan-Meier survival curves and the Log-Rank test were performed to assess the prognostic value. The univariate and multivariate Cox regression analysis were used to identify the independent prognostic predictors in ccRCC patients. In addition, R version 4.2.0 with its suitable packages were used to perform the functional enrichment analysis, immune infiltration analysis, and m6A methylation analysis. Statistical significance was set at the P value <0.05. Results: The expression level of ALDOB was significantly down-regulated in ccRCC compared to normal tissue, and the ALDOB expression level was noticeably correlated with T stage, M stage, and histologic grade of patients with ccRCC. The survival analysis revealed that ALODB was the independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) of ccRCC patients. In addition, the functional enrichment analysis showed that ALDOB and its related genes were mainly involved in the metabolism and metabolic pathways of multiple substances, including glycolysis, gluconeogenesis, and fatty acid degradation. Finally, the immune infiltration analysis and the m6A methylation analysis suggested that ALDOB was closely correlated with the infiltration abundance of immune cells and stromal cells in the tumor microenvironment and several types of m6A regulators in ccRCC. Conclusions: As a potential prognostic biomarker for patients with ccRCC, downregulation of ALDOB was closely associated with the clinicopathological features, poor prognosis, immune infiltration, and m6A modification in ccRCC patients.

SUV39H1 is a prognosis and immune microenvironment-related biomarker in diffuse large B-cell lymphoma.

BACKGROUND: The tumor microenvironment plays a crucial role in the oncogenesis and treatment of diffuse large B-cell lymphoma (DLBCL). The H3K9me3-specific histone methyltransferase Suppressor of variegation 3-9 homolog 1 (SUV39H1) is a significant gene that promotes the progression of various malignancies. However, the specific expression of SUV39H1 in DLBCL remains unclear. METHODS: By retrieving data from GEPIA, UCSC XENA and TCGA public databases, we observed the high expression of SUV39H1 in DLBCL. Combined with an immunohistochemical validation assay, we analyzed our hospital's clinical characteristics and prognosis of 67 DLBCL patients. The results showed that high SUV39H1 expression was closely associated with age over 50 years (P = 0.014) and low albumin levels (P = 0.023) of patients. Furthermore, the experiments in vitro were deployed to evaluate the regulation of SUV39H1 on the DLBCL immune microenvironment. RESULTS: The results showed that high SUV39H1 expression was closely associated with age over 50 years (P = 0.014) and low albumin levels (P = 0.023) of patients. The prognostic analysis showed that the high SUV39H1 expression group had a lower disease-free survival (DFS) rate than the low SUV39H1 expression group (P < 0.05). We further discovered that SUV39H1 upregulated the expression of CD86+ and CD163+ tumor-associated macrophages by DLBCL patients' tissues and cell experiments in vitro (P < 0.05). And SUV39H1-associated T lymphocyte subsets and cytokines IL-6/CCL-2 were downregulated in DLBCL (P < 0.05). CONCLUSIONS: In summary, SUV39H1 might be not only a potential target for treating DLBCL but also a clinical indicator for doctors to evaluate the trend of disease development.

Machine Learning to Dynamically Predict In-Hospital Venous Thromboembolism After Inguinal Hernia Surgery: Results From the CHAT-1 Study.

BACKGROUND: The accuracy of current prediction tools for venous thromboembolism (VTE) events following hernia surgery remains insufficient for individualized patient management strategies. To address this issue, we have developed a machine learning (ML)-based model to dynamically predict in-hospital VTE in Chinese patients after hernia surgery. METHODS: ML models for the prediction of postoperative VTE were trained on a cohort of 11 305 adult patients with hernia from the CHAT-1 trial, which included patients across 58 institutions in China. In data processing, data imputation was conducted using random forest (RF) algorithm, and balanced sampling was done by adaptive synthetic sampling algorithm. Data were split into a training cohort (80%) and internal validation cohort (20%) prior to oversampling. Clinical features available pre-operatively and postoperatively were separately selected using the Sequence Forward Selection algorithm. Nine-candidate ML models were applied to the pre-operative and combined datasets, and their performance was evaluated using various metrics, including area under the receiver operating characteristic curve (AUROC). Model interpretations were generated using importance scores, which were calculated by transforming model features into scaled variables and representing them in radar plots. RESULTS: The modeling cohort included 2856 patients, divided into 2536 cases for derivation and 320 cases for validation. Eleven pre-operative variables and 15 combined variables were explored as predictors related to in-hospital VTE. Acceptable-performing models for pre-operative data had an AUROC ≥ 0.60, including logistic regression, support vector machine with linear kernel (SVM_Linear), attentive interpretable Tabular learning (TabNet), and RF. For combined data, logistic regression, SVM_Linear, and TabNet had better performance, with an AUROC ≥ 0.65 for each model. Based on these models, 7 pre-operative predictors and 10 combined predictors were depicted in radar plots. CONCLUSIONS: A ML-based approach for the identification of in-hospital VTE events after hernia surgery is feasible. TabNet showed acceptable performance, and might be useful to guide clinical decision making and VTE prevention. Further validated study will strengthen this finding.

The Role of Colchicine in Different Clinical Phenotypes of Behcet Disease.

PURPOSE: Behcet disease (BD) is a multisystemic disorder characterized by variable clinical manifestations that affect nearly all systems and organs. Colchicine, an alkaloid plant extract, is considered as the first-line therapy for gout, pericarditis, and familial Mediterranean fever. However, the role of colchicine in the treatment of different clinical phenotypes of BD has not been clearly described. This narrative review summarizes the clinical use of colchicine in BD. METHODS: All relevant literature from 1980 to March 2021 was searched in PubMed, MEDLINE, and Cochrane Library. The Medical Subject Heading terms and related words that were searched are as follows: Behcet's disease, Behcet's syndrome, BD, colchicine, management, treatment, and therapy. FINDINGS: BD is an autoimmune systemic vasculitis with various clinical phenotypes, with involvement of skin mucosa, joints, eyes, and gastrointestinal, vascular, and neurologic systems. Colchicine has been used for centuries, acts by binding to tubulin to prevent the mitotic process, and has anti-inflammatory, antitumor, and antifibrotic properties. Colchicine has been reported to be an effective option for the treatment of skin, mucosal, and joint involvement in patients with certain BD clinical phenotypes. IMPLICATIONS: Colchicine reduces the severity of certain clinical phenotypes and may improve the overall disease activity index in patients with BD. More randomized clinical trials are needed to confirm the value of colchicine in the treatment of BD, and further elucidation of the mechanisms is also needed, which may reveal new application of colchicine that has been used for centuries.

Gamma distribution based predicting model for breast cancer drug response based on multi-layer feature selection.

In the pursuit of precision medicine for cancer, a promising step is to predict drug response based on data mining, which can provide clinical decision support for cancer patients. Although some machine learning methods for predicting drug response from genomic data already exist, most of them focus on point prediction, which cannot reveal the distribution of predicted results. In this paper, we propose a three-layer feature selection combined with a gamma distribution based GLM and a two-layer feature selection combined with an ANN. The two regression methods are applied to the Encyclopedia of Cancer Cell Lines (CCLE) and the Cancer Drug Sensitivity Genomics (GDSC) datasets. Using ten-fold cross-validation, our methods achieve higher accuracy on anticancer drug response prediction compared to existing methods, with an R 2 and RMSE of 0.87 and 0.53, respectively. Through data validation, the significance of assessing the reliability of predictions by predicting confidence intervals and its role in personalized medicine are illustrated. The correlation analysis of the genes selected from the three layers of features also shows the effectiveness of our proposed methods.

Epigenetic Age Acceleration Markers Are Associated With Physiologic Frailty and All-Cause Mortality in People With Human Immunodeficiency Virus.

BACKGROUND: Biomarkers that provide insight into drivers of aging are needed for people with human immunodeficiency virus (PWH). The study objective was to determine if epigenetic age acceleration (EAA) markers are associated with physiologic frailty measured by the Veterans Aging Cohort Study (VACS) Index and predict all-cause mortality for PWH. METHODS: Epigenome-wide DNA methylation was profiled in VACS total white blood cell samples collected during 2005-2007 from 531 PWH to generate 6 established markers of EAA. The association of each EAA marker was tested with VACS Index 2.0. All-cause mortality was assessed over 10 years. For each EAA marker, the hazard ratio per increased year was determined using Cox regression. To evaluate mortality discrimination, C-statistics were derived. RESULTS: Participants were mostly men (98.5%) and non-Hispanic Black (84.4%), with a mean age of 52.4 years (standard deviation [SD], 7.8 years). Mean VACS Index score was 59.3 (SD, 16.4) and 136 deaths occurred over a median follow-up of 8.7 years. Grim age acceleration (AA), PhenoAA, HannumAA, and extrinsic epigenetic AA were associated with the VACS Index and mortality. HorvathAA and intrinsic epigenetic AA were not associated with either outcome. GrimAA had the greatest mortality discrimination among EAA markers and predicted mortality independently of the VACS Index. One-year increase in GrimAA was associated with a 1-point increase in VACS Index and a 10% increased hazard for mortality. CONCLUSIONS: The observed associations between EAA markers with physiologic frailty and mortality support future research to provide mechanistic insight into the accelerated aging process and inform interventions tailored to PWH for promoting increased healthspan.

Real-world evidence of ABVD-like regimens compared with ABVD in classical Hodgkin lymphoma: a 10-year study from China.

BACKGROUND: Doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) has been regarded as the standard treatment regimen for classical Hodgkin lymphoma. In recent years, ABVD-like regimens, which emerged due to shortages and the lung toxicity of bleomycin or the emergence of immune checkpoint inhibitors and antibody-drug conjugates, may be favorable, but have not yet been tested. METHODS: We compared the outcomes of ABVD with ABVD-like regimens, which include bleomycin was completely or partially omitted; meanwhile, etoposide or PD-1 inhibitors were added. RESULTS: 5-Year progression-free survival (PFS) was higher for ABVD than ABVD-like regimens in young patients (82.1% vs. 67.0%, p = 0.029), patients with serum beta-2 microglobulin (ß2-MG) ≥ 1.85 mg/L (75.8% vs. 57.6%, p = 0.046), and advanced-stage patients with IPS score 4-7(63.1%, 18.3%, p = 0.038). For elderly (60.5% vs.76.1%, p = 0.089), patients with ß2-MG < 1.85 mg/L (83.1% vs 76.1%, p = 0.282), and advanced-stage patients with IPS score 0-3(84.6% vs. 81.3%, p = 0.476), 5-year PFS for ABVD did not differ from ABVD-like regimens. Elderly patients treated with bleomycin-free regimens showed a better survival trend compared with ABVD (99.3% vs. 61.3%, p = 0.270). CONCLUSION: ABVD is superior to ABVD-like regimens in achieving PFS in young patients or patients with poor prognosis including high IPS score and ß2-MG level. ABVD-like regimens are as effective as ABVD in elderly or low-risk patients including low IPS score and ß2-MG level; elderly patients treated with bleomycin-free regimens exhibit a better survival trend compared with ABVD.

Clinical and therapeutical significances of the cluster and signature based on oxidative stress for osteosarcoma.

BACKGROUND: It is of great clinical significance to find out the ideal tumor biomarkers and therapeutic targets to improve the prognosis of patients with osteosarcoma (OS). Oxidative stress (OXS) can directly target intracellular macromolecules and exhibit dual effects of tumor promotion and suppression. METHODS: OXS-related genes (OXRGs) were extracted from public databases, including TARGET and GEO. Univariate Cox regression analysis, Random Survival Forest algorithm, and LASSO regression were performed to identify prognostic genes and establish the OXS-signature. The efficacy of the OXS-signature was further evaluated by Kaplan-Meier curves and timeROC package. Evaluation of immunological characteristics was achieved based on ESTIMATE algorithm and ssGSEA. Submap algorithm was used to explore the response to anti-PD1 and anti-CTLA4 therapy for OS. Drug response prediction was conducted by using pRRophetic package. The expression values of related genes in the OXS-signature were detected with PCR assays. RESULTS: Two OXS-clusters were identified for OS, with remarkable differences of clusters presented in prognosis. Kyoto Encyclopedia of Genes Genomes (KEGG) analysis showed that differentially expressed genes (DEGs) between the OXS-clusters were significantly enriched in several immune-related pathways. Patients with lower OS-scores attained better clinical outcomes, and presented more sensitivity to ICB therapy. By contrast, OS patients with higher OS-scores revealed more sensitivity to certain drugs. Furthermore, critical genes, RHBDL2 and CGREF1 from the model, were significantly higher expressed in OS cell lines. CONCLUSIONS: Our study identified the clusters and signature based on OXS, which would lay the foundation for molecular experimental research, disease prevention and treatment of OS.

The Interaction of Trauma Exposure and DNA Methylation on Blood Pressure Among Black Women in the InterGEN Study.

Objective: Despite evidence that trauma exposure is linked to higher risk of hypertension, epigenetic mechanisms (such as DNA methylation) by which trauma potentially influences hypertension risk among Black adults remain understudied. Methods: Data from a longitudinal study of Black mothers were used to test the hypothesis that direct childhood trauma (ie, personal exposure) and vicarious trauma (ie, childhood trauma experienced by their children) would interact with DNA methylation to increase blood pressure (BP). Separate linear mixed effects models were fitted at each CpG site with the DNA methylation beta-value and direct and vicarious trauma as predictors and systolic and diastolic BP modeled as dependent variables adjusted for age, cigarette smoking, and body mass index. Interaction terms between DNA methylation beta-values with direct and vicarious trauma were added. Results: The sample included 244 Black mothers with a mean age of 31.2 years (SD = ±5.8). Approximately 45% of participants reported at least one form of direct childhood trauma and 49% reported at least one form of vicarious trauma. Epigenome-wide interaction analyses found that no CpG sites passed the epigenome-wide significance level indicating the interaction between direct or vicarious trauma with DNAm did not influence systolic or diastolic BP. Conclusions: This is one of the first studies to simultaneously examine whether direct or vicarious exposure to trauma interact with DNAm to influence BP. Although findings were null, this study highlights directions for future research that investigates epigenetic mechanisms that may link trauma exposure with hypertension risk in Black women.

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer.

The human oral microbiome correlates with numerous diseases, including lung cancer. Identifying the functional changes by metaproteomics helps understand the disease-related dysbiosis, yet characterizing low-abundant bacteria is challenging. Here, we developed a free-flow isoelectric focusing electrophoresis-mass spectrometry- (FFIEF-MS-) based metaproteomics strategy to reduce host interferences and enrich low-abundant bacteria for in-depth interpretation of the oral microbiome. With our method, the number of interfering peptides decreased by 52.87%, whereas the bacterial peptides and species increased by 94.97% and 44.90%, respectively, compared to the conventional metaproteomics approach. We identified 3647 bacterial proteins, which is the most comprehensive oral metaproteomics study to date. Lung cancer-associated bacteria were validated among an independent cohort. The imbalanced Fusobacterium nucleatum and Prevotella histicola and their dysregulated functions in inhibiting immune response and maintaining cell redox homeostasis were revealed. The FFIEF-MS may serve as a valuable strategy to study the mechanisms between human diseases and microbiomes with broader applications.