Immunogenicity and safety of a recombinant gE-Fc fusion protein subunit vaccine for herpes zoster in adults ≥50 years of age: a randomised, active-controlled, non-inferiority trial.

The licensed adjuvanted recombinant glycoprotein E (gE) subunit vaccine (HZ/su) is highly effective against herpes zoster (HZ). This randomised, active-controlled, non-inferiority trial (ChiCTR2300079076) compared the immunogenicity and safety of a novel gE-Fc fusion protein vaccine candidate (LZ901) with HZ/su in 300 healthy adults aged ≥50 years without prior HZ vaccination in Wuxi, China. Participants received either two doses of LZ901 (30-day interval; n = 151) or HZ/su (60-day interval; n = 149).

Evaluating the Impact of Oral Contraceptives on Pancreatic Cancer Risk: A Two-Sample Mendelian Randomization Analysis.

The relationship between oral contraceptive (OC) use and pancreatic cancer (PC) risk remains controversial, with inconsistent findings reported in observational studies. To clarify this relationship and better identify potential risk factors for PC prevention, more unbiased and robust approaches are needed. We investigated the potential causal relationship between OC use and PC risk using a two-sample Mendelian randomization (MR) analysis, with blood protein quantitative trait loci (pQTLs) as instrumental variables.

TODO: A Triple-Outcome Double-Criterion Optimal Design for Dose Monitoring-and-Optimization in Multi-Dose Randomized Trials.

Detecting the efficacy signal and determining the optimal dose are critical steps to increase the probability of success and expedite the drug development in cancer treatment. After identifying a safe dose range through phase I studies, conducting a multidose randomized trial becomes an effective approach to achieve this objective. However, there have been limited formal statistical designs for such multidose trials, and dose selection in practice is often ad hoc, relying on descriptive statistics.

Accounting for the impact of rare variants on causal inference with RARE: a novel multivariable Mendelian randomization method.

Mendelian randomization (MR) method utilizes genetic variants as instrumental variables to infer the causal effect of an exposure on an outcome. However, the impact of rare variants on traits is often neglected, and traditional MR assumptions can be violated by correlated horizontal pleiotropy (CHP) and uncorrelated horizontal pleiotropy (UHP). To address these issues, we propose a multivariable MR approach, an extension of the standard MR framework: MVMR incorporating Rare variants Accounting for multiple Risk factors and shared horizontal plEiotropy (RARE).

Enhanced efficacy of ipilimumab plus nivolumab in angiogenic subtypes of metastatic clear-cell renal cell carcinoma.

In metastatic clear-cell renal cell carcinoma (mccRCC), choosing between immuno-oncology (IO) combinations and IO plus anti-VEGF therapies is uncertain. The BIONIKK trial revealed that ipilimumab plus nivolumab (Ipi/Nivo) achieved a 70% objective response rate in angiogenic cluster1/2 versus 41% in cluster4/5, which featured T-effector/cell-cycle signatures (p = 0.048).

Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma.

Background: Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) response in solid tumors, particularly metastatic clear-cell renal cell carcinoma (ccRCC), remains inadequately explored.

Methods: This study analyzed patients with metastatic ccRCC from two prospective clinical trials, encompassing 181 patients receiving nivolumab in the CheckMate trials (-009 to -010 and -025) and 48 patients treated with the ipilimumab-nivolumab combination in the BIONIKK trial.

Determining doses for backfill cohorts based on patient-reported outcome.

Background: Incorporating backfill cohorts in phase I oncology trials is a recently developed strategy for dose optimization. However, the efficacy assessment window is long in general, causing a lag in identifying ineffective doses and more patients being backfilled to those doses. There is necessity to investigate how to use patient-reported outcomes (PRO) to determine doses for backfill cohorts.

Integrative analysis of single-cell and bulk multi-omics data to reveal subtype-specific characteristics and therapeutic strategies in clear cell renal cell carcinoma patients.

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of malignant renal cell carcinoma and is well known as a common genitourinary cancer. Stratifying tumors based on heterogeneity is essential for better treatment options. In this study, consensus clusters were constructed based on gene expression, DNA methylation, and gene mutation data, which were combined with multiple clustering algorithms.

Allogeneic CD5-specific CAR-T therapy for relapsed/refractory T-ALL: a phase 1 trial.

Refractory or relapsed T cell acute lymphoblastic leukemia (r/r T-ALL) patients have poor prognoses, due to the lack of effective salvage therapies. Recently, CD7-targeting chimeric antigen receptor (CAR)-T therapies show efficacy in patients with r/r T-ALL, but relapse with CD7 loss is common. This study evaluates a CD5-gene-edited CAR-T cell therapy targeting CD5 in 19 r/r T-ALL patients, most of whom had previously failed CD7 CAR-T interventions.

The role of cGAS-STING signaling in the development and therapy of head and neck squamous cell carcinoma.

The cGAS-STING signaling pathway plays a critical role in innate immunity and defense against viral infections by orchestrating intracellular and adaptive immune responses to DNA. In the context of head and neck squamous cell carcinoma (HNSCC), this pathway has garnered significant attention due to its potential relevance in disease development and progression. HNSCC is strongly associated with risk factors such as smoking, heavy alcohol consumption, and human papillomavirus (HPV) infection.

MC-Keyboard: A Practical Phase I Trial Design for Targeted Therapies and Immunotherapies Integrating Multiple-Grade Toxicities.

In targeted therapies and immunotherapies, the occurrence of low-grade (e.g., grade 1-2) toxicities (LGT) is common, while dose-limiting toxicities (DLT) are relatively rare.

Integrative analysis identifies region- and sex-specific gene networks and Mef2c as a mediator of anxiety-like behavior.

The molecular mechanisms underlying multi-brain region origins and sexual dimorphism of anxiety remain unclear. Here, we leverage large-scale transcriptomics from seven brain regions in mouse models of anxiety and extensive experiments to dissect brain-region- and sex-specific gene networks. We identify 4,840 genes with sex-specific expression alterations across seven brain regions, organized into ten network modules with sex-biased expression patterns.

Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty-five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification.

PIPET: predicting relevant subpopulations in single-cell data using phenotypic information from bulk data.

Single-cell RNA sequencing has revealed cellular heterogeneity in complex tissues, notably benefiting research on diseases such as cancer. However, the integration of single-cell data from small samples with extensive clinical features in bulk data remains underexplored. In this study, we introduce PIPET, an algorithmic method for predicting relevant subpopulations in single-cell data based on multivariate phenotypic information from bulk data.

Adaptive promising zone design for cancer immunotherapy with heterogeneous delayed treatment effect.

Indirect mechanisms of cancer immunotherapies result in delayed treatment effects that vary among patients. Consequently, the use of the log-rank test in trial design and analysis can lead to significant power loss and pose additional challenges for interim decisions in adaptive designs. In this paper, we describe patients' survival using a piecewise proportional hazard model with random lag time and propose an adaptive promising zone design for cancer immunotherapy with heterogeneous delayed effects.

Cardiac injury activates STING signaling via upregulating SIRT6 in macrophages after myocardial infarction.

Aims: This work sought to investigate the mechanism underlying the STING signaling pathway during myocardial infarction (MI), and explore the involvement and the role of SIRT6 in the process.

Main Methods: Mice underwent the surgery of permanent left anterior descending (LAD) artery constriction. Primary cardiomyocytes (CMs) and fibroblasts were subjected to hypoxia to mimic MI in vitro.

AKT2 deficiency alleviates doxorubicin-induced cardiac injury via alleviating oxidative stress in cardiomyocytes.

Doxorubicin (DOX), a widely used chemotherapy agent in cancer treatment, encounters limitations in clinical efficacy due to associated cardiotoxicity. This study aims to explore the role of AKT serine/threonine kinase 2 (AKT2) in mitigating DOX-induced oxidative stress within the heart through both intracellular and extracellular signaling pathways. Utilizing Akt2 knockout (KO) and Nrf2 KO murine models, alongside neonatal rat cardiomyocytes (NRCMs), we systematically investigate the impact of AKT2 deficiency on DOX-induced cardiac injury.

Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses.

In precision oncology, integrating multiple cancer patient subgroups into a single master protocol allows for the simultaneous assessment of treatment effects in these subgroups and promotes the sharing of information between them, ultimately reducing sample sizes and costs and enhancing scientific validity. However, the safety and efficacy of these therapies may vary across different subgroups, resulting in heterogeneous outcomes. Therefore, identifying subgroup-specific optimal doses in early-phase clinical trials is crucial for the development of future trials.

Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer.

: Most of the current research on prognostic model construction for non-small cell lung cancer (NSCLC) only involves in bulk RNA-seq data without integration of single-cell RNA-seq (scRNA-seq) data. Besides, most of the prognostic models are constructed by predictive genes, ignoring other predictive variables such as clinical features. : We obtained scRNA-seq data from GEO database and bulk RNA-seq data from TCGA database.

The role of Keap1-Nrf2 signaling pathway during the progress and therapy of diabetic retinopathy.

Diabetic retinopathy is a complex and progressive ocular complication of diabetes mellitus and is a leading cause of blindness in people of working age worldwide. The pathophysiology of diabetic retinopathy involves multifactorial processes, including oxidative stress, inflammation and vascular abnormalities. Understanding the underlying molecular mechanisms involved in its pathogenesis is essential for the development of effective therapeutic interventions.

MIDAS-2: an enhanced Bayesian platform design for immunotherapy combinations with subgroup efficacy exploration.

Although immunotherapy combinations have revolutionised cancer treatment, the rapid screening of effective and optimal therapies from large numbers of candidate combinations, as well as exploring subgroup efficacy, remains challenging. This necessitates innovative, integrated, and efficient trial designs. In this study, we extend the MIDAS design to include subgroup exploration and propose an enhanced Bayesian information borrowing platform design called MIDAS-2.

Enhancing phase I dose-finding trials design through dynamic borrowing information and handling late-onset toxicity.

In recent years, there has been a growing trend among regulatory agencies to consider the use of historical controls in clinical trials as a means of improving the efficiency of trial design. In this paper, to enhance the statistical operating characteristic of Phase I dose-finding trials, we propose a novel model-assisted design method named "MEM-Keyboard". The proposed design is based on the multisource exchangeability models (MEMs) that allows for dynamic borrowing of information from multiple supplemental data sources, including historical trial data, to inform the dose-escalation process.