Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

In the 2023 series, we summarized the major clinical research advances in gynecologic oncology based on communications at the conference of Asian Society of Gynecologic Oncology Review Course. The review consisted of 1) Endometrial cancer: immune checkpoint inhibitor, antibody drug conjugates (ADCs), selective inhibitor of nuclear export, CDK4/6 inhibitors WEE1 inhibitor, poly (ADP-ribose) polymerase (PARP) inhibitors. 2) Cervical cancer: surgery in low-risk early-stage cervical cancer, therapy for locally advanced stage and advanced, metastatic, or recurrent setting; and 3) Ovarian cancer: immunotherapy, triplet therapies using immune checkpoint inhibitors along with antiangiogenic agents and PARP inhibitors, and ADCs. In 2023, the field of endometrial cancer treatment witnessed a landmark year, marked by several practice-changing outcomes with immune checkpoint inhibitors and the reliable efficacy of PARP inhibitors and ADCs.

Background/Aims: Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Methods: Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. Results: The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Conclusions Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

In the 2023 series, we summarized the major clinical research advances in gynecologic oncology based on communications at the conference of Asian Society of Gynecologic Oncology Review Course. The review consisted of 1) Endometrial cancer: immune checkpoint inhibitor, antibody drug conjugates (ADCs), selective inhibitor of nuclear export, CDK4/6 inhibitors WEE1 inhibitor, poly (ADP-ribose) polymerase (PARP) inhibitors. 2) Cervical cancer: surgery in low-risk early-stage cervical cancer, therapy for locally advanced stage and advanced, metastatic, or recurrent setting; and 3) Ovarian cancer: immunotherapy, triplet therapies using immune checkpoint inhibitors along with antiangiogenic agents and PARP inhibitors, and ADCs. In 2023, the field of endometrial cancer treatment witnessed a landmark year, marked by several practice-changing outcomes with immune checkpoint inhibitors and the reliable efficacy of PARP inhibitors and ADCs.